Preparation of mesoporous chitosan cobalt supported nano-catalyst for the catalyzed reduction of quinoline to quinoline aldehyde

Preparation of mesoporous chitosan cobalt supported nano-catalyst for the catalyzed reduction of quinoline to quinoline aldehyde | 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 Preparation of mesoporous chitosan cobalt supported nano-catalyst for the catalyzed reduction of quinoline to quinoline aldehyde Lan Wu, Yongchao Liu, Ze Wang, Xinyu Ye, Zhenhua Li, Yaozong Liu, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5391338/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Supported nanocatalysts with environmental sustainability and high catalytic performance have attracted much attention. Research interest in sustainable catalysis. A supported nanocatalyst Co@NSC has been studied in this paper. Porous materials with catalytic properties were prepared by anchoring transition metal cobalt onto porous materials doped with nitrogen. Carbon material with chitosan as raw material. The results of the scanning electron microscopy (SEM), X-ray diffraction (XRD) and Fourier transform infrared spectroscopy (FT-IR) tests demonstrate that the catalyst obtained exhibits an excellent mesoporous structure and a uniform distribution of cobalt elements. The scaffold is rich in N atoms, which can provide enough anchor points for cobalt to form cobalt-NX. Cobalt groups can improve the catalytic activity of the catalyst. In addition, Co@NSC is porous, the structure has the potential to facilitate the mass transfer of the reactants, thereby enhancing the overall efficiency of the reaction. Furthermore, the prepared catalyst was employed in the conversion of quinoline into the corresponding quinoline aldehyde. The results show that quinoline can be directly reduced to produce the corresponding quinoline aldehyde. Subsequently, the selectivity and stability of the prepared catalyst were validated. Supported nano-catalyst Reduction reaction Transition metal Porous carbon material Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Introduction Tetrahydroquinoline and its derivatives are extensively employed in the realm of fine chemicals, pharmaceutical intermediates, pesticides, dyes, and various other sectors [ 1 , 2 ]. They serve as pivotal constituents in the domain of asymmetric synthesis and the complete synthesis of natural products within the realms of medicine and the chemical industry. On one hand, these compounds exhibit a myriad of biological activities, rendering them viable for synthesizing drugs aimed at combating ailments such as low levels of high-density lipoprotein cholesterol, arteriosclerosis, and arrhythmia. On the other hand, from a structural perspective, tetrahydroquinoline showcases an exquisite capacity to supply electrons to chromophores, thereby making it a promising candidate for the syntheses of dispersing dyes that emanate vivid hues [ 3 ]. Currently, the procedures for acquiring tetrahydroquinoline encompass the Beckman rearrangement, catalytic cyclization, and selective hydrogenation of quinoline. Amongst these approaches, the direct hydrogenation of quinoline has garnered significant interest due to its concise reaction pathway and remarkable atomic efficacy. Most of the prestigious heterogeneous catalysts utilized for the hydrogenation of quinoline compounds predominantly consist of noble metals (such as Pd, Ru, V). Nonetheless, their selectivity often falls short of expectations [ 4 ]. Furthermore, the scarcity and exorbitance of these invaluable metal catalysts pose limitations on their pragmatic implementation. Within the confines of conventional synthesis protocols, the frequent deployment of said precious metal catalysts invariably culminates in environmental contamination and the squandering of finite resources. Consequently, this quandary represents a grave predicament confronted by the stringent demands of contemporary society for eco-friendly and sustainable progression [ 5 – 7 ]. The advancement of affordable and plentiful catalysts utilizing non-precious metals is pivotal in attaining the proficient dehydrogenation of quinoline and its derivatives. Nanocatalysts,fortified by transition metals (such as Fe, Co, Ni, Mn, Cu), are meticulously synthesized upon nitrogen-doped porous carbon substrates [ 8 ]. Transition metal cobalt-supported nanocatalysts, characterized by their cost effectiveness and exceptional catalytic performance, emerge as the epitome of catalyst materials [ 9 ]. The reactivity of these metal catalysts hinges on the accessibility of their active metal sites, prompting the pursuit of strategies to enhance their catalytic activity through a reduction in nanoparticle size [ 10 ]. When cobalt nanoparticles are diminished in size, they become susceptible to agglomeration during catalytic reactions, thereby compromising both their size and performance. Enlightening investigations have substantiated that the amalgamation of metals and supports, coupled with the judicious design of efficient supported metal nanoparticle catalysts and the astute utilization of metal-support interactions, can not only ameliorate the dispersion of metal nanoparticles, but efficiently mitigate the agglomeration phenomenon that transpires throughout the catalytic process [ 11 ]. Gonget al. [ 12 ] successfully prepared ultra-fine Co nanoparticles (NPs) with Co-NX active sites as high-performance selective hydrogenation catalysts by using nitrogen-doped carbon nanotubes derived from ZIF-67. Zhao et al. [ 13 ] reported a Fe-Co nanoparticles (NPs) supported by bimetallic Fe-Co on nitrogen-doped carbon support were used as selective hydrogenation catalysts. Due to the remarkable abundance, low toxicity, exceptional activity, and enduring stability of nitrogen-doped porous carbon materials, they have garnered significant attention in scholarly circles [ 14 , 15 ]. In the course of fabricating nano-catalysts supported by nitrogen-doped porous carbon, the selection of appropriate nitrogen-doped carbon materials emerges as a pivotal juncture. Biomass, an unparalleled renewable resource on our planet [ 16 ], finds extensive utilization in the realms of biomedicine [ 17 ], fuel [ 18 ] and catalysis [ 19 ]. Renewable biomass ingeniously embodies high absorption potential, a distinctive structure, copious resources, inherent biodegradability, and minimal cost implications [ 20 ]. Hence, employing renewable biomass as nitrogen-doped carbon material represents an astute decision [ 21 ]. Against this backdrop, the present study espouses the application of chitosan as a support for the synthesis of supported nanocatalysts. The introduction of transition metals is another key factor in the preparation of supported catalysts. Primo et al. [ 22 ] using graphene oxide as a catalyst, catalyzed the oxidation of primary amine to imine. However, because the transition metal is not introduced into the catalyst, the catalyst is used in the reaction process is very large, which limits the practical application of the catalyst to a large extent. Wu et al. [ 23 ], showed significant electrocatalytic hydrogen evolution activity by grafting graphene nanosheet catalysts embedded with carbon nanotubes containing Co nanoparticles. Chen et al. [ 24 ] embedded Ni, Co bimetallic nanoparticles into nitrogen-doped carbon nanotube (NCNT) tips, which exhibited stronger catalytic and selective than the monometallic-based catalysts. Therefore, in this work, a high performance supported nano-catalyst (Co-NC) was prepared by using transition metal Co anchor on a nitrogenous doped porous carbon material derived from chitosan, which was used to catalyze the direct reduction of quinoline to quinoline aldehyde at 110 oC under atmospheric pressure, with formic acid as green hydrogen source and toluene as solvent. In summary, a way for the efficient synthesis of quinoline aldehyde was provided. 2. Experimental 2.1. Materials Chitosan, Cobalt (II) Phthalocyanine were provided from Sinopharm chemical Reagent Co., Ltd. (China). Quinoline, toluene, methanol (CH3OH), ethanol (CH3CH2OH), formic acid (HCOOH) were purchased from Aladdin Industrial Corporation. 2.2. Synthesis of Co@NSC catalysts In general, 3g of chitosan is added to a 200 mL round bottom flask containing 150 mL of acetic acid solution and fully stirred to completely dissolve in water. Then, Co(NO3)2 was dissolved in water to make a salt solution and slowly dropped into an aqueous chitosan solution. The mixture was continuously stirred magnetically for 6 h, and the mixture was dried and crushed to obtain the final blue-green powder. Finally, the obtained powder was placed into the porcelain cup, heated to 800 oC at 10 oC/min in the tube furnace under nitrogen atmosphere, keeping for 2 hours, then cooled to room temperature to obtained the black powder material Co@NC-800. In addition, in order to further explore the influence of pyrolysis temperature on the catalytic activity, catalysts Co-NC-700 and Co-NC-900 were obtained by pyrolysis at 700, 900 oC respectively. 2.3. Catalytic reduction of quinoline to quinoline aldehyde Usually, 0.25 mmol of quinoline, 50 mg of catalyst Co@NC-800 and 20 eq. HCOOH were added to a 10 mL high-pressure tube containing 3 mL of toluene for hydrogenation at 110 oC. In addition, the catalyst Co@NC-T can be easily separated by external magnets, and the catalyst can still be used for the next reaction after multiple washing with distilled water and ethanol. 2.4. Characterization A series of characterization was carried out to better grasp the catalyst. Thermogravimetric analysis (TGA) was used to record the whole pyrolysis process of the catalyst at 10 oC/min rising from room temperature to 1000 oC in the atmosphere of nitrogen. Fourier transform infrared spectroscopy (FTIR) was measured by the Bruker spectrometer (VERTEX 70) to analyze the fracture and formation of various chemical bonds in the catalyst. The ID/IG value can be obtained by Raman spectroscopy (Jobin Yvon Lab Ram HR evolution) and the defect degree of catalyst can be observed. The absorption-desorption curve and pore size distribution of the catalyst can be measured by Brunauer-Emmett-Teller (BET, Micromeritics ASAP 2010). The morphology, size and distribution of metal particles of catalyst Co@NC-T were observed by transmission electron microscopy (TEM, Tecnai G20 F30, 200 kv). Crystal structure of catalyst can be solved through powder X-ray diffraction (PXRD, Rigaku D/Max-2400). The chemical electron states of various elements in the catalyst were analyzed by X-ray photoelectron spectroscopy (XPS, perkin-elmer PHI-5702). The use of inductively coupled plasma Emission Spectrometry (ICP) allows for the precise determination of metal particle content within a catalyst. The relative contents of various elements in the catalyst can be measured by elemental analysis. The conversion and selectivity of the whole reaction were detected by GC-MS (Agilent 5977E). 3. Results and discussion 3.1. Characterization of catalyst A series of characterization of the catalyst was carried out to further explore the physicochemical properties of Co@NC-T catalyst prepared by water heat treatment with chitosan and Cobalt (II) Phthalocyanine as raw material (Scheme 1 ). From the Fourier infrared spectrum in Fig. 1 a, the chemical bond changes in the raw material, catalyst precursor and catalyst Co@NC-800 can be clearly observed. Among them, the O-H stretching vibration peak at 2929 cm-1 is present in the raw material and catalyst precursor and disappears after pyrolysis, which may be due to the evaporation of water molecules with increasing temperature.The stretching vibration peaks at positions 1562.9 and 1408.6 were C = N and C-O, respectively, while the peaks almost disappeared after water heat treatment, which may be due to coordination between chitosan and Cobalt (II) Phthalocyanine during this process. Additionally, theN-H and C-N stretching vibration peaks at 3430.7 and 1075.0cm-1 were still preserved after high temperature pyrolysis, and the presence of C-N bond greatly enriched the performance of carbon materials [ 25 ].Conversely, in order to further explore the thermal stability of the catalyst, the thermogravimetric analysis of the catalyst precursor Co@NC was carried out, and it can be clearly observed from Fig. 1 b that the mass of the catalyst precursor gradually decreases and tends to be stable as the pyrolysis temperature increases. when the pyrolysis temperature rose to 227.7 oC, the mass of the catalyst precursor lost 28.8%, which may be caused by the overflow of water molecules and gas during the process.The mass of catalyst precursor in the temperature segment from 227.7 oC to 342.1 oC showed a linear decline, with a loss of 30.9%, which may be related to the sublimation pyrolysis of the product after coordination of chitosan and Cobalt (II) Phthalocyanine. When the pyrolysis temperature increased from 342.1 oC to 975.9 oC, the mass loss was 16.25%, which maybe related to the gradual formation of stable structure by further pyrolysis of carbon materials. In addition, the presence and contents of C, N, O and Coin catalysts at different pyrolysis temperatures can be observed from the XPS full spectrum in Fig. S2 . The high resolution XPS spectra of C 1s, N 1s and Co 2p were comprehensively analyzed to clearly explain the bond form of each element in the sample. In the C1s high-resolution spectrum in Fig. 2 a, it can be observed that the characteristic peaks corresponding to 284.44, 285.19 and 288.54 eV are C = C, C = N and O-C = O respectively [ 26 ]. It is noteworthy that the appearance of the characteristic peak of O-C = O is contingent upon the carbonization temperature reaching 900°C. This may be attributed to the degree of carbonization, and the presence of the C = N bond serves to enhance the physical and chemical properties of pure carbon materials. The high resolution spectrum of N 1s in Fig. 2 b shows the existence form of N. There are two main peaks at 398.10 and 400.60 eV, respectively, pyridine N and graphite N [ 27 – 29 ]. The presence of nitrogen compounds not only in beneficial to stabilize and disperse metal nanoparticles, but also causes certain defect sites and promotes the catalytic activity of catalysts. From the high resolution spectrum of Co 2p in Fig. 2 c, it can be observed that the corresponding characteristic peaks at 780 and 798 eV are respectively Co 2p 3/2 and Co 2p 1/2. In the Co 2p 3/2 spectrum, two basic peaks are Co-N and satellite peaks at 780.2 and 797.32 eV respectively [ 30 ]. In addition, there is no Co 0, and Co exists in the catalyst in the form of Co-N complex at different carbonization temperatures. The view that N atoms were doped into carbon was again proved by XPS. Figure 3 a shows the crystal structure of each material in the catalyst at different carbonation temperatures, and the characteristic peak of graphite carbon (002) at around 24.7° can be clearly observed from the figure. In addition, no obvious characteristic peak of any crystal type of Co was observed in the XPS spectrum, and no characteristic peak of Co was found in the XPS spectrum of the catalyst with the highest Co content ( Fig. S3 ), which maybe caused by the low Co content in the catalyst, and the highest Co content known by ICP was only 0.96%. From Fig. 3 b, it is clear to observe the ID/IG values of each catalyst at different pyrolysis temperatures, and then judge the degree of defects. Peak D and peak G are Raman characteristic peaks of a C atomic crystal, occurring at approximately 1300 cm-1 and 1580 cm-1, respectively. Peak D represents the defects of the lattice of C atoms, while peak G represents the in-plane expansion vibration of sp2 hybridization of C atoms. When the pyrolysis temperature is 800 oC, the ID/IG value is lower, which may be due to the degree of graphitization at this temperature is higher and the defect degree is reduced. The distribution of nitrogen adsorption-desorption isotherms and pore size of catalyst Co@NC-800 and NC-800 can be intuitively observed from Fig. 4 . The nitrogen adsorption-desorption isotherm of the catalyst exhibited a typical Type IV behavior, accompanied by the appearance of a hysteresis loop. Obviously, it can be seen from Fig. 4 b that the pore diameter of catalyst Co@NC-800 is mainly distributed in the range of 2–5 nm, and there are some mesoporous pores with the size of 30–35 nm. Compared with catalyst NC-800, this shows that the abundant pore diameter of catalyst Co@NC-800 is conducive to promoting the substrate diffusion and thus improving the catalytic performance of catalyst. Furthermore, the specific surface area of catalyst Co@NC-800 was 268.19 m2/g, and the large specific surface area also played a positive role in the catalytic reaction ( Table S3 ). 3.2. Conditional screening of transfer hydrogenation of quinolone over Co@NC-800 By means of a series of characterization methods, the physical and chemical properties of catalyst Co@NC-800 have been further studied, and the catalytic performance of catalyst has been investigated by transfer hydrogenation of quinoline compounds. Using quinoline as substrate, toluene as solvent and green formic acid as hydrogen source, the conditions of transfer hydrogenation reaction was investigated under relatively mild conditions. As can be observed from Table 1 , the conversion of quinoline transfer hydrogenation presents a volcanic trend with the increase of pyrolysis temperature (Co@NC-800 > Co@NC-900 > Co@NC-700). This may be caused by the amount of the Co content. When the pyrolysis temperature is 900°C, the catalytic effect of the catalyst is finally observed. At this temperature, the Co content of the catalyst prepared is up to 0.96 wt % (Table 1 , entries 1–3 and Table S2 ). In addition, the presence of a certain amount of N enables Co to disperse in the N-doped carbon material more uniformly, thus promoting the catalytic activity of the catalyst ( table S1 ) [ 31 ]. In order to gain further insight into the impact of Co content on the catalytic performance of the catalyst, a series of samples with Co concentrations of 0.45, 0.56 and 0.96 wt % were prepared for the transfer hydrogenation of quinoline, with all other conditions held constant (Table 1 , entries 2, 4–5 and 13 ). It can be observed that with the increase of Co content, the catalytic effect of the catalyst became outstanding with the optimal conversion rate reaching 100% and selectivity as high as 99% ( Table S2 ). When the catalyst prepared without any cobalt source was used to catalyze the hydrogenation reaction of quinoline, there was almost no product generation. The subsequent phase of the study was to investigate the impact of the solvent on the catalytic performance of the catalyst. Methanol, ethanol, toluene and water were selected as solvents for the reaction, and the sequence of activity was: toluene > water > ethanol > methanol, in which, when methanol was selected as the solvent, almost no products were generated. However, when toluene was used as the solvent, the conversion and selectivity were optimal (Table 1 , entries 2, 6–8 ). What's more, a reduction in the amount of catalyst resulted in a corresponding decline in the catalytic performance of the catalyst. In particular, the transfer hydrogenation of quinoline is basically impossible without the addition of catalyst (Table 1 , entries 2, 9–11 ). It was observed that the catalyst was unable to catalyse the reaction in the absence of an added hydrogen source. When 0.2 mmol KSCN was added, which is more readily poisonous to the metal, the catalytic performance of the catalyst was significantly diminished. This finding provides additional evidence that the active site is Co on the catalyst in the catalytic hydrogenation of quinoline transfer (Table 1 , entries 13–14 ).Furthermore, the TOF values under different reaction conditions indicated that Co@NC-800 was the most excellent catalyst. Table 1 Optimization of transfer hydrogenation conditions of quinolone over Co-catalyst.a Entry Catalyst Mass (mg) Solvent Time (h) Conv. b (%) Sel. b (%) TOFg (h-1) 1 Co@NC-700 50 toluene 12 3 99 1.07 2 Co@NC-800 50 toluene 12 100 99 2.53 3 Co@NC-900 50 toluene 12 38 99 1.73 4 c Co@NC-800 50 toluene 12 12 99 0.31 5 d Co@NC-800 50 toluene 12 76 99 1.92 6 Co@NC-800 50 methanol 12 trace - - 7 Co@NC-800 50 ethanol 12 11% 72 0.20 8 Co@NC-800 50 water 12 31 90 0.72 9 Co@NC-800 30 toluene 12 94 99 2.38 10 Co@NC-800 10 toluene 12 87 99 2.20 11 Co@NC-800 0 toluene 12 trace - - 12 e Co@NC-800 50 toluene 12 trace - - 13 NC-800 50 toluene 12 trace - - 14f Co@NC-800 50 toluene 12 trace - - a Reaction conditions: quinoline (0.25 mmol), catalyst (0.96 wt % Co), 130 oC, 12h, toluene (3ml), 20 eq. HCOOH; b Determined by GC-MS; c 0.45 wt % Co; d 0.59% wt % Co; e 0 eq. HCOOH; f adding 0.2 mmol KSCN; g TOF = [moles of converted substrate] × [(moles of Co) × (reaction time in h)]-1. 3.3. Catalytic transfer hydrogenation of quinoline to generate the corresponding N- for my ltetrahydroquinoline over Co@NC-800 To further investigate the universality of catalyst Co@NC-800, transfer hydrogenation of various substrates was carried out under optimal reaction conditions (Table 2 ). As can be observed from Table 2 , entries 1–2 , both quinoline and isoquinoline demonstrated excellent conversion and selectivity following a 12-hour reaction period. The transfer hydrogenation of 2-methyl-quinoline, 8-methyl-quinoline, and 6-methoxyquinoline with electron-absorbent groups can be achieved after a prolonged reaction time. The conversion of 8-methyl-quinoline is higher than that of 2-methyl-quinoline, which may be attributed to steric hindrance (Table 2 , entries 3–5 ). It is noteworthy that the reaction of 3-bromine quinoline and 4-bromine isoquinoline with an electronic group results in the formation of N-formyltetrahydroquinoline, which exhibits the phenomenon of debromination. Additionally, a notable amount of 1,2,3,4-tetrahydroquinoline is generated throughout the course of the reaction (Table 2 , entries 6–7 ). The conversion and selectivity of 6-nitroquinoline are up to 99%, which reflected the excellent catalytic activity of the catalyst (Table 2 , entries 8 ). Reaction substrates with complex functional groups such as 8-hydroxyquinoline, 8-borate and 2-formaldehydel-8-hydroxyquinoline all show good conversion, which demonstrate the resistance and stability of catalyst Co@NC-800 to functional groups (Table 2 , entries 9–11 ). Table 2 Co@NC-800 catalyst catalytic transfer hydrogenation of quinoline to generate the corresponding N-formyltetrahydroquinoline. a 3.4. Cyclic test of quinoline transfer hydrogenation over catalyst Co@NC-800 The reusability of catalysts is a significant criterion for assessing their performance. Accordingly, the catalyst Co@NC-800 was employed for the transfer hydrogenation of quinoline. The recovered catalyst was subjected to repeated washing with distilled water and ethanol, followed by vacuum drying prior to the subsequent reaction.It can be observed from Fig. 5 that six consecutive cyclic reactions have been conducted, and the detection of GC-MS indicates that the catalyst Co@NC- 800 still has high activity and selectivity, which reflects the chemical stability of the catalyst. Compared with the freshly prepared catalyst, the recovered catalyst Co@NC-800 did not change significantly in the TEM. The recovered catalyst was also characterized by XRD, and there was basically no significant change, which further proved the excellent stability of the catalyst ( Fig. S4 ). 4. Conclusions Supported catalyst Co@NSC was prepared by highly dispersing transition metal cobalt on nitrogen-doped porous carbon material. Quinoline can be directly reduced and catalyzed to produce quinoline aldehyde by using toluene as solvent in a high pressure tube at 110 oC. Concurrently, a variety of quinolines can be efficiently transformed into the corresponding quinolinaldehyde with a high yield and excellent selectivity. The findings demonstrate that the catalytic activity of nitrogen-doped porous carbon materials can be significantly enhanced through the incorporation of cobalt. It is worthy of mention that the presence of nitrogen-containing compounds is not only conducive to stabilizing and dispersing metal nanoparticles, but also causes certain defect sites to promote the catalytic activity of the catalyst. The abundant pore size of the catalyst Co@NC- 800 is conducive to promoting substrate diffusion and improving the catalytic performance of the catalyst. Adding cobalt to nitrogen-doped porous carbon can reduce the use of cobalt, thereby reducing environmental pollution and avoiding resource waste. The catalyst was used for the transfer hydrogenation of quinoline, and the recovered catalyst could be washed with distilled water and ethanol for reuse, and the catalytic activity remained high through six cycles of experiments. This shows that the catalyst is not only easy to recover, but also further proves the excellent stability of the catalyst. In summary, the reasonable design of the catalyst Co@NSC in this study provides a way for the future research and development of other supported heterogeneous catalysts. Declarations Ethics and Consent to Participate Disclosure of potential conflicts of interest Research involving Human Participants and/or Animals Informed consent Consent for Publication Competing Interest declaration The authors have no competing interests to declare that are relevant to the content of this article Author Contribution Lan Wu: Funding acquisition, Writing-original draft, Conceptualization, Data curation, Formal analysis; Yongchao Liu: Investigation, Formal analysis, Data curation, Writing-original draft; Ze Wang: Formal analysis, Visualization.; Xinyu Ye: Data Curation, Project administration, Supervision.; Yaozong Liu: Validation, Writing –review & editing, Supervision, Data curation; Zhenhua Li: Funding acquisition, Project administration, Supervision, Writing-review & editing; Zhengping Dong: Conceptualization, Supervision, Resources.All authors reviewed the manuscript. Declaration of competing interest The authors declare no competing financial interest. Funding Not applicable Availability of data and materials All relevant data are within the paper Acknowledgements This work is supported by the National Natural Science Foundation of China (No. 31760608), the Key Program of Natural Science Foundation of Gansu Province (No. 22JR5RA178), the Fundamental Research Funds for the Central Universities (No. 31920230168) . the Key Program of Natural Science Foundation of Gansu Province (No. 22JR5RA178 and 23ZDGD001), the Fundamental Research Funds for the Central Universities (No. 31920230168) and the Natural Science Foundation of Gansu Province (No. 23JRRA716). the Lanzhou Chengguan District Science and Technology Plan Project (No. 2022JSCX0009), the Gansu Province University Teacher Innovation Fund Project (No. 2023B-049) References Wang X, Chen W, Zhang L, Yao T, Liu W, Lin Y, Ju H, Dong J, Zheng L, Yan W, Zheng X, Li Z, Wang X, Yang J, He D, Wang Y, Deng Z, Wu Y, Li Y (2017) Uncoordinated Amine Groups ofMetal-Organic Frameworks to Anchor Single Ru Sites as Chemoselective Catalysts toward the Hydrogenation of Quinoline. 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ACS Appl Mater Interfaces 14:24425–24434. https://doi.org/10.1021/acsami.2c04826 Wang J-C, Ding F-W, Ma J-P, Liu Q-K, Cheng J-Y, Dong Y-B (2015) Co(II)-MOF: A Highly Efficient Organic Oxidation Catalyst with Open Metal Sites. Inorg Chem 54:10865–10872. https://doi.org/10.1021/acs.inorgchem.5b01938 Zhou S, Dai F, Dang C, Wang M, Liu D, Lu F, Qi H (2019) Scale-up biopolymer-chelated fabrication of cobalt nanoparticles encapsulated inN-enriched graphene shells for biofuel upgrade with formic acid. Green Chem 21:4732–4747. https://doi.org/10.1039/C9GC01720H Bai L, Hsu C-S, Alexander DTL, Chen HM, Hu X (2019) A Cobalt-Iron Double-Atom Catalyst for the Oxygen Evolution Reaction. J Am Chem Soc 141:14190–14199. https://doi.org/10.1021/jacs.9b05268 Zhang M, Wang Y-G, Chen W, Dong J, Zheng L, Luo J, Wan J, Tian S, Cheong W-C, Wang D, Li Y (2017) Metal (Hydr)oxides@Polymer Core-Shell Strategy to Metal Single-Atom Materials. J Am Chem Soc 139:10976–10979. https://doi.org/10.1021/jacs.7b05372 Zhang J, Zhao Y, Chen C, Huang Y-C, Dong C-L, Chen C-J, Liu R-S, Wang C, Yan K, Li Y, Wang G (2019) Tuning the Coordination Environment in Single-Atom Catalysts to Achieve Highly Efficient Oxygen Reduction Reactions. J Am Chem Soc 141:20118–20126. https://doi.org/10.1021/jacs.9b09352 Zhou H, Hong S, Zhang H, Chen Y, Xu H, Wang X, Jiang Z, Chen S, Liu Y (2019) Toward biomass -based single-atom catalysts and plastics: Highly active single-atom Co on N-doped carbon for oxidative esterification of primary alcohols. Appl Catal B: Environ 256:117767. https://doi.org/10.1016/j.apcatb.2019.117767 Zhao Y, Zhou H, Chen W, Tong Y, Zhao C, Lin Y, Jiang Z, Zhang Q, Xue Z, Cheong W-C, Jin B, Zhou F, Wang W, Chen M, Hong X, Dong J, Wei S, Li Y, Wu Y (2019) Two-Step Carbothermal Welding to Access Atomically Dispersed Pd 1 on Three-Dimensional Zirconia Nanonet for Direct Indole Synthesis. J Am Chem Soc 141:10590–10594. https://doi.org/10.1021/jacs.9b03182 Scheme 1 Scheme 1 is available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files Tables.docx Supportinginformation.docx Supportinginformation.docx Schem1.png Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 08 Dec, 2024 Reviews received at journal 26 Nov, 2024 Reviews received at journal 22 Nov, 2024 Reviewers agreed at journal 17 Nov, 2024 Reviewers agreed at journal 17 Nov, 2024 Reviewers invited by journal 16 Nov, 2024 Editor assigned by journal 11 Nov, 2024 Submission checks completed at journal 11 Nov, 2024 First submitted to journal 04 Nov, 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. 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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-5391338","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":383128832,"identity":"dcd55e93-3865-4b6e-8412-0632949849dc","order_by":0,"name":"Lan Wu","email":"","orcid":"","institution":"Northwest Minzu University","correspondingAuthor":false,"prefix":"","firstName":"Lan","middleName":"","lastName":"Wu","suffix":""},{"id":383128833,"identity":"5cd45706-1fff-4687-a7a2-8fda7affed82","order_by":1,"name":"Yongchao Liu","email":"","orcid":"","institution":"Northwest Minzu University","correspondingAuthor":false,"prefix":"","firstName":"Yongchao","middleName":"","lastName":"Liu","suffix":""},{"id":383128834,"identity":"15e30c2b-ce29-4ad4-91b4-35c104abbd6a","order_by":2,"name":"Ze Wang","email":"","orcid":"","institution":"Northwest Minzu University","correspondingAuthor":false,"prefix":"","firstName":"Ze","middleName":"","lastName":"Wang","suffix":""},{"id":383128835,"identity":"a5923aa4-b62c-4c1d-b6ef-d35cf448478d","order_by":3,"name":"Xinyu Ye","email":"","orcid":"","institution":"Northwest Minzu University","correspondingAuthor":false,"prefix":"","firstName":"Xinyu","middleName":"","lastName":"Ye","suffix":""},{"id":383128836,"identity":"c68bb4b0-9a9d-419e-a934-e53e3458e2e5","order_by":4,"name":"Zhenhua Li","email":"","orcid":"","institution":"Gansu Yinguang Juyin Chemical Co., Ltd","correspondingAuthor":false,"prefix":"","firstName":"Zhenhua","middleName":"","lastName":"Li","suffix":""},{"id":383128837,"identity":"ece6564d-4f74-421a-9c0d-55c812b9dd68","order_by":5,"name":"Yaozong Liu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9ElEQVRIie2RPwrCMBSHEypxCXatCPUKlkJQyE1cUoS4qIurQ6WgiwfwEg4uzoVAJ6GrbnqDjpnEFztKo6NgvuWRPx+/vBeEHI4fpOO9Cg+Jh9e3ipsFXuc2hdSKjDvtTEV7+VJSu1IXlYS0kD0q66VdaVPW1UgKEswGPS54ctgqSFnxcfPDKAsCxBdGiWdCxuycgFLIeWpToodcGmUy1ypkOSg4VXZFQC8bUNRQKMrK+xdKbhRaJBkSkHL5mEKWoxSGTGDIeGd6uUCKsPTi++p41fCV/QxvtYaJncrp/VateKMCtIL3PdF83eBV9nOHw+H4e57RWlbmF+sQUAAAAABJRU5ErkJggg==","orcid":"","institution":"Northwest Minzu University","correspondingAuthor":true,"prefix":"","firstName":"Yaozong","middleName":"","lastName":"Liu","suffix":""},{"id":383128838,"identity":"07a3fb45-af5d-4710-b6e6-408aaaf7e795","order_by":6,"name":"Zhengping Dong","email":"","orcid":"","institution":"Lanzhou University","correspondingAuthor":false,"prefix":"","firstName":"Zhengping","middleName":"","lastName":"Dong","suffix":""}],"badges":[],"createdAt":"2024-11-05 01:53:34","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5391338/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5391338/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":70164570,"identity":"9dea79c8-932f-4485-8798-c5f5e262ef4f","added_by":"auto","created_at":"2024-11-29 05:34:35","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":296585,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e(a) FTIR spectra of Co@NC-800, Co@NC precursor and the raw materials; (b) TGA curve of the Co@NC precursor under N2 condition.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5391338/v1/cc79c8232cf322d9250bf4a4.png"},{"id":70164246,"identity":"7f251522-cbc8-489d-909b-9b5b92159584","added_by":"auto","created_at":"2024-11-29 05:26:35","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":324607,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHigh-resolution XPS spectra for (a) C 1s, (b) N 1s, (c) Co 2p spectra of Co@NC-T catalysts.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5391338/v1/bf53d2ae3411f7a0adc1d211.png"},{"id":70165806,"identity":"b0931146-7e7c-4c5d-93bf-69288afa5fd8","added_by":"auto","created_at":"2024-11-29 05:42:35","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":535556,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e(a) XRD spectra of Co@NC-2-T catalysts; (b) Raman spectra of Co@NC-2-T catalysts.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5391338/v1/771c84f221f1f54c2610e404.png"},{"id":70165804,"identity":"f38d2389-d8d4-4d72-95e7-6ad48ba30919","added_by":"auto","created_at":"2024-11-29 05:42:35","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":212428,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e(a) Nitrogen adsorption-desorption isotherms and (b) the corresponding pore size distribution curves of NC-800 and Co@NC-800.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-5391338/v1/54a09ccaf3b730fd9944ea2a.png"},{"id":70164251,"identity":"de105d55-b833-42a9-9545-cb977df78b26","added_by":"auto","created_at":"2024-11-29 05:26:35","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":180857,"visible":true,"origin":"","legend":"\u003cp\u003eCyclic performance of Co@NC-800 catalyst in quinoline transfer hydrogenation.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-5391338/v1/2b434598d11a9a84ed13d366.png"},{"id":70166794,"identity":"2ede3492-d360-476c-8080-80bbe98d16f9","added_by":"auto","created_at":"2024-11-29 05:58:40","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2357304,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5391338/v1/1fc2f738-e9b2-4838-b95d-cd762b9584cd.pdf"},{"id":70164254,"identity":"4049a1a9-32bc-4ad2-8442-61fc8059e61f","added_by":"auto","created_at":"2024-11-29 05:26:35","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":224873,"visible":true,"origin":"","legend":"","description":"","filename":"Tables.docx","url":"https://assets-eu.researchsquare.com/files/rs-5391338/v1/a31fb04712d727c2bf4ce539.docx"},{"id":70164573,"identity":"c8139474-abcf-4dc3-b7c4-c70feffa1b35","added_by":"auto","created_at":"2024-11-29 05:34:35","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":525207,"visible":true,"origin":"","legend":"","description":"","filename":"Supportinginformation.docx","url":"https://assets-eu.researchsquare.com/files/rs-5391338/v1/df87ee469ab270bbfee39de9.docx"},{"id":70164255,"identity":"a421346e-973a-464d-bfab-d10eb228ee6b","added_by":"auto","created_at":"2024-11-29 05:26:35","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":525207,"visible":true,"origin":"","legend":"","description":"","filename":"Supportinginformation.docx","url":"https://assets-eu.researchsquare.com/files/rs-5391338/v1/07c8dafa441e16fc1d8c7ba2.docx"},{"id":70166792,"identity":"6c32143a-4642-4fec-a327-f09a7449bb85","added_by":"auto","created_at":"2024-11-29 05:58:35","extension":"png","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":60308,"visible":true,"origin":"","legend":"","description":"","filename":"Schem1.png","url":"https://assets-eu.researchsquare.com/files/rs-5391338/v1/f3d524dc780df3e8040d0f62.png"}],"financialInterests":"No competing interests reported.","formattedTitle":"Preparation of mesoporous chitosan cobalt supported nano-catalyst for the catalyzed reduction of quinoline to quinoline aldehyde","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eTetrahydroquinoline and its derivatives are extensively employed in the realm of fine chemicals, pharmaceutical intermediates, pesticides, dyes, and various other sectors [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. They serve as pivotal constituents in the domain of asymmetric synthesis and the complete synthesis of natural products within the realms of medicine and the chemical industry. On one hand, these compounds exhibit a myriad of biological activities, rendering them viable for synthesizing drugs aimed at combating ailments such as low levels of high-density lipoprotein cholesterol, arteriosclerosis, and arrhythmia. On the other hand, from a structural perspective, tetrahydroquinoline showcases an exquisite capacity to supply electrons to chromophores, thereby making it a promising candidate for the syntheses of dispersing dyes that emanate vivid hues [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Currently, the procedures for acquiring tetrahydroquinoline encompass the Beckman rearrangement, catalytic cyclization, and selective hydrogenation of quinoline. Amongst these approaches, the direct hydrogenation of quinoline has garnered significant interest due to its concise reaction pathway and remarkable atomic efficacy.\u003c/p\u003e \u003cp\u003eMost of the prestigious heterogeneous catalysts utilized for the hydrogenation of quinoline compounds predominantly consist of noble metals (such as Pd, Ru, V). Nonetheless, their selectivity often falls short of expectations [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Furthermore, the scarcity and exorbitance of these invaluable metal catalysts pose limitations on their pragmatic implementation. Within the confines of conventional synthesis protocols, the frequent deployment of said precious metal catalysts invariably culminates in environmental contamination and the squandering of finite resources. Consequently, this quandary represents a grave predicament confronted by the stringent demands of contemporary society for eco-friendly and sustainable progression [\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The advancement of affordable and plentiful catalysts utilizing non-precious metals is pivotal in attaining the proficient dehydrogenation of quinoline and its derivatives. Nanocatalysts,fortified by transition metals (such as Fe, Co, Ni, Mn, Cu), are meticulously synthesized upon nitrogen-doped porous carbon substrates [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Transition metal cobalt-supported nanocatalysts, characterized by their cost effectiveness and exceptional catalytic performance, emerge as the epitome of catalyst materials [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The reactivity of these metal catalysts hinges on the accessibility of their active metal sites, prompting the pursuit of strategies to enhance their catalytic activity through a reduction in nanoparticle size [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. When cobalt nanoparticles are diminished in size, they become susceptible to agglomeration during catalytic reactions, thereby compromising both their size and performance. Enlightening investigations have substantiated that the amalgamation of metals and supports, coupled with the judicious design of efficient supported metal nanoparticle catalysts and the astute utilization of metal-support interactions, can not only ameliorate the dispersion of metal nanoparticles, but efficiently mitigate the agglomeration phenomenon that transpires throughout the catalytic process [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Gonget al. [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] successfully prepared ultra-fine Co nanoparticles (NPs) with Co-NX active sites as high-performance selective hydrogenation catalysts by using nitrogen-doped carbon nanotubes derived from ZIF-67. Zhao et al. [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] reported a Fe-Co nanoparticles (NPs) supported by bimetallic Fe-Co on nitrogen-doped carbon support were used as selective hydrogenation catalysts.\u003c/p\u003e \u003cp\u003eDue to the remarkable abundance, low toxicity, exceptional activity, and enduring stability of nitrogen-doped porous carbon materials, they have garnered significant attention in scholarly circles [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. In the course of fabricating nano-catalysts supported by nitrogen-doped porous carbon, the selection of appropriate nitrogen-doped carbon materials emerges as a pivotal juncture. Biomass, an unparalleled renewable resource on our planet [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], finds extensive utilization in the realms of biomedicine [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], fuel [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] and catalysis [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Renewable biomass ingeniously embodies high absorption potential, a distinctive structure, copious resources, inherent biodegradability, and minimal cost implications [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Hence, employing renewable biomass as nitrogen-doped carbon material represents an astute decision [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Against this backdrop, the present study espouses the application of chitosan as a support for the synthesis of supported nanocatalysts.\u003c/p\u003e \u003cp\u003eThe introduction of transition metals is another key factor in the preparation of supported catalysts. Primo et al. [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] using graphene oxide as a catalyst, catalyzed the oxidation of primary amine to imine. However, because the transition metal is not introduced into the catalyst, the catalyst is used in the reaction process is very large, which limits the practical application of the catalyst to a large extent. Wu et al. [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], showed significant electrocatalytic hydrogen evolution activity by grafting graphene nanosheet catalysts embedded with carbon nanotubes containing Co nanoparticles. Chen et al. [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] embedded Ni, Co bimetallic nanoparticles into nitrogen-doped carbon nanotube (NCNT) tips, which exhibited stronger catalytic and selective than the monometallic-based catalysts. Therefore, in this work, a high performance supported nano-catalyst (Co-NC) was prepared by using transition metal Co anchor on a nitrogenous doped porous carbon material derived from chitosan, which was used to catalyze the direct reduction of quinoline to quinoline aldehyde at 110 oC under atmospheric pressure, with formic acid as green hydrogen source and toluene as solvent. In summary, a way for the efficient synthesis of quinoline aldehyde was provided.\u003c/p\u003e"},{"header":"2. Experimental","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Materials\u003c/h2\u003e \u003cp\u003eChitosan, Cobalt (II) Phthalocyanine were provided from Sinopharm chemical Reagent Co., Ltd. (China). Quinoline, toluene, methanol (CH3OH), ethanol (CH3CH2OH), formic acid (HCOOH) were purchased from Aladdin Industrial Corporation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Synthesis of Co@NSC catalysts\u003c/h2\u003e \u003cp\u003eIn general, 3g of chitosan is added to a 200 mL round bottom flask containing 150 mL of acetic acid solution and fully stirred to completely dissolve in water. Then, Co(NO3)2 was dissolved in water to make a salt solution and slowly dropped into an aqueous chitosan solution. The mixture was continuously stirred magnetically for 6 h, and the mixture was dried and crushed to obtain the final blue-green powder. Finally, the obtained powder was placed into the porcelain cup, heated to 800 oC at 10 oC/min in the tube furnace under nitrogen atmosphere, keeping for 2 hours, then cooled to room temperature to obtained the black powder material Co@NC-800. In addition, in order to further explore the influence of pyrolysis temperature on the catalytic activity, catalysts Co-NC-700 and Co-NC-900 were obtained by pyrolysis at 700, 900 oC respectively.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Catalytic reduction of quinoline to quinoline aldehyde\u003c/h2\u003e \u003cp\u003eUsually, 0.25 mmol of quinoline, 50 mg of catalyst Co@NC-800 and 20 eq.\u0026nbsp;HCOOH were added to a 10 mL high-pressure tube containing 3 mL of toluene for hydrogenation at 110 oC. In addition, the catalyst Co@NC-T can be easily separated by external magnets, and the catalyst can still be used for the next reaction after multiple washing with distilled water and ethanol.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Characterization\u003c/h2\u003e \u003cp\u003eA series of characterization was carried out to better grasp the catalyst. Thermogravimetric analysis (TGA) was used to record the whole pyrolysis process of the catalyst at 10 oC/min rising from room temperature to 1000 oC in the atmosphere of nitrogen. Fourier transform infrared spectroscopy (FTIR) was measured by the Bruker spectrometer (VERTEX 70) to analyze the fracture and formation of various chemical bonds in the catalyst. The ID/IG value can be obtained by Raman spectroscopy (Jobin Yvon Lab Ram HR evolution) and the defect degree of catalyst can be observed. The absorption-desorption curve and pore size distribution of the catalyst can be measured by Brunauer-Emmett-Teller (BET, Micromeritics ASAP 2010). The morphology, size and distribution of metal particles of catalyst Co@NC-T were observed by transmission electron microscopy (TEM, Tecnai G20 F30, 200 kv). Crystal structure of catalyst can be solved through powder X-ray diffraction (PXRD, Rigaku D/Max-2400). The chemical electron states of various elements in the catalyst were analyzed by X-ray photoelectron spectroscopy (XPS, perkin-elmer PHI-5702). The use of inductively coupled plasma Emission Spectrometry (ICP) allows for the precise determination of metal particle content within a catalyst. The relative contents of various elements in the catalyst can be measured by elemental analysis. The conversion and selectivity of the whole reaction were detected by GC-MS (Agilent 5977E).\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results and discussion","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003e3.1. Characterization of catalyst\u003c/h2\u003e\n \u003cp\u003eA series of characterization of the catalyst was carried out to further explore the physicochemical properties of Co@NC-T catalyst prepared by water heat treatment with chitosan and Cobalt (II) Phthalocyanine as raw material (Scheme \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). From the Fourier infrared spectrum in Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ea, the chemical bond changes in the raw material, catalyst precursor and catalyst Co@NC-800 can be clearly observed. Among them, the O-H stretching vibration peak at 2929 cm-1 is present in the raw material and catalyst precursor and disappears after pyrolysis, which may be due to the evaporation of water molecules with increasing temperature.The stretching vibration peaks at positions 1562.9 and 1408.6 were C\u0026thinsp;=\u0026thinsp;N and C-O, respectively, while the peaks almost disappeared after water heat treatment, which may be due to coordination between chitosan and Cobalt (II) Phthalocyanine during this process. Additionally, theN-H and C-N stretching vibration peaks at 3430.7 and 1075.0cm-1 were still preserved after high temperature pyrolysis, and the presence of C-N bond greatly enriched the performance of carbon materials [\u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e].Conversely, in order to further explore the thermal stability of the catalyst, the thermogravimetric analysis of the catalyst precursor Co@NC was carried out, and it can be clearly observed from Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eb that the mass of the catalyst precursor gradually decreases and tends to be stable as the pyrolysis temperature increases. when the pyrolysis temperature rose to 227.7 oC, the mass of the catalyst precursor lost 28.8%, which may be caused by the overflow of water molecules and gas during the process.The mass of catalyst precursor in the temperature segment from 227.7 oC to 342.1 oC showed a linear decline, with a loss of 30.9%, which may be related to the sublimation pyrolysis of the product after coordination of chitosan and Cobalt (II) Phthalocyanine. When the pyrolysis temperature increased from 342.1 oC to 975.9 oC, the mass loss was 16.25%, which maybe related to the gradual formation of stable structure by further pyrolysis of carbon materials.\u003c/p\u003e\n \u003cp\u003eIn addition, the presence and contents of C, N, O and Coin catalysts at different pyrolysis temperatures can be observed from the XPS full spectrum in \u003cstrong\u003eFig. S2\u003c/strong\u003e. The high resolution XPS spectra of C 1s, N 1s and Co 2p were comprehensively analyzed to clearly explain the bond form of each element in the sample. In the C1s high-resolution spectrum in Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ea, it can be observed that the characteristic peaks corresponding to 284.44, 285.19 and 288.54 eV are C\u0026thinsp;=\u0026thinsp;C, C\u0026thinsp;=\u0026thinsp;N and O-C\u0026thinsp;=\u0026thinsp;O respectively [\u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e]. It is noteworthy that the appearance of the characteristic peak of O-C\u0026thinsp;=\u0026thinsp;O is contingent upon the carbonization temperature reaching 900\u0026deg;C. This may be attributed to the degree of carbonization, and the presence of the C\u0026thinsp;=\u0026thinsp;N bond serves to enhance the physical and chemical properties of pure carbon materials. The high resolution spectrum of N 1s in Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eb shows the existence form of N. There are two main peaks at 398.10 and 400.60 eV, respectively, pyridine N and graphite N [\u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e]. The presence of nitrogen compounds not only in beneficial to stabilize and disperse metal nanoparticles, but also causes certain defect sites and promotes the catalytic activity of catalysts. From the high resolution spectrum of Co 2p in Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ec, it can be observed that the corresponding characteristic peaks at 780 and 798 eV are respectively Co 2p 3/2 and Co 2p 1/2. In the Co 2p 3/2 spectrum, two basic peaks are Co-N and satellite peaks at 780.2 and 797.32 eV respectively [\u003cspan class=\"CitationRef\"\u003e30\u003c/span\u003e]. In addition, there is no Co 0, and Co exists in the catalyst in the form of Co-N complex at different carbonization temperatures. The view that N atoms were doped into carbon was again proved by XPS.\u003c/p\u003e\n \u003cp\u003eFigure \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003ea shows the crystal structure of each material in the catalyst at different carbonation temperatures, and the characteristic peak of graphite carbon (002) at around 24.7\u0026deg; can be clearly observed from the figure. In addition, no obvious characteristic peak of any crystal type of Co was observed in the XPS spectrum, and no characteristic peak of Co was found in the XPS spectrum of the catalyst with the highest Co content (\u003cstrong\u003eFig. S3\u003c/strong\u003e), which maybe caused by the low Co content in the catalyst, and the highest Co content known by ICP was only 0.96%. From Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eb, it is clear to observe the ID/IG values of each catalyst at different pyrolysis temperatures, and then judge the degree of defects. Peak D and peak G are Raman characteristic peaks of a C atomic crystal, occurring at approximately 1300 cm-1 and 1580 cm-1, respectively. Peak D represents the defects of the lattice of C atoms, while peak G represents the in-plane expansion vibration of sp2 hybridization of C atoms. When the pyrolysis temperature is 800 oC, the ID/IG value is lower, which may be due to the degree of graphitization at this temperature is higher and the defect degree is reduced.\u003c/p\u003e\n \u003cp\u003eThe distribution of nitrogen adsorption-desorption isotherms and pore size of catalyst Co@NC-800 and NC-800 can be intuitively observed from Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e. The nitrogen adsorption-desorption isotherm of the catalyst exhibited a typical Type IV behavior, accompanied by the appearance of a hysteresis loop. Obviously, it can be seen from Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eb that the pore diameter of catalyst Co@NC-800 is mainly distributed in the range of 2\u0026ndash;5 nm, and there are some mesoporous pores with the size of 30\u0026ndash;35 nm. Compared with catalyst NC-800, this shows that the abundant pore diameter of catalyst Co@NC-800 is conducive to promoting the substrate diffusion and thus improving the catalytic performance of catalyst. Furthermore, the specific surface area of catalyst Co@NC-800 was 268.19 m2/g, and the large specific surface area also played a positive role in the catalytic reaction (\u003cstrong\u003eTable S3\u003c/strong\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003e3.2. Conditional screening of transfer hydrogenation of quinolone over Co@NC-800\u003c/h2\u003e\n \u003cp\u003eBy means of a series of characterization methods, the physical and chemical properties of catalyst Co@NC-800 have been further studied, and the catalytic performance of catalyst has been investigated by transfer hydrogenation of quinoline compounds. Using quinoline as substrate, toluene as solvent and green formic acid as hydrogen source, the conditions of transfer hydrogenation reaction was investigated under relatively mild conditions. As can be observed from Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e, the conversion of quinoline transfer hydrogenation presents a volcanic trend with the increase of pyrolysis temperature (Co@NC-800\u0026thinsp;\u0026gt;\u0026thinsp;Co@NC-900\u0026thinsp;\u0026gt;\u0026thinsp;Co@NC-700). This may be caused by the amount of the Co content. When the pyrolysis temperature is 900\u0026deg;C, the catalytic effect of the catalyst is finally observed. At this temperature, the Co content of the catalyst prepared is up to 0.96 wt % (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e, \u003cstrong\u003eentries 1\u0026ndash;3\u003c/strong\u003e and \u003cstrong\u003eTable S2\u003c/strong\u003e). In addition, the presence of a certain amount of N enables Co to disperse in the N-doped carbon material more uniformly, thus promoting the catalytic activity of the catalyst (\u003cstrong\u003etable \u003cspan class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/strong\u003e) [\u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e]. In order to gain further insight into the impact of Co content on the catalytic performance of the catalyst, a series of samples with Co concentrations of 0.45, 0.56 and 0.96 wt % were prepared for the transfer hydrogenation of quinoline, with all other conditions held constant (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e, \u003cstrong\u003eentries 2, 4\u0026ndash;5\u003c/strong\u003e and \u003cstrong\u003e13\u003c/strong\u003e). It can be observed that with the increase of Co content, the catalytic effect of the catalyst became outstanding with the optimal conversion rate reaching 100% and selectivity as high as 99% (\u003cstrong\u003eTable S2\u003c/strong\u003e). When the catalyst prepared without any cobalt source was used to catalyze the hydrogenation reaction of quinoline, there was almost no product generation. The subsequent phase of the study was to investigate the impact of the solvent on the catalytic performance of the catalyst. Methanol, ethanol, toluene and water were selected as solvents for the reaction, and the sequence of activity was: toluene\u0026thinsp;\u0026gt;\u0026thinsp;water\u0026thinsp;\u0026gt;\u0026thinsp;ethanol\u0026thinsp;\u0026gt;\u0026thinsp;methanol, in which, when methanol was selected as the solvent, almost no products were generated. However, when toluene was used as the solvent, the conversion and selectivity were optimal (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e, \u003cstrong\u003eentries 2, 6\u0026ndash;8\u003c/strong\u003e). What\u0026apos;s more, a reduction in the amount of catalyst resulted in a corresponding decline in the catalytic performance of the catalyst. In particular, the transfer hydrogenation of quinoline is basically impossible without the addition of catalyst (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e, \u003cstrong\u003eentries 2, 9\u0026ndash;11\u003c/strong\u003e). It was observed that the catalyst was unable to catalyse the reaction in the absence of an added hydrogen source. When 0.2 mmol KSCN was added, which is more readily poisonous to the metal, the catalytic performance of the catalyst was significantly diminished. This finding provides additional evidence that the active site is Co on the catalyst in the catalytic hydrogenation of quinoline transfer (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e, \u003cstrong\u003eentries 13\u0026ndash;14\u003c/strong\u003e).Furthermore, the TOF values under different reaction conditions indicated that Co@NC-800 was the most excellent catalyst.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e Optimization of transfer hydrogenation conditions of quinolone over Co-catalyst.a\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u003cimg 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\"\u003e\u003c/div\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003ctable id=\"Taba\" border=\"1\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eEntry\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCatalyst\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMass (mg)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSolvent\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTime (h)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eConv. b (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSel. b (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTOFg (h-1)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCo@NC-700\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003etoluene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCo@NC-800\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003etoluene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCo@NC-900\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003etoluene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCo@NC-800\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003etoluene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCo@NC-800\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003etoluene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.92\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCo@NC-800\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emethanol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003etrace\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCo@NC-800\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eethanol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCo@NC-800\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ewater\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCo@NC-800\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003etoluene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.38\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCo@NC-800\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003etoluene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCo@NC-800\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003etoluene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003etrace\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12 e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCo@NC-800\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003etoluene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003etrace\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNC-800\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003etoluene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003etrace\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14f\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCo@NC-800\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003etoluene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003etrace\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003ea Reaction conditions: quinoline (0.25 mmol), catalyst (0.96 wt % Co), 130 oC, 12h, toluene (3ml), 20 eq.\u0026nbsp;HCOOH; b Determined by GC-MS; c 0.45 wt % Co; d 0.59% wt % Co; e 0 eq.\u0026nbsp;HCOOH; f adding 0.2 mmol KSCN; g TOF = [moles of converted substrate] \u0026times; [(moles of Co) \u0026times; (reaction time in h)]-1.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003e3.3. Catalytic transfer hydrogenation of quinoline to generate the corresponding N- for my ltetrahydroquinoline over Co@NC-800\u003c/h2\u003e\n \u003cp\u003eTo further investigate the universality of catalyst Co@NC-800, transfer hydrogenation of various substrates was carried out under optimal reaction conditions (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). As can be observed from Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e, \u003cstrong\u003eentries 1\u0026ndash;2\u003c/strong\u003e, both quinoline and isoquinoline demonstrated excellent conversion and selectivity following a 12-hour reaction period. The transfer hydrogenation of 2-methyl-quinoline, 8-methyl-quinoline, and 6-methoxyquinoline with electron-absorbent groups can be achieved after a prolonged reaction time. The conversion of 8-methyl-quinoline is higher than that of 2-methyl-quinoline, which may be attributed to steric hindrance (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e, \u003cstrong\u003eentries 3\u0026ndash;5\u003c/strong\u003e). It is noteworthy that the reaction of 3-bromine quinoline and 4-bromine isoquinoline with an electronic group results in the formation of N-formyltetrahydroquinoline, which exhibits the phenomenon of debromination. Additionally, a notable amount of 1,2,3,4-tetrahydroquinoline is generated throughout the course of the reaction (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e, \u003cstrong\u003eentries 6\u0026ndash;7\u003c/strong\u003e). The conversion and selectivity of 6-nitroquinoline are up to 99%, which reflected the excellent catalytic activity of the catalyst (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e, \u003cstrong\u003eentries 8\u003c/strong\u003e). Reaction substrates with complex functional groups such as 8-hydroxyquinoline, 8-borate and 2-formaldehydel-8-hydroxyquinoline all show good conversion, which demonstrate the resistance and stability of catalyst Co@NC-800 to functional groups (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e, \u003cstrong\u003eentries 9\u0026ndash;11\u003c/strong\u003e).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e Co@NC-800 catalyst catalytic transfer hydrogenation of quinoline to generate the corresponding N-formyltetrahydroquinoline.\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cimg 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\"\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003e3.4. Cyclic test of quinoline transfer hydrogenation over catalyst Co@NC-800\u003c/h2\u003e\n \u003cp\u003eThe reusability of catalysts is a significant criterion for assessing their performance. Accordingly, the catalyst Co@NC-800 was employed for the transfer hydrogenation of quinoline. The recovered catalyst was subjected to repeated washing with distilled water and ethanol, followed by vacuum drying prior to the subsequent reaction.It can be observed from Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e that six consecutive cyclic reactions have been conducted, and the detection of GC-MS indicates that the catalyst Co@NC- 800 still has high activity and selectivity, which reflects the chemical stability of the catalyst. Compared with the freshly prepared catalyst, the recovered catalyst Co@NC-800 did not change significantly in the TEM. The recovered catalyst was also characterized by XRD, and there was basically no significant change, which further proved the excellent stability of the catalyst (\u003cstrong\u003eFig. S4\u003c/strong\u003e).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"4. Conclusions","content":"\u003cp\u003eSupported catalyst Co@NSC was prepared by highly dispersing transition metal cobalt on nitrogen-doped porous carbon material. Quinoline can be directly reduced and catalyzed to produce quinoline aldehyde by using toluene as solvent in a high pressure tube at 110 oC. Concurrently, a variety of quinolines can be efficiently transformed into the corresponding quinolinaldehyde with a high yield and excellent selectivity. The findings demonstrate that the catalytic activity of nitrogen-doped porous carbon materials can be significantly enhanced through the incorporation of cobalt. It is worthy of mention that the presence of nitrogen-containing compounds is not only conducive to stabilizing and dispersing metal nanoparticles, but also causes certain defect sites to promote the catalytic activity of the catalyst. The abundant pore size of the catalyst Co@NC- 800 is conducive to promoting substrate diffusion and improving the catalytic performance of the catalyst. Adding cobalt to nitrogen-doped porous carbon can reduce the use of cobalt, thereby reducing environmental pollution and avoiding resource waste. The catalyst was used for the transfer hydrogenation of quinoline, and the recovered catalyst could be washed with distilled water and ethanol for reuse, and the catalytic activity remained high through six cycles of experiments. This shows that the catalyst is not only easy to recover, but also further proves the excellent stability of the catalyst. In summary, the reasonable design of the catalyst Co@NSC in this study provides a way for the future research and development of other supported heterogeneous catalysts.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics and Consent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDisclosure of potential conflicts of interest\u003c/p\u003e\n\u003cp\u003eResearch involving Human Participants and/or Animals\u003c/p\u003e\n\u003cp\u003eInformed consent\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interest declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no competing interests to declare that are relevant to the content of this article\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLan Wu: Funding acquisition, Writing-original draft, Conceptualization, Data curation, Formal analysis; Yongchao Liu: Investigation, Formal analysis, Data curation, Writing-original draft; Ze Wang: Formal analysis, Visualization.; Xinyu Ye: Data Curation, Project administration, Supervision.; Yaozong Liu: Validation, Writing \u0026ndash;review \u0026amp; editing, Supervision, Data curation; Zhenhua Li: Funding acquisition, Project administration, Supervision, Writing-review \u0026amp; editing; Zhengping Dong: Conceptualization, Supervision, Resources.All authors reviewed the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of competing interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing financial interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll relevant data are within the paper\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work is supported by the National Natural Science Foundation of China (No. 31760608), the Key Program of Natural Science Foundation of Gansu Province (No. 22JR5RA178), the Fundamental Research Funds for the Central Universities (No. 31920230168) . the Key Program of Natural Science Foundation of Gansu Province (No. 22JR5RA178 and 23ZDGD001), the Fundamental Research Funds for the Central Universities (No. 31920230168) and the Natural Science Foundation of Gansu Province (No. 23JRRA716). the Lanzhou Chengguan District Science and Technology Plan Project (No. 2022JSCX0009), the Gansu Province University Teacher Innovation Fund Project (No. 2023B-049)\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWang X, Chen W, Zhang L, Yao T, Liu W, Lin Y, Ju H, Dong J, Zheng L, Yan W, Zheng X, Li Z, Wang X, Yang J, He D, Wang Y, Deng Z, Wu Y, Li Y (2017) Uncoordinated Amine Groups ofMetal-Organic Frameworks to Anchor Single Ru Sites as Chemoselective Catalysts toward the Hydrogenation of Quinoline. 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J Am Chem Soc 141:10590\u0026ndash;10594. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1021/jacs.9b03182\u003c/span\u003e\u003cspan address=\"10.1021/jacs.9b03182\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Scheme 1","content":"\u003cp\u003eScheme 1 is 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":"catalysis-letters","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Catalysis Letters](https://link.springer.com/journal/10562)","snPcode":"10562","submissionUrl":"https://submission.springernature.com/new-submission/10562/3","title":"Catalysis Letters","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Supported nano-catalyst, Reduction reaction, Transition metal, Porous carbon material","lastPublishedDoi":"10.21203/rs.3.rs-5391338/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5391338/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSupported nanocatalysts with environmental sustainability and high catalytic performance have attracted much attention. Research interest in sustainable catalysis. A supported nanocatalyst Co@NSC has been studied in this paper. Porous materials with catalytic properties were prepared by anchoring transition metal cobalt onto porous materials doped with nitrogen. Carbon material with chitosan as raw material. The results of the scanning electron microscopy (SEM), X-ray diffraction (XRD) and Fourier transform infrared spectroscopy (FT-IR) tests demonstrate that the catalyst obtained exhibits an excellent mesoporous structure and a uniform distribution of cobalt elements. The scaffold is rich in N atoms, which can provide enough anchor points for cobalt to form cobalt-NX. Cobalt groups can improve the catalytic activity of the catalyst. In addition, Co@NSC is porous, the structure has the potential to facilitate the mass transfer of the reactants, thereby enhancing the overall efficiency of the reaction. Furthermore, the prepared catalyst was employed in the conversion of quinoline into the corresponding quinoline aldehyde. The results show that quinoline can be directly reduced to produce the corresponding quinoline aldehyde. Subsequently, the selectivity and stability of the prepared catalyst were validated.\u003c/p\u003e","manuscriptTitle":"Preparation of mesoporous chitosan cobalt supported nano-catalyst for the catalyzed reduction of quinoline to quinoline aldehyde","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-29 05:26:29","doi":"10.21203/rs.3.rs-5391338/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-12-08T10:50:09+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-11-27T02:35:45+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-11-22T07:35:29+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"76304480753247075979141823946405819941","date":"2024-11-18T01:46:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"164229977396487655404915455708516946046","date":"2024-11-17T06:19:00+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-11-16T16:20:12+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-11-12T00:09:54+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-11-12T00:09:40+00:00","index":"","fulltext":""},{"type":"submitted","content":"Catalysis Letters","date":"2024-11-05T01:46:21+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"catalysis-letters","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Catalysis Letters](https://link.springer.com/journal/10562)","snPcode":"10562","submissionUrl":"https://submission.springernature.com/new-submission/10562/3","title":"Catalysis Letters","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"8de52066-f487-40b0-bb80-4e730e89a0aa","owner":[],"postedDate":"November 29th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-01-15T10:08:13+00:00","versionOfRecord":[],"versionCreatedAt":"2024-11-29 05:26:29","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5391338","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5391338","identity":"rs-5391338","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}