Biomass waste as a raw material for the mesoporous catalyst synthesis and its application in HDO of guaiacol for biofuel production

Biomass waste as a raw material for the mesoporous catalyst synthesis and its application in HDO of guaiacol for biofuel production | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Biomass waste as a raw material for the mesoporous catalyst synthesis and its application in HDO of guaiacol for biofuel production Lorena P. Rivoira, Brenda C. Ledesma, María V. Fraire, Verónica A. Valles, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4999409/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 31 Dec, 2024 Read the published version in Clean Technologies and Environmental Policy → Version 1 posted 9 You are reading this latest preprint version Abstract Platinum-modified activated carbon was synthesized and studied for hydrodeoxygenation (HDO) of guaiacol. The activated carbon support was prepared using orange peel from industrial waste. Platinum was added by wetness impregnation. The activity was compared with that of platinum supported on mesoporous silica and commercial activated carbon catalysts. The catalysts prepared were characterized by different techniques: XRD and N 2 adsorption isotherms to confirm the mesoporous structure, and XPS, H 2 -Chemisorption and Boehm titration to determine active sites and acidity. The results showed that high-surface-area active carbon support favors the formation of small platinum metallic particles, highly dispersed over the surface. The catalysts were active for guaiacol HDO performed in the laboratory at 200° C and 12 atm of H 2 in a Batch PARR reactor. Carbon was activated using phosphoric acid during the synthesis. The interaction between the peculiar acidity generated on the support by H 3 PO 4 , accompanied by the high hydrogenation capacity of the metallic platinum particles, enhanced catalytic activity, and selectivity for deoxygenated products. This research aims at developing an environmentally friendly catalyst to produce biomolecules of high aggregated value. HDO activated carbon biomass platinum Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 INTRODUCTION The imminent replacement of fossil fuels has led the scientific community to achieve efficient, economical, and environmentally friendly processes. We are thus committed to integrating various environmental aspects in the same industrial process, involving sustainable catalyst synthesis method and the use of renewable source for fuel production. The molecules derived from lignocellulosic biomass are polymeric networks with a high oxygen content, avoiding the possibility of being used as a renewable source of energy. At this point, hydrodeoxygenation (HDO) plays a leading role because it allows transformation to obtain molecules with the necessary calorific potential as a biofuel. The HDO process requires excess hydrogen and an appropriate heterogeneous catalyst that facilitates and accelerates the desired chemical reaction. In line with the global energy revolution, we propose that the intervening catalyst in the HDO reaction to obtain biofuel would also be a material produced from a renewable energy source, such as biomass industrial waste. The proposed process goes beyond the guidelines of the old linear economy, where each resource has a beginning and an end, to be more like modern processes founded on the concept of a circular economy. Thus, tending towards greater environmental sustainability, economic activity attempts to maintain or improve the environmental system by recycling or extending the durability of resources as much as possible, minimizing waste generation, and even reusing part of it (D´Amato et al. 2017 ; Wang et al. 2020 ). Large amounts of biomass waste are annually produced, leading to negative economic, environmental, and health impacts. The possibility of making profitable use of voluminous worldwide waste such as agricultural, forestry, and industrial waste, supports the concept of circular economy and sustainable growth. Lignocellulosic biomass is key to the ecological development of significant products such as chemicals, liquid fuels, and bioplastics. Replacing traditional feedstock with renewable biomass tends to reduce its carbon footprint. In addition, existing products can be substituted with safer manufacturing alternatives (Sheldon 2016 ). The green synthesis of nanomaterials (Omran et al. 2022; Lu et al. 2020) offers an approach to green chemistry and circularity, increasing benefits and reducing economic loss and environmental pollution. Current global alimentary trends in fruit and vegetable consumption leads to significant loss in the fresh and processing industries. The waste generated here mostly comprises seeds, skin or peel, rind, and pomace. These residues contain valuable bioactive compounds, proving a potential feedstock capable of replacing conventional raw material to synthesize a nanocatalyst (Su et al. 2022 ; Sagar et al. 2018 ). Lignocellulosic biomass can be treated by fast pyrolysis; yet subsequent handling is required to obtain efficient liquid fuel. The thermal conversion of this type of biomass results in an interesting mixture of condensable gases or bio-oils with a high number of oxygenated species present in different organic molecules, such as carboxylic acids, alcohols, phenols, aldehydes, ketones, esters, and ethers. Consequently, this bio-oil is immiscible with conventional fuels because of its high polarity; however, it is highly miscible with water. These aspects are responsible for the characteristic low calorific value of this bio-oil. Lignin pyrolysis oil can be upgraded by HDO (Huang et al. 2016 ; Hu et al. 2021 ; Teles et al. 2018 ; Jin et al. 2023 ; Elkasabi et al. 2014 ; Shu et al. 2019 ; Bharath et al. 2020 ; Li et al. 2020 ) to yield a mixture of aromatic compounds resembling liquid crude oil. The HDO process is commonly carried out at high hydrogen pressure. Huang et. al. ( 2016 ) focused on finding the optimal reaction conditions (temperature and hydrogen pressure) for upgrading pyrolysis bio-oil from pine saw dust using Zn/Pd/C catalyst. In this research, they found that increasing temperature resulted in major coke yield however the highest hydrocarbon content was found for treatments at 250°C and 14 atm. Guaiacol is a phenolic compound containing a methoxy functional group. It is one of the components most widely found in lignocellulosic bio-oil and the most representative due to the presence of both methoxy and hydroxyl groups. These are two particularly common oxygenated functional groups that, according to their molecular structure, induce steric effects. Hu et al. ( 2021 ) studied HDO conversion of guaiacol over three different zeolites using Pd as a catalyst. They found higher catalytic activity using Pd 2% /Hβ catalyst at 220°C, 30 atm of H 2 in 4 h of reaction time and concluded that there is an important synergetic effect between the size of metal nanoparticles and the acid sites of the catalyst, resulting in enhanced selectivity to cycloalkanes. Teles et al. ( 2018 ) reported that the performance of HDO is closely linked to the nature of the support, regardless of the model molecule used. They reported that the HDO of guaiacol mainly resulted in the formation of phenol and methanol over all the niobia-supported catalysts tested, but a higher selectivity for benzene was found over the Pd/Nb 2 O 5 catalyst. Noble metal catalysts are exceptional in the HDO process, although they are not a low-cost option, restricting their application in the industry. Jin et al. ( 2023 ) investigated the behavior of Ni-Pt/AC catalysts for the HDO of guaiacol using methanol and glycerol as a hydrogen source at 300°C and 100 atm in a batch reactor. They found that the bimetallic Ni-Pt/AC catalyst displayed a decrease in guaiacol conversion compared to the monometallic Pt catalyst. Notably, the Pt/AC catalyst exhibited exceptional performance, achieving a guaiacol conversion beyond 96% and higher selectivity for hydrogenated products (cyclohexanol and cyclohexanone) and phenol, in marked contrast to Ni which improved no catalytic activity. Elkasabi et al. ( 2014 ) analyzed HDO reactions from three types of biomass feedstocks (herbaceous grasses, woody biomass, and animal waste) over catalysts of Pt, Ru, and Pd supported over activated carbon. Platinum showed the highest upgrading efficiency, yielding the highest degree of deoxygenation. Our research group previously studied the HDO of guaiacol over a Pt-mesoporous siliceous catalyst, finding the optimal reaction conditions to convert guaiacol into a high-quality biofuel using low-loaded platinum-supported catalyst (0.5 wt. %) (Rivoira et al. 2021 ). On the other hand, activated carbon is a less expensive and more sustainable support since it can be synthesized from biomass waste extracted from the orange juice industry and subsequently activated by a chemical process with phosphoric acid (Ledesma et al. 2021 ). The current research focuses on upgrading pyrolysis bio-oil by the HDO of guaiacol over Pt-supported activated carbon catalysts. The reaction conditions and platinum load were the same as those used in our previous research (Rivoira et al. 2021 ). In addition, we evaluated whether the support acidity promotes the catalytic activity of the noble metal nanoparticles in the HDO of the oxygenated model compound derived from the biomass selected in this study. EXPERIMENTAL Synthesis of the activated carbon support Activated carbon samples (ACS) were synthesized by chemical activation of orange peels. The steps prior to activation were: (i) washing of oranges to remove dust and other remains and (ii) peeling. First, small pieces of orange peels were cut and placed in an oven at 100°C overnight for drying. The raw material was then crushed and minced. Subsequently, the samples were rinsed with warm water, dried, and screened to obtain the initial material. A fraction was then impregnated with 30, 40, or 50 wt. % solution of H 3 PO 4 , with the biomass to H 3 PO 4 weight ratio of 3:1 or 6:1 without resting time and with resting time at room temperature for 24 h. The samples were then heated in an electric oven. Temperature was increased from room temperature to 470°C at a rate of 3°C/min and held at this temperature for 1 h (Misnon et al. 2015 ; Wei et al. 2019 ; Gonzales-Garcia 2018). Afterwards, the synthesized material was cooled to room temperature. This was followed by the addition of deionized water to neutralize the surplus acid in the activated carbon. Finally, the ACS produced was placed in an oven to dry until reaching a constant weight, and its effectiveness was assessed. Table 1 lists all the synthesized samples along with their respective preparation characteristics. Table 1 Synthetized samples used as a catalyst support. Sample H 3 PO 4 acid solution concentration Acid/precursor ratio Rest time ACS 1 30% 3:1 24 h ACS 2 30% 3:1 0 ACS 3 30% 6:1 24 h ACS 4 30% 6:1 0 h ACS 5 40% 3:1 24 h ACS 6 40% 3:1 0h ACS 7 40% 6:1 24 h ACS 8 40% 6:1 0h ACS 9 50% 3:1 24h ACS 10 50% 3:1 0h ACS 11 50% 6:1 24h ACS 12 50% 6:1 0h Incorporation of platinum nanoparticles Platinum nanoparticles were incorporated by traditional wet impregnation method using chloroplatinic acid (H 2 PtCl 6 xH 2 O) as a platinum source. A solution of chloroplatinic acid in ethanol was added to the carbonaceous support in a rotary evaporator to achieve metal deposition and evaporating the ethanol in the solution. The soaked powder was dried overnight at 120°C and subsequently desorbed under nitrogen atmosphere. The desorption process was conducted from room temperature to 470°C at a heating rate of 4°C/min and maintained at 470°C for 5 h. The material was finally reduced with 20 mL/min H 2, using the same temperature program described above. All synthesized samples are referred to as Pt-ACS x. Characterization of catalysts A series of analyses and studies were conducted to determine the textural properties of the supports and catalysts. Surface area and porosity were analyzed with an ASAP 2020 instrument. All samples were outgassed before analysis. N 2 adsorption/desorption isotherms were obtained at -196°C. The specific surface area and pore size distribution of the materials were calculated by the BET method (S BET ) and BJH, respectively. Elemental analysis of platinum was performed by inductively coupled plasma-atomic emission spectroscopy (ICP-AES; VISTA-MPX) operated at high frequency, and Pt loading was close to 0.5 wt.% in all cases. X-ray diffraction (XRD) was used to categorize the framework structure of the supports and their behavior after metal incorporation. XRD patterns were obtained using a Philips X’Pert PRO PANalytical diffractometer operated with high-intensity CuKα X-ray radiation (40 mA and 45 kV) and a 0.5º to 5º scan technique range. The catalyst surface was analyzed by X-ray photoelectron spectroscopy (XPS). EDX analyses were done in a Jeol JSM 5410 microscope (Jeol, Tokyo, Japan). It was performed by a Microtech-Multilb3000 spectrometer equipped with an Al Kα X-ray source (1486.6 eV, 12 kV, 15 mA). Each signal was corrected using the C 1s reference at 284.8 eV. The platinum particle diameter was evaluated via Hydrogen Chemisorption analysis performed on a Chemisorb 2720 Micromeritics. The first step in the method measurement was to prepare the sample: 0.5 g of catalyst was reduced by 30 mL/min of an H 2 stream at high temperature (400°C) during 2 h, followed by a purge with a N 2 stream of 25 mL/min for further 0.5 h. After cooling, samples were titrated by H 2 pulses in a stream of N 2 until a constant output TCD signal indicated saturation. The average diameter of Pt particles was calculated assuming a spherical shape and stoichiometric ratio of H/Pt = 1. The accuracy of the results was above ± 1.5% with ± 0.5% reproducibility. From pulse chemisorption analysis, the active metal surface per gram of metal (MSAm in m 2 /g of metal) is obtained, therefore \(\:dp=\frac{{F}_{g}}{\rho\:\:MSAm}\:\frac{1\:{m}^{3}}{{10}^{6}{cm}^{3}}\:\frac{{10}^{9}nm}{1m}\) Eq. 1 where Fg is a geometric factor, and ρ (g/cm 3 ) the specific gravity of the active metal and dp the estimated mean crystallite (or particle) diameter in nm. ChemiSorb 2720 Operator’s Manual 272-42801-01 April 2009. Turnover frequency (TOF) was calculated according to the following equations: $$\:TOF=\frac{Converted\:molecules\:of\:guaiacol\:}{Active\:sites\:x\:h}\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:Eq.2$$ $$\:Converted\:molecules\:of\:guaiacol=\frac{Initial\:molecules\:of\:guaiacol\:x\:Conversion\:}{100}\:\:\:\:\:\:\:\:\:\:\:\:\:\:Eq.3$$ $$\:Active\:sites=\frac{\text{A}\text{c}\text{t}\text{i}\text{v}\text{e}\:\text{s}\text{u}\text{r}\text{f}\text{a}\text{c}\text{e}\:\text{a}\text{r}\text{e}\text{a}\:\text{o}\text{f}\:\text{}\text{}\text{m}\text{e}\text{t}\text{a}\text{l}\:\text{p}\text{e}\text{r}\:\text{g}\text{r}\text{a}\text{m}\:\text{o}\text{f}\:\text{s}\text{a}\text{m}\text{p}\text{l}\text{e}\:\left(\frac{\text{m}2}{\text{g}}\right)\text{x}\:\text{m}\text{a}\text{s}\text{s}\:\text{o}\text{f}\:\text{c}\text{a}\text{t}\text{a}\text{l}\text{y}\text{s}\text{t}\text{s}\:\left(\text{g}\right)\:}{Cross\:section\:area\:of\:Pt\:\left(m2\right)}Eq.\:4$$ where cross section area of Pt is 8x10 − 20 m 2 . The Bohem titration method was used to determine the surface acidity of solid catalysts (Boehm 1994 ; Vifttaria et al. 2019 ). Weak, moderate, and strong acid sites can be quantified by acid-base neutralization reactions with strong, moderate, or weak bases. This method allows determining and calculating each type of functional group on the support surface. Catalytic Activity The HDO of guaiacol was performed in a 600 mL stirred stainless steel batch reactor (4563 Parr). The catalytic activity was evaluated under 12 atm H 2 at 200°C. To avoid internal and external mass transfer limitations, a series of previous experiments were carried out. Commercial carbon catalysts and Pt-ACS-11 were used in this study under typical reaction conditions. The results are shown in the supplementary section (Figs. 1 S and 2 S). According to the results obtained by varying rpm and catalyst particle size, we chose to work at 360 rpm and sieve the catalyst to a size of 0.4 mm, thus ensuring no mass transfer limitations. Catalyst reduction is imperative because of the crucial importance of the oxidation state of noble metal nanoparticles. Then, 0.2 g of the reduced catalyst was added to the reactant mixture. To obtain a different guaiacol/catalyst mass ratio, the feedstock consisted of 50 mL of 1–3 v/v % solution of guaiacol (99% Sigma-Aldrich) in dodecane (99% Sigma-Aldrich). The components of the liquid products were analyzed using a gas chromatograph HP 5890 Series II GC and HP-5 column, and the products were identified with GC-MS. Guaiacol conversions were determined using an internal standard (n-decane). Experiments were performed three times to confirm reproducibility of the catalytic activity. RESULTS AND DISCUSSION Characterization of the catalysts N 2 adsorption–desorption and BET area analysis The structural and textural properties of the synthesized activated carbon are shown in Figs. 1 and Table 2 . The values in Table 2 were calculated using the BET and QSDFT methods. The N 2 adsorption–desorption isotherms showed the following results: AC materials from samples 7–12 exhibited type IV isotherms, characteristic of solids with mesoporous pore structures, while samples ACS 1–6 exhibited type I isotherms, corresponding to typical microporous materials, showing high gas adsorption at low pressures and no observable increase at higher relative pressures (Sing.et al. 2004). Regarding the phosphoric acid concentration and acid-precursor ratios used in the synthesis procedure, the activated carbons synthesized with the highest acid concentration and acid/precursor ratio, respectively, showed the most suitable structural and textural results. According to Higai et al. ( 2020 ), phosphate groups expand the structure, and mesopores are thus formed. This suggests that a higher acid concentration improves the support areas. The mechanism of phosphoric acid activation widens the micropores, thereby increasing the mesoporous volume, as shown in Fig. 2 , which displays the pore size distribution (PSD) (Higai et al. 2020 ; Martinez-Prieto et al. 2020). Better results were afforded when the precursor material was left in contact with the acid for a longer time (24 h) before washing and neutralization. Hence, if we compare the two types of materials synthesized (with and without resting time) using the same acid concentration and precursor ratios, higher areas were found for those kept in contact for 24 h. The hysteresis isotherm loops are H2(b) type. H2 hysteresis loops are given by complex pore structures where network effects are important. Particularly, the type H2(b) loop is associated with pore blocking and the size distribution of neck widths is broad. Hydrothermal synthesis with phosphoric acid probably produces a range of mesopores (as observed in the PSD analysis, Fig. 1 b) that have cavities with narrow necks (ink-bottle pores). According to Fig. 1 , ACS 11 and 12 showed the best isotherm results, presenting higher surface area and mesopore volume; therefore, ACS 11 reached 1429 m 2 /g (Table 2 ). Metal incorporation into the structure produces a slight decrease in N 2 adsorption compared to that of the pure carbonaceous support, decreasing the BET surface area of all materials. Table 3 shows the results obtained for catalysts with type IV isotherms (higher mesoporosity), whose surface areas were maintained at about 1000 m 2 /g, and their mesoporous character was retained after platinum incorporation in all cases, indicating small and well-dispersed active site nanoparticles, in agreement with XRD results (Fig. 2 ). To summarize the results and allow their comparison, only catalysts that yielded better surface area and higher mesoporosity are shown in Table 3 (Pt-ACS 7, 8, 9, 10, 11, and 12). On the other hand, Pt-SBA-15 (Ballesteros et al. 2019; Ledesma et al. 2021 ) and Pt-AC commercial catalysts were added to the characterization for a textural and catalytic comparative purpose. Table 2 Textural properties of all carbon supports. Sample S BET (m 2 /g) S mic (m 2 /g) S ext (m 2 /g) V t (cm 3 /g) V mic (cm 3 /g) V mes (cm 3 /g) AC-commercial 1100 ACS 1 900 856 44 0.43 0.42 0.01 ACS 2 856 815 41 0.40 0.39 0.01 ACS 3 950 908 42 0.52 0.50 0.02 ACS 4 920 867 53 0.50 0.49 0.01 ACS 5 1034 946 88 0.65 0.48 0.17 ACS 6 910 840 70 0.55 0.45 0.10 ACS 7 1020 800 220 0.62 0.48 0.14 ACS 8 980 866 114 0.67 0.48 0.19 ACS 9 1203 631 572 0.91 0.31 0.60 ACS 10 1003 608 395 0.75 0.30 0.45 ACS 11 1429 722 707 1.30 0.36 0.94 ACS 12 1251 715 536 1.10 0.31 0.79 S BET , total specific surface area; S mic , microporous area; S ext , mesoporous and microporous area; V t , total pore volume; V mic , microporous volume; V mes , mesoporous volume. Table 3 Textural properties of the catalysts. Sample S BET (m 2 /g) S mic (m 2 /g) S ext (m 2 /g) V t (cm 3 /g) V mic (cm 3 /g) V mes (cm 3 /g) Pt-AC commercial 920 - - - - - Pt-SBA-15 690 - - 1.10 - - Pt -ACS 7 1008 795 213 0.56 0.47 0.09 Pt -ACS 8 968 900 68 0.62 0.46 0.16 Pt -ACS 9 1165 613 552 0.89 0.30 0.59 Pt -ACS 10 991 603 388 0.71 0.28 0.43 Pt -ACS 11 1400 712 688 1.20 0.35 0.85 Pt -ACS 12 1223 710 513 1.00 0.30 0.70 S BET , total specific surface area; S mic , microporous area; S ext , external area; V t , total pore volume; V mic , microporous volume; V mes , mesoporous volume. Table 4 shows the elemental composition of the activated carbon analyzed by energy-dispersive X-ray spectroscopy (EDX). The composition of the synthesized activated carbon is listed. We observed the presence of P in all the samples. P concentration increases with the increase of the activating agent concentration. Table 4 EDX of the samples. Sample Element (wt.%) O Si P S C ACS 7 26.54 0.22 1.35 0.09 71.80 ACS 8 25.74 0.19 1.25 0.06 72.76 ACS 9 25.53 0.19 2.37 0.07 71.84 ACS 10 26.24 0.18 2.25 0.07 71.26 ACS 11 25.67 0.22 2.45 0.06 71.60 ACS 12 25.62 0.20 2.40 0.08 71.70 Hydrogen chemisorption In addition, hydrogen chemisorption confirmed that better Pt dispersion was achieved in samples with higher surface areas (Table 5 ). Pt-ACS-11 showed the best dispersion and lowest Pt particle size. Pt-ACS 1, 2, 3, 4, 5, and 6 materials are not shown in Tables 3 , 4 and 5 because of their lower surface area and higher microporous surface (type I isotherm). Table 5 Hydrogen chemisorption results. Catalyst Average crystal size, nm Active surface area of ​​metal (per gram of metal) Chemisorbed volume per gram of sample cm 3 /g Active surface area of ​​metal (per gram of sample) m 2 /g of sample % Dispersion Pt-AC Commercial 4.0 71.1 0.16 0.35 28 Pt SBA15 2.7 105.4 0.24 0.53 42 ACS7 2.8 101.6 0.23 0.51 40 ACS8 3.0 94.8 0.22 0.47 38 ACS9 2.3 123.7 0.29 0.62 49 ACS10 2.8 101.6 0.23 0.51 40 ACS11 1.9 149.7 0.35 0.75 59 ACS12 2.2 129.3 0.30 0.65 51 XRD XRD characterization confirmed the distinctive nanostructure of the synthesized carbons. Figure 2 shows wide-angle XRD patterns of all Pt-supported samples. Two typical broad graphite peaks can be seen in all catalysts at 26° and 43° of 2 theta corresponding to the (002) and (100) planes of the carbonaceous support (Osman et al. 2019 ). Metallic Pt characteristic signals appear at 39.8°, 46.3°, 67.7°, 81.3°, and 85.8° of 2θ corresponding to the (111), (200), (220), (311), and (222) planes of face-centered cubic (FCC) metallic platinum facets (PDF 01-087-0640) (Li et al. 2014 ; Hernadez-Morales 2020; Hämäläinen 2008). As expected, the catalysts with higher surface area (Table 3 ) showed better dispersion of the metallic platinum particles. The absence of visible peaks and the well-resolved (002) and (100) plane reflections are attributed to a better dispersion of the metallic platinum particles without modifying the overall structure. As shown in Fig. 2 , higher Pt dispersion is suggested for Pt-ACS 7, 9, 10, 11, and 12 catalysts according to the absence of a typical Pt signal at 39.8° of 2θ. Nevertheless, a relatively significant peak appeared at this 2θ intensity for Pt-ACS 1, 2, 3, 4, 5, and 6 catalysts, indicating a rather large number of atomic clusters. XPS Metal dispersion strongly affects the catalytic performance of materials, but the characteristics of the metal phase in the catalysts play a crucial role in determining their performance as active sites on the carbon surface (Ramos et al. 2017 ). Table 6 shows the data extracted from XPS analysis of the synthesized catalysts with the best textural properties. Those parameters were considered because they are important for the development of high catalytic activity. According to the analysis of XPS results, the C1 excitation indicates that various species were found on the surface of the carbon. Table 6 XPS analysis of the catalysts. Sample C1s Si2p3 O1s P2p Pt4f 7/2 Pt 0 (%); Pt + 2 (%) Pt-ACS 7 284.4 (55) 285.6 (23) 288.4 (22) 531.7(60) 533.4(24) 535.7(16) 134.5 72.4 (83); 73.5 (17) Pt-ACS 8 284.4 (54) 285.5 (24) 288.3 (22) 531.6(59) 533.4(25) 535.7(16) 134.5 72.2 (73); 73.3 (27) Pt-ACS 9 284.5 (51) 285.7 (28) 288.2(21) 531.5(65) 533.3(23) 535.6(12) 134.4 72.1 (85); 73.3 (15) Pt-ACS 10 284.4 (53) 285.4 (25) 289.1 (22) 531.5(59) 533.3(23) 535.6(18) 134.5 72.2 (77); 73.3 (23) Pt-ACS 11 284.4 (51) 285.6 (25) 288.3(24) 531.5(70) 533.4(20) 535.8(10) 134.6 72.5 (89); 73.5 (11) Pt-ACS 12 284.3 (53) 285.5 (27) 288.5(20) 531.6(65) 533.4(25) 535.6(10) 134.7 72.3 (88); 73.5 (12) Pt-SBA-15 103 532.8 -- 71.2 (87); 72.8 (13) The signals could be assigned to graphitic carbon at 284 eV, carbon species in alcoholic groups (C-O-H) at 286 eV, and ether groups (C-O-C), C-O-P bonding, and/or carbon in carbonyl groups (C = O) at 288 eV. The presence of oxygenated carbon indicates a reaction between carbon and phosphoric acid (Puziy et al. 2008 ). The pair of peaks centered on 71 eV and 72 eV in the binding energy spectrum corresponds to Pt 0 and Pt + 2 , respectively (Toda et al. 1999 ; Waisaka et al. 2006; Radev et al. 2012 ). Although all catalysts were subjected to an exhaustive reduction method, it was found that a small part of Pt was in an oxidized state. Analysis of the peak areas reveals a substantial presence of metallic Pt in the prepared samples, with Pt 0 content exceeding 70% in all instances. Boehm titration Support acidity intervenes in the reduction of metal particle size, and metal dispersion increases because of metal-support interaction. In this case, the carbon acidity of the surface was conferred by activation with H 3 PO 4 during the synthesis of the materials. To quantify the number of strong and weak surface acidic sites generated in the Pt catalyst during the carbonization and activation stages, the Boehm method was applied. The Boehm method offers a quantitative assessment of the quantity of acid sites on the surface of a coal material. The choice of this technique is because it is relatively simple and inexpensive compared to other analytical techniques. The Boehm method has been widely used and validated in the scientific literature, showing accuracy and reliability (Kim et al. 2016: Ederer et al. 2016 ). Table 7 shows the difference between the concentration of acidic groups detected by NaHCO, Na 2 CO 3 , and NaOH. According to the literature (Kim et al. 2016: Ederer et al. 2016 ), NaHCO can only detect strong acid sites, including carboxylic and sulfonic groups. Sodium hydroxide (NaOH) neutralizes carboxylic, phenolic, and lactonic groups, while sodium carbonate (Na 2 CO 3 ) neutralizes carboxylic and lactonic groups. The values shown in Table 7 indicate that, although all the evaluated catalysts present strong acid sites and that the acid sites are mainly oxygen-containing groups, the Pt-ACS 11 catalyst is the most acidic, showing a trend with the type of activation and the concentration of acid used in the activation step during synthesis (Tables 1 and 4 ). Table 7 Boehm titration results [mmol/g]. Sample carboxylic a lactonic b phenolic c all Pt-ACS 7 0.8 0.5 0.7 2.2 Pt-ACS 8 0.6 0.4 0.6 1.6 Pt-ACS 9 0.9 0.7 0.7 2.3 Pt-ACS 10 0.6 0.3 0.5 1.4 Pt-ACS 11 1.4 0.6 0.6 2.6 Pt-ACS 12 1.2 0.6 0.5 2.3 a Strong acid sites; b Moderate acid sites; c Weak acid sites. Catalytic activity According to the results obtained from the characterization study, the materials with the best textural and physicochemical properties were chosen for testing in the HDO of guaiacol. The catalytic activity was compared with that of Pt-SBA-15 (mesoporous silica support) and Pt-commercial activated carbon. Figure 3 shows the catalytic activity in the HDO reaction of guaiacol using different mass ratios of guaiacol and catalyst. Among the synthesized catalysts, Pt-ACS 11 and 12 showed the highest conversions in all cases, followed by Pt-ACS 9 and 7. In principle, we can observe a direct correlation with the greater surface area and better characteristics of the support and the catalyst, both structural and physicochemical, such as a greater proportion of reduced platinum species, smaller metallic particle size, and good dispersion. As can be seen in the catalytic activity, the catalysts with higher mesoporosity increase conversion. Therefore, it was necessary to obtain a greater quantity of mesoporous in the synthesis process. In these mesoporous catalysts the reaction probably occurs mainly in the mesopores than inside micropores; this can be understood in terms of the mass diffusion limitations. It’s probably that Pt nanoclusters insert in mesopore framework (due to the size of the crystallite, it would not enter the micropores), therefore, when adding the metal, the mesopore volume and the area decrease mainly than micropore volume (see Table 3 ). Then the reaction occurs where the active sites are located (inside mesopores). If we analyze the effect of the substrate/catalyst mass ratio, we can observe that in the case of a low guaiacol/catalyst mass ratio of 2.8, conversions are high, but not much higher than those when a higher ratio is used, for example of 5.6. This suggests that in the first case, there is an excess of catalyst and that it does not translate into greater conversion. Similarly, when we increased the ratio to 8.4, we observed a decrease in conversion in all cases. Industrially, we consider that an average ratio of 5.6 is appropriate for comparing the catalysts. Figure 4 compares the activity of the most active catalyst synthesized in this study and two catalysts with the same loading of platinum but using a commercial activated carbon support and an SBA-15 support synthesized in a previous work (Rivoira et al. 2016). Figure 4 shows that Pt-ACS 11 is more active than Pt-SBA-15, in addition to the fact that the activated carbon contemplates an environmental (eco-friendly) and, consequently, an economical advantage. The difference in activity between Pt-ACS 11 and these two catalysts must be analyzed in greater depth, considering the characteristics of the support, the nature of the surface, and its acidity. Pt-ACS 11 shows the highest conversion in all cases. It is evident that by increasing the ratio of the mass of guaiacol and the catalyst, greater differences are observed in the conversion between the different catalysts, especially at shorter times. For this reason, the intermediate guaiacol/catalyst ratio of 5.6 is more suitable for comparison. To compare the activity of the synthesized catalysts more precisely, the turnover frequency (TOF) was calculated considering the number of converted molecules per Pt metal site (Eq. 2, Eq. 3 and Eq. 4); the active surface area of Pt was obtained by hydrogen chemisorption (Table 5 ). Table 8 shows the results. TOF was calculated at two different reaction times, 200 and 400 min, and for the three guaiacol/catalyst ratios. In Table 8 , another TOF was calculated using only the acid sites (total and strong) to relate the catalytic activity to the two types of active sites (metal and acids), and thus interpret and correlate the conversion results with the nature of the catalytic surface of the various materials. According to the TOF values ​​for all guaiacol/catalyst ratios, Pt-ACS 11 and Pt-ACS-12 are the most active followed by Pt-ACS-9 and 7. This trend is more evident at higher ratios. The increased activity can be easily attributed to the structural characteristics and properties of the catalysts. Catalysts whose supports have greater surface area and better mesoporosity allowed better dispersion of the platinum species, the active sites of the hydrogenation/hydrogenolysis reaction. The TOF values ​​at 400 min are almost always lower than those at 200 min, indicating that the reaction rate decreases as the conversion increases, probably due to the formation of products that block the active centers and compete. Pt-ACS 11 is, from the point of view of its physical and chemical properties, the best catalyst: it has the greatest surface area, the best dispersion of Pt, and the smallest metal particle size, in addition to the greatest proportion of reduced Pt, which is known to be required for the hydrogenation of guaiacol. However, in some cases, the TOF of Pt-ACS 12 is greater than that of Pt-ACS 11. This indicates that the reaction is not as sensitive to the dispersion of Pt, or that there may be another factor involved in the mechanism. To elucidate this, we calculated the TOF in relation to the acidic sites of each catalyst. The acidic sites were calculated by Boehm titration; values ​​are listed in Table 7 . The TOF of the acid sites were calculated for the total number of acid sites and strong acid sites. If we consider the values in Table 8 , the trend is different for both types of sites, i.e., the highest TOF for the total acid sites is found for the most active catalysts Pt-ACS 11 and 12 for the three guaiacol/catalyst ratios. However, this trend is reversed when we calculate it using strong acid sites. This suggests that the active acid sites of this reaction are sites of medium acidity and not sites of strong acidity. Paying special attention to both acidic and metallic TOF values ​​at the highest guaiacol/catalyst ratios (more guaiacol/less catalyst), it can be observed that Pt-ACS 11 is the most active catalyst. In addition, there is a synergistic effect between the platinum sites and the medium acid sites. Table 8 TOF of the catalysts. Catalyst TOF2.8 TOF5.6 TOF8.4 TOF2.8 Acid sites, 200 min TOF5.6 Acid sites, 200 min TOF8.4 Acid sites, 200 min % HDO min min min 200 400 200 400 200 400 Total Strong Total Strong Total Strong Pt-ACComm. 440 370 146 Pt-SBA-15 495 374 191 Pt-ACS7 310 196 475 376 329 342 0.29 0.82 0.45 1.25 0.31 0.87 218 Pt-ACS8 208 154 275 208 103 125 0.25 0.68 0.33 0.90 0.12 0.34 110 Pt-ACS9 308 190 527 383 477 441 0.34 0.88 0.58 1.51 0.53 1.36 205 Pt-ACS10 245 169 226 155 155 156 0.37 0.86 0.42 0.99 0.23 0.55 109 Pt-ACS11 329 204 387 683 683 491 0.39 0.73 0.70 1.32 0.81 1.52 300 Pt-ACS12 345 213 407 654 654 522 0.40 0.77 0.68 1.31 0.76 1.46 292 TOF calculated considering the number of converted molecules per platinum metal site (col 1–3) at 200 and 400 min of reaction time, and TOF calculated considering the number of converted molecules per total and strong acid sites (col. 4–6). In all cases for the three guaiacol/catalyst ratio. Col.8 shows TOF for HDO products. According to the main reaction products identified by GC chromatography in this study, a simplified scheme for the HDO of guaiacol is shown in Scheme 1 . Phenol, anisole, catechol, benzene and cyclohexane were identified. Many other peaks corresponding to heavy products and/or oxygenated products were observed at high retention time in the chromatography, they were grouped as “other products” since they appeared in very small quantities or were difficult to identify. Toluene and methyl cyclohexene could be formed according to Ghampson et.al ( 2012 ) but were not detected in this study. The evolution of the reaction explained by the mechanism proposed in Scheme 1 arises from the identified main products mentioned above and the understanding of three possible pathways: demethylation (DME), demethoxylation (DMO), and dehydroxylation (DHY) of guaiacol. For instance, C. A. Teles et al. ( 2022 ) reported that the HDO reaction of guaiacol over different supported Pd catalysts may occur as follows: the methoxy group removal from guaiacol to produce phenol can take place by direct DMO producing methanol, or indirectly by DME of anisole (formed by DHY of guaiacol) producing methane, or by DHY of catechol (formed by DME of guaiacol) releasing water. Thus, phenol can be considered a main product or an intermediate for further deoxygenation in guaiacol HDO. Lai et al. ( 2016 ) proposed a complex mechanism for the HDO of guaiacol, including these three pathways over Ni@Pd and Ni@Pt bimetallic catalysts involving formation of xylenols and xylenes. Methyl transfer (conversion of methoxy to a methyl group instead of methane) may occur in anisole to produce cresol followed by subsequent methylation, resulting in xylenol. This pathway can be explained in terms of the acidic properties of the support and the noble metal catalyst (Gutierrez et al 2009 ; Bui et al 2011 ; Nimmanwudipong et al. 2011 ). Anisole can also be deoxygenated by DMO to form benzene, but direct transalkylation may occur, also affording xylenol, as proposed by Lai et al. ( 2016 ). These products were not favored under our reaction conditions. The latest stage of the mechanism occurs specifically in consequence of the presence of platinum active sites involving the appearance of the two deoxygenated and desired products (benzene and cyclohexane), in which phenol can be further hydrodeoxygenated, forming benzene followed by the hydrogenation of the aromatic ring to yield cyclohexane (He et al. 2018 ; Gao et al. 2015 ). These consecutive reactions agree with those proposed by Zhu et al. ( 2011 ). They reported that acid sites catalyze methyl transfer, while metals catalyze demethylation and hydrodeoxygenation. Product yield and selectivity were calculated considering 100% of the products identified in the chromatography, including "other" products. Guaiacol HDO products observed in this work seem to correspond to a series of consecutive hydrodeoxygenations, as proposed in the literature [Teles et al. 2018 , Ghampson et al. 2012 ) (see Scheme 1 ). Demethylation occurs to yield catechol, but it is likely to occur in a smaller proportion. The selectivity of the synthesized catalysts for the different products of guaiacol HDO is presented in Fig. 5 . Phenol was the main product in all cases, followed by anisole and catechol, according to the reaction steps described in Scheme 1 . Then, the desired deoxygenated products such as benzene and cyclohexane were observed for all catalysts. However, the most active catalysts, Pt-ACS 11 and 12, obtained the highest selectivity of 18% and 12%, respectively, followed by Pt-ACS 9 and 7 (10%). Figure 6 compares the selectivity of Pt-ACS 11 with Pt-SBA-15 and Pt-AC Commercial. The main products of the three catalysts were phenol, anisole, and catechol; phenol and anisole are direct products of HDO with consecutive formation of benzene and cyclohexane. All these products (phenol, anisole, benzene, and cyclohexane) were considered to calculate the HDO ratio, which is a percentage of the guaiacol conversion to deoxygenated products, since there is a portion of the reagent that goes to the undesired pathway, producing catechol and other products. HDO % was calculated as follows: HDO % = (selectivity of phenol + anisole + benzene + cyclohexane) x guaiacol conversion/100. It is important to clarify that phenol and anisole are products from partial dexoygenation of guaiacol while benzene and cyclohexane from total deoxygenation. The selectivity to benzene and cyclohexane for Pt-ACS 11 was much higher than that for Pt-SBA-15 and Pt-AC Commercial catalysts. The TOF of HDO % with respect to the Pt active sites was calculated; the results are shown in the last column of Table 8 . As expected, the Pt-ACS 11 catalyst shows the highest TOF, followed by Pt-ACS 12. The TOF values ​​obtained for Pt-SBA-15 and the commercial catalyst are lower. The last two catalysts present a large proportion of catechol, indicating that the demethylation pathway is favored in these catalysts. Comparing our results, we see that they are in good agreement with those found in the literature similar systems and conditions. Teles et al. ( 2022 ) investigated the HDO of guaiacol over supported Pd catalysts at atmospheric pressure and a temperature of 300°C. Demethoxylation which afforded phenol was the major reaction pathway for all catalysts, showing only a slight contribution from the demethylation reaction. Yet, a significant dehydroxylation reaction was still found in catalysts with Pd supported on ZrO 2 and TiO 2 . Author reported that the hydroxyl group was strongly adsorbed on the catalyst surface, which could block the catalytic sites and hinder further conversion of phenol, ultimately leading to reduced deoxygenation rates. The conclusion drawn was that demethylation with the production of catechol as a reaction intermediate was the most straightforward reaction. In this work, however, phenol and anisole were the main products yielded, which suggests that phenol was directly formed through cleavage of CAr–OCH3 bond in all catalysts. Following Teles et al. ( 2022 ) anisole was afforded by dehydroxylation of guaiacol. As the cleavage of CAr–OH bond requires higher energy that that of CAr–OCH3 bond (414 and 356 KJ/mol, respectively) (Bui et al. 2011 ), demethoxylation is expected to produce phenol over dehydroxylation. This result was consistent with ours. Ghampson et al. ( 2012 ) researched the HDO of guaiacol in a batch reactor over SBA-15 silica-supported molybdenum nitride catalysts at 300°C and 49 atm of H 2 pressure. SBA-15 silica-supported catalysts transformed guaiacol directly to phenol through demethoxylation with no production of catechol. The lower catechol production with the SBA-15 silica support was significant to minimize coking reactions and reduce consumption of hydrogen. They obtained 44% conversion with 30% yield of phenol. All catalysts in this study yielded more phenol than catechol. SBA-15 support shows Si-OH groups, which act as Lewis acid sites, allowing demethoxylation. In this study, with the carbons activated with phosphoric acid, the acidity obtained and determined by Bohem titration showed that direct demethoxylation is also favored. The commercial carbon support showed greater ability for demethylation, yielding catechol, transformed into phenol through hydrogenolysis (Saidi et al 2014 ; Sepulveda et al 2011; Yang et al. 2014 ). Pt/C catalyst was studied in the HDO of guaiacol in a fixed-bed reactor at different temperatures and atmospheric pressure, affording high kinetic constants in the HDO of guaiacol. The primary products of the liquid-phase reaction were phenol, catechol and cyclopentanone (Zhu et al.2011). The HDO of guaiacol was also studied on La-modified Pt/Al 2 O 3 batch reactor at 215°C and 30 atm, obtaining 80% of HDO at 100% conversion (Escobar et al. 2023 ). It is widely agreed that the HDO reaction requires a bifunctional catalyst, i.e., a metal associated with a specific support close to an acid site. Some studies suggest that the reaction occurs on the metal sites close to an acid site. Figure 7 summarizes the comparison between the catalysts and correlates the guaiacol conversion with the HDO ratio and the total acidity of the catalysts synthesized, using the activated carbon supports. The higher HDO ratio correlates well with the higher conversion and with total acidity. The good performance of activated carbon could be linked to the incorporation of phosphorus species in the structure. Li et al. ( 2018 ) have explored the impact of phosphorus on the hydrogenation process, employing a P-doped Ni/Al 2 O 3 catalyst. The results indicate that the incorporation of phosphorus species could act as a catalytic promoter, enhancing the activity and selectivity of the catalyst. Chen et al. ( 2020 ) also investigated the hydrogenation of nitrobenzene to aniline using phosphorus-doped carbon nanotubes and discovered that phosphorus could act as a catalytic promoter. Subsequently, Yangcheng et al. ( 2023 ) found that the presence of active P species in Pd/PHS led to the selective conversion of vanillin and, consequently, improved the yield of hydrodeoxygenated compounds. These studies have demonstrated the benefits of the presence of phosphorus in HDO reactions. Dieu-Phuong et al. (2020) studied the hydrodeoxygenation of oleic acid over P-modified catalyst and observed that the HDO reaction is highly dependent on the potency and arrangement of acid sites. Therefore, the introduction of phosphoric acid enhances the reactivity of the electrophilic acid center, effectively activating the oxygen atom of some of the functional groups present on the carbon surface, e.g. the acyl bond, making it susceptible to attack by hydrogen atoms (Scheme 2 ). Hence, we could explain the better performance of our catalysts due to the synergy between the acid sites and metal sites in the guaiacol HDO reaction. In the current investigation, phosphorus was incorporated during the synthesis of carbon as an activating agent, and P compounds were incorporated into the material without the need for post-synthesis incorporation. The presence of phosphorous, responsible for the acidity of the surface materials, could contribute to the improved performance of the HDO reaction. The presence of oxygenated surface groups, such as phenolic compounds and carboxylic acids, on the AC surface facilitates interaction with the oxygen unshared pairs of electrons in phosphoric acid and with phosphate anions. They probably react to produce an acyl group (R-CO-) generated by the elimination of hydroxyl group from a surface carboxylic acid by phosphorous action (Scheme 2 ). The acyl group generally exists in its cationic form because its radical form is particularly unstable and decomposes quickly. In the mechanism proposed, the cationic acyl generated (Lewis acid site) can accommodate the unshared electrons present in the guaiacol hydroxyl group (–OH) or in its methoxy group (–O-CH3) due to its electrophilic nature. Nucleophilic attraction (ion–dipole) keeps the substrate molecule adsorbed over the carbon surface. The –OH o –O-CH3 guaiacol bond is susceptible cleavage by the entry of hydrogen adsorbed on the neighboring Pt metal site. Analogous mechanisms may occur with other carbon groups that, in a similar way, interact with the phosphorous species, attracting the guaiacol molecule and its intermediates. On the other hand, chemisorption of H 2 showed that the Pt nanoparticles were well dispersed on the support material. Yangcheng et al. ( 2023 ) studied the dispersion of Pd metal particles on a zeolite, with and without phosphorus species. They observed that in their nanoparticle-supported catalyst, there was a shift towards a higher dispersion, achieving nanoparticles with a size around 1.5 nm. They found that the presence of phosphorus enhanced Pd dispersion on the support. Thus, we believe that the acidity incorporated in the activation stage of the catalyst through phosphoric acid, has a positive influence on the dispersion of the metallic particles. Finally, the joint effect of the higher particle dispersion (which could be attributed to acidity and the large surface area obtained for the synthesized catalyst) and the contribution of acidity to HDO reactions make the Pt particles over the active carbon a particularly efficient catalyst. Considering the low manufacturing cost, we could affirm that it is a promising material for the HDO reaction of biofuels. CONCLUSIONS The HDO of guaiacol was performed using platinum-activated carbon as a catalyst. The raw material for carbon was obtained from orange peel waste, and the carbonaceous supports were activated by simple impregnation using H 3 PO 4 as an activating agent, which is a critical aspect for enhancing HDO performance. The HDO results were better than those obtained for the Pt-SBA-15 catalyst. In addition, synthetized activated carbons are very low cost and eco-friendly since they are obtained from local industrial waste. Highly dispersed Pt active sites were key to the catalytic performance, probably due to the following reasons. i) High Pt dispersion provides a high metal surface available and easily reached by the substrate (reactive) to form the activated complex during the chemical reaction attributed to the small Pt particle size. ii) The acidic nature of the catalysts had a synergistic effect with metal sites. Activation of the materials using H 3 PO 4 seemed to be the main reason for the alterations in the as-synthetized materials, interacting with the support and modifying its acidity, improving the catalyst itself. The characterization of acidity was performed by a simple titration method, in which the most acidic catalyst was the most active in the HDO of guaiacol, reaching 88 mol% of guaiacol conversion. However, a more important result was the selectivity discovered, since 70% of the guaiacol conversion was toward HDO products. In this study it was revealed that the presence of acidity over the surface and the presence of P species are the main reasons for the high activity displayed by the Pt-supported active carbon in the HDO of guaiacol. Declarations ACKNOWLEDGMENT NANOTEC, CONICET, Universidad Tecnológica Nacional, Maestro López y Cruz Roja Argentina. We acknowledge the financial support provided by CONICET Argentina, PIP CONICET 11220210100325. 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(2019) Upgrading phenolic compounds and bio-oil through hydrodeoxygenation using highly dispersed Pt/TiO 2 catalyst. Fuel. 239:1083-1090. https://doi.org/10.1016/j.fuel.2018.11.107 Sing KSW, William RT (2004) Physisorption Hysteresis Loops and the Characterization of Nanoporous Materials. Adsorpt. Sci. Technol. 22:773-782. https://doi.org/10.1260/0263617053499032 Su G, Chan C, He J (2022) Enhanced biobutanol production from starch waste via orange peel doping. Renew. Energ. 193:576-583. https://doi.org/10.1016/j.renene.2022.04.096 Teles CA, de Souza PM, Rabelo-Neto RC et al. (2018) Catalytic upgrading of biomass pyrolysis vapors and model compounds using niobia supported Pd catalyst. Appl. Catal. B: Environ. 238:38-50. https://doi.org/10.1016/j.apcatb.2018.06.073 Teles CA, de Souza PM, Rabelo-Neto RC, Teran A, Jacobs G, Vilela Weikert C, Magriotis ZM, Gonçalves VO,. Resasco DE. Noronha FB (2022) Reaction pathways for the HDO of guaiacol over supported Pd catalysts: Effect of support type in the deoxygenation of hydroxyl and methoxy groups. Molecular Catalysis 523:111491. https://doi.org/10.1016/j.mcat.2021.111491. Toda T, Igarashi H, Uchida H et al (1999), Enhancement of the Electroreduction of Oxygen on Pt Alloys with Fe, Ni, and Co. Soc. 146:3750-3756. https://doi.org/10.1149/1.1392544 Vifttaria M, Nurhayati, S, Anita J (2019) Surface Acidity of Sulfuric Acid Activated Maredan Clay Catalysts with Boehm Titration Method and Pyridine Adsorption-FTIR. Phys.: Conf. Ser.; 1351:012040. https://doi.org/10.1088/1742-6596/1351/1/012040 Wakisaka M, Mitsui S, Hirose Y et al (2006) Electronic Structures of Pt−Co and Pt−Ru Alloys for CO-Tolerant Anode Catalysts in Polymer Electrolyte Fuel Cells Studied by EC−XPS. J Phys Chem B 110:23489–23496. https://doi.org/10.1021/jp0653510 Wang H, Schandl H, Wang X et al. (2020) Measuring progress of China's circular economy. Resour. Conserv. Recycl. 163:105070. https://doi.org/10.1016/j.resconrec.2020.105070 Wei Q, Chen Z, Cheng Y et al (2019) Preparation and electrochemical performance of orange peel based-activated carbons activated by different activators. Colloids Surf. A: Phys. Eng. Asp. 574:221-227. https://doi.org/10.1016/j.colsurfa.2019.04.065 Yang Y, Ochoa-Hernandez C, de la Peña O’Shea VA, Pizarro P, Coronado JM, Serrano DP (2014) Effect of metal–support interaction on the selective hydrodeoxygenation of anisole to aromatics over Ni-based catalysts. Appl. Catal. B-Environ. 145:91–100. https://doi.org/10.1016/j.apcatb.2013.03.038. Yangcheng R, Cui Y, Luo S et al (2023) Hierarchical pore-trapped and hydrogen-bonded phosphoric acid in Pd-supported zeolite for the efficient aqueous hydrodeoxygenation of lignin derivatives at ambient temperature. Micropor Mesopor Mat 350:112460. https://doi.org/10.1016/j.micromeso.2023.112460 Zhu X, Lobban LL, Mallinson RG, Resasco DE (2011) Bifunctional transalkylation and hydrodeoxygenation of anisole over a Pt/HBeta catalyst. J. Catal. 281:21-29. https://doi.org/10.1016/j.jcat.2011.03.030 Schemes Schemes are available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files SupplementaryFile.docx Scheme1.png Scheme 1: Simplified scheme of the products obtained after guaiacol conversion. Scheme2.png Scheme 2: Acyl group on the active carbon surface. Cite Share Download PDF Status: Published Journal Publication published 31 Dec, 2024 Read the published version in Clean Technologies and Environmental Policy → Version 1 posted Editorial decision: Revision requested 15 Oct, 2024 Reviews received at journal 13 Oct, 2024 Reviews received at journal 02 Oct, 2024 Reviewers agreed at journal 22 Sep, 2024 Reviewers agreed at journal 11 Sep, 2024 Reviewers invited by journal 11 Sep, 2024 Editor assigned by journal 07 Sep, 2024 Submission checks completed at journal 30 Aug, 2024 First submitted to journal 29 Aug, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4999409","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":357514213,"identity":"3b8d2274-5b7a-4ee4-acd5-da2582155686","order_by":0,"name":"Lorena P. Rivoira","email":"","orcid":"","institution":"Universidad Tecnológica Nacional, Maestro López y Cruz Roja Argentina","correspondingAuthor":false,"prefix":"","firstName":"Lorena","middleName":"P.","lastName":"Rivoira","suffix":""},{"id":357514214,"identity":"fe2401fc-d052-4d4d-8165-9642421a0503","order_by":1,"name":"Brenda C. Ledesma","email":"","orcid":"","institution":"Universidad Tecnológica Nacional, Maestro López y Cruz Roja Argentina","correspondingAuthor":false,"prefix":"","firstName":"Brenda","middleName":"C.","lastName":"Ledesma","suffix":""},{"id":357514215,"identity":"7a889c46-198c-44a5-9815-d34618fac735","order_by":2,"name":"María V. Fraire","email":"","orcid":"","institution":"Universidad Tecnológica Nacional, Maestro López y Cruz Roja Argentina","correspondingAuthor":false,"prefix":"","firstName":"María","middleName":"V.","lastName":"Fraire","suffix":""},{"id":357514216,"identity":"91dccdb9-6f8c-4bdd-8172-fac3a31a0f1a","order_by":3,"name":"Verónica A. Valles","email":"","orcid":"","institution":"Universidad Tecnológica Nacional, Maestro López y Cruz Roja Argentina","correspondingAuthor":false,"prefix":"","firstName":"Verónica","middleName":"A.","lastName":"Valles","suffix":""},{"id":357514217,"identity":"ebf40bcf-5de4-4ed1-8706-fada3c1960c5","order_by":4,"name":"Marcos B. Gómez Costa","email":"","orcid":"","institution":"Universidad Tecnológica Nacional, Maestro López y Cruz Roja Argentina","correspondingAuthor":false,"prefix":"","firstName":"Marcos","middleName":"B. Gómez","lastName":"Costa","suffix":""},{"id":357514218,"identity":"84b72419-e011-4fee-8c58-7699120480a3","order_by":5,"name":"Andrea R. Beltramone","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABBklEQVRIie3PsUrDQBzH8X8IZIrteiKkr/APQhchL+ISCNQloU4l4OAQcLK4tuhD+AAdfuXgXELmgxZMF+e6iIvgFdosJlKcHO47HH9y9+EuRDbbf0yQg/3o1Hnz2fuVEPbG5bI5fSTxxFGk/1hAvi+iy/5ZofLlIiJ+nYK2E2m20ErEWsXAW5LNn9RIm4FY9WJnVkkSVdx+jU4ZgJs963S42po3svLZPbmTRGW7GOixOYdbQ8Yf1ziQL0MGHYR1an4fcneLRw1xDOEOEq4Vo8RLNp+NzgWQ+Kcq5eV9deWHHSRYFZs6x032IJKNeWIU9GQZ1p+TiyDoID/ydwsOg81ms9n+1jfsP20OIKcEwAAAAABJRU5ErkJggg==","orcid":"","institution":"Universidad Tecnológica Nacional, Maestro López y Cruz Roja Argentina","correspondingAuthor":true,"prefix":"","firstName":"Andrea","middleName":"R.","lastName":"Beltramone","suffix":""}],"badges":[],"createdAt":"2024-08-29 17:40:30","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4999409/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4999409/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10098-024-03119-z","type":"published","date":"2024-12-31T15:57:46+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":65637784,"identity":"6c943627-7b89-41e7-9b00-7ffec4edc871","added_by":"auto","created_at":"2024-09-30 18:49:38","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":107157,"visible":true,"origin":"","legend":"\u003cp\u003ea) N\u003csub\u003e2\u003c/sub\u003e adsorption isotherms of all carbon-synthesized supports. b) Pore size distribution of the samples using QSDFT methods (PSD was obtained using slit and cylindrical pore kernels from Quantachrome software).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4999409/v1/c93c9fee5738a760fe19aed6.png"},{"id":65639016,"identity":"091290c8-3939-41c5-8d7b-4af4f6ab8d8a","added_by":"auto","created_at":"2024-09-30 19:05:39","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":35009,"visible":true,"origin":"","legend":"\u003cp\u003eXRD patterns of all the catalysts.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4999409/v1/8c36568389afa6f49e584bfb.png"},{"id":65639017,"identity":"67bdbdba-5a87-4c9b-96df-e462bc2773e4","added_by":"auto","created_at":"2024-09-30 19:05:39","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":104229,"visible":true,"origin":"","legend":"\u003cp\u003eCatalytic activity of the catalysts at 200 °C, 12 atm of H\u003csub\u003e2\u003c/sub\u003e, and 360 rpm. A) Mass ratio guaiacol/cat=2.8, b) Mass ratio guaiacol/cat=5.6, and c) Mass ratio guaiacol/cat=8.4\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4999409/v1/61b2dc6cbab6f4ea57b4efd5.png"},{"id":65637789,"identity":"bd8edca3-4e3c-4635-b85f-8aed9758f747","added_by":"auto","created_at":"2024-09-30 18:49:39","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":115429,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of the HDO of guaiacol of Pt-ACS 11 with Pt-SBA-15 and Pt-AC Commercial at 200 °C, 12 atm of H\u003csub\u003e2\u003c/sub\u003e, 360 rpm, mass ratio guaiacol/cat=5.6.\u0026nbsp;\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-4999409/v1/b141678d1e957f8c0473dec5.png"},{"id":65637786,"identity":"7e0596de-b9a3-4465-b871-b3c32cecf787","added_by":"auto","created_at":"2024-09-30 18:49:39","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":66213,"visible":true,"origin":"","legend":"\u003cp\u003eSelectivity of the guaiacol HDO for the most active catalysts. At 200 °C, 12 atm of H\u003csub\u003e2\u003c/sub\u003e, 360 rpm, mass ratio of guaiacol/cat=5.6, and reaction time of 400 min.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-4999409/v1/a6ac93091a0858628e64d9b2.png"},{"id":65638500,"identity":"8f38b0b6-b3e9-467b-a8d4-2a8aadf9435a","added_by":"auto","created_at":"2024-09-30 18:57:39","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":55199,"visible":true,"origin":"","legend":"\u003cp\u003eSelectivity of the guaiacol HDO for Pt-ACS 11, Pt-SBA-15, and Pt-AC Commercial. At 200 °C, 12 atm of H\u003csub\u003e2\u003c/sub\u003e, 360 rpm, mass ratio of guaiacol/cat=5.6, and a reaction time of 400 min.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-4999409/v1/29d9d47c64577a570aad57be.png"},{"id":65637793,"identity":"f1b0ec05-556f-446f-bf76-ae129a5adfe9","added_by":"auto","created_at":"2024-09-30 18:49:40","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":118454,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of the HDO ratio and conversion of guaiacol between catalysts. At 200 °C, 12 atm of H\u003csub\u003e2\u003c/sub\u003e, 360 rpm, mass ratio of guaiacol/cat=5.6, and reaction time of 400 min.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-4999409/v1/17577dc1b66c8bd4af75705e.png"},{"id":73094776,"identity":"de5e79dd-eb97-4016-ace7-d194ffba5740","added_by":"auto","created_at":"2025-01-06 16:24:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1589692,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4999409/v1/28ac4977-fd8d-4a95-a4cf-e4beb2cc597a.pdf"},{"id":65638504,"identity":"38a9f589-d99c-46c3-9b6a-d308e4242d35","added_by":"auto","created_at":"2024-09-30 18:57:39","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":317525,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFile.docx","url":"https://assets-eu.researchsquare.com/files/rs-4999409/v1/326f07a34a7926a35d3058ce.docx"},{"id":65638501,"identity":"529a35aa-c79c-4303-821c-17faaecb0ca4","added_by":"auto","created_at":"2024-09-30 18:57:39","extension":"png","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":460665,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eScheme 1:\u003c/strong\u003e Simplified scheme of the products obtained after guaiacol conversion.\u003c/p\u003e","description":"","filename":"Scheme1.png","url":"https://assets-eu.researchsquare.com/files/rs-4999409/v1/26b49f711d7d7157db05cbdc.png"},{"id":65638506,"identity":"28dcb191-e763-4b0b-a789-ede73433c72d","added_by":"auto","created_at":"2024-09-30 18:57:40","extension":"png","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":385044,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eScheme 2: \u003c/strong\u003eAcyl group on the active carbon surface.\u003c/p\u003e","description":"","filename":"Scheme2.png","url":"https://assets-eu.researchsquare.com/files/rs-4999409/v1/61ac05a58146f5f0d4661d7d.png"}],"financialInterests":"No competing interests reported.","formattedTitle":"Biomass waste as a raw material for the mesoporous catalyst synthesis and its application in HDO of guaiacol for biofuel production","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eThe imminent replacement of fossil fuels has led the scientific community to achieve efficient, economical, and environmentally friendly processes. We are thus committed to integrating various environmental aspects in the same industrial process, involving sustainable catalyst synthesis method and the use of renewable source for fuel production. The molecules derived from lignocellulosic biomass are polymeric networks with a high oxygen content, avoiding the possibility of being used as a renewable source of energy. At this point, hydrodeoxygenation (HDO) plays a leading role because it allows transformation to obtain molecules with the necessary calorific potential as a biofuel. The HDO process requires excess hydrogen and an appropriate heterogeneous catalyst that facilitates and accelerates the desired chemical reaction. In line with the global energy revolution, we propose that the intervening catalyst in the HDO reaction to obtain biofuel would also be a material produced from a renewable energy source, such as biomass industrial waste. The proposed process goes beyond the guidelines of the old linear economy, where each resource has a beginning and an end, to be more like modern processes founded on the concept of a circular economy. Thus, tending towards greater environmental sustainability, economic activity attempts to maintain or improve the environmental system by recycling or extending the durability of resources as much as possible, minimizing waste generation, and even reusing part of it (D\u0026acute;Amato et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Wang et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Large amounts of biomass waste are annually produced, leading to negative economic, environmental, and health impacts. The possibility of making profitable use of voluminous worldwide waste such as agricultural, forestry, and industrial waste, supports the concept of circular economy and sustainable growth. Lignocellulosic biomass is key to the ecological development of significant products such as chemicals, liquid fuels, and bioplastics. Replacing traditional feedstock with renewable biomass tends to reduce its carbon footprint. In addition, existing products can be substituted with safer manufacturing alternatives (Sheldon \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The green synthesis of nanomaterials (Omran et al. 2022; Lu et al. 2020) offers an approach to green chemistry and circularity, increasing benefits and reducing economic loss and environmental pollution. Current global alimentary trends in fruit and vegetable consumption leads to significant loss in the fresh and processing industries. The waste generated here mostly comprises seeds, skin or peel, rind, and pomace. These residues contain valuable bioactive compounds, proving a potential feedstock capable of replacing conventional raw material to synthesize a nanocatalyst (Su et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Sagar et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eLignocellulosic biomass can be treated by fast pyrolysis; yet subsequent handling is required to obtain efficient liquid fuel. The thermal conversion of this type of biomass results in an interesting mixture of condensable gases or bio-oils with a high number of oxygenated species present in different organic molecules, such as carboxylic acids, alcohols, phenols, aldehydes, ketones, esters, and ethers. Consequently, this bio-oil is immiscible with conventional fuels because of its high polarity; however, it is highly miscible with water. These aspects are responsible for the characteristic low calorific value of this bio-oil. Lignin pyrolysis oil can be upgraded by HDO (Huang et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Hu et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Teles et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Jin et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Elkasabi et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Shu et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Bharath et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Li et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) to yield a mixture of aromatic compounds resembling liquid crude oil. The HDO process is commonly carried out at high hydrogen pressure. Huang et. al. (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) focused on finding the optimal reaction conditions (temperature and hydrogen pressure) for upgrading pyrolysis bio-oil from pine saw dust using Zn/Pd/C catalyst. In this research, they found that increasing temperature resulted in major coke yield however the highest hydrocarbon content was found for treatments at 250\u0026deg;C and 14 atm.\u003c/p\u003e \u003cp\u003eGuaiacol is a phenolic compound containing a methoxy functional group. It is one of the components most widely found in lignocellulosic bio-oil and the most representative due to the presence of both methoxy and hydroxyl groups. These are two particularly common oxygenated functional groups that, according to their molecular structure, induce steric effects. Hu et al. (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) studied HDO conversion of guaiacol over three different zeolites using Pd as a catalyst. They found higher catalytic activity using Pd\u003csub\u003e2%\u003c/sub\u003e/Hβ catalyst at 220\u0026deg;C, 30 atm of H\u003csub\u003e2\u003c/sub\u003e in 4 h of reaction time and concluded that there is an important synergetic effect between the size of metal nanoparticles and the acid sites of the catalyst, resulting in enhanced selectivity to cycloalkanes. Teles et al. (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) reported that the performance of HDO is closely linked to the nature of the support, regardless of the model molecule used. They reported that the HDO of guaiacol mainly resulted in the formation of phenol and methanol over all the niobia-supported catalysts tested, but a higher selectivity for benzene was found over the Pd/Nb\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e5\u003c/sub\u003e catalyst. Noble metal catalysts are exceptional in the HDO process, although they are not a low-cost option, restricting their application in the industry. Jin et al. (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) investigated the behavior of Ni-Pt/AC catalysts for the HDO of guaiacol using methanol and glycerol as a hydrogen source at 300\u0026deg;C and 100 atm in a batch reactor. They found that the bimetallic Ni-Pt/AC catalyst displayed a decrease in guaiacol conversion compared to the monometallic Pt catalyst. Notably, the Pt/AC catalyst exhibited exceptional performance, achieving a guaiacol conversion beyond 96% and higher selectivity for hydrogenated products (cyclohexanol and cyclohexanone) and phenol, in marked contrast to Ni which improved no catalytic activity.\u003c/p\u003e \u003cp\u003eElkasabi et al. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) analyzed HDO reactions from three types of biomass feedstocks (herbaceous grasses, woody biomass, and animal waste) over catalysts of Pt, Ru, and Pd supported over activated carbon. Platinum showed the highest upgrading efficiency, yielding the highest degree of deoxygenation. Our research group previously studied the HDO of guaiacol over a Pt-mesoporous siliceous catalyst, finding the optimal reaction conditions to convert guaiacol into a high-quality biofuel using low-loaded platinum-supported catalyst (0.5 wt. %) (Rivoira et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). On the other hand, activated carbon is a less expensive and more sustainable support since it can be synthesized from biomass waste extracted from the orange juice industry and subsequently activated by a chemical process with phosphoric acid (Ledesma et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The current research focuses on upgrading pyrolysis bio-oil by the HDO of guaiacol over Pt-supported activated carbon catalysts. The reaction conditions and platinum load were the same as those used in our previous research (Rivoira et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In addition, we evaluated whether the support acidity promotes the catalytic activity of the noble metal nanoparticles in the HDO of the oxygenated model compound derived from the biomass selected in this study.\u003c/p\u003e"},{"header":"EXPERIMENTAL","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSynthesis of the activated carbon support\u003c/h2\u003e \u003cp\u003eActivated carbon samples (ACS) were synthesized by chemical activation of orange peels. The steps prior to activation were: (i) washing of oranges to remove dust and other remains and (ii) peeling. First, small pieces of orange peels were cut and placed in an oven at 100\u0026deg;C overnight for drying. The raw material was then crushed and minced. Subsequently, the samples were rinsed with warm water, dried, and screened to obtain the initial material. A fraction was then impregnated with 30, 40, or 50 wt. % solution of H\u003csub\u003e3\u003c/sub\u003ePO\u003csub\u003e4\u003c/sub\u003e, with the biomass to H\u003csub\u003e3\u003c/sub\u003ePO\u003csub\u003e4\u003c/sub\u003e weight ratio of 3:1 or 6:1 without resting time and with resting time at room temperature for 24 h. The samples were then heated in an electric oven. Temperature was increased from room temperature to 470\u0026deg;C at a rate of 3\u0026deg;C/min and held at this temperature for 1 h (Misnon et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Wei et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Gonzales-Garcia 2018). Afterwards, the synthesized material was cooled to room temperature. This was followed by the addition of deionized water to neutralize the surplus acid in the activated carbon. Finally, the ACS produced was placed in an oven to dry until reaching a constant weight, and its effectiveness was assessed. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e lists all the synthesized samples along with their respective preparation characteristics.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSynthetized samples used as a catalyst support.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSample\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eH\u003csub\u003e3\u003c/sub\u003ePO\u003csub\u003e4\u003c/sub\u003e acid solution concentration\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAcid/precursor ratio\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRest time\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACS 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3:1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24 h\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACS 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3:1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACS 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6:1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24 h\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACS 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6:1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 h\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACS 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3:1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24 h\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACS 6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3:1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0h\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACS 7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6:1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24 h\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACS 8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6:1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0h\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACS 9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3:1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24h\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACS 10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3:1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0h\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACS 11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6:1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24h\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACS 12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6:1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0h\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eIncorporation of platinum nanoparticles\u003c/h2\u003e \u003cp\u003ePlatinum nanoparticles were incorporated by traditional wet impregnation method using chloroplatinic acid (H\u003csub\u003e2\u003c/sub\u003ePtCl\u003csub\u003e6\u003c/sub\u003exH\u003csub\u003e2\u003c/sub\u003eO) as a platinum source. A solution of chloroplatinic acid in ethanol was added to the carbonaceous support in a rotary evaporator to achieve metal deposition and evaporating the ethanol in the solution. The soaked powder was dried overnight at 120\u0026deg;C and subsequently desorbed under nitrogen atmosphere. The desorption process was conducted from room temperature to 470\u0026deg;C at a heating rate of 4\u0026deg;C/min and maintained at 470\u0026deg;C for 5 h. The material was finally reduced with 20 mL/min H\u003csub\u003e2,\u003c/sub\u003e using the same temperature program described above. All synthesized samples are referred to as Pt-ACS x.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eCharacterization of catalysts\u003c/h2\u003e \u003cp\u003eA series of analyses and studies were conducted to determine the textural properties of the supports and catalysts. Surface area and porosity were analyzed with an ASAP 2020 instrument. All samples were outgassed before analysis. N\u003csub\u003e2\u003c/sub\u003e adsorption/desorption isotherms were obtained at -196\u0026deg;C. The specific surface area and pore size distribution of the materials were calculated by the BET method (S\u003csub\u003eBET\u003c/sub\u003e) and BJH, respectively. Elemental analysis of platinum was performed by inductively coupled plasma-atomic emission spectroscopy (ICP-AES; VISTA-MPX) operated at high frequency, and Pt loading was close to 0.5 wt.% in all cases. X-ray diffraction (XRD) was used to categorize the framework structure of the supports and their behavior after metal incorporation. XRD patterns were obtained using a Philips X\u0026rsquo;Pert PRO PANalytical diffractometer operated with high-intensity CuKα X-ray radiation (40 mA and 45 kV) and a 0.5\u0026ordm; to 5\u0026ordm; scan technique range. The catalyst surface was analyzed by X-ray photoelectron spectroscopy (XPS). EDX analyses were done in a Jeol JSM 5410 microscope (Jeol, Tokyo, Japan). It was performed by a Microtech-Multilb3000 spectrometer equipped with an Al Kα X-ray source (1486.6 eV, 12 kV, 15 mA). Each signal was corrected using the C 1s reference at 284.8 eV. The platinum particle diameter was evaluated via Hydrogen Chemisorption analysis performed on a Chemisorb 2720 Micromeritics. The first step in the method measurement was to prepare the sample: 0.5 g of catalyst was reduced by 30 mL/min of an H\u003csub\u003e2\u003c/sub\u003e stream at high temperature (400\u0026deg;C) during 2 h, followed by a purge with a N\u003csub\u003e2\u003c/sub\u003e stream of 25 mL/min for further 0.5 h. After cooling, samples were titrated by H\u003csub\u003e2\u003c/sub\u003e pulses in a stream of N\u003csub\u003e2\u003c/sub\u003e until a constant output TCD signal indicated saturation. The average diameter of Pt particles was calculated assuming a spherical shape and stoichiometric ratio of H/Pt\u0026thinsp;=\u0026thinsp;1. The accuracy of the results was above \u0026plusmn;\u0026thinsp;1.5% with \u0026plusmn;\u0026thinsp;0.5% reproducibility. From pulse chemisorption analysis, the active metal surface per gram of metal (MSAm in m\u003csup\u003e2\u003c/sup\u003e/g of metal) is obtained, therefore\u003c/p\u003e \u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\(\\:dp=\\frac{{F}_{g}}{\\rho\\:\\:MSAm}\\:\\frac{1\\:{m}^{3}}{{10}^{6}{cm}^{3}}\\:\\frac{{10}^{9}nm}{1m}\\)\u003c/span\u003e \u003c/span\u003e \u003cem\u003eEq.\u0026nbsp;1\u003c/em\u003e\u003c/p\u003e \u003cp\u003ewhere Fg is a geometric factor, and ρ (g/cm\u003csup\u003e3\u003c/sup\u003e) the specific gravity of the active metal and dp the estimated mean crystallite (or particle) diameter in nm. ChemiSorb 2720 Operator\u0026rsquo;s Manual 272-42801-01 April 2009. Turnover frequency (TOF) was calculated according to the following equations:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:TOF=\\frac{Converted\\:molecules\\:of\\:guaiacol\\:}{Active\\:sites\\:x\\:h}\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:Eq.2$$\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equb\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e\n$$\\:Converted\\:molecules\\:of\\:guaiacol=\\frac{Initial\\:molecules\\:of\\:guaiacol\\:x\\:Conversion\\:}{100}\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:Eq.3$$\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equc\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equc\" name=\"EquationSource\"\u003e\n$$\\:Active\\:sites=\\frac{\\text{A}\\text{c}\\text{t}\\text{i}\\text{v}\\text{e}\\:\\text{s}\\text{u}\\text{r}\\text{f}\\text{a}\\text{c}\\text{e}\\:\\text{a}\\text{r}\\text{e}\\text{a}\\:\\text{o}\\text{f}\\:\\text{}\\text{}\\text{m}\\text{e}\\text{t}\\text{a}\\text{l}\\:\\text{p}\\text{e}\\text{r}\\:\\text{g}\\text{r}\\text{a}\\text{m}\\:\\text{o}\\text{f}\\:\\text{s}\\text{a}\\text{m}\\text{p}\\text{l}\\text{e}\\:\\left(\\frac{\\text{m}2}{\\text{g}}\\right)\\text{x}\\:\\text{m}\\text{a}\\text{s}\\text{s}\\:\\text{o}\\text{f}\\:\\text{c}\\text{a}\\text{t}\\text{a}\\text{l}\\text{y}\\text{s}\\text{t}\\text{s}\\:\\left(\\text{g}\\right)\\:}{Cross\\:section\\:area\\:of\\:Pt\\:\\left(m2\\right)}Eq.\\:4$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere cross section area of Pt is 8x10\u003csup\u003e\u0026minus;\u0026thinsp;20\u003c/sup\u003e m\u003csup\u003e2\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe Bohem titration method was used to determine the surface acidity of solid catalysts (Boehm \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; Vifttaria et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Weak, moderate, and strong acid sites can be quantified by acid-base neutralization reactions with strong, moderate, or weak bases. This method allows determining and calculating each type of functional group on the support surface.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eCatalytic Activity\u003c/h2\u003e \u003cp\u003eThe HDO of guaiacol was performed in a 600 mL stirred stainless steel batch reactor (4563 Parr). The catalytic activity was evaluated under 12 atm H\u003csub\u003e2\u003c/sub\u003e at 200\u0026deg;C. To avoid internal and external mass transfer limitations, a series of previous experiments were carried out. Commercial carbon catalysts and Pt-ACS-11 were used in this study under typical reaction conditions. The results are shown in the supplementary section (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eS and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eS). According to the results obtained by varying rpm and catalyst particle size, we chose to work at 360 rpm and sieve the catalyst to a size of 0.4 mm, thus ensuring no mass transfer limitations.\u003c/p\u003e \u003cp\u003eCatalyst reduction is imperative because of the crucial importance of the oxidation state of noble metal nanoparticles. Then, 0.2 g of the reduced catalyst was added to the reactant mixture. To obtain a different guaiacol/catalyst mass ratio, the feedstock consisted of 50 mL of 1\u0026ndash;3 v/v % solution of guaiacol (99% Sigma-Aldrich) in dodecane (99% Sigma-Aldrich). The components of the liquid products were analyzed using a gas chromatograph HP 5890 Series II GC and HP-5 column, and the products were identified with GC-MS. Guaiacol conversions were determined using an internal standard (n-decane). Experiments were performed three times to confirm reproducibility of the catalytic activity.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS AND DISCUSSION","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eCharacterization of the catalysts\u003c/h2\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003eN\u003csub\u003e2\u003c/sub\u003e adsorption\u0026ndash;desorption and BET area analysis\u003c/h2\u003e \u003cp\u003eThe structural and textural properties of the synthesized activated carbon are shown in Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The values in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e were calculated using the BET and QSDFT methods.\u003c/p\u003e \u003cp\u003eThe N\u003csub\u003e2\u003c/sub\u003e adsorption\u0026ndash;desorption isotherms showed the following results: AC materials from samples 7\u0026ndash;12 exhibited type IV isotherms, characteristic of solids with mesoporous pore structures, while samples ACS 1\u0026ndash;6 exhibited type I isotherms, corresponding to typical microporous materials, showing high gas adsorption at low pressures and no observable increase at higher relative pressures (Sing.et al. 2004). Regarding the phosphoric acid concentration and acid-precursor ratios used in the synthesis procedure, the activated carbons synthesized with the highest acid concentration and acid/precursor ratio, respectively, showed the most suitable structural and textural results. According to Higai et al. (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), phosphate groups expand the structure, and mesopores are thus formed. This suggests that a higher acid concentration improves the support areas. The mechanism of phosphoric acid activation widens the micropores, thereby increasing the mesoporous volume, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, which displays the pore size distribution (PSD) (Higai et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Martinez-Prieto et al. 2020). Better results were afforded when the precursor material was left in contact with the acid for a longer time (24 h) before washing and neutralization. Hence, if we compare the two types of materials synthesized (with and without resting time) using the same acid concentration and precursor ratios, higher areas were found for those kept in contact for 24 h. The hysteresis isotherm loops are H2(b) type. H2 hysteresis loops are given by complex pore structures where network effects are important. Particularly, the type H2(b) loop is associated with pore blocking and the size distribution of neck widths is broad. Hydrothermal synthesis with phosphoric acid probably produces a range of mesopores (as observed in the PSD analysis, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb) that have cavities with narrow necks (ink-bottle pores). According to Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, ACS 11 and 12 showed the best isotherm results, presenting higher surface area and mesopore volume; therefore, ACS 11 reached 1429 m\u003csup\u003e2\u003c/sup\u003e/g (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eMetal incorporation into the structure produces a slight decrease in N\u003csub\u003e2\u003c/sub\u003e adsorption compared to that of the pure carbonaceous support, decreasing the BET surface area of all materials. Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows the results obtained for catalysts with type IV isotherms (higher mesoporosity), whose surface areas were maintained at about 1000 m\u003csup\u003e2\u003c/sup\u003e/g, and their mesoporous character was retained after platinum incorporation in all cases, indicating small and well-dispersed active site nanoparticles, in agreement with XRD results (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). To summarize the results and allow their comparison, only catalysts that yielded better surface area and higher mesoporosity are shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e (Pt-ACS 7, 8, 9, 10, 11, and 12). On the other hand, Pt-SBA-15 (Ballesteros et al. 2019; Ledesma et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and Pt-AC commercial catalysts were added to the characterization for a textural and catalytic comparative purpose.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTextural properties of all carbon supports.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSample\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS\u003csub\u003eBET\u003c/sub\u003e (m\u003csup\u003e2\u003c/sup\u003e/g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eS\u003csub\u003emic\u003c/sub\u003e (m\u003csup\u003e2\u003c/sup\u003e/g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eS\u003csub\u003eext\u003c/sub\u003e (m\u003csup\u003e2\u003c/sup\u003e/g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eV\u003csub\u003et\u003c/sub\u003e (cm\u003csup\u003e3\u003c/sup\u003e/g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eV\u003csub\u003emic\u003c/sub\u003e\u003c/p\u003e \u003cp\u003e(cm\u003csup\u003e3\u003c/sup\u003e/g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eV\u003csub\u003emes\u003c/sub\u003e (cm\u003csup\u003e3\u003c/sup\u003e/g)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAC-commercial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACS 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e900\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e856\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACS 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e856\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e815\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACS 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e950\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e908\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACS 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e920\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e867\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACS 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e946\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACS 6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e910\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e840\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACS 7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e800\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e220\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACS 8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e980\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e866\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACS 9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e631\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e572\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACS 10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e608\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e395\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACS 11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1429\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e722\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e707\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACS 12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1251\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e715\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e536\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eS\u003csub\u003eBET\u003c/sub\u003e, total specific surface area; S\u003csub\u003emic\u003c/sub\u003e, microporous area; S\u003csub\u003eext\u003c/sub\u003e, mesoporous and microporous area; V\u003csub\u003et\u003c/sub\u003e, total pore volume; V\u003csub\u003emic\u003c/sub\u003e, microporous volume; V\u003csub\u003emes\u003c/sub\u003e, mesoporous volume.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTextural properties of the catalysts.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSample\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS\u003csub\u003eBET\u003c/sub\u003e (m\u003csup\u003e2\u003c/sup\u003e/g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eS\u003csub\u003emic\u003c/sub\u003e (m\u003csup\u003e2\u003c/sup\u003e/g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eS\u003csub\u003eext\u003c/sub\u003e (m\u003csup\u003e2\u003c/sup\u003e/g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eV\u003csub\u003et\u003c/sub\u003e (cm\u003csup\u003e3\u003c/sup\u003e/g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eV\u003csub\u003emic\u003c/sub\u003e\u003c/p\u003e \u003cp\u003e(cm\u003csup\u003e3\u003c/sup\u003e/g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eV\u003csub\u003emes\u003c/sub\u003e (cm\u003csup\u003e3\u003c/sup\u003e/g)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePt-AC commercial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e920\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePt-SBA-15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e690\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePt -ACS 7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e795\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e213\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePt -ACS 8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e968\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e900\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePt -ACS 9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1165\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e613\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e552\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePt -ACS 10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e991\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e603\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e388\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePt -ACS 11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e712\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e688\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePt -ACS 12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1223\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e710\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e513\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eS\u003csub\u003eBET\u003c/sub\u003e, total specific surface area; S\u003csub\u003emic\u003c/sub\u003e, microporous area; S\u003csub\u003eext\u003c/sub\u003e, external area; V\u003csub\u003et\u003c/sub\u003e, total pore volume; V\u003csub\u003emic\u003c/sub\u003e, microporous volume; V\u003csub\u003emes\u003c/sub\u003e, mesoporous volume.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e shows the elemental composition of the activated carbon analyzed by energy-dispersive X-ray spectroscopy (EDX). The composition of the synthesized activated carbon is listed. We observed the presence of P in all the samples. P concentration increases with the increase of the activating agent concentration.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEDX of the samples.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSample\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e \u003cp\u003eElement (wt.%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eO\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eSi\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACS 7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e71.80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACS 8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e72.76\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACS 9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e71.84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACS 10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e71.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACS 11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e71.60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACS 12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e71.70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eHydrogen chemisorption\u003c/h2\u003e \u003cp\u003eIn addition, hydrogen chemisorption confirmed that better Pt dispersion was achieved in samples with higher surface areas (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Pt-ACS-11 showed the best dispersion and lowest Pt particle size. Pt-ACS 1, 2, 3, 4, 5, and 6 materials are not shown in Tables\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and \u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e because of their lower surface area and higher microporous surface (type I isotherm).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHydrogen chemisorption results.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCatalyst\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAverage crystal size, nm\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eActive surface area of ​​metal (per gram of metal)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eChemisorbed volume per gram of sample cm\u003csup\u003e3\u003c/sup\u003e/g\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eActive surface area of ​​metal (per gram of sample) m\u003csup\u003e2\u003c/sup\u003e/g of sample\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e% Dispersion\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePt-AC Commercial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e71.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePt SBA15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e105.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACS7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e101.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACS8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e94.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACS9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e123.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACS10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e101.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACS11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e149.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACS12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e129.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eXRD\u003c/h2\u003e \u003cp\u003eXRD characterization confirmed the distinctive nanostructure of the synthesized carbons. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows wide-angle XRD patterns of all Pt-supported samples. Two typical broad graphite peaks can be seen in all catalysts at 26\u0026deg; and 43\u0026deg; of 2 theta corresponding to the (002) and (100) planes of the carbonaceous support (Osman et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Metallic Pt characteristic signals appear at 39.8\u0026deg;, 46.3\u0026deg;, 67.7\u0026deg;, 81.3\u0026deg;, and 85.8\u0026deg; of 2θ corresponding to the (111), (200), (220), (311), and (222) planes of face-centered cubic (FCC) metallic platinum facets (PDF 01-087-0640) (Li et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Hernadez-Morales 2020; H\u0026auml;m\u0026auml;l\u0026auml;inen 2008). As expected, the catalysts with higher surface area (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) showed better dispersion of the metallic platinum particles. The absence of visible peaks and the well-resolved (002) and (100) plane reflections are attributed to a better dispersion of the metallic platinum particles without modifying the overall structure. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, higher Pt dispersion is suggested for Pt-ACS 7, 9, 10, 11, and 12 catalysts according to the absence of a typical Pt signal at 39.8\u0026deg; of 2θ. Nevertheless, a relatively significant peak appeared at this 2θ intensity for Pt-ACS 1, 2, 3, 4, 5, and 6 catalysts, indicating a rather large number of atomic clusters.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eXPS\u003c/h2\u003e \u003cp\u003eMetal dispersion strongly affects the catalytic performance of materials, but the characteristics of the metal phase in the catalysts play a crucial role in determining their performance as active sites on the carbon surface (Ramos et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e shows the data extracted from XPS analysis of the synthesized catalysts with the best textural properties. Those parameters were considered because they are important for the development of high catalytic activity. According to the analysis of XPS results, the C1 excitation indicates that various species were found on the surface of the carbon.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eXPS analysis of the catalysts.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSample\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC1s\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSi2p3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eO1s\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP2p\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePt4f\u003csub\u003e7/2\u003c/sub\u003e\u003c/p\u003e \u003cp\u003ePt\u003csup\u003e0\u003c/sup\u003e(%); Pt\u003csup\u003e+\u0026thinsp;2\u003c/sup\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePt-ACS 7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e284.4 (55)\u003c/p\u003e \u003cp\u003e285.6 (23)\u003c/p\u003e \u003cp\u003e288.4 (22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e531.7(60)\u003c/p\u003e \u003cp\u003e533.4(24)\u003c/p\u003e \u003cp\u003e535.7(16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e134.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e72.4 (83); 73.5 (17)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePt-ACS 8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e284.4 (54)\u003c/p\u003e \u003cp\u003e285.5 (24)\u003c/p\u003e \u003cp\u003e288.3 (22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e531.6(59)\u003c/p\u003e \u003cp\u003e533.4(25)\u003c/p\u003e \u003cp\u003e535.7(16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e134.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e72.2 (73); 73.3 (27)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePt-ACS 9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e284.5 (51)\u003c/p\u003e \u003cp\u003e285.7 (28)\u003c/p\u003e \u003cp\u003e288.2(21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e531.5(65)\u003c/p\u003e \u003cp\u003e533.3(23)\u003c/p\u003e \u003cp\u003e535.6(12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e134.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e72.1 (85); 73.3 (15)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePt-ACS 10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e284.4 (53)\u003c/p\u003e \u003cp\u003e285.4 (25)\u003c/p\u003e \u003cp\u003e289.1 (22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e531.5(59)\u003c/p\u003e \u003cp\u003e533.3(23)\u003c/p\u003e \u003cp\u003e535.6(18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e134.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e72.2 (77); 73.3 (23)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePt-ACS 11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e284.4 (51)\u003c/p\u003e \u003cp\u003e285.6 (25)\u003c/p\u003e \u003cp\u003e288.3(24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e531.5(70)\u003c/p\u003e \u003cp\u003e533.4(20)\u003c/p\u003e \u003cp\u003e535.8(10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e134.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e72.5 (89); 73.5 (11)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePt-ACS 12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e284.3 (53)\u003c/p\u003e \u003cp\u003e285.5 (27)\u003c/p\u003e \u003cp\u003e288.5(20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e531.6(65)\u003c/p\u003e \u003cp\u003e533.4(25)\u003c/p\u003e \u003cp\u003e535.6(10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e134.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e72.3 (88); 73.5 (12)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePt-SBA-15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e532.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e71.2 (87); 72.8 (13)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe signals could be assigned to graphitic carbon at 284 eV, carbon species in alcoholic groups (C-O-H) at 286 eV, and ether groups (C-O-C), C-O-P bonding, and/or carbon in carbonyl groups (C\u0026thinsp;=\u0026thinsp;O) at 288 eV. The presence of oxygenated carbon indicates a reaction between carbon and phosphoric acid (Puziy et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). The pair of peaks centered on 71 eV and 72 eV in the binding energy spectrum corresponds to Pt\u003csup\u003e0\u003c/sup\u003e and Pt\u003csup\u003e+\u0026thinsp;2\u003c/sup\u003e, respectively (Toda et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Waisaka et al. 2006; Radev et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Although all catalysts were subjected to an exhaustive reduction method, it was found that a small part of Pt was in an oxidized state. Analysis of the peak areas reveals a substantial presence of metallic Pt in the prepared samples, with Pt\u003csup\u003e0\u003c/sup\u003e content exceeding 70% in all instances.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eBoehm titration\u003c/h2\u003e \u003cp\u003eSupport acidity intervenes in the reduction of metal particle size, and metal dispersion increases because of metal-support interaction. In this case, the carbon acidity of the surface was conferred by activation with H\u003csub\u003e3\u003c/sub\u003ePO\u003csub\u003e4\u003c/sub\u003e during the synthesis of the materials. To quantify the number of strong and weak surface acidic sites generated in the Pt catalyst during the carbonization and activation stages, the Boehm method was applied. The Boehm method offers a quantitative assessment of the quantity of acid sites on the surface of a coal material. The choice of this technique is because it is relatively simple and inexpensive compared to other analytical techniques. The Boehm method has been widely used and validated in the scientific literature, showing accuracy and reliability (Kim et al. 2016: Ederer et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e shows the difference between the concentration of acidic groups detected by NaHCO, Na\u003csub\u003e2\u003c/sub\u003eCO\u003csub\u003e3\u003c/sub\u003e, and NaOH. According to the literature (Kim et al. 2016: Ederer et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), NaHCO can only detect strong acid sites, including carboxylic and sulfonic groups. Sodium hydroxide (NaOH) neutralizes carboxylic, phenolic, and lactonic groups, while sodium carbonate (Na\u003csub\u003e2\u003c/sub\u003eCO\u003csub\u003e3\u003c/sub\u003e) neutralizes carboxylic and lactonic groups. The values shown in Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e indicate that, although all the evaluated catalysts present strong acid sites and that the acid sites are mainly oxygen-containing groups, the Pt-ACS 11 catalyst is the most acidic, showing a trend with the type of activation and the concentration of acid used in the activation step during synthesis (Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBoehm titration results [mmol/g].\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSample\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ecarboxylic\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003elactonic\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ephenolic\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eall\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePt-ACS 7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePt-ACS 8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePt-ACS 9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePt-ACS 10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePt-ACS 11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePt-ACS 12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003csup\u003ea\u003c/sup\u003e Strong acid sites; \u003csup\u003eb\u003c/sup\u003e Moderate acid sites; \u003csup\u003ec\u003c/sup\u003e Weak acid sites.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eCatalytic activity\u003c/h2\u003e \u003cp\u003eAccording to the results obtained from the characterization study, the materials with the best textural and physicochemical properties were chosen for testing in the HDO of guaiacol. The catalytic activity was compared with that of Pt-SBA-15 (mesoporous silica support) and Pt-commercial activated carbon. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows the catalytic activity in the HDO reaction of guaiacol using different mass ratios of guaiacol and catalyst. Among the synthesized catalysts, Pt-ACS 11 and 12 showed the highest conversions in all cases, followed by Pt-ACS 9 and 7. In principle, we can observe a direct correlation with the greater surface area and better characteristics of the support and the catalyst, both structural and physicochemical, such as a greater proportion of reduced platinum species, smaller metallic particle size, and good dispersion. As can be seen in the catalytic activity, the catalysts with higher mesoporosity increase conversion. Therefore, it was necessary to obtain a greater quantity of mesoporous in the synthesis process. In these mesoporous catalysts the reaction probably occurs mainly in the mesopores than inside micropores; this can be understood in terms of the mass diffusion limitations. It\u0026rsquo;s probably that Pt nanoclusters insert in mesopore framework (due to the size of the crystallite, it would not enter the micropores), therefore, when adding the metal, the mesopore volume and the area decrease mainly than micropore volume (see Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Then the reaction occurs where the active sites are located (inside mesopores).\u003c/p\u003e \u003cp\u003eIf we analyze the effect of the substrate/catalyst mass ratio, we can observe that in the case of a low guaiacol/catalyst mass ratio of 2.8, conversions are high, but not much higher than those when a higher ratio is used, for example of 5.6. This suggests that in the first case, there is an excess of catalyst and that it does not translate into greater conversion. Similarly, when we increased the ratio to 8.4, we observed a decrease in conversion in all cases. Industrially, we consider that an average ratio of 5.6 is appropriate for comparing the catalysts. Figure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e compares the activity of the most active catalyst synthesized in this study and two catalysts with the same loading of platinum but using a commercial activated carbon support and an SBA-15 support synthesized in a previous work (Rivoira et al. 2016). Figure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e shows that Pt-ACS 11 is more active than Pt-SBA-15, in addition to the fact that the activated carbon contemplates an environmental (eco-friendly) and, consequently, an economical advantage. The difference in activity between Pt-ACS 11 and these two catalysts must be analyzed in greater depth, considering the characteristics of the support, the nature of the surface, and its acidity.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003ePt-ACS 11 shows the highest conversion in all cases. It is evident that by increasing the ratio of the mass of guaiacol and the catalyst, greater differences are observed in the conversion between the different catalysts, especially at shorter times. For this reason, the intermediate guaiacol/catalyst ratio of 5.6 is more suitable for comparison. To compare the activity of the synthesized catalysts more precisely, the turnover frequency (TOF) was calculated considering the number of converted molecules per Pt metal site (Eq.\u0026nbsp;2, Eq.\u0026nbsp;3 and Eq.\u0026nbsp;4); the active surface area of Pt was obtained by hydrogen chemisorption (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e shows the results. TOF was calculated at two different reaction times, 200 and 400 min, and for the three guaiacol/catalyst ratios. In Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e, another TOF was calculated using only the acid sites (total and strong) to relate the catalytic activity to the two types of active sites (metal and acids), and thus interpret and correlate the conversion results with the nature of the catalytic surface of the various materials. According to the TOF values ​​for all guaiacol/catalyst ratios, Pt-ACS 11 and Pt-ACS-12 are the most active followed by Pt-ACS-9 and 7. This trend is more evident at higher ratios. The increased activity can be easily attributed to the structural characteristics and properties of the catalysts. Catalysts whose supports have greater surface area and better mesoporosity allowed better dispersion of the platinum species, the active sites of the hydrogenation/hydrogenolysis reaction.\u003c/p\u003e \u003cp\u003eThe TOF values ​​at 400 min are almost always lower than those at 200 min, indicating that the reaction rate decreases as the conversion increases, probably due to the formation of products that block the active centers and compete. Pt-ACS 11 is, from the point of view of its physical and chemical properties, the best catalyst: it has the greatest surface area, the best dispersion of Pt, and the smallest metal particle size, in addition to the greatest proportion of reduced Pt, which is known to be required for the hydrogenation of guaiacol. However, in some cases, the TOF of Pt-ACS 12 is greater than that of Pt-ACS 11. This indicates that the reaction is not as sensitive to the dispersion of Pt, or that there may be another factor involved in the mechanism. To elucidate this, we calculated the TOF in relation to the acidic sites of each catalyst. The acidic sites were calculated by Boehm titration; values ​​are listed in Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e. The TOF of the acid sites were calculated for the total number of acid sites and strong acid sites. If we consider the values in Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e, the trend is different for both types of sites, i.e., the highest TOF for the total acid sites is found for the most active catalysts Pt-ACS 11 and 12 for the three guaiacol/catalyst ratios. However, this trend is reversed when we calculate it using strong acid sites. This suggests that the active acid sites of this reaction are sites of medium acidity and not sites of strong acidity. Paying special attention to both acidic and metallic TOF values ​​at the highest guaiacol/catalyst ratios (more guaiacol/less catalyst), it can be observed that Pt-ACS 11 is the most active catalyst. In addition, there is a synergistic effect between the platinum sites and the medium acid sites.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTOF of the catalysts.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"14\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eCatalyst\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eTOF2.8\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eTOF5.6\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eTOF8.4\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c9\" namest=\"c8\" rowspan=\"2\"\u003e \u003cp\u003eTOF2.8\u003c/p\u003e \u003cp\u003eAcid sites,\u003c/p\u003e \u003cp\u003e200 min\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c11\" namest=\"c10\" rowspan=\"2\"\u003e \u003cp\u003eTOF5.6\u003c/p\u003e \u003cp\u003eAcid sites,\u003c/p\u003e \u003cp\u003e200 min\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c13\" namest=\"c12\" rowspan=\"2\"\u003e \u003cp\u003eTOF8.4\u003c/p\u003e \u003cp\u003eAcid sites,\u003c/p\u003e \u003cp\u003e200 min\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e% HDO\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003emin\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003emin\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003emin\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e400\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e400\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e400\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eStrong\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eStrong\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003eStrong\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePt-ACComm.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e440\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e370\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e146\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePt-SBA-15\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e495\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e374\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e191\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePt-ACS7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e310\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e196\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e475\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e376\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e329\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e342\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e218\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePt-ACS8\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e208\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e154\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e275\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e208\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e110\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePt-ACS9\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e308\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e190\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e527\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e383\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e477\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e441\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e1.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e205\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePt-ACS10\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e245\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e169\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e226\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e109\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePt-ACS11\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e329\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e204\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e387\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e683\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e683\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e491\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e1.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e300\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePt-ACS12\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e345\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e213\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e407\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e654\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e654\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e522\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e1.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e292\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTOF calculated considering the number of converted molecules per platinum metal site (col 1\u0026ndash;3) at 200 and 400 min of reaction time, and TOF calculated considering the number of converted molecules per total and strong acid sites (col. 4\u0026ndash;6). In all cases for the three guaiacol/catalyst ratio. Col.8 shows TOF for HDO products.\u003c/p\u003e \u003cp\u003eAccording to the main reaction products identified by GC chromatography in this study, a simplified scheme for the HDO of guaiacol is shown in Scheme \u003cspan refid=\"Sch1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Phenol, anisole, catechol, benzene and cyclohexane were identified. Many other peaks corresponding to heavy products and/or oxygenated products were observed at high retention time in the chromatography, they were grouped as \u0026ldquo;other products\u0026rdquo; since they appeared in very small quantities or were difficult to identify. Toluene and methyl cyclohexene could be formed according to Ghampson et.al (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) but were not detected in this study.\u003c/p\u003e \u003cp\u003eThe evolution of the reaction explained by the mechanism proposed in Scheme \u003cspan refid=\"Sch1\" class=\"InternalRef\"\u003e1\u003c/span\u003e arises from the identified main products mentioned above and the understanding of three possible pathways: demethylation (DME), demethoxylation (DMO), and dehydroxylation (DHY) of guaiacol. For instance, C. A. Teles et al. (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) reported that the HDO reaction of guaiacol over different supported Pd catalysts may occur as follows: the methoxy group removal from guaiacol to produce phenol can take place by direct DMO producing methanol, or indirectly by DME of anisole (formed by DHY of guaiacol) producing methane, or by DHY of catechol (formed by DME of guaiacol) releasing water. Thus, phenol can be considered a main product or an intermediate for further deoxygenation in guaiacol HDO. Lai et al. (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) proposed a complex mechanism for the HDO of guaiacol, including these three pathways over Ni@Pd and Ni@Pt bimetallic catalysts involving formation of xylenols and xylenes. Methyl transfer (conversion of methoxy to a methyl group instead of methane) may occur in anisole to produce cresol followed by subsequent methylation, resulting in xylenol. This pathway can be explained in terms of the acidic properties of the support and the noble metal catalyst (Gutierrez et al \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Bui et al \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Nimmanwudipong et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Anisole can also be deoxygenated by DMO to form benzene, but direct transalkylation may occur, also affording xylenol, as proposed by Lai et al. (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). These products were not favored under our reaction conditions. The latest stage of the mechanism occurs specifically in consequence of the presence of platinum active sites involving the appearance of the two deoxygenated and desired products (benzene and cyclohexane), in which phenol can be further hydrodeoxygenated, forming benzene followed by the hydrogenation of the aromatic ring to yield cyclohexane (He et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Gao et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). These consecutive reactions agree with those proposed by Zhu et al. (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). They reported that acid sites catalyze methyl transfer, while metals catalyze demethylation and hydrodeoxygenation.\u003c/p\u003e \u003cp\u003eProduct yield and selectivity were calculated considering 100% of the products identified in the chromatography, including \"other\" products. Guaiacol HDO products observed in this work seem to correspond to a series of consecutive hydrodeoxygenations, as proposed in the literature [Teles et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2018\u003c/span\u003e, Ghampson et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) (see Scheme \u003cspan refid=\"Sch1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Demethylation occurs to yield catechol, but it is likely to occur in a smaller proportion.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe selectivity of the synthesized catalysts for the different products of guaiacol HDO is presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. Phenol was the main product in all cases, followed by anisole and catechol, according to the reaction steps described in Scheme \u003cspan refid=\"Sch1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Then, the desired deoxygenated products such as benzene and cyclohexane were observed for all catalysts. However, the most active catalysts, Pt-ACS 11 and 12, obtained the highest selectivity of 18% and 12%, respectively, followed by Pt-ACS 9 and 7 (10%).\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e compares the selectivity of Pt-ACS 11 with Pt-SBA-15 and Pt-AC Commercial. The main products of the three catalysts were phenol, anisole, and catechol; phenol and anisole are direct products of HDO with consecutive formation of benzene and cyclohexane. All these products (phenol, anisole, benzene, and cyclohexane) were considered to calculate the HDO ratio, which is a percentage of the guaiacol conversion to deoxygenated products, since there is a portion of the reagent that goes to the undesired pathway, producing catechol and other products. HDO % was calculated as follows: HDO % = (selectivity of phenol\u0026thinsp;+\u0026thinsp;anisole\u0026thinsp;+\u0026thinsp;benzene\u0026thinsp;+\u0026thinsp;cyclohexane) x guaiacol conversion/100. It is important to clarify that phenol and anisole are products from partial dexoygenation of guaiacol while benzene and cyclohexane from total deoxygenation. The selectivity to benzene and cyclohexane for Pt-ACS 11 was much higher than that for Pt-SBA-15 and Pt-AC Commercial catalysts. The TOF of HDO % with respect to the Pt active sites was calculated; the results are shown in the last column of Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e. As expected, the Pt-ACS 11 catalyst shows the highest TOF, followed by Pt-ACS 12. The TOF values ​​obtained for Pt-SBA-15 and the commercial catalyst are lower. The last two catalysts present a large proportion of catechol, indicating that the demethylation pathway is favored in these catalysts.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eComparing our results, we see that they are in good agreement with those found in the literature similar systems and conditions. Teles et al. (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) investigated the HDO of guaiacol over supported Pd catalysts at atmospheric pressure and a temperature of 300\u0026deg;C. Demethoxylation which afforded phenol was the major reaction pathway for all catalysts, showing only a slight contribution from the demethylation reaction. Yet, a significant dehydroxylation reaction was still found in catalysts with Pd supported on ZrO\u003csub\u003e2\u003c/sub\u003e and TiO\u003csub\u003e2\u003c/sub\u003e. Author reported that the hydroxyl group was strongly adsorbed on the catalyst surface, which could block the catalytic sites and hinder further conversion of phenol, ultimately leading to reduced deoxygenation rates. The conclusion drawn was that demethylation with the production of catechol as a reaction intermediate was the most straightforward reaction. In this work, however, phenol and anisole were the main products yielded, which suggests that phenol was directly formed through cleavage of CAr\u0026ndash;OCH3 bond in all catalysts. Following Teles et al. (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) anisole was afforded by dehydroxylation of guaiacol. As the cleavage of CAr\u0026ndash;OH bond requires higher energy that that of CAr\u0026ndash;OCH3 bond (414 and 356 KJ/mol, respectively) (Bui et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), demethoxylation is expected to produce phenol over dehydroxylation. This result was consistent with ours. Ghampson et al. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) researched the HDO of guaiacol in a batch reactor over SBA-15 silica-supported molybdenum nitride catalysts at 300\u0026deg;C and 49 atm of H\u003csub\u003e2\u003c/sub\u003e pressure. SBA-15 silica-supported catalysts transformed guaiacol directly to phenol through demethoxylation with no production of catechol. The lower catechol production with the SBA-15 silica support was significant to minimize coking reactions and reduce consumption of hydrogen. They obtained 44% conversion with 30% yield of phenol. All catalysts in this study yielded more phenol than catechol. SBA-15 support shows Si-OH groups, which act as Lewis acid sites, allowing demethoxylation. In this study, with the carbons activated with phosphoric acid, the acidity obtained and determined by Bohem titration showed that direct demethoxylation is also favored. The commercial carbon support showed greater ability for demethylation, yielding catechol, transformed into phenol through hydrogenolysis (Saidi et al \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Sepulveda et al 2011; Yang et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Pt/C catalyst was studied in the HDO of guaiacol in a fixed-bed reactor at different temperatures and atmospheric pressure, affording high kinetic constants in the HDO of guaiacol. The primary products of the liquid-phase reaction were phenol, catechol and cyclopentanone (Zhu et al.2011). The HDO of guaiacol was also studied on La-modified Pt/Al\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e batch reactor at 215\u0026deg;C and 30 atm, obtaining 80% of HDO at 100% conversion (Escobar et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIt is widely agreed that the HDO reaction requires a bifunctional catalyst, i.e., a metal associated with a specific support close to an acid site. Some studies suggest that the reaction occurs on the metal sites close to an acid site.\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e summarizes the comparison between the catalysts and correlates the guaiacol conversion with the HDO ratio and the total acidity of the catalysts synthesized, using the activated carbon supports. The higher HDO ratio correlates well with the higher conversion and with total acidity.\u003c/p\u003e \u003cp\u003eThe good performance of activated carbon could be linked to the incorporation of phosphorus species in the structure. Li et al. (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) have explored the impact of phosphorus on the hydrogenation process, employing a P-doped Ni/Al\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e catalyst. The results indicate that the incorporation of phosphorus species could act as a catalytic promoter, enhancing the activity and selectivity of the catalyst. Chen et al. (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) also investigated the hydrogenation of nitrobenzene to aniline using phosphorus-doped carbon nanotubes and discovered that phosphorus could act as a catalytic promoter. Subsequently, Yangcheng et al. (\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) found that the presence of active P species in Pd/PHS led to the selective conversion of vanillin and, consequently, improved the yield of hydrodeoxygenated compounds. These studies have demonstrated the benefits of the presence of phosphorus in HDO reactions. Dieu-Phuong et al. (2020) studied the hydrodeoxygenation of oleic acid over P-modified catalyst and observed that the HDO reaction is highly dependent on the potency and arrangement of acid sites. Therefore, the introduction of phosphoric acid enhances the reactivity of the electrophilic acid center, effectively activating the oxygen atom of some of the functional groups present on the carbon surface, e.g. the acyl bond, making it susceptible to attack by hydrogen atoms (Scheme \u003cspan refid=\"Sch2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Hence, we could explain the better performance of our catalysts due to the synergy between the acid sites and metal sites in the guaiacol HDO reaction. In the current investigation, phosphorus was incorporated during the synthesis of carbon as an activating agent, and P compounds were incorporated into the material without the need for post-synthesis incorporation. The presence of phosphorous, responsible for the acidity of the surface materials, could contribute to the improved performance of the HDO reaction. The presence of oxygenated surface groups, such as phenolic compounds and carboxylic acids, on the AC surface facilitates interaction with the oxygen unshared pairs of electrons in phosphoric acid and with phosphate anions. They probably react to produce an acyl group (R-CO-) generated by the elimination of hydroxyl group from a surface carboxylic acid by phosphorous action (Scheme \u003cspan refid=\"Sch2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The acyl group generally exists in its cationic form because its radical form is particularly unstable and decomposes quickly.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn the mechanism proposed, the cationic acyl generated (Lewis acid site) can accommodate the unshared electrons present in the guaiacol hydroxyl group (\u0026ndash;OH) or in its methoxy group (\u0026ndash;O-CH3) due to its electrophilic nature. Nucleophilic attraction (ion\u0026ndash;dipole) keeps the substrate molecule adsorbed over the carbon surface. The \u0026ndash;OH o \u0026ndash;O-CH3 guaiacol bond is susceptible cleavage by the entry of hydrogen adsorbed on the neighboring Pt metal site. Analogous mechanisms may occur with other carbon groups that, in a similar way, interact with the phosphorous species, attracting the guaiacol molecule and its intermediates.\u003c/p\u003e \u003cp\u003eOn the other hand, chemisorption of H\u003csub\u003e2\u003c/sub\u003e showed that the Pt nanoparticles were well dispersed on the support material. Yangcheng et al. (\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) studied the dispersion of Pd metal particles on a zeolite, with and without phosphorus species. They observed that in their nanoparticle-supported catalyst, there was a shift towards a higher dispersion, achieving nanoparticles with a size around 1.5 nm. They found that the presence of phosphorus enhanced Pd dispersion on the support. Thus, we believe that the acidity incorporated in the activation stage of the catalyst through phosphoric acid, has a positive influence on the dispersion of the metallic particles. Finally, the joint effect of the higher particle dispersion (which could be attributed to acidity and the large surface area obtained for the synthesized catalyst) and the contribution of acidity to HDO reactions make the Pt particles over the active carbon a particularly efficient catalyst. Considering the low manufacturing cost, we could affirm that it is a promising material for the HDO reaction of biofuels.\u003c/p\u003e \u003c/div\u003e"},{"header":"CONCLUSIONS","content":"\u003cp\u003eThe HDO of guaiacol was performed using platinum-activated carbon as a catalyst. The raw material for carbon was obtained from orange peel waste, and the carbonaceous supports were activated by simple impregnation using H\u003csub\u003e3\u003c/sub\u003ePO\u003csub\u003e4\u003c/sub\u003e as an activating agent, which is a critical aspect for enhancing HDO performance. The HDO results were better than those obtained for the Pt-SBA-15 catalyst. In addition, synthetized activated carbons are very low cost and eco-friendly since they are obtained from local industrial waste. Highly dispersed Pt active sites were key to the catalytic performance, probably due to the following reasons. i) High Pt dispersion provides a high metal surface available and easily reached by the substrate (reactive) to form the activated complex during the chemical reaction attributed to the small Pt particle size. ii) The acidic nature of the catalysts had a synergistic effect with metal sites. Activation of the materials using H\u003csub\u003e3\u003c/sub\u003ePO\u003csub\u003e4\u003c/sub\u003e seemed to be the main reason for the alterations in the as-synthetized materials, interacting with the support and modifying its acidity, improving the catalyst itself. The characterization of acidity was performed by a simple titration method, in which the most acidic catalyst was the most active in the HDO of guaiacol, reaching 88 mol% of guaiacol conversion. However, a more important result was the selectivity discovered, since 70% of the guaiacol conversion was toward HDO products. In this study it was revealed that the presence of acidity over the surface and the presence of P species are the main reasons for the high activity displayed by the Pt-supported active carbon in the HDO of guaiacol.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eACKNOWLEDGMENT\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNANOTEC, CONICET, Universidad Tecnol\u0026oacute;gica Nacional, Maestro L\u0026oacute;pez y Cruz Roja Argentina.\u0026nbsp;We acknowledge the financial support provided by CONICET Argentina, PIP CONICET 11220210100325.\u0026nbsp;\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBallesteros-Plata D, Infantes-Molina A, Rodr\u0026iacute;guez-Castell\u0026oacute;n E (2019) Study of bifunctionality of Pt/SBA-15 catalysts for HDO of Dibenzofuran reaction: Addition of Mo or use of an acidic support. Appl. Catal. 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Catal. 281:21-29. https://doi.org/10.1016/j.jcat.2011.03.030\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Schemes ","content":"\u003cp\u003eSchemes are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"clean-technologies-and-environmental-policy","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ctep","sideBox":"Learn more about [Clean Technologies and Environmental Policy](https://www.springer.com/journal/10098)","snPcode":"10098","submissionUrl":"https://submission.nature.com/new-submission/10098/3","title":"Clean Technologies and Environmental Policy","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"HDO, activated carbon, biomass, platinum","lastPublishedDoi":"10.21203/rs.3.rs-4999409/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4999409/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePlatinum-modified activated carbon was synthesized and studied for hydrodeoxygenation (HDO) of guaiacol. The activated carbon support was prepared using orange peel from industrial waste. Platinum was added by wetness impregnation. The activity was compared with that of platinum supported on mesoporous silica and commercial activated carbon catalysts. The catalysts prepared were characterized by different techniques: XRD and N\u003csub\u003e2\u003c/sub\u003e adsorption isotherms to confirm the mesoporous structure, and XPS, H\u003csub\u003e2\u003c/sub\u003e-Chemisorption and Boehm titration to determine active sites and acidity. The results showed that high-surface-area active carbon support favors the formation of small platinum metallic particles, highly dispersed over the surface. The catalysts were active for guaiacol HDO performed in the laboratory at 200\u0026deg; C and 12 atm of H\u003csub\u003e2\u003c/sub\u003e in a Batch PARR reactor. Carbon was activated using phosphoric acid during the synthesis. The interaction between the peculiar acidity generated on the support by H\u003csub\u003e3\u003c/sub\u003ePO\u003csub\u003e4\u003c/sub\u003e, accompanied by the high hydrogenation capacity of the metallic platinum particles, enhanced catalytic activity, and selectivity for deoxygenated products. This research aims at developing an environmentally friendly catalyst to produce biomolecules of high aggregated value.\u003c/p\u003e","manuscriptTitle":"Biomass waste as a raw material for the mesoporous catalyst synthesis and its application in HDO of guaiacol for biofuel production","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-09-30 18:49:34","doi":"10.21203/rs.3.rs-4999409/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-10-15T19:38:06+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-10-13T05:15:23+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-10-02T23:11:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"45988548977763516057593061127673676160","date":"2024-09-22T17:16:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"136217190451206914428433127390651247583","date":"2024-09-11T20:09:56+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-09-11T12:58:53+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-09-07T20:18:23+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-08-30T10:39:28+00:00","index":"","fulltext":""},{"type":"submitted","content":"Clean Technologies and Environmental Policy","date":"2024-08-29T17:38:56+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"clean-technologies-and-environmental-policy","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ctep","sideBox":"Learn more about [Clean Technologies and Environmental Policy](https://www.springer.com/journal/10098)","snPcode":"10098","submissionUrl":"https://submission.nature.com/new-submission/10098/3","title":"Clean Technologies and Environmental Policy","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"8684f24e-42f1-4113-9eb5-4d8010850a86","owner":[],"postedDate":"September 30th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-01-06T16:22:25+00:00","versionOfRecord":{"articleIdentity":"rs-4999409","link":"https://doi.org/10.1007/s10098-024-03119-z","journal":{"identity":"clean-technologies-and-environmental-policy","isVorOnly":false,"title":"Clean Technologies and Environmental Policy"},"publishedOn":"2024-12-31 15:57:46","publishedOnDateReadable":"December 31st, 2024"},"versionCreatedAt":"2024-09-30 18:49:34","video":"","vorDoi":"10.1007/s10098-024-03119-z","vorDoiUrl":"https://doi.org/10.1007/s10098-024-03119-z","workflowStages":[]},"version":"v1","identity":"rs-4999409","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4999409","identity":"rs-4999409","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}