Effect of different structure of Cu/Mn catalysts on ozone decomposition ability

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Abstract

A simple co-precipitation method was utilized to synthesize Cu/Mn catalysts with different physiochemical properties for high humidity ozone decomposition. The catalysts were then tested for their activity and stability in decomposing ozone, and their physical and chemical properties were analyzed through various characterization techniques. Furthermore, the characterization after stability testing provided insights into the internal mechanism of the ozone reaction process. The Cu/Mn-NN catalyst demonstrated excellent ozone decomposition activity in the temperature of 25–100°C, maintaining the conversion above 91% for continuous ozone decomposition for 12 hours at room temperature, the relative humidity (RH) of 85%, and the weight space velocity of 300 L·g − 1 ·h − 1 . Characterization revealed that the Cu/Mn-NN catalyst, exhibited the larger specific surface area, better reducibility and oxygen storage capacity, richer surface functional groups and oxygen vacancies. Additionally, characterization after the stability test confirmed the accumulation of oxygen intermediate species on the catalyst surface. The findings also suggested that the catalytic environment created by nitrate precursors played a vital role in preventing catalyst particle aggregation, facilitating electron transfer within the catalyst, ensuring uninterrupted migration of lattice oxygen, and timely regeneration of oxygen vacancies.
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The catalysts were then tested for their activity and stability in decomposing ozone, and their physical and chemical properties were analyzed through various characterization techniques. Furthermore, the characterization after stability testing provided insights into the internal mechanism of the ozone reaction process. The Cu/Mn-NN catalyst demonstrated excellent ozone decomposition activity in the temperature of 25–100°C, maintaining the conversion above 91% for continuous ozone decomposition for 12 hours at room temperature, the relative humidity (RH) of 85%, and the weight space velocity of 300 L·g − 1 ·h − 1 . Characterization revealed that the Cu/Mn-NN catalyst, exhibited the larger specific surface area, better reducibility and oxygen storage capacity, richer surface functional groups and oxygen vacancies. Additionally, characterization after the stability test confirmed the accumulation of oxygen intermediate species on the catalyst surface. The findings also suggested that the catalytic environment created by nitrate precursors played a vital role in preventing catalyst particle aggregation, facilitating electron transfer within the catalyst, ensuring uninterrupted migration of lattice oxygen, and timely regeneration of oxygen vacancies. Cu/Mn catalyst precursor ozone decomposition post-reaction characterization Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Introduction Over the past few years, the levels of ozone pollution in the lower atmosphere have escalated, particularly in many urban and industrialized regions over the world [ 1 ], which is primarily due to the excessive emission of gaseous ozone precursors and the release of ozone during industrial production and daily life. Between June and August of 2016, ozone emerged as the primary pollutant in in many cities, surpassing particulate matter PM10 and PM2.5. Over the last 5 years, the annual average ground ozone mixing ratio in China has been the only air pollutant taken the high growth trend, according to a government report in 2021 [ 2 ]. Ozone, as a secondary pollutant, now is known to pose a significant threat to human health and crop growth due to its potent oxidation abilities. Even at low concentrations, prolonged exposure to ozone can cause severe damage to cardiopulmonary function, while high concentrations of ozone can lead to various respiratory and cardiovascular diseases, ultimately resulting in increased mortality rates [ 3 – 6 ]. Apart from its direct impact on human health and crop growth, ozone can also interact with volatile organic compounds, leading to the production of even more toxic oxidation products. Additionally, ozone has the potential to corrode materials such as rubber and buildings, which means that even at concentrations below regulated levels, it can still be harmful [ 7 – 9 ]. Therefore, it is imperative to research effective methods of decomposing ozone for the preservation of the environment and the betterment of human health. Currently, there are several widely used methods for decomposing ozone, including adsorption, thermal decomposition, solution absorption, and catalytic decomposition [ 3 , 10 – 12 ]. Activated carbon is primarily utilized for its potent adsorption capacity to eliminate low-concentration ozone, however, the substantial amount of heat produced during the ozone adsorption has the potential to trigger fires and explosions. Thermal decomposition is effective for treating high-concentration ozone, but it demands a significant amount of energy to eliminate ozone waste gas, resulting in high costs and limited economic advantages. Therefore, it is not ideal for indoor and outdoor ozone removal but rather for treating high-concentration industrial waste gas. Although the solution absorption method effectively purifies low-concentration ozone, it relies on costly sodium thiosulfate or sodium sulfite, resulting in the production of significant volumes of waste liquids that are challenging to manage, posing the risk of secondary pollution. The catalytic decomposition method is widely considered the most ideal approach for ozone removal due to its ability to catalyze decomposition at room temperature, stability, environmental friendliness, safety, and economic benefits [ 13 – 15 ]. However, due to the frequent need to effectively decompose ozone at low temperature and high humidity, it is important to develop catalysts with superior activity adapted to the environment. Ozone decomposition catalysts can be categorized into two groups based on their active components: noble metal catalysts and transition metal oxide catalysts. Precious metal catalysts, including gold (Au) [ 16 – 18 ], silver (Ag) [ 19 ], palladium (Pd) [ 20 ], platinum (Pt) [ 21 ], and rhodium (Rh) [ 21 ], exhibit exceptional ozone decomposition activity and remarkable water resistance. In comparison to precious metal catalysts, transition metal oxides are more fitting for large-scale ozone catalytic decomposition due to the low cost, abundant availability, exceptional redox activity, and variable valence state, making them highly promising for catalytic applications. The transition metal oxides group encompasses metals such as manganese (Mn) [ 22 – 24 ], cobalt (Co) [ 25 ], copper (Cu) [ 26 – 28 ], nickel (Ni) [ 29 ], and iron (Fe) [ 30 ]. For instance, Dhandapani and Oyama [ 31 ] deposited various metal oxides onto a 20% γ-Al 2 O 3 loaded cordierite foam supporter by multiple impregnations, and demonstrated that MnO 2 was superior to other metal oxide for ozone decomposition. Manganese oxide then has emerged as a major focus of catalytic research due to its stable valence, ease of preparation, versatile structure, and extensive applications in the field of catalysis. Cryptomelane-type manganese oxide (OMS-2) is a form of manganese dioxide characterized by a one-dimensional tunnel structure made up of 2×2 edge-shared MnO 6 octahedral chains connected by corners to form a 4.6×4.6 Å tunnel. Wang et al. [ 32 ] conducted a hydrothermal synthesis of OMS-2 catalysts using various Mn 2+ precursors for ozone decomposition, and revealed the ozone decomposition performance of OMS-2-Ac synthesized with acetate as the precursor was found to be superior to that of nitrate and chloride under 90% RH and GHSV = 600000 h − 1 . According to the study, utilizing acetate as the precursor for Mn 2+ resulted in improved dispersion of manganese oxides in the OMS-2-Ac catalyst due to the formation of smaller particles, leading to a lower Mn-Mn coordination number and more defects for ozone molecular adsorption. In other words, the surface structure and oxygen vacancy that affected the catalytic performance of ozone decomposition, is firmly dependent on synthesis parameters of the manganese oxide catalyst, highlighting the need for further investigation into the effects of oxygen intermediate accumulation during the catalytic process on catalyst properties. Manganese oxide catalysts are prone to deactivation under dry and wet conditions due to the existence of competitive adsorption and the occupation of oxygen vacancy by oxygen intermediates during the ozone decomposition reaction. To increase the active sites content and enhance the stability of these catalysts, they are often modified by doping with other metals such as Fe, Ag, Cu, or Ni [ 3 , 31 ]. By investigating the subtle structural control of Mn-based catalysts, the structure-activity relationship between the catalytic activity of ozone and the microstructure can be better constructed, so as to directionally synthesize efficient catalysts with low cost and excellent water resistance. In this study, a simple co-precipitation method was utilized to synthesize Cu/Mn catalysts with different Cu 2+ and Mn 2+ precursors, and the corresponding activities and stabilities of ozone decomposition were systematically assessed over these Cu/Mn-based catalysts. Then, the structures of fresh and spent catalysts underwent characterization using XRD, SEM, BET, FI-IR, O 2 -TPD, H 2 -TPR, TG and XPS as far as possible, and the deactivation reason and reaction mechanism for ozone decomposition were discussed through the changes observed in the catalysts before and after the reaction. Experimental Catalyst preparation Cu(NO 3 ) 2 ·3H 2 O, Mn(NO 3 ) 2 , Mn(CH 3 COO) 2 ·4H 2 O, Cu(CH 3 COO) 2 ·H 2 O, KOH, and KMnO 4 were obtained from Shanghai McLean Biochemical Technology Co., Ltd, China. All other reagents were of analytical grade and used without any additional purification steps. The catalysts were synthesized by a straightforward co-precipitation method. Typically, equal molar amounts of Cu(NO 3 ) 2 ·3H 2 O and 50% Mn(NO 3 ) 2 (with a Mn : Cu molar ratio of 2.5) were dissolved in deionized water, stirred to form a homogeneous solution, and then dissolved KOH and KMnO 4 in deionized water. The precipitant was slowly added to the metal salt solution, and the quantity of precipitant was twice the total molar amount of metal ions. After slow titration at 400 rpm and aging at 200 rpm for 2 hours at 30°C, the resulting green solution was washed thrice with deionized water until it was neutral, and then dried overnight at 80°C. The obtained catalyst was labeled as Cu/Mn-NN after annealing in a muffle furnace at 450°C for 2 hours. Cu/Mn-CN was labeled using Cu(CH 3 COO) 2 ·H 2 O and Mn(CH 3 COO) 2 ·4H 2 O as Cu 2+ and Mn 2+ precursors, respectively. The same nomenclature was used for Cu/Mn-NC and Cu/Mn-CN catalysts. Catalyst Characterization The catalysts obtained were analyzed using a German Bruker D8 ADVANCE X-ray powder diffractometer (XRD) at 25°C. The excitation light source used was CuKα X-ray, with a wavelength of 0.1542 nm. The scanning range was 5°-70°, with a scanning rate of 8.0 o /min and a step size of 0.02 o . The Autosorb iQ multi-function automatic specific surface area and porosity analyzer was employed for characterization. Prior to the test, the sample underwent vacuum degassing at 423 K for 2 hours, and then a nitrogen adsorption-desorption test was carried out at 77 K. The total pore volume was determined from the adsorption capacity of the adsorption isotherm at a relative pressure of 0.95. The specific surface area of the sample was calculated using the BET method, and the pore diameter and pore volume were calculated using the BJH method. The surface morphology of the catalysts was analyzed using a TESCAN VEGA3 scanning electron microscope (TESCAN, Czechoslovakia) with an accelerating voltage of 5 KV. Prior to testing, the samples were dried at 120°C, and a small amount of powder was affixed to the conductive adhesive for testing. The thermal stability of the catalyst was measured by a thermogravimetric instrument (Shimadzu, Japan, TG-50), which was heated from 30°C to 800°C at a rate of 10°C per minute in an argon atmosphere. A 10 mg catalyst sample was weighed, and the flow rate of argon gas was set to 50 mL/min. The H 2 -TPR test was conducted using the ChemBET Pulsar chemisorption instrument from the United States. The sample (50 mg) was weighed and purged with He gas at 150°C for 30 minutes. After cooling to room temperature, the gas circuit was switched to 10 vol% H 2 /Ar mixture. The temperature was then increased to 700°C at 10°C/min, and the H 2 -TPR curves were collected after baseline stabilization. Additionally, the instrument was also used for the O 2 -TPD test. For this, the sample (50 mg) was heated to 110°C in the helium environment, and purged for 60 minutes to remove surface H 2 O. After natural cooling to room temperature, a 5 vol% O 2 /He mixture was introduced for 1 hour to reach saturation, followed by purging with He gas for 30 minutes to remove physically adsorbed O 2 from the sample's surface. After baseline stabilization, the gas path was switched to the 5 vol% O 2 /He mixture and the temperature was raised to 700°C at 10°C/min to collect the O 2 -TPD curve. The surface functional groups of the catalyst were examined using an FT-IR infrared spectrometer (Thermo, IS50-FTIR) with a wavelength scanning range of 4000 − 500 cm − 1 and a resolution of 4 cm − 1 . The instrument was calibrated by scanning the background spectrogram 32 times and the sample spectrogram 4 times to ensure high-quality results. Prior to the analysis, the raw and reaction gases were passed through a cold trap to remove H 2 O, and the infrared spectra of the samples were recorded in the air background. The element content and valence state on the catalyst surface were analyzed using an X-ray spectrometer (Thermo, SCIENTIFIC) under ultra-high vacuum conditions with AIKα radiation as the X-ray source. The combined energy spectrum of the elements was obtained, and the carbon spectrum (BE = 284.8 eV) was used for calibration. Catalyst Activity Measurement The fixed bed continuous flow adaptive reactor (i. d. =14 mm) was used to measure the ozone decomposition activity and stability of the prepared catalysts at a total air flow of 1300 mL/min. The activity tests were performed at various temperature points, using 0.13 g of sample with a size of 40–60 mesh, under the conditions of the relative humidity of 85% and the weight space velocity of 600 L·g − 1 ·h − 1 . The relative humidity of feed gas was regulated using the air through the thermostatic bubbler and assessed by the humidity equipment (SSN23E, YOWEXA, China). Stability tests were performed in the same fixed reactor, at temperature of 25°C, 85%RH, 0.26 g catalyst mass, and weight space velocity of 300 L·g − 1 ·h − 1 . Ozone was generated by electrolyzing oxygen from an ozone generator (OSAN, China), and the ideal inlet ozone concentration was 80 ppm. An ozone analyzer (model 106-L, US 2B Technology) was used to measure ozone concentrations at both inlet and outlet. The ozone conversion formula of the catalyst was: $${\eta }=\frac{{\left[{\text{O}}_{3}\right]}_{\text{i}\text{n}\text{l}\text{e}\text{t}}-{\left[{\text{O}}_{3}\right]}_{\text{o}\text{u}\text{t}\text{p}\text{u}\text{t}}}{{\left[{\text{O}}_{3}\right]}_{\text{i}\text{n}\text{l}\text{e}\text{t}}}\times 100\text{\%} \left(1\right)$$ Where \({\left[{\text{O}}_{3}\right]}_{\text{i}\text{n}\text{l}\text{e}\text{t}}\) and \({\left[{\text{O}}_{3}\right]}_{\text{o}\text{u}\text{t}\text{p}\text{u}\text{t}}\) represent the ozone concentration at the inlet and outlet of the detector, respectively. Results And Discussion Catalytic activity of ozone decomposition The ozone conversion activities of Cu/Mn catalysts were investigated over the temperature of 25–100°C, RH = 85%, and weight space velocity of 600 L·g − 1 ·h − 1 , as depicted in Fig. 1 . Cu/Mn-NN and Cu/Mn-NC catalysts showed a significant increase in ozone conversion before 45°C, which then stabilized, while Cu/Mn-CN and Cu/Mn-CC catalysts displayed similar ozone decomposition curves. As per the Arrhenius formula, the increase in temperature enhances the molecular thermal movement inside the catalyst, leading to accelerated ozone decomposition. The as-prepared catalysts exhibited different ozone decomposition activities, owing to their unique structure, physicochemical properties, and water resistance under high humidity conditions [ 33 , 34 ]. The peak ozone conversion followed the order: Cu/Mn-NN (89.5%) > Cu/Mn-CN (76.1%) > Cu/Mn-CC (75.1%) > Cu/Mn-NC (68.3%). The Cu/Mn-NN catalyst showed the highest catalytic activity, which may be caused by the micro regulation of structural characteristics and optimization of physical and chemical properties by nitrate precursors, making it more suitable for ozone decomposition. The stability of catalysts was tested under conditions of the temperature at 25°C, RH = 85%, and the weight space velocity of 300 L·g − 1 ·h − 1 . The ozone conversion for the different catalysts declined to varying degrees during the 12 hours reaction period, as seen in Fig. 2 . Notably, the Cu/Mn-NN catalyst displayed impressive stability, maintaining over 91% ozone conversion throughout the entire 12 hours ozone decomposition process. In contrast, the ozone conversion of the other catalysts all experienced significant declines within the first 4 hours. After the stability test, the ozone conversion for the Cu/Mn-CN and Cu/Mn-CC catalysts remained at 78% and 69%, respectively, whereas the Cu/Mn-NC catalyst dropped to 48%, indicating poor stability. It could be seen that the catalytic environment constructed and regulated by nitric acid groups of manganese nitrate under high humidity could more effectively remove ozone. Therefore, it is necessary to further investigate the effect of different precursors on the structural properties of catalysts. Crystal structure, morphology and specific surfaces Figure 3 a displayed the XRD patterns of the fresh catalysts, and their diffraction peaks could be attributed to the tetragonal Mn 3 O 4 phase (JCPDS card no. 24–0734) and the CuMn 2 O 4 phase (JCPDS card no. 74-2422). The diffraction peaks were observed at 2θ = 18.2°, 29.0°, 31.1°, 32.5°, 36.2°, 38.2°, 44.6° 58.5° and 64.7°, corresponding to the crystal planes (101), (112), (200), (103), (211), (004), (220), (321) and (400) of Mn 3 O 4 phase, respectively. The overlapping parts correspond to the crystal planes (111), (220), (311) and (511) of CuMn 2 O 4 phase. Notably, no diffraction peaks of other crystal by-products were detected, indicating that the catalyst possessed high purity and crystallinity throughout the preparation process. The figure illustrated that the catalysts synthesized by different precursors had the same crystal type, but there were differences in crystallinity. The Cu/Mn-CC catalyst had the best crystallinity, but comparatively, Cu/Mn-NN catalyst had poor crystallinity, which would cause more defects in the catalyst and may increase the specific surface area, so it was beneficial to the ozone decomposition [ 35 ]. The stability test demonstrated that the activity of all catalysts declined to varying degrees with the reaction time increased, because of the deactivation of active sites during the catalyst decomposition process. Therefore, investigating the deactivation mechanism of catalysts during the reaction process is critical for developing more efficient and stable catalysts. Initially, the crystal structure of the catalysts was investigated before and after the reaction via XRD analysis. Figure 3 b displayed the XRD pattern diffraction peak of the spent catalyst, which could also be attributed to tetragonal Mn 3 O 4 phase (JCPDS card no. 24–0734) and the CuMn 2 O 4 phase (JCPDS card no. 74-2422). After the reaction, except Cu/M-NN catalyst, the diffraction intensity of the characteristic peak in the catalyst increased compared to before the reaction. Furthermore, some characteristic diffraction peaks of crystal planes emerged, implying that the crystallinity of the catalyst was reinforced during the ozone decomposition process, making the crystal plane easier to detect. This could be attributed to the oxidation-reduction reaction taking place during the catalytic reaction process, leading to the aggregation of catalyst grains, which ultimately hampered the efficiency of the catalytic reaction. The Cu/Mn-NN catalyst exhibited lower diffraction peak intensity, indicating the higher dispersion of crystalline grains than other catalysts. This may be because the concentration of nitric acid groups in the solution was higher than that of other solutions during the synthesis process, and the nitric acid group may form a bond with the hydroxyl groups on the catalyst surface, thus allowing better separation of catalyst particles [ 32 ]. This feature could prevent the further aggregation of catalyst particles and explain the superior ozonolysis performance of the catalyst. As is widely acknowledged, the specific surface area of catalysts is a crucial factor affecting catalytic activity. The N 2 adsorption-desorption at 77 K was used to analyze the specific surface area and pore structure of Cu/Mn catalysts, as depicted in Fig. 4 and Table 1 . Figure 4 a illustrated that the adsorption isotherms of the synthesized catalysts were V-shaped with a typical H3 hysteresis loop, indicating that nitrogen underwent capillary condensation within the mesoporous gap formed by the oxide nanoparticle aggregation [ 35 , 36 ]. The hysteresis loops of catalysts were all observed to be in the range of 0.8 < P/P 0 < 1.0, indicating larger pore sizes of 25.85, 33.4, 26.62, and 29.09 nm, respectively, as exhibited in Fig. 4 b. It is widely accepted that a larger pore size facilitates contact between the active sites and more ozone molecules, thereby reducing mass transfer resistance and promoting the diffusion of reactants on the catalyst surface. The data presented in Table 1 revealed that Cu/Mn-NN catalyst exhibited the highest specific surface area of 59.1 m 2 ·g − 1 , which surpassed the specific surface areas of Cu/Mn-CN (42.8 m 2 ·g − 1 ), Cu/Mn-CC (49.8 m 2 ·g − 1 ) and Cu/Mn-NC (44.4 m 2 ·g − 1 ) catalysts. This larger specific surface area indicated that there were more active sites available for ozone molecule adsorption, ultimately leading to improved activity and stability for ozone decomposition. Table 1 Textural properties of Cu/Mn catalysts Catalysts S BET (m 2 ·g − 1 ) Pore Volume (mLg − 1 ) Average Pore Size (nm) Cu/Mn-NN 59.1 0.38 25.85 Cu/Mn-CN 42.8 0.36 33.4 Cu/Mn-NC 49.8 0.33 26.62 Cu/Mn-CC 44.4 0.32 29.09 The morphology of catalysts was investigated using scanning electron microscopy, as illustrated in Fig. 5 a-d. The images showed that catalysts showed a similar morphology with aggregated flocculating particles and an uneven surface, which could increase the surface area and generate abundant adsorption sites, thereby enhancing the ozone decomposition activity. No remarkable difference in the morphology was observed among the as-made catalysts, suggesting that the morphology was not a significant factor influencing the catalytic performance variations. Reducibility, oxygen species type and thermal stability. H 2 -TPR analysis was used to further investigate the reduction behavior of catalysts. Figure 6 a illustrated that all synthesized catalysts exhibited comparable reduction characteristics, with only a broad reduction region present below 500°C. Based on the XRD pattern, Mn 3 O 4 and CuMn 2 O 4 were the crystalline phase of the catalysts, implying that the reduction peak corresponded to the reduction of Mn 3 O 4 to MnO and the reduction of divalent Cu ions and trivalent Mn ions in CuMn 2 O 4 . Moreover, catalysts with lower initial reduction temperatures exhibited better reducibility, and the initial reduction temperatures for all catalysts were in the following order: Cu/Mn-CC > Cu/Mn-NC > Cu/Mn-CN > Cu/Mn-NN. Interestingly, the initial reduction temperature of Cu/Mn-NN catalyst shifted forward by 10–20°C to the low-temperature stage, and the catalyst showed relatively more H 2 consumption, which could promote the desorption of the oxygen intermediate on the occupied oxygen vacancy, indicating better reduction capacity compared to other catalysts. This stronger reducibility could facilitate the redox cycle and accelerate the regeneration of oxygen vacancies, ultimately resulting in improved ozone decomposition performance. The H 2 -TPR curve of the spent catalysts, as illustrated in Fig. 6 b, displayed a shift towards lower temperature in the initial reduction peak. This could be attributed to the adsorption and reaction of ozone molecules at the active sites, leading to the formation of oxygen intermediate O 2 * . This phenomenon facilitates the transfer of electrons from adsorbed oxygen anions to the surface of Cu/Mn catalysts, thereby enhancing the reduction ability of the catalyst. Therefore, all the catalysts showed a stronger electrophilicity, which increased the likelihood of the reduction reaction to occur. Moreover, the Cu/Mn-NC and Cu/Mn-CC catalysts displayed two smaller shoulder peaks at 217°C and 193°C, respectively. As is known, the reduction peak at the lower temperature range corresponds to the reduction of MnO 2 to Mn 2 O 3 and Mn 3 O 4 [ 37 ]. This implied that during the ozone decomposition process, some Mn 2+ or Mn 3+ was oxidized to Mn 4+ , but the Mn 4+ was not restored to the low valent manganese ion in a timely manner. The desorption of oxygen intermediates plays a crucial role in the oxidation and reduction cycle of ozone decomposition. The failure of Mn 4+ to reduce in a timely manner suggests that the long-term occupation of oxygen vacancies by oxygen intermediates has resulted in the deactivation of catalysts. This inactivation phenomenon hinders the catalytic cycles of ozone decomposition and ultimately leads to poor stability, as confirmed by the stability test results. Furthermore, the temperature shift of the main reduction peak was calculated, and the order of the shift was as follows: Cu/Mn-NN (28°C) < Cu/Mn-CN (33°C) < Cu/Mn-NC (43°C) < Cu/Mn-CC (49°C). It was evident that the Cu/Mn-NN catalyst showed the smallest temperature shift of the main reduction peak, suggesting Cu/Mn-NN catalyst under high humidity and high space velocity conditions possessed a robust structure and reduction stability. To identify the evolution of oxygen in the catalysts, O 2 -TPD analysis was conducted on the catalysts, as exhibited in Fig. 7 . The O 2 -TPD curve of the catalysts comprised of two segments: the desorption peak below 350°C, which corresponded to the release of chemically adsorbed oxygen molecules and active surface oxygen, such as peroxide O 2 -ads, and the desorption peak in the range of 350–650°C, which indicated the release of sub-surface lattice oxygen [ 38 , 39 ]. In general, oxygen with a lower desorption temperature is less strongly bound to the manganese atoms in the catalyst framework, resulting in higher oxygen mobility. Figure 7 a demonstrated that the desorption temperature sequence for the catalysts was Cu/Mn-NN < Cu/Mn-CN < Cu/Mn-NC < Cu/Mn-CC, indicating that the Cu/Mn-NN catalyst exhibited the highest oxygen mobility. The peak below 200°C corresponds to the desorption of physically adsorbed oxygen, and its peak area reflects the content of oxygen species [ 40 ]. The physical adsorption oxygen peak area of Cu/Mn-NN and Cu/Mn-CN catalysts was larger than that of Cu/Mn-NC and Cu/Mn-CC catalysts, suggesting that more active sites were available on the catalysts. Catalysts contained oxygen species mainly in the form of sub-surface lattice oxygen, and the inability to release lattice oxygen was a crucial factor in the reduced activity of manganese-based ozone catalysts. As for the temperature range of 350°C-650°C, the desorption peak area of Cu/Mn-NN and Cu/Mn-CN catalysts was larger, and the desorption temperature of sub-surface lattice oxygen was lower. This finding indicated that the catalysts had better oxygen storage and release capacity, which was significant in enhancing the ozone decomposition activity and stability. The O 2 -TPD curve of the spent catalysts was displayed in Fig. 7 b, and the curve distribution was like that of the fresh catalysts. Below 350°C, all catalysts exhibited desorption peaks for adsorption oxygen, with the Cu/Mn-NN catalyst having the largest desorption peak area. This indicated that the oxygen intermediates produced during ozone decomposition were adsorbed onto the active sites, and the content of oxygen vacancy was highest in the Cu/Mn-NN catalyst. Compared to the pre-reaction state, the sub-surface lattice oxygen desorption peak underwent significant changes between 350°C and 650°C. Specifically, the peak narrowed, and its area decreased, indicating that a significant amount of sub-surface lattice oxygen was consumed during the reaction to compensate for the oxygen vacancy. By comparing the diagrams before and after the reaction of the four catalysts, it was apparent that the reduction in catalyst activity was caused by the insufficient conversion between lattice oxygen and surface adsorbed oxygen. Additionally, the desorption curves before and after the reaction revealed that Cu/Mn-NN and Cu/Mn-CN catalysts possessed superior structural stability, which would facilitate maintaining outstanding stability during continuous reaction. The thermal stability of the prepared catalysts was assessed through thermogravimetric analysis, as depicted in Fig. 8 . Weight loss below 180°C corresponded to physically adsorbed water and surface adsorbed oxygen, whereas weight loss above 250°C indicated the evolution and phase change of catalyst lattice oxygen. The weight loss within these two ranges reflected the desorption of chemically adsorbed water and surface active oxygen [ 24 , 41 ]. As the temperature continued to rise, the thermogravimetric curves of the fresh catalysts displayed a similar trend. Figure 8 a illustrated that the order of maximum weight loss was Cu/Mn-CC (10.3%) < Cu/Mn-NN (11.2%) < Cu/Mn-CN (11.4%) < Cu/Mn-NC (12.1%). The thermogravimetric curve of the spent catalysts was presented in Fig. 8 b and the order of maximum weight loss was: Cu/Mn-CC (6.3%) < Cu/Mn-CN (6.7%) < Cu/Mn-NN (7.8%) < Cu/Mn-NC (11.2%). The thermal stability of the spent catalysts was improved compared to the original catalysts because the reaction consumed a portion of the lattice oxygen. Notably, the weight loss of Cu/Mn-NC catalyst corresponding to lattice oxygen evolution and phase transition above 250°C remained relatively unchanged before and after the reaction, indicating its excellent lattice oxygen stability. However, the low ozone decomposition stability of catalyst was due to the relatively challenging release of lattice oxygen. Surface chemical functional groups, components and oxygen vacancies The surface functional groups of fresh and spent catalysts were analyzed by FI-IR spectroscopy, as presented in Fig. 9 . Five types of surface functional groups were identified based on the literature and peak positions: (i) 500 ~ 800 cm − 1 related to the Cu/Mn-O vibration mode in the catalyst matrix, (ii) 800 ~ 1000 cm − 1 was derived from the stretching vibration of O-O bond of oxygen intermediate species, (iii) 1000 ~ 1450 cm − 1 was due to the combined stretching vibration of Cu/Mn metal ions and –OH groups in the catalyst, (iv) 1500 ~ 1640 cm − 1 was owing to the bending vibrational mode of interlayer water, (v) 3300 ~ 3800 cm − 1 was connected with the stretching vibration of hydroxyl [ 42 – 45 ]. The surface functional group analysis of the fresh catalysts was presented in Fig. 9 a. The Cu/Mn-NN catalyst exhibited the most robust O-O bond stretching vibration at 942 cm − 1 and showed higher stretching vibration intensity of Cu/Mn-OH compared to the other catalysts at 1068 and 1380 cm − 1 . Based on the O 2 -TPD and stability test results, it can be inferred that the surface of the Cu/Mn-NN catalyst had abundant active oxygen species that converted into -OH groups to link with metal ions, inhibiting the accumulation rate of oxygen intermediates, thereby enhancing the ozone decomposition activity under high humidity conditions. In general, the competitive adsorption of water molecules would cause decreased activity and even deactivation of the catalyst. The surface hydroxyl and water base of the as-made catalysts was detected at 1626 and 3412 cm − 1 , and Cu/Mn-NN catalyst had higher vibration intensity. Based on the stability test results, the Cu/Mn-NN catalyst exhibited better ozone decomposition performance, which suggested that the surface hydroxyl group and water group may have participated in the catalytic reaction of the intermediate, leading to the promotion of ozone decomposition on the catalyst surface. This would be demonstrated with the FI-IR spectrum of the catalyst after the reaction, as discussed below. Despite the significant variations in the surface functional group content of the fresh catalysts, the FI-IR spectra of the spent catalysts showed a consistent trend, as depicted in Fig. 9 b. Initially, the vibration intensity of the Cu/Mn-O bond of all catalysts weakened, with the Cu/Mn-NN catalyst exhibiting the most significant weakening. This observation implied that during the reaction process, oxygen species in the Cu/Mn-O bond escaped to replenish oxygen vacancies and sustain the ozone decomposition cycle reaction. Notably, the Cu/Mn-O bond in Cu/Mn-NN was the loosest, indicating that this catalyst exhibited highest oxygen mobility. The change of the vibration intensity of the O-O bond on the catalyst surface and the reduction of hydroxyl group and interlayer water were the second observable changes. These changes suggested that various oxygen intermediates were produced and adsorbed on the catalyst surface, with the hydroxyl and water groups participating in the catalytic reaction of the intermediates, leading to the weakening of the vibration intensity. Lastly, the variation in the vibration intensity of Cu/Mn-OH on the catalyst surface was associated with the occupancy of oxygen vacancies by water molecules during the reaction. It was worth noting that the FI-IR spectrum curve of Cu/Mn-NC catalyst showed little difference by reaction, illustrating that the number of active sites on catalyst surface was limited, resulting in the worst ozone decomposition activity and stability. On the other hand, Cu/Mn-NN catalyst exhibited the opposite behavior, and the changes in its spectrum indicated that the catalyst had a better ability to regenerate active sites during the reaction to maintain high ozone conversion. Figure 10 displayed the XPS spectrum results which were used to identify the surface composition, element valence, and surface oxygen vacancies of Cu/Mn catalysts. As exhibited in Fig. 10 a, Cu, Mn, C, and O elements existed on the catalyst surface. To elaborate, Fig. 10 b demonstrates that the Cu 2p spectrum of the catalysts obtained could be analyzed into two primary peak regions corresponding to the Cu 2p 3/2 state (928–938 eV) and Cu 2p 1/2 state (948–958 eV), with corresponding shake-up satellite peaks located at 940–946 eV (S1) and 960–965 eV (S2), respectively. The regions positioned at 930.0-930.5 eV and 951.0-951.5 eV among the two main peaks were attributed to Cu + species, while the regions centered at 935.0-940.0 eV and 953.5–954.0 eV were identified as Cu 2+ species [ 46 ]. The XPS spectrum was utilized to compute the relative content ratio of Cu + and Cu 2+ and presented in Table 2 . The main form of Cu in the prepared catalyst was Cu 2+ , and Cu/Mn-NC catalyst had the highest proportion of Cu 2+ at 82.8%, which corresponded to the worst catalytic activity. The appropriate proportion of Cu + /Cu 2+ facilitated electron transfer between the redox pairs formed with multivalent Mn ions, but an excessive Cu 2+ content weakened the electron transfer ability of the redox pairs in the catalyst. As a result, the active sites became difficult to recover and could even lead to deactivation, reducing the ozone decomposition performance. The XPS spectrum of the Mn 2p was presented in Fig. 10 c, which showed two main peak regions of Mn 2p 3/2 state and Mn 2p 1/2 state with binding energies of 641 eV and 654 eV, respectively [ 24 , 47 ]. The Mn 2p 3/2 spectrum was separated into three binding energy bands positioned at 640.0-641.5 eV, 642.0-642.5 eV, and 643.5–645.0 eV, which corresponded to Mn 2+ , Mn 3+ , and Mn 4+ , respectively [ 48 ]. Table 2 presented the relative content of Mn ions with different valence states calculated based on the XPS spectra. The results proved that the content of Mn 3+ was the highest in all catalysts, which was consistent with the XRD findings. Notably, Cu/Mn-NN catalyst, had the highest Mn 3+ content of 70.5%, which correlated with the best ozone decomposition activity. Therefore, it could be inferred that the formation of Mn 3+ species facilitated the improvement of the ozone decomposition performance. The catalytic role of the mixed valence of the Mn element is associated with the redox process of the catalyst, and the Mn 3+ /Mn 4+ ratio serves as an indicator for measuring the charge balance on the oxygen vacancy [ 49 ]. The molar ratio of Mn 3+ /Mn 4+ for all catalysts was as follows: Cu/Mn-NN (3.18) > Cu/Mn-CN (2.12) > Cu/Mn-CC (1.90) > Cu/Mn-NC (1.52). The Mn 3+ /Mn 4+ ratio for Cu/Mn-NN catalyst was more than twice that of Cu/Mn-NC catalyst, indicating that the catalytic environment created by the nitric acid groups could better maintain the charge balance caused by oxygen vacancies, thus improving the ozone decomposition activity and stability at room temperature. The O 1s XPS spectrum for all Cu/Mn catalysts was displayed in Fig. 10 d and the primary peak region was deconvoluted into three parts: lattice oxygen O α (530.0 eV), surface adsorbed oxygen O β (531.5 eV), and surface adsorbed water and hydroxyl species O γ (533.2 eV). The vacancies in metal oxides are considered as sites for oxygen molecule adsorption. Hence, the ratio of O β /O α can indicate the abundance of oxygen vacancies in the catalyst [ 50 ]. The O β /O α ratios for the four catalysts were Cu/Mn-NN (0.321) > Cu/Mn-CN (0.291) > Cu/Mn-CC (0.290) > Cu/Mn-NC (0.228), indicating that Cu/Mn-NN catalyst possessed more surface oxygen vacancies and a higher amount of surface adsorbed oxygen. These oxygen vacancies acted as active sites could help improve the catalytic performance. Table 2 Component on the surface of the catalysts calculated from XPS results Samples Cu (%) Mn (%) O (%) Cu + Cu 2+ Mn 2+ Mn 3+ Mn 4+ O α O β O γ Cu/Mn-NN 28.8 71.2 7.3 70.5 22.2 71.1 22.8 6.1 Cu/Mn-CN 27.9 72.1 11.8 59.9 28.3 74.24 21.6 4.2 Cu/Mn-NC 17.2 82.8 8.0 55.5 36.5 76.0 17.3 6.7 Cu/Mn-CC 31.3 68.7 31.5 44.8 23.6 74.8 21.7 3.5 Conclusion A simple coprecipitation method was used to prepare Cu/Mn catalysts with different physiochemical properties. The effects of the precursors on the relationship of structure and ozone decomposition performance were investigated by various characterization techniques. The ozone decomposition activity was evaluated at ozone concentration of 80 ppm, 85%RH, and weight space velocity of 600 L·g − 1 ·h − 1 , while the ozone reaction stability was tested at ozone concentration of 80 ppm, 85% RH, and weight space velocity of 300 L·g − 1 ·h − 1 at 25°C. The Cu/Mn-NN catalyst showed remarkable ozone conversion activity and stability, with the conversion of over 91% maintained during 12 hours ozone reaction. The XRD pattern revealed that the crystal structure of the catalysts was Mn 3 O 4 and CuMn 2 O 4 , and different precursors resulted in different crystallinity of the catalyst, resulting in different degrees of dispersion of catalyst particles. Among them, the Cu/Mn-NN catalyst had the largest specific surface area, providing more active sites for ozone adsorption. Characterization showed that using nitrate as the precursors enhanced the reduction and oxygen storage capacity of the catalysts, improved oxygen mobility, enriched the chemical functional groups on the catalyst surface, and provided more recyclable active sites. Furthermore, the comparison of the fresh and spent catalyst curves confirmed the excellent structural stability of the Cu/Mn-NN catalyst and the enrichment of oxygen intermediate species on the catalyst surface. XPS analysis indicated that Cu, Mn, and O elements of the catalysts were mainly in the form of Cu 2+ , Mn 3+ , and lattice oxygen O α , respectively. Notably, the Mn 3+ ion content of the Cu/Mn-NN catalyst was as high as 70.5%, and the ratio of O β /O α was the highest among all the catalysts tested. This result could be attributed to the catalytic environment created by the nitric acid groups, which enriched the metal cation vacancies in the catalyst and enhanced the catalytic ozone reaction. By utilizing different precursors materials for Cu/Mn catalysts to improve their ozone decomposition activity and stability, this study provides valuable insights into the purification of waste gases generated from oxidation processes such as food processing, healthcare, and water treatment. Declarations Author contributions HL designed, conducted the experimental work, and analysed and wrote the paper under the supervision of TS. YL and ML helped to analyse the characterization data and conceptualization. BZ supported experiments, characterizations, and conceptualization. PW analysed experimental data. The manuscript was revised through discussion and comments of all the authors. Funding This work is financially supported by grants from the National Natural Science Foundation of China (No. 22078037). Data availability All the data analyzed during this study are included in this article. Conflict of interes t The authors declare that they have no conflicts of interest. Competing interests The authors declare no competing interests. Ethical approval Not applicable. References T. Tao, Y. Shi, K.M. Gilbert, X. Liu, Sci. Rep-UK. 12, 4293 (2022). https://doi.org/10.1038/s41598-022-08377-9 . Y. Lu, Z. Wu, X. Pang, H. Wu, B. Xing, J. Li, Q. Xiang, J. Chen, D. Shi, Int. J. Environ. Res. Public Health. 20, 168 (2023). https://doi.org/10.3390/ijerph20010168 . X. Li, J. Ma, H. He, J. Environ. Sci. 94, 14 (2020). https://doi.org/10.1016/j.jes.2020.03.058 . C. Guo, Z. Gao, J. Shen, Build. Environ. 158, 302 (2019). https://doi.org/10.1016/j.buildenv.2019.05.024 . M.O. Fadeyi, Sustain. Cities. Soc. 18, 78 (2015). https://doi.org/10.1016/j.scs.2015.05.011 . K.W. Tham, M.O. Fadeyi, Build. Environ. 88, 55 (2015). https://doi.org/10.1016/j.buildenv.2014.10.014 . J. Jia, P. Zhang, L. Chen, Appl. Catal. B: Environ. 189, 210 (2016). https://doi.org/10.1016/j.apcatb.2016.02.055 . C.J. Weschler, N. Carslaw, Environ. Sci. Technol. 52, 2419 (2018). https://doi.org/10.1021/acs.est.7b06387 . W. Ye, X. Zhang, J. Gao, G. Cao, X. Zhou, X. Su, Sci. Total. Environ. 586, 696 (2017). https://doi.org/10.1016/j.scitotenv.2017.02.047 . H. Hellén, P. Kuronen, H. Hakola, Atmos. Environ. 57, 35 (2012). https://doi.org/10.1016/j.atmosenv.2012.04.019 . C.C. Lin, C.Y. Chao M.Y. Liu, J. Ind. Eng. Chem. 16, 140 (2010). https://doi.org/10.1016/j.jiec.2010.01.005 . C. Subrahmanyam, D.A. Bulushev, L. Kiwi-Minsker, Appl. Catal. B: Environ. 61, 98 (2005). https://doi.org/10.1016/j.apcatb.2005.04.013 . R. Cao, L. Li, P. Zhang, L. Gao, S. Rong, Environ. Sci-Nano. 8, 1628 (2021). https://doi.org/10.1039/D1EN00149C . K.C. Cho, K.C. Hwang, T. Sano, K. Takeuchi, S. Matsuzawa, J. Photoch. Photobio. A. 161, 155 (2004). https://doi.org/10.1016/S1010-6030(03)00287-9 . H. Liu, S. Liu, B. Xue, Z. Lv, Z. Meng, X. Yang, T. Xue, Q. Yu, K. He, Atmos. Environ. 173, 223 (2018). https://doi.org/10.1016/j.atmosenv.2017.11.014 . M. Haruta, Catal. Today. 36, 153 (1997). https://doi.org/10.1016/S0920-5861(96)00208-8 . M. Haruta, M.Daté, Appl. Catal. A: Gen. 222, 427 (2001). https://doi.org/10.1016/S0926-860X(01)00847-X . Z. Hao, D. Cheng, Y. Guo, Y. Liang, Appl. Catal. B: Environ. 33, 217 (2001). https://doi.org/10.1016/S0926-3373(01)00172-2 . X. Li, G. He, J. Ma, X. Shao, Y. Chen, H. He, Environ. Sci. Technol. 55, 16143 (2021). https://doi.org/10.1021/acs.est.1c05765 . H. Touati, A. Mehri, F. Karouia, F. Karouia, F. Richard, C. Batiot-Dupeyrat, S. Daniele, J.M. Clacens, Catalysts. 12, 448 (2022). https://doi.org/10.3390/catal12040448 . C.L. Chang, T.S. Lin, React. Kinet. Catal. L. 86, 91 (2005). https://doi.org/10.1007/s11144-005-0299-x . Z. Xu, W. Yang, W. Si, J. Chen, Y. Peng, J. Li, J. Hazard. Mater. 420, 126641 (2021). https://doi.org/10.1016/j.jhazmat.2021.126641 . L. Zhang, S. Wang, L. Lv, Y. Ding, D. Tian, S. Wang, Langmuir. 37, 1410 (2021). https://doi.org/10.1021/acs.langmuir.0c02841 . L. Zhang, S. Wang, C. Ni, M. Wang, S. Wang, Chem. Eng. Sci. 229, 116011 (2021). https://doi.org/10.1016/j.ces.2020.116011 . D. Li, B. Cen, C. Fang, X. Leng, W. Wang, Y. Wang, J. Chen, M. Luo, New. J. Chem. 45, 561 (2021). https://doi.org/10.1039/D0NJ04876C . A.S. Azhariyah, A. Pradyasti, S. Bismo, IOP Conf. Ser.: Earth Environ. Sci. 105, 012012 (2018). https://doi.org/10.1088/1755-1315/105/1/012012 . S. Gong, J. Chen, X. Wu, N. Han, Y. Chen, Catal. Commun. 106, 25 (2018). https://doi.org/10.1016/j.catcom.2017.12.003 . S. Gong, X. Wu, J. Zhang, N. Han, Y. Chen, CrystEngComm. 20, 3096 (2018). https://doi.org/10.1039/C8CE00203G . S. Gong, A. Wang, Y. Wang, H. Liu, N. Han, Y. Chen, ACS Appl. Nano Mater. 3, 597 (2019). https://doi.org/10.1021/acsanm.9b02143 . J. Jia, W. Yang, P. Zhang, J. Zhang, Appl. Catal. A: Gen. 546, 79 (2017). https://doi.org/10.1016/j.apcata.2017.08.013 . B. Dhandapani, S.T. Oyama, Appl. Catal. B: Environ. 11, 129 (1997). https://doi.org/10.1016/S0926-3373(96)00044-6 . C. Wang, J. Ma, F. Liu, H. He, R. Zhang, J. Phys. Chem. C. 119, 23119 (2015). https://doi.org/10.1021/acs.jpcc.5b08095 . Z. Lian, J. Ma, H. He. Catal. Commun. 59, 156 (2015). https://doi.org/10.1016/j.catcom.2014.10.005 . Z.B. Sun, Y.N. Si, S.N. Zhao, Q.Y. Wang, S.Q. Zang, J. Am. Chem. Soc. 143, 5150 (2021). https://doi.org/10.1021/jacs.1c01027 . H. Liang, K. Zhang, Q. Zheng, Q. Wang, H. Huang, L. Wang, Res Chem Intermed. 48, 4929 (2022). https://doi.org/10.1007/s11164-022-04843-1 . Y. Liu, P. Zhang. Appl. Catal. A: Gen. 530, 102 (2017). https://doi.org/10.1016/j.apcata.2016.11.028 . Y. Yang, S. Zhang, S. Wang, K. Zhang, H. Wang, J. Huang, S. Deng, B. Wang, Y. Wang, G. Yu, Environ. Sci. Technol. 49, 4473 (2015). https://doi.org/10.1021/es505232f . Y. Xie, Y. Yu, X. Gong, Y. Guo, Y. Guo, Y. Wang, G. Lu, CrystEngComm. 17,3005 (2015). https://doi.org/10.1039/C5CE00058K . Y. Yang, J. Huang, S. Wang, S. Deng, B. Wang, G. Yu, Appl. Catal. B: Environ. 142, 568 (2013). https://doi.org/10.1016/j.apcatb.2013.05.048 . H. Sun, Z. Liu, S. Chen, X. Quan, Chem. Eng. J. 270, 58 (2015). https://doi.org/10.1016/j.cej.2015.02.017 . X. Li, J. Ma, C. Zhang, R. Zhang, H. He, J. Environ. Sci., 80, 159 (2019). https://doi.org/10.1016/j.jes.2018.12.008 . R. Cao, P. Zhang, Y. Liu, X. Zheng, Appl. Surf. Sci. 495, 143607 (2019). https://doi.org/10.1016/j.apsusc.2019.143607 . S.K. Shinde, D.P. Dubal, G.S. Ghodake, P. Gomez-Romero, S. Kim, V.J. Fulari, RSC ADV. 5, 30478 (2015). https://doi.org/10.1039/C5RA01093D . S. Wang, Y. Zhu, Y. Zhang, B. Wang, H. Yan, W. Liu, Y. Lin, Nanoscale. 12, 12817 (2020). https://doi.org/10.1039/D0NR02796K . Z. Zeng, P. Sun, J. Zhu, X. Zhu, Surf. Interfaces. 8, 73(2017). https://doi.org/10.1016/j.surfin.2017.04.011 . T. Zhou, A. Xie, Q. Wang, X. Li, Z. Zhu, W. Zhang, Y. Tao, S. Luo, Environ. Sci. Pollut. Res. 27, 43150 (2020). https://doi.org/10.1007/s11356-020-10190-8 . W. Hong, M. Shao, T. Zhu, H. Wang, Y. Sun, F. Shen, X. Li, Appl. Catal. B: Environ. 274, 119088 (2020). https://doi.org/10.1016/j.apcatb.2020.119088 . L. Tao, G. Zhao, P. Chen, Z. Zhang, Y. Liu, Y. Lu, Chemcatchem. 11, 1131 (2019). https://doi.org/10.1002/cctc.201801401 . X. Li, J. Ma, L. Yang, G. He, C. Zhang, R. Zhang, H. He, Environ. Sci. Technol. 52 12685 (2018). https://doi.org/10.1021/acs.est.8b04294 . J. Chen, D. Yan, Z. Xu, X. Chen, X. Chen, W. Xu, H. Jia, J. Chen, Environ. Sci. Technol. 52 4728 (2018). https://doi.org/10.1021/acs.est.7b06039 . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 29 Jul, 2023 Read the published version in Research on Chemical Intermediates → Version 1 posted Editorial decision: Major revision 23 Jun, 2023 Reviews received at journal 13 Jun, 2023 Reviewers agreed at journal 02 Jun, 2023 Reviews received at journal 17 May, 2023 Reviewers agreed at journal 15 May, 2023 Reviewers invited by journal 04 May, 2023 Editor assigned by journal 24 Apr, 2023 Submission checks completed at journal 24 Apr, 2023 First submitted to journal 23 Apr, 2023 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. 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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-2850692","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":194670699,"identity":"9c2e9fb5-430c-4ae8-a0e5-1977a10606ee","order_by":0,"name":"Hao Li","email":"","orcid":"","institution":"Dalian Maritime University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Hao","middleName":"","lastName":"Li","suffix":""},{"id":194670700,"identity":"2e6a94c4-6b4a-40af-b40e-ecaff6b2325c","order_by":1,"name":"Yunhe Li","email":"","orcid":"","institution":"Dalian Maritime 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4","display":"","copyAsset":false,"role":"figure","size":203592,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Nitrogen adsorption-desorption isotherms at 77 K (b) and the pore size distribution of Cu/Mn catalysts\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-2850692/v1/755b862d19819a563c928f00.jpeg"},{"id":36396766,"identity":"89dc750d-eefd-4798-ad88-e12311158e57","added_by":"auto","created_at":"2023-04-27 21:41:38","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":917806,"visible":true,"origin":"","legend":"\u003cp\u003eSEM images of the (a) Cu/Mn-NN, (b) Cu/Mn-NC, (c) Cu/Mn-CN and (d) Cu/Mn-CC catalysts\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-2850692/v1/7af20269c9bb15179657109a.png"},{"id":36398096,"identity":"5bd26b1a-0562-4abf-91e6-c714e6a2fc94","added_by":"auto","created_at":"2023-04-27 21:57:38","extension":"jpeg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":236620,"visible":true,"origin":"","legend":"\u003cp\u003eH\u003csub\u003e2\u003c/sub\u003e-TPR profiles of (a) fresh and (b) spent Cu/Mn catalysts\u003c/p\u003e","description":"","filename":"floatimage6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-2850692/v1/d8f59acefaf75c9cb87c0b1c.jpeg"},{"id":36396764,"identity":"9191ec26-7bf8-4726-aa51-990651b82f59","added_by":"auto","created_at":"2023-04-27 21:41:38","extension":"jpeg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":268021,"visible":true,"origin":"","legend":"\u003cp\u003eO\u003csub\u003e2\u003c/sub\u003e-TPD profiles of (a) fresh and (b) spent Cu/Mn catalysts\u003c/p\u003e","description":"","filename":"floatimage7.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-2850692/v1/7437ef3f2ed611d45ea5dd6a.jpeg"},{"id":36397572,"identity":"169944b4-b78d-446a-8543-b4a393c0c4d1","added_by":"auto","created_at":"2023-04-27 21:49:38","extension":"jpeg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":226157,"visible":true,"origin":"","legend":"\u003cp\u003eTG profiles of (a) fresh and (b) spent Cu/Mn catalysts\u003c/p\u003e","description":"","filename":"floatimage8.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-2850692/v1/d5cafddd8a5820126c19b4be.jpeg"},{"id":36396769,"identity":"52dae75a-1649-412a-b45c-ea11c574cfac","added_by":"auto","created_at":"2023-04-27 21:41:38","extension":"jpeg","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":277165,"visible":true,"origin":"","legend":"\u003cp\u003eFT-IR spectra of (a) fresh and (b) spent Cu/Mn catalysts\u003c/p\u003e","description":"","filename":"floatimage9.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-2850692/v1/6b33199c08a725c137428a29.jpeg"},{"id":36398097,"identity":"300b3e42-e59d-4905-ae36-d330a6727854","added_by":"auto","created_at":"2023-04-27 21:57:38","extension":"jpeg","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":707229,"visible":true,"origin":"","legend":"\u003cp\u003e(a)The XPS survey spectra, and the (b)Cu 2p, (c)Mn 2p, and (d)O 1S spectra of Cu/Mn catalysts\u003c/p\u003e","description":"","filename":"floatimage10.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-2850692/v1/250492a693e893335188f797.jpeg"},{"id":44734091,"identity":"e696a987-a2cb-4732-a7e0-3c394ebc05dc","added_by":"auto","created_at":"2023-10-16 22:14:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2119961,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2850692/v1/26c6d9a4-900e-479e-988b-e61e3372bce7.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Effect of different structure of Cu/Mn catalysts on ozone decomposition ability","fulltext":[{"header":"Introduction","content":"\u003cp\u003eOver the past few years, the levels of ozone pollution in the lower atmosphere have escalated, particularly in many urban and industrialized regions over the world [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], which is primarily due to the excessive emission of gaseous ozone precursors and the release of ozone during industrial production and daily life. Between June and August of 2016, ozone emerged as the primary pollutant in in many cities, surpassing particulate matter PM10 and PM2.5. Over the last 5 years, the annual average ground ozone mixing ratio in China has been the only air pollutant taken the high growth trend, according to a government report in 2021 [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Ozone, as a secondary pollutant, now is known to pose a significant threat to human health and crop growth due to its potent oxidation abilities. Even at low concentrations, prolonged exposure to ozone can cause severe damage to cardiopulmonary function, while high concentrations of ozone can lead to various respiratory and cardiovascular diseases, ultimately resulting in increased mortality rates [\u003cspan additionalcitationids=\"CR4 CR5\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Apart from its direct impact on human health and crop growth, ozone can also interact with volatile organic compounds, leading to the production of even more toxic oxidation products. Additionally, ozone has the potential to corrode materials such as rubber and buildings, which means that even at concentrations below regulated levels, it can still be harmful [\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Therefore, it is imperative to research effective methods of decomposing ozone for the preservation of the environment and the betterment of human health.\u003c/p\u003e \u003cp\u003eCurrently, there are several widely used methods for decomposing ozone, including adsorption, thermal decomposition, solution absorption, and catalytic decomposition [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Activated carbon is primarily utilized for its potent adsorption capacity to eliminate low-concentration ozone, however, the substantial amount of heat produced during the ozone adsorption has the potential to trigger fires and explosions. Thermal decomposition is effective for treating high-concentration ozone, but it demands a significant amount of energy to eliminate ozone waste gas, resulting in high costs and limited economic advantages. Therefore, it is not ideal for indoor and outdoor ozone removal but rather for treating high-concentration industrial waste gas. Although the solution absorption method effectively purifies low-concentration ozone, it relies on costly sodium thiosulfate or sodium sulfite, resulting in the production of significant volumes of waste liquids that are challenging to manage, posing the risk of secondary pollution. The catalytic decomposition method is widely considered the most ideal approach for ozone removal due to its ability to catalyze decomposition at room temperature, stability, environmental friendliness, safety, and economic benefits [\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. However, due to the frequent need to effectively decompose ozone at low temperature and high humidity, it is important to develop catalysts with superior activity adapted to the environment.\u003c/p\u003e \u003cp\u003eOzone decomposition catalysts can be categorized into two groups based on their active components: noble metal catalysts and transition metal oxide catalysts. Precious metal catalysts, including gold (Au) [\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], silver (Ag) [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], palladium (Pd) [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], platinum (Pt) [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], and rhodium (Rh) [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], exhibit exceptional ozone decomposition activity and remarkable water resistance. In comparison to precious metal catalysts, transition metal oxides are more fitting for large-scale ozone catalytic decomposition due to the low cost, abundant availability, exceptional redox activity, and variable valence state, making them highly promising for catalytic applications. The transition metal oxides group encompasses metals such as manganese (Mn) [\u003cspan additionalcitationids=\"CR23\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], cobalt (Co) [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], copper (Cu) [\u003cspan additionalcitationids=\"CR27\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], nickel (Ni) [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], and iron (Fe) [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. For instance, Dhandapani and Oyama [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] deposited various metal oxides onto a 20% γ-Al\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e loaded cordierite foam supporter by multiple impregnations, and demonstrated that MnO\u003csub\u003e2\u003c/sub\u003e was superior to other metal oxide for ozone decomposition. Manganese oxide then has emerged as a major focus of catalytic research due to its stable valence, ease of preparation, versatile structure, and extensive applications in the field of catalysis. Cryptomelane-type manganese oxide (OMS-2) is a form of manganese dioxide characterized by a one-dimensional tunnel structure made up of 2\u0026times;2 edge-shared MnO\u003csub\u003e6\u003c/sub\u003e octahedral chains connected by corners to form a 4.6\u0026times;4.6 \u0026Aring; tunnel. Wang et al. [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] conducted a hydrothermal synthesis of OMS-2 catalysts using various Mn\u003csup\u003e2+\u003c/sup\u003e precursors for ozone decomposition, and revealed the ozone decomposition performance of OMS-2-Ac synthesized with acetate as the precursor was found to be superior to that of nitrate and chloride under 90% RH and GHSV\u0026thinsp;=\u0026thinsp;600000 h\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. According to the study, utilizing acetate as the precursor for Mn\u003csup\u003e2+\u003c/sup\u003e resulted in improved dispersion of manganese oxides in the OMS-2-Ac catalyst due to the formation of smaller particles, leading to a lower Mn-Mn coordination number and more defects for ozone molecular adsorption. In other words, the surface structure and oxygen vacancy that affected the catalytic performance of ozone decomposition, is firmly dependent on synthesis parameters of the manganese oxide catalyst, highlighting the need for further investigation into the effects of oxygen intermediate accumulation during the catalytic process on catalyst properties.\u003c/p\u003e \u003cp\u003eManganese oxide catalysts are prone to deactivation under dry and wet conditions due to the existence of competitive adsorption and the occupation of oxygen vacancy by oxygen intermediates during the ozone decomposition reaction. To increase the active sites content and enhance the stability of these catalysts, they are often modified by doping with other metals such as Fe, Ag, Cu, or Ni [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. By investigating the subtle structural control of Mn-based catalysts, the structure-activity relationship between the catalytic activity of ozone and the microstructure can be better constructed, so as to directionally synthesize efficient catalysts with low cost and excellent water resistance. In this study, a simple co-precipitation method was utilized to synthesize Cu/Mn catalysts with different Cu\u003csup\u003e2+\u003c/sup\u003e and Mn\u003csup\u003e2+\u003c/sup\u003e precursors, and the corresponding activities and stabilities of ozone decomposition were systematically assessed over these Cu/Mn-based catalysts. Then, the structures of fresh and spent catalysts underwent characterization using XRD, SEM, BET, FI-IR, O\u003csub\u003e2\u003c/sub\u003e-TPD, H\u003csub\u003e2\u003c/sub\u003e-TPR, TG and XPS as far as possible, and the deactivation reason and reaction mechanism for ozone decomposition were discussed through the changes observed in the catalysts before and after the reaction.\u003c/p\u003e"},{"header":"Experimental","content":"\u003cp\u003eCatalyst preparation\u003c/p\u003e \u003cp\u003eCu(NO\u003csub\u003e3\u003c/sub\u003e)\u003csub\u003e2\u003c/sub\u003e\u0026middot;3H\u003csub\u003e2\u003c/sub\u003eO, Mn(NO\u003csub\u003e3\u003c/sub\u003e)\u003csub\u003e2\u003c/sub\u003e, Mn(CH\u003csub\u003e3\u003c/sub\u003eCOO)\u003csub\u003e2\u003c/sub\u003e\u0026middot;4H\u003csub\u003e2\u003c/sub\u003eO, Cu(CH\u003csub\u003e3\u003c/sub\u003eCOO)\u003csub\u003e2\u003c/sub\u003e\u0026middot;H\u003csub\u003e2\u003c/sub\u003eO, KOH, and KMnO\u003csub\u003e4\u003c/sub\u003e were obtained from Shanghai McLean Biochemical Technology Co., Ltd, China. All other reagents were of analytical grade and used without any additional purification steps.\u003c/p\u003e \u003cp\u003eThe catalysts were synthesized by a straightforward co-precipitation method. Typically, equal molar amounts of Cu(NO\u003csub\u003e3\u003c/sub\u003e)\u003csub\u003e2\u003c/sub\u003e\u0026middot;3H\u003csub\u003e2\u003c/sub\u003eO and 50% Mn(NO\u003csub\u003e3\u003c/sub\u003e)\u003csub\u003e2\u003c/sub\u003e (with a Mn : Cu molar ratio of 2.5) were dissolved in deionized water, stirred to form a homogeneous solution, and then dissolved KOH and KMnO\u003csub\u003e4\u003c/sub\u003e in deionized water. The precipitant was slowly added to the metal salt solution, and the quantity of precipitant was twice the total molar amount of metal ions. After slow titration at 400 rpm and aging at 200 rpm for 2 hours at 30\u0026deg;C, the resulting green solution was washed thrice with deionized water until it was neutral, and then dried overnight at 80\u0026deg;C. The obtained catalyst was labeled as Cu/Mn-NN after annealing in a muffle furnace at 450\u0026deg;C for 2 hours. Cu/Mn-CN was labeled using Cu(CH\u003csub\u003e3\u003c/sub\u003eCOO)\u003csub\u003e2\u003c/sub\u003e\u0026middot;H\u003csub\u003e2\u003c/sub\u003eO and Mn(CH\u003csub\u003e3\u003c/sub\u003eCOO)\u003csub\u003e2\u003c/sub\u003e\u0026middot;4H\u003csub\u003e2\u003c/sub\u003eO as Cu\u003csup\u003e2+\u003c/sup\u003e and Mn\u003csup\u003e2+\u003c/sup\u003e precursors, respectively. The same nomenclature was used for Cu/Mn-NC and Cu/Mn-CN catalysts.\u003c/p\u003e \u003cp\u003eCatalyst Characterization\u003c/p\u003e \u003cp\u003eThe catalysts obtained were analyzed using a German Bruker D8 ADVANCE X-ray powder diffractometer (XRD) at 25\u0026deg;C. The excitation light source used was CuKα X-ray, with a wavelength of 0.1542 nm. The scanning range was 5\u0026deg;-70\u0026deg;, with a scanning rate of 8.0 \u003csup\u003eo\u003c/sup\u003e/min and a step size of 0.02\u003csup\u003eo\u003c/sup\u003e. The Autosorb iQ multi-function automatic specific surface area and porosity analyzer was employed for characterization. Prior to the test, the sample underwent vacuum degassing at 423 K for 2 hours, and then a nitrogen adsorption-desorption test was carried out at 77 K. The total pore volume was determined from the adsorption capacity of the adsorption isotherm at a relative pressure of 0.95. The specific surface area of the sample was calculated using the BET method, and the pore diameter and pore volume were calculated using the BJH method. The surface morphology of the catalysts was analyzed using a TESCAN VEGA3 scanning electron microscope (TESCAN, Czechoslovakia) with an accelerating voltage of 5 KV. Prior to testing, the samples were dried at 120\u0026deg;C, and a small amount of powder was affixed to the conductive adhesive for testing. The thermal stability of the catalyst was measured by a thermogravimetric instrument (Shimadzu, Japan, TG-50), which was heated from 30\u0026deg;C to 800\u0026deg;C at a rate of 10\u0026deg;C per minute in an argon atmosphere. A 10 mg catalyst sample was weighed, and the flow rate of argon gas was set to 50 mL/min.\u003c/p\u003e \u003cp\u003eThe H\u003csub\u003e2\u003c/sub\u003e-TPR test was conducted using the ChemBET Pulsar chemisorption instrument from the United States. The sample (50 mg) was weighed and purged with He gas at 150\u0026deg;C for 30 minutes. After cooling to room temperature, the gas circuit was switched to 10 vol% H\u003csub\u003e2\u003c/sub\u003e/Ar mixture. The temperature was then increased to 700\u0026deg;C at 10\u0026deg;C/min, and the H\u003csub\u003e2\u003c/sub\u003e-TPR curves were collected after baseline stabilization. Additionally, the instrument was also used for the O\u003csub\u003e2\u003c/sub\u003e-TPD test. For this, the sample (50 mg) was heated to 110\u0026deg;C in the helium environment, and purged for 60 minutes to remove surface H\u003csub\u003e2\u003c/sub\u003eO. After natural cooling to room temperature, a 5 vol% O\u003csub\u003e2\u003c/sub\u003e/He mixture was introduced for 1 hour to reach saturation, followed by purging with He gas for 30 minutes to remove physically adsorbed O\u003csub\u003e2\u003c/sub\u003e from the sample's surface. After baseline stabilization, the gas path was switched to the 5 vol% O\u003csub\u003e2\u003c/sub\u003e/He mixture and the temperature was raised to 700\u0026deg;C at 10\u0026deg;C/min to collect the O\u003csub\u003e2\u003c/sub\u003e-TPD curve.\u003c/p\u003e \u003cp\u003eThe surface functional groups of the catalyst were examined using an FT-IR infrared spectrometer (Thermo, IS50-FTIR) with a wavelength scanning range of 4000\u0026thinsp;\u0026minus;\u0026thinsp;500 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and a resolution of 4 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The instrument was calibrated by scanning the background spectrogram 32 times and the sample spectrogram 4 times to ensure high-quality results. Prior to the analysis, the raw and reaction gases were passed through a cold trap to remove H\u003csub\u003e2\u003c/sub\u003eO, and the infrared spectra of the samples were recorded in the air background. The element content and valence state on the catalyst surface were analyzed using an X-ray spectrometer (Thermo, SCIENTIFIC) under ultra-high vacuum conditions with AIKα radiation as the X-ray source. The combined energy spectrum of the elements was obtained, and the carbon spectrum (BE\u0026thinsp;=\u0026thinsp;284.8 eV) was used for calibration.\u003c/p\u003e \u003cp\u003eCatalyst Activity Measurement\u003c/p\u003e \u003cp\u003eThe fixed bed continuous flow adaptive reactor (i. d. =14 mm) was used to measure the ozone decomposition activity and stability of the prepared catalysts at a total air flow of 1300 mL/min. The activity tests were performed at various temperature points, using 0.13 g of sample with a size of 40\u0026ndash;60 mesh, under the conditions of the relative humidity of 85% and the weight space velocity of 600 L\u0026middot;g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u0026middot;h\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The relative humidity of feed gas was regulated using the air through the thermostatic bubbler and assessed by the humidity equipment (SSN23E, YOWEXA, China). Stability tests were performed in the same fixed reactor, at temperature of 25\u0026deg;C, 85%RH, 0.26 g catalyst mass, and weight space velocity of 300 L\u0026middot;g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u0026middot;h\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. Ozone was generated by electrolyzing oxygen from an ozone generator (OSAN, China), and the ideal inlet ozone concentration was 80 ppm. An ozone analyzer (model 106-L, US 2B Technology) was used to measure ozone concentrations at both inlet and outlet. The ozone conversion formula of the catalyst was:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$${\\eta }=\\frac{{\\left[{\\text{O}}_{3}\\right]}_{\\text{i}\\text{n}\\text{l}\\text{e}\\text{t}}-{\\left[{\\text{O}}_{3}\\right]}_{\\text{o}\\text{u}\\text{t}\\text{p}\\text{u}\\text{t}}}{{\\left[{\\text{O}}_{3}\\right]}_{\\text{i}\\text{n}\\text{l}\\text{e}\\text{t}}}\\times 100\\text{\\%} \\left(1\\right)$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\left[{\\text{O}}_{3}\\right]}_{\\text{i}\\text{n}\\text{l}\\text{e}\\text{t}}\\)\u003c/span\u003e\u003c/span\u003e and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\left[{\\text{O}}_{3}\\right]}_{\\text{o}\\text{u}\\text{t}\\text{p}\\text{u}\\text{t}}\\)\u003c/span\u003e\u003c/span\u003e represent the ozone concentration at the inlet and outlet of the detector, respectively.\u003c/p\u003e"},{"header":"Results And Discussion","content":"\u003cp\u003eCatalytic activity of ozone decomposition\u003c/p\u003e \u003cp\u003eThe ozone conversion activities of Cu/Mn catalysts were investigated over the temperature of 25\u0026ndash;100\u0026deg;C, RH\u0026thinsp;=\u0026thinsp;85%, and weight space velocity of 600 L\u0026middot;g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u0026middot;h\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, as depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Cu/Mn-NN and Cu/Mn-NC catalysts showed a significant increase in ozone conversion before 45\u0026deg;C, which then stabilized, while Cu/Mn-CN and Cu/Mn-CC catalysts displayed similar ozone decomposition curves. As per the Arrhenius formula, the increase in temperature enhances the molecular thermal movement inside the catalyst, leading to accelerated ozone decomposition. The as-prepared catalysts exhibited different ozone decomposition activities, owing to their unique structure, physicochemical properties, and water resistance under high humidity conditions [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. The peak ozone conversion followed the order: Cu/Mn-NN (89.5%)\u0026thinsp;\u0026gt;\u0026thinsp;Cu/Mn-CN (76.1%)\u0026thinsp;\u0026gt;\u0026thinsp;Cu/Mn-CC (75.1%)\u0026thinsp;\u0026gt;\u0026thinsp;Cu/Mn-NC (68.3%). The Cu/Mn-NN catalyst showed the highest catalytic activity, which may be caused by the micro regulation of structural characteristics and optimization of physical and chemical properties by nitrate precursors, making it more suitable for ozone decomposition.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe stability of catalysts was tested under conditions of the temperature at 25\u0026deg;C, RH\u0026thinsp;=\u0026thinsp;85%, and the weight space velocity of 300 L\u0026middot;g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u0026middot;h\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The ozone conversion for the different catalysts declined to varying degrees during the 12 hours reaction period, as seen in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Notably, the Cu/Mn-NN catalyst displayed impressive stability, maintaining over 91% ozone conversion throughout the entire 12 hours ozone decomposition process. In contrast, the ozone conversion of the other catalysts all experienced significant declines within the first 4 hours. After the stability test, the ozone conversion for the Cu/Mn-CN and Cu/Mn-CC catalysts remained at 78% and 69%, respectively, whereas the Cu/Mn-NC catalyst dropped to 48%, indicating poor stability. It could be seen that the catalytic environment constructed and regulated by nitric acid groups of manganese nitrate under high humidity could more effectively remove ozone. Therefore, it is necessary to further investigate the effect of different precursors on the structural properties of catalysts.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eCrystal structure, morphology and specific surfaces\u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea displayed the XRD patterns of the fresh catalysts, and their diffraction peaks could be attributed to the tetragonal Mn\u003csub\u003e3\u003c/sub\u003eO\u003csub\u003e4\u003c/sub\u003e phase (JCPDS card no. 24\u0026ndash;0734) and the CuMn\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e4\u003c/sub\u003e phase (JCPDS card no. 74-2422). The diffraction peaks were observed at 2θ\u0026thinsp;=\u0026thinsp;18.2\u0026deg;, 29.0\u0026deg;, 31.1\u0026deg;, 32.5\u0026deg;, 36.2\u0026deg;, 38.2\u0026deg;, 44.6\u0026deg; 58.5\u0026deg; and 64.7\u0026deg;, corresponding to the crystal planes (101), (112), (200), (103), (211), (004), (220), (321) and (400) of Mn\u003csub\u003e3\u003c/sub\u003eO\u003csub\u003e4\u003c/sub\u003e phase, respectively. The overlapping parts correspond to the crystal planes (111), (220), (311) and (511) of CuMn\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e4\u003c/sub\u003e phase. Notably, no diffraction peaks of other crystal by-products were detected, indicating that the catalyst possessed high purity and crystallinity throughout the preparation process. The figure illustrated that the catalysts synthesized by different precursors had the same crystal type, but there were differences in crystallinity. The Cu/Mn-CC catalyst had the best crystallinity, but comparatively, Cu/Mn-NN catalyst had poor crystallinity, which would cause more defects in the catalyst and may increase the specific surface area, so it was beneficial to the ozone decomposition [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe stability test demonstrated that the activity of all catalysts declined to varying degrees with the reaction time increased, because of the deactivation of active sites during the catalyst decomposition process. Therefore, investigating the deactivation mechanism of catalysts during the reaction process is critical for developing more efficient and stable catalysts. Initially, the crystal structure of the catalysts was investigated before and after the reaction via XRD analysis. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb displayed the XRD pattern diffraction peak of the spent catalyst, which could also be attributed to tetragonal Mn\u003csub\u003e3\u003c/sub\u003eO\u003csub\u003e4\u003c/sub\u003e phase (JCPDS card no. 24\u0026ndash;0734) and the CuMn\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e4\u003c/sub\u003e phase (JCPDS card no. 74-2422). After the reaction, except Cu/M-NN catalyst, the diffraction intensity of the characteristic peak in the catalyst increased compared to before the reaction. Furthermore, some characteristic diffraction peaks of crystal planes emerged, implying that the crystallinity of the catalyst was reinforced during the ozone decomposition process, making the crystal plane easier to detect. This could be attributed to the oxidation-reduction reaction taking place during the catalytic reaction process, leading to the aggregation of catalyst grains, which ultimately hampered the efficiency of the catalytic reaction. The Cu/Mn-NN catalyst exhibited lower diffraction peak intensity, indicating the higher dispersion of crystalline grains than other catalysts. This may be because the concentration of nitric acid groups in the solution was higher than that of other solutions during the synthesis process, and the nitric acid group may form a bond with the hydroxyl groups on the catalyst surface, thus allowing better separation of catalyst particles [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. This feature could prevent the further aggregation of catalyst particles and explain the superior ozonolysis performance of the catalyst.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAs is widely acknowledged, the specific surface area of catalysts is a crucial factor affecting catalytic activity. The N\u003csub\u003e2\u003c/sub\u003e adsorption-desorption at 77 K was used to analyze the specific surface area and pore structure of Cu/Mn catalysts, as depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Figure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea illustrated that the adsorption isotherms of the synthesized catalysts were V-shaped with a typical H3 hysteresis loop, indicating that nitrogen underwent capillary condensation within the mesoporous gap formed by the oxide nanoparticle aggregation [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. The hysteresis loops of catalysts were all observed to be in the range of 0.8\u0026thinsp;\u0026lt;\u0026thinsp;P/P\u003csub\u003e0\u003c/sub\u003e\u0026thinsp;\u0026lt;\u0026thinsp;1.0, indicating larger pore sizes of 25.85, 33.4, 26.62, and 29.09 nm, respectively, as exhibited in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb. It is widely accepted that a larger pore size facilitates contact between the active sites and more ozone molecules, thereby reducing mass transfer resistance and promoting the diffusion of reactants on the catalyst surface. The data presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e revealed that Cu/Mn-NN catalyst exhibited the highest specific surface area of 59.1 m\u003csup\u003e2\u003c/sup\u003e\u0026middot;g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, which surpassed the specific surface areas of Cu/Mn-CN (42.8 m\u003csup\u003e2\u003c/sup\u003e\u0026middot;g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), Cu/Mn-CC (49.8 m\u003csup\u003e2\u003c/sup\u003e\u0026middot;g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and Cu/Mn-NC (44.4 m\u003csup\u003e2\u003c/sup\u003e\u0026middot;g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) catalysts. This larger specific surface area indicated that there were more active sites available for ozone molecule adsorption, ultimately leading to improved activity and stability for ozone decomposition.\u003c/p\u003e \u003cp\u003e \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\u003eTextural properties of Cu/Mn 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=\"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\u003eCatalysts\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\u0026middot;g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003ePore Volume (mLg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eAverage Pore Size (nm)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCu/Mn-NN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e59.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25.85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCu/Mn-CN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e42.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e33.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCu/Mn-NC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e49.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e26.62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCu/Mn-CC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e44.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e29.09\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 morphology of catalysts was investigated using scanning electron microscopy, as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea-d. The images showed that catalysts showed a similar morphology with aggregated flocculating particles and an uneven surface, which could increase the surface area and generate abundant adsorption sites, thereby enhancing the ozone decomposition activity. No remarkable difference in the morphology was observed among the as-made catalysts, suggesting that the morphology was not a significant factor influencing the catalytic performance variations.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eReducibility, oxygen species type and thermal stability.\u003c/p\u003e \u003cp\u003eH\u003csub\u003e2\u003c/sub\u003e-TPR analysis was used to further investigate the reduction behavior of catalysts. Figure\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea illustrated that all synthesized catalysts exhibited comparable reduction characteristics, with only a broad reduction region present below 500\u0026deg;C. Based on the XRD pattern, Mn\u003csub\u003e3\u003c/sub\u003eO\u003csub\u003e4\u003c/sub\u003e and CuMn\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e4\u003c/sub\u003e were the crystalline phase of the catalysts, implying that the reduction peak corresponded to the reduction of Mn\u003csub\u003e3\u003c/sub\u003eO\u003csub\u003e4\u003c/sub\u003e to MnO and the reduction of divalent Cu ions and trivalent Mn ions in CuMn\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e4\u003c/sub\u003e. Moreover, catalysts with lower initial reduction temperatures exhibited better reducibility, and the initial reduction temperatures for all catalysts were in the following order: Cu/Mn-CC\u0026thinsp;\u0026gt;\u0026thinsp;Cu/Mn-NC\u0026thinsp;\u0026gt;\u0026thinsp;Cu/Mn-CN\u0026thinsp;\u0026gt;\u0026thinsp;Cu/Mn-NN. Interestingly, the initial reduction temperature of Cu/Mn-NN catalyst shifted forward by 10\u0026ndash;20\u0026deg;C to the low-temperature stage, and the catalyst showed relatively more H\u003csub\u003e2\u003c/sub\u003e consumption, which could promote the desorption of the oxygen intermediate on the occupied oxygen vacancy, indicating better reduction capacity compared to other catalysts. This stronger reducibility could facilitate the redox cycle and accelerate the regeneration of oxygen vacancies, ultimately resulting in improved ozone decomposition performance.\u003c/p\u003e \u003cp\u003eThe H\u003csub\u003e2\u003c/sub\u003e-TPR curve of the spent catalysts, as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eb, displayed a shift towards lower temperature in the initial reduction peak. This could be attributed to the adsorption and reaction of ozone molecules at the active sites, leading to the formation of oxygen intermediate O\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e*\u003c/sup\u003e. This phenomenon facilitates the transfer of electrons from adsorbed oxygen anions to the surface of Cu/Mn catalysts, thereby enhancing the reduction ability of the catalyst. Therefore, all the catalysts showed a stronger electrophilicity, which increased the likelihood of the reduction reaction to occur. Moreover, the Cu/Mn-NC and Cu/Mn-CC catalysts displayed two smaller shoulder peaks at 217\u0026deg;C and 193\u0026deg;C, respectively. As is known, the reduction peak at the lower temperature range corresponds to the reduction of MnO\u003csub\u003e2\u003c/sub\u003e to Mn\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e and Mn\u003csub\u003e3\u003c/sub\u003eO\u003csub\u003e4\u003c/sub\u003e [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. This implied that during the ozone decomposition process, some Mn\u003csup\u003e2+\u003c/sup\u003e or Mn\u003csup\u003e3+\u003c/sup\u003e was oxidized to Mn\u003csup\u003e4+\u003c/sup\u003e, but the Mn\u003csup\u003e4+\u003c/sup\u003e was not restored to the low valent manganese ion in a timely manner. The desorption of oxygen intermediates plays a crucial role in the oxidation and reduction cycle of ozone decomposition. The failure of Mn\u003csup\u003e4+\u003c/sup\u003e to reduce in a timely manner suggests that the long-term occupation of oxygen vacancies by oxygen intermediates has resulted in the deactivation of catalysts. This inactivation phenomenon hinders the catalytic cycles of ozone decomposition and ultimately leads to poor stability, as confirmed by the stability test results. Furthermore, the temperature shift of the main reduction peak was calculated, and the order of the shift was as follows: Cu/Mn-NN (28\u0026deg;C)\u0026thinsp;\u0026lt;\u0026thinsp;Cu/Mn-CN (33\u0026deg;C)\u0026thinsp;\u0026lt;\u0026thinsp;Cu/Mn-NC (43\u0026deg;C)\u0026thinsp;\u0026lt;\u0026thinsp;Cu/Mn-CC (49\u0026deg;C). It was evident that the Cu/Mn-NN catalyst showed the smallest temperature shift of the main reduction peak, suggesting Cu/Mn-NN catalyst under high humidity and high space velocity conditions possessed a robust structure and reduction stability.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo identify the evolution of oxygen in the catalysts, O\u003csub\u003e2\u003c/sub\u003e-TPD analysis was conducted on the catalysts, as exhibited in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e. The O\u003csub\u003e2\u003c/sub\u003e-TPD curve of the catalysts comprised of two segments: the desorption peak below 350\u0026deg;C, which corresponded to the release of chemically adsorbed oxygen molecules and active surface oxygen, such as peroxide O\u003csub\u003e2\u003c/sub\u003e-ads, and the desorption peak in the range of 350\u0026ndash;650\u0026deg;C, which indicated the release of sub-surface lattice oxygen [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. In general, oxygen with a lower desorption temperature is less strongly bound to the manganese atoms in the catalyst framework, resulting in higher oxygen mobility. Figure\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ea demonstrated that the desorption temperature sequence for the catalysts was Cu/Mn-NN\u0026thinsp;\u0026lt;\u0026thinsp;Cu/Mn-CN\u0026thinsp;\u0026lt;\u0026thinsp;Cu/Mn-NC\u0026thinsp;\u0026lt;\u0026thinsp;Cu/Mn-CC, indicating that the Cu/Mn-NN catalyst exhibited the highest oxygen mobility. The peak below 200\u0026deg;C corresponds to the desorption of physically adsorbed oxygen, and its peak area reflects the content of oxygen species [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. The physical adsorption oxygen peak area of Cu/Mn-NN and Cu/Mn-CN catalysts was larger than that of Cu/Mn-NC and Cu/Mn-CC catalysts, suggesting that more active sites were available on the catalysts. Catalysts contained oxygen species mainly in the form of sub-surface lattice oxygen, and the inability to release lattice oxygen was a crucial factor in the reduced activity of manganese-based ozone catalysts. As for the temperature range of 350\u0026deg;C-650\u0026deg;C, the desorption peak area of Cu/Mn-NN and Cu/Mn-CN catalysts was larger, and the desorption temperature of sub-surface lattice oxygen was lower. This finding indicated that the catalysts had better oxygen storage and release capacity, which was significant in enhancing the ozone decomposition activity and stability.\u003c/p\u003e \u003cp\u003eThe O\u003csub\u003e2\u003c/sub\u003e-TPD curve of the spent catalysts was displayed in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eb, and the curve distribution was like that of the fresh catalysts. Below 350\u0026deg;C, all catalysts exhibited desorption peaks for adsorption oxygen, with the Cu/Mn-NN catalyst having the largest desorption peak area. This indicated that the oxygen intermediates produced during ozone decomposition were adsorbed onto the active sites, and the content of oxygen vacancy was highest in the Cu/Mn-NN catalyst. Compared to the pre-reaction state, the sub-surface lattice oxygen desorption peak underwent significant changes between 350\u0026deg;C and 650\u0026deg;C. Specifically, the peak narrowed, and its area decreased, indicating that a significant amount of sub-surface lattice oxygen was consumed during the reaction to compensate for the oxygen vacancy. By comparing the diagrams before and after the reaction of the four catalysts, it was apparent that the reduction in catalyst activity was caused by the insufficient conversion between lattice oxygen and surface adsorbed oxygen. Additionally, the desorption curves before and after the reaction revealed that Cu/Mn-NN and Cu/Mn-CN catalysts possessed superior structural stability, which would facilitate maintaining outstanding stability during continuous reaction.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe thermal stability of the prepared catalysts was assessed through thermogravimetric analysis, as depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e. Weight loss below 180\u0026deg;C corresponded to physically adsorbed water and surface adsorbed oxygen, whereas weight loss above 250\u0026deg;C indicated the evolution and phase change of catalyst lattice oxygen. The weight loss within these two ranges reflected the desorption of chemically adsorbed water and surface active oxygen [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. As the temperature continued to rise, the thermogravimetric curves of the fresh catalysts displayed a similar trend. Figure\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003ea illustrated that the order of maximum weight loss was Cu/Mn-CC (10.3%)\u0026thinsp;\u0026lt;\u0026thinsp;Cu/Mn-NN (11.2%)\u0026thinsp;\u0026lt;\u0026thinsp;Cu/Mn-CN (11.4%)\u0026thinsp;\u0026lt;\u0026thinsp;Cu/Mn-NC (12.1%). The thermogravimetric curve of the spent catalysts was presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eb and the order of maximum weight loss was: Cu/Mn-CC (6.3%)\u0026thinsp;\u0026lt;\u0026thinsp;Cu/Mn-CN (6.7%)\u0026thinsp;\u0026lt;\u0026thinsp;Cu/Mn-NN (7.8%)\u0026thinsp;\u0026lt;\u0026thinsp;Cu/Mn-NC (11.2%). The thermal stability of the spent catalysts was improved compared to the original catalysts because the reaction consumed a portion of the lattice oxygen. Notably, the weight loss of Cu/Mn-NC catalyst corresponding to lattice oxygen evolution and phase transition above 250\u0026deg;C remained relatively unchanged before and after the reaction, indicating its excellent lattice oxygen stability. However, the low ozone decomposition stability of catalyst was due to the relatively challenging release of lattice oxygen.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eSurface chemical functional groups, components and oxygen vacancies\u003c/p\u003e \u003cp\u003eThe surface functional groups of fresh and spent catalysts were analyzed by FI-IR spectroscopy, as presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e. Five types of surface functional groups were identified based on the literature and peak positions: (i) 500\u0026thinsp;~\u0026thinsp;800 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e related to the Cu/Mn-O vibration mode in the catalyst matrix, (ii) 800\u0026thinsp;~\u0026thinsp;1000 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e was derived from the stretching vibration of O-O bond of oxygen intermediate species, (iii) 1000\u0026thinsp;~\u0026thinsp;1450 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e was due to the combined stretching vibration of Cu/Mn metal ions and \u0026ndash;OH groups in the catalyst, (iv) 1500\u0026thinsp;~\u0026thinsp;1640 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e was owing to the bending vibrational mode of interlayer water, (v) 3300\u0026thinsp;~\u0026thinsp;3800 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e was connected with the stretching vibration of hydroxyl [\u003cspan additionalcitationids=\"CR43 CR44\" citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe surface functional group analysis of the fresh catalysts was presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003ea. The Cu/Mn-NN catalyst exhibited the most robust O-O bond stretching vibration at 942 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and showed higher stretching vibration intensity of Cu/Mn-OH compared to the other catalysts at 1068 and 1380 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. Based on the O\u003csub\u003e2\u003c/sub\u003e-TPD and stability test results, it can be inferred that the surface of the Cu/Mn-NN catalyst had abundant active oxygen species that converted into -OH groups to link with metal ions, inhibiting the accumulation rate of oxygen intermediates, thereby enhancing the ozone decomposition activity under high humidity conditions. In general, the competitive adsorption of water molecules would cause decreased activity and even deactivation of the catalyst. The surface hydroxyl and water base of the as-made catalysts was detected at 1626 and 3412 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, and Cu/Mn-NN catalyst had higher vibration intensity. Based on the stability test results, the Cu/Mn-NN catalyst exhibited better ozone decomposition performance, which suggested that the surface hydroxyl group and water group may have participated in the catalytic reaction of the intermediate, leading to the promotion of ozone decomposition on the catalyst surface. This would be demonstrated with the FI-IR spectrum of the catalyst after the reaction, as discussed below.\u003c/p\u003e \u003cp\u003eDespite the significant variations in the surface functional group content of the fresh catalysts, the FI-IR spectra of the spent catalysts showed a consistent trend, as depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eb. Initially, the vibration intensity of the Cu/Mn-O bond of all catalysts weakened, with the Cu/Mn-NN catalyst exhibiting the most significant weakening. This observation implied that during the reaction process, oxygen species in the Cu/Mn-O bond escaped to replenish oxygen vacancies and sustain the ozone decomposition cycle reaction. Notably, the Cu/Mn-O bond in Cu/Mn-NN was the loosest, indicating that this catalyst exhibited highest oxygen mobility. The change of the vibration intensity of the O-O bond on the catalyst surface and the reduction of hydroxyl group and interlayer water were the second observable changes. These changes suggested that various oxygen intermediates were produced and adsorbed on the catalyst surface, with the hydroxyl and water groups participating in the catalytic reaction of the intermediates, leading to the weakening of the vibration intensity. Lastly, the variation in the vibration intensity of Cu/Mn-OH on the catalyst surface was associated with the occupancy of oxygen vacancies by water molecules during the reaction. It was worth noting that the FI-IR spectrum curve of Cu/Mn-NC catalyst showed little difference by reaction, illustrating that the number of active sites on catalyst surface was limited, resulting in the worst ozone decomposition activity and stability. On the other hand, Cu/Mn-NN catalyst exhibited the opposite behavior, and the changes in its spectrum indicated that the catalyst had a better ability to regenerate active sites during the reaction to maintain high ozone conversion.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e displayed the XPS spectrum results which were used to identify the surface composition, element valence, and surface oxygen vacancies of Cu/Mn catalysts. As exhibited in Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003ea, Cu, Mn, C, and O elements existed on the catalyst surface. To elaborate, Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003eb demonstrates that the Cu 2p spectrum of the catalysts obtained could be analyzed into two primary peak regions corresponding to the Cu 2p\u003csub\u003e3/2\u003c/sub\u003e state (928\u0026ndash;938 eV) and Cu 2p\u003csub\u003e1/2\u003c/sub\u003e state (948\u0026ndash;958 eV), with corresponding shake-up satellite peaks located at 940\u0026ndash;946 eV (S1) and 960\u0026ndash;965 eV (S2), respectively. The regions positioned at 930.0-930.5 eV and 951.0-951.5 eV among the two main peaks were attributed to Cu\u003csup\u003e+\u003c/sup\u003e species, while the regions centered at 935.0-940.0 eV and 953.5\u0026ndash;954.0 eV were identified as Cu\u003csup\u003e2+\u003c/sup\u003e species [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. The XPS spectrum was utilized to compute the relative content ratio of Cu\u003csup\u003e+\u003c/sup\u003e and Cu\u003csup\u003e2+\u003c/sup\u003e and presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The main form of Cu in the prepared catalyst was Cu\u003csup\u003e2+\u003c/sup\u003e, and Cu/Mn-NC catalyst had the highest proportion of Cu\u003csup\u003e2+\u003c/sup\u003e at 82.8%, which corresponded to the worst catalytic activity. The appropriate proportion of Cu\u003csup\u003e+\u003c/sup\u003e/Cu\u003csup\u003e2+\u003c/sup\u003e facilitated electron transfer between the redox pairs formed with multivalent Mn ions, but an excessive Cu\u003csup\u003e2+\u003c/sup\u003e content weakened the electron transfer ability of the redox pairs in the catalyst. As a result, the active sites became difficult to recover and could even lead to deactivation, reducing the ozone decomposition performance.\u003c/p\u003e \u003cp\u003eThe XPS spectrum of the Mn 2p was presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003ec, which showed two main peak regions of Mn 2p\u003csub\u003e3/2\u003c/sub\u003e state and Mn 2p\u003csub\u003e1/2\u003c/sub\u003e state with binding energies of 641 eV and 654 eV, respectively [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. The Mn 2p\u003csub\u003e3/2\u003c/sub\u003e spectrum was separated into three binding energy bands positioned at 640.0-641.5 eV, 642.0-642.5 eV, and 643.5\u0026ndash;645.0 eV, which corresponded to Mn\u003csup\u003e2+\u003c/sup\u003e, Mn\u003csup\u003e3+\u003c/sup\u003e, and Mn\u003csup\u003e4+\u003c/sup\u003e, respectively [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presented the relative content of Mn ions with different valence states calculated based on the XPS spectra. The results proved that the content of Mn\u003csup\u003e3+\u003c/sup\u003e was the highest in all catalysts, which was consistent with the XRD findings. Notably, Cu/Mn-NN catalyst, had the highest Mn\u003csup\u003e3+\u003c/sup\u003e content of 70.5%, which correlated with the best ozone decomposition activity. Therefore, it could be inferred that the formation of Mn\u003csup\u003e3+\u003c/sup\u003e species facilitated the improvement of the ozone decomposition performance. The catalytic role of the mixed valence of the Mn element is associated with the redox process of the catalyst, and the Mn\u003csup\u003e3+\u003c/sup\u003e/Mn\u003csup\u003e4+\u003c/sup\u003e ratio serves as an indicator for measuring the charge balance on the oxygen vacancy [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. The molar ratio of Mn\u003csup\u003e3+\u003c/sup\u003e/Mn\u003csup\u003e4+\u003c/sup\u003e for all catalysts was as follows: Cu/Mn-NN (3.18)\u0026thinsp;\u0026gt;\u0026thinsp;Cu/Mn-CN (2.12)\u0026thinsp;\u0026gt;\u0026thinsp;Cu/Mn-CC (1.90)\u0026thinsp;\u0026gt;\u0026thinsp;Cu/Mn-NC (1.52). The Mn\u003csup\u003e3+\u003c/sup\u003e/Mn\u003csup\u003e4+\u003c/sup\u003e ratio for Cu/Mn-NN catalyst was more than twice that of Cu/Mn-NC catalyst, indicating that the catalytic environment created by the nitric acid groups could better maintain the charge balance caused by oxygen vacancies, thus improving the ozone decomposition activity and stability at room temperature.\u003c/p\u003e \u003cp\u003eThe O 1s XPS spectrum for all Cu/Mn catalysts was displayed in Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003ed and the primary peak region was deconvoluted into three parts: lattice oxygen O\u003csub\u003eα\u003c/sub\u003e (530.0 eV), surface adsorbed oxygen O\u003csub\u003eβ\u003c/sub\u003e (531.5 eV), and surface adsorbed water and hydroxyl species O\u003csub\u003eγ\u003c/sub\u003e (533.2 eV). The vacancies in metal oxides are considered as sites for oxygen molecule adsorption. Hence, the ratio of O\u003csub\u003eβ\u003c/sub\u003e/O\u003csub\u003eα\u003c/sub\u003e can indicate the abundance of oxygen vacancies in the catalyst [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. The O\u003csub\u003eβ\u003c/sub\u003e/O\u003csub\u003eα\u003c/sub\u003eratios for the four catalysts were Cu/Mn-NN (0.321)\u0026thinsp;\u0026gt;\u0026thinsp;Cu/Mn-CN (0.291)\u0026thinsp;\u0026gt;\u0026thinsp;Cu/Mn-CC (0.290)\u0026thinsp;\u0026gt;\u0026thinsp;Cu/Mn-NC (0.228), indicating that Cu/Mn-NN catalyst possessed more surface oxygen vacancies and a higher amount of surface adsorbed oxygen. These oxygen vacancies acted as active sites could help improve the catalytic performance.\u003c/p\u003e \u003cp\u003e \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\u003eComponent on the surface of the catalysts calculated from XPS results\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSamples\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eCu (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c8\" namest=\"c5\"\u003e \u003cp\u003eMn (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c11\" namest=\"c9\"\u003e \u003cp\u003eO (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCu\u003csup\u003e+\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCu\u003csup\u003e2+\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eMn\u003csup\u003e2+\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMn\u003csup\u003e3+\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMn\u003csup\u003e4+\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eO\u003csub\u003eα\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eO\u003csub\u003eβ\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eO\u003csub\u003eγ\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCu/Mn-NN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e7.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e70.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e22.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e71.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e22.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e6.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCu/Mn-CN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e11.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e59.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e28.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e74.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e21.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCu/Mn-NC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e82.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e8.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e55.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e36.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e76.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e17.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e6.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCu/Mn-CC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e31.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e44.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e23.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e74.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e21.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eA simple coprecipitation method was used to prepare Cu/Mn catalysts with different physiochemical properties. The effects of the precursors on the relationship of structure and ozone decomposition performance were investigated by various characterization techniques. The ozone decomposition activity was evaluated at ozone concentration of 80 ppm, 85%RH, and weight space velocity of 600 L\u0026middot;g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u0026middot;h\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, while the ozone reaction stability was tested at ozone concentration of 80 ppm, 85% RH, and weight space velocity of 300 L\u0026middot;g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u0026middot;h\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e at 25\u0026deg;C. The Cu/Mn-NN catalyst showed remarkable ozone conversion activity and stability, with the conversion of over 91% maintained during 12 hours ozone reaction. The XRD pattern revealed that the crystal structure of the catalysts was Mn\u003csub\u003e3\u003c/sub\u003eO\u003csub\u003e4\u003c/sub\u003e and CuMn\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e4\u003c/sub\u003e, and different precursors resulted in different crystallinity of the catalyst, resulting in different degrees of dispersion of catalyst particles. Among them, the Cu/Mn-NN catalyst had the largest specific surface area, providing more active sites for ozone adsorption. Characterization showed that using nitrate as the precursors enhanced the reduction and oxygen storage capacity of the catalysts, improved oxygen mobility, enriched the chemical functional groups on the catalyst surface, and provided more recyclable active sites. Furthermore, the comparison of the fresh and spent catalyst curves confirmed the excellent structural stability of the Cu/Mn-NN catalyst and the enrichment of oxygen intermediate species on the catalyst surface. XPS analysis indicated that Cu, Mn, and O elements of the catalysts were mainly in the form of Cu\u003csup\u003e2+\u003c/sup\u003e, Mn\u003csup\u003e3+\u003c/sup\u003e, and lattice oxygen O\u003csub\u003eα\u003c/sub\u003e, respectively. Notably, the Mn\u003csup\u003e3+\u003c/sup\u003e ion content of the Cu/Mn-NN catalyst was as high as 70.5%, and the ratio of O\u003csub\u003eβ\u003c/sub\u003e/O\u003csub\u003eα\u003c/sub\u003e was the highest among all the catalysts tested. This result could be attributed to the catalytic environment created by the nitric acid groups, which enriched the metal cation vacancies in the catalyst and enhanced the catalytic ozone reaction. By utilizing different precursors materials for Cu/Mn catalysts to improve their ozone decomposition activity and stability, this study provides valuable insights into the purification of waste gases generated from oxidation processes such as food processing, healthcare, and water treatment.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions \u003c/strong\u003eHL designed, conducted the experimental work, and analysed and wrote the paper under the supervision of TS. YL and ML helped to analyse the characterization data and conceptualization. BZ supported experiments, characterizations, and conceptualization. PW analysed experimental data. The manuscript was revised through discussion and comments of all the authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding \u003c/strong\u003eThis work is financially supported by grants from the National Natural Science Foundation of China (No. 22078037).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e All the data analyzed during this study are included in this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interes\u003c/strong\u003et The authors declare that they have no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests \u003c/strong\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval \u003c/strong\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eT. Tao, Y. Shi, K.M. Gilbert, X. Liu, Sci. Rep-UK. 12, 4293 (2022). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41598-022-08377-9\u003c/span\u003e\u003cspan address=\"10.1038/s41598-022-08377-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eY. Lu, Z. Wu, X. Pang, H. Wu, B. Xing, J. Li, Q. Xiang, J. Chen, D. Shi, Int. J. Environ. Res. Public Health. 20, 168 (2023). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/ijerph20010168\u003c/span\u003e\u003cspan address=\"10.3390/ijerph20010168\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eX. Li, J. Ma, H. He, J. Environ. Sci. 94, 14 (2020). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jes.2020.03.058\u003c/span\u003e\u003cspan address=\"10.1016/j.jes.2020.03.058\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eC. Guo, Z. Gao, J. Shen, Build. Environ. 158, 302 (2019). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.buildenv.2019.05.024\u003c/span\u003e\u003cspan address=\"10.1016/j.buildenv.2019.05.024\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eM.O. Fadeyi, Sustain. Cities. Soc. 18, 78 (2015). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.scs.2015.05.011\u003c/span\u003e\u003cspan address=\"10.1016/j.scs.2015.05.011\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eK.W. Tham, M.O. Fadeyi, Build. Environ. 88, 55 (2015). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.buildenv.2014.10.014\u003c/span\u003e\u003cspan address=\"10.1016/j.buildenv.2014.10.014\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJ. Jia, P. Zhang, L. Chen, Appl. Catal. B: Environ. 189, 210 (2016). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.apcatb.2016.02.055\u003c/span\u003e\u003cspan address=\"10.1016/j.apcatb.2016.02.055\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eC.J. Weschler, N. Carslaw, Environ. Sci. Technol. 52, 2419 (2018). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1021/acs.est.7b06387\u003c/span\u003e\u003cspan address=\"10.1021/acs.est.7b06387\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eW. Ye, X. Zhang, J. Gao, G. Cao, X. Zhou, X. Su, Sci. Total. Environ. 586, 696 (2017). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.scitotenv.2017.02.047\u003c/span\u003e\u003cspan address=\"10.1016/j.scitotenv.2017.02.047\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eH. Hell\u0026eacute;n, P. Kuronen, H. Hakola, Atmos. Environ. 57, 35 (2012). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.atmosenv.2012.04.019\u003c/span\u003e\u003cspan address=\"10.1016/j.atmosenv.2012.04.019\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eC.C. Lin, C.Y. Chao M.Y. Liu, J. Ind. Eng. Chem. 16, 140 (2010). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jiec.2010.01.005\u003c/span\u003e\u003cspan address=\"10.1016/j.jiec.2010.01.005\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eC. Subrahmanyam, D.A. Bulushev, L. Kiwi-Minsker, Appl. Catal. B: Environ. 61, 98 (2005). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.apcatb.2005.04.013\u003c/span\u003e\u003cspan address=\"10.1016/j.apcatb.2005.04.013\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eR. Cao, L. Li, P. Zhang, L. Gao, S. Rong, Environ. Sci-Nano. 8, 1628 (2021). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1039/D1EN00149C\u003c/span\u003e\u003cspan address=\"10.1039/D1EN00149C\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eK.C. Cho, K.C. Hwang, T. Sano, K. Takeuchi, S. Matsuzawa, J. Photoch. Photobio. A. 161, 155 (2004). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S1010-6030(03)00287-9\u003c/span\u003e\u003cspan address=\"10.1016/S1010-6030(03)00287-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eH. Liu, S. Liu, B. Xue, Z. Lv, Z. Meng, X. Yang, T. Xue, Q. Yu, K. He, Atmos. Environ. 173, 223 (2018). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.atmosenv.2017.11.014\u003c/span\u003e\u003cspan address=\"10.1016/j.atmosenv.2017.11.014\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eM. Haruta, Catal. Today. 36, 153 (1997). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S0920-5861(96)00208-8\u003c/span\u003e\u003cspan address=\"10.1016/S0920-5861(96)00208-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eM. Haruta, M.Dat\u0026eacute;, Appl. Catal. A: Gen. 222, 427 (2001). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S0926-860X(01)00847-X\u003c/span\u003e\u003cspan address=\"10.1016/S0926-860X(01)00847-X\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZ. Hao, D. Cheng, Y. Guo, Y. Liang, Appl. Catal. B: Environ. 33, 217 (2001). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S0926-3373(01)00172-2\u003c/span\u003e\u003cspan address=\"10.1016/S0926-3373(01)00172-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eX. Li, G. He, J. Ma, X. Shao, Y. Chen, H. He, Environ. Sci. Technol. 55, 16143 (2021). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1021/acs.est.1c05765\u003c/span\u003e\u003cspan address=\"10.1021/acs.est.1c05765\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eH. Touati, A. Mehri, F. Karouia, F. Karouia, F. Richard, C. Batiot-Dupeyrat, S. Daniele, J.M. Clacens, Catalysts. 12, 448 (2022). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/catal12040448\u003c/span\u003e\u003cspan address=\"10.3390/catal12040448\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eC.L. Chang, T.S. Lin, React. Kinet. Catal. L. 86, 91 (2005). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s11144-005-0299-x\u003c/span\u003e\u003cspan address=\"10.1007/s11144-005-0299-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZ. Xu, W. Yang, W. Si, J. Chen, Y. Peng, J. Li, J. Hazard. Mater. 420, 126641 (2021). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jhazmat.2021.126641\u003c/span\u003e\u003cspan address=\"10.1016/j.jhazmat.2021.126641\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eL. Zhang, S. Wang, L. Lv, Y. Ding, D. Tian, S. Wang, Langmuir. 37, 1410 (2021). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1021/acs.langmuir.0c02841\u003c/span\u003e\u003cspan address=\"10.1021/acs.langmuir.0c02841\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eL. Zhang, S. Wang, C. Ni, M. Wang, S. Wang, Chem. Eng. Sci. 229, 116011 (2021). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ces.2020.116011\u003c/span\u003e\u003cspan address=\"10.1016/j.ces.2020.116011\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eD. Li, B. Cen, C. Fang, X. Leng, W. Wang, Y. Wang, J. Chen, M. Luo, New. J. Chem. 45, 561 (2021). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1039/D0NJ04876C\u003c/span\u003e\u003cspan address=\"10.1039/D0NJ04876C\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eA.S. Azhariyah, A. Pradyasti, S. Bismo, IOP Conf. Ser.: Earth Environ. Sci. 105, 012012 (2018). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1088/1755-1315/105/1/012012\u003c/span\u003e\u003cspan address=\"10.1088/1755-1315/105/1/012012\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eS. Gong, J. Chen, X. Wu, N. Han, Y. Chen, Catal. Commun. 106, 25 (2018). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.catcom.2017.12.003\u003c/span\u003e\u003cspan address=\"10.1016/j.catcom.2017.12.003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eS. Gong, X. Wu, J. Zhang, N. Han, Y. Chen, CrystEngComm. 20, 3096 (2018). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1039/C8CE00203G\u003c/span\u003e\u003cspan address=\"10.1039/C8CE00203G\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eS. Gong, A. Wang, Y. Wang, H. Liu, N. Han, Y. Chen, ACS Appl. Nano Mater. 3, 597 (2019). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1021/acsanm.9b02143\u003c/span\u003e\u003cspan address=\"10.1021/acsanm.9b02143\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJ. Jia, W. Yang, P. Zhang, J. Zhang, Appl. Catal. A: Gen. 546, 79 (2017). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.apcata.2017.08.013\u003c/span\u003e\u003cspan address=\"10.1016/j.apcata.2017.08.013\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eB. Dhandapani, S.T. Oyama, Appl. Catal. B: Environ. 11, 129 (1997). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S0926-3373(96)00044-6\u003c/span\u003e\u003cspan address=\"10.1016/S0926-3373(96)00044-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eC. Wang, J. Ma, F. Liu, H. He, R. Zhang, J. Phys. Chem. C. 119, 23119 (2015). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1021/acs.jpcc.5b08095\u003c/span\u003e\u003cspan address=\"10.1021/acs.jpcc.5b08095\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZ. Lian, J. Ma, H. He. Catal. Commun. 59, 156 (2015). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.catcom.2014.10.005\u003c/span\u003e\u003cspan address=\"10.1016/j.catcom.2014.10.005\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZ.B. Sun, Y.N. Si, S.N. Zhao, Q.Y. Wang, S.Q. Zang, J. Am. Chem. Soc. 143, 5150 (2021). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1021/jacs.1c01027\u003c/span\u003e\u003cspan address=\"10.1021/jacs.1c01027\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eH. Liang, K. Zhang, Q. Zheng, Q. Wang, H. Huang, L. Wang, Res Chem Intermed. 48, 4929 (2022). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s11164-022-04843-1\u003c/span\u003e\u003cspan address=\"10.1007/s11164-022-04843-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eY. Liu, P. Zhang. Appl. Catal. A: Gen. 530, 102 (2017). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.apcata.2016.11.028\u003c/span\u003e\u003cspan address=\"10.1016/j.apcata.2016.11.028\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eY. Yang, S. Zhang, S. Wang, K. Zhang, H. Wang, J. Huang, S. Deng, B. Wang, Y. Wang, G. Yu, Environ. Sci. Technol. 49, 4473 (2015). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1021/es505232f\u003c/span\u003e\u003cspan address=\"10.1021/es505232f\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eY. Xie, Y. Yu, X. Gong, Y. Guo, Y. Guo, Y. Wang, G. Lu, CrystEngComm. 17,3005 (2015). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1039/C5CE00058K\u003c/span\u003e\u003cspan address=\"10.1039/C5CE00058K\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eY. Yang, J. Huang, S. Wang, S. Deng, B. Wang, G. Yu, Appl. Catal. B: Environ. 142, 568 (2013). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.apcatb.2013.05.048\u003c/span\u003e\u003cspan address=\"10.1016/j.apcatb.2013.05.048\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e .\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eH. Sun, Z. Liu, S. Chen, X. Quan, Chem. Eng. J. 270, 58 (2015). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.cej.2015.02.017\u003c/span\u003e\u003cspan address=\"10.1016/j.cej.2015.02.017\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eX. Li, J. Ma, C. Zhang, R. Zhang, H. He, J. Environ. Sci., 80, 159 (2019). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jes.2018.12.008\u003c/span\u003e\u003cspan address=\"10.1016/j.jes.2018.12.008\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eR. Cao, P. Zhang, Y. Liu, X. Zheng, Appl. Surf. Sci. 495, 143607 (2019). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.apsusc.2019.143607\u003c/span\u003e\u003cspan address=\"10.1016/j.apsusc.2019.143607\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eS.K. Shinde, D.P. Dubal, G.S. Ghodake, P. Gomez-Romero, S. Kim, V.J. Fulari, RSC ADV. 5, 30478 (2015). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1039/C5RA01093D\u003c/span\u003e\u003cspan address=\"10.1039/C5RA01093D\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eS. Wang, Y. Zhu, Y. Zhang, B. Wang, H. Yan, W. Liu, Y. Lin, Nanoscale. 12, 12817 (2020). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1039/D0NR02796K\u003c/span\u003e\u003cspan address=\"10.1039/D0NR02796K\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZ. Zeng, P. Sun, J. Zhu, X. Zhu, Surf. Interfaces. 8, 73(2017). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.surfin.2017.04.011\u003c/span\u003e\u003cspan address=\"10.1016/j.surfin.2017.04.011\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eT. Zhou, A. Xie, Q. Wang, X. Li, Z. Zhu, W. Zhang, Y. Tao, S. Luo, Environ. Sci. Pollut. Res. 27, 43150 (2020). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s11356-020-10190-8\u003c/span\u003e\u003cspan address=\"10.1007/s11356-020-10190-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eW. Hong, M. Shao, T. Zhu, H. Wang, Y. Sun, F. Shen, X. Li, Appl. Catal. B: Environ. 274, 119088 (2020). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.apcatb.2020.119088\u003c/span\u003e\u003cspan address=\"10.1016/j.apcatb.2020.119088\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eL. Tao, G. Zhao, P. Chen, Z. Zhang, Y. Liu, Y. Lu, Chemcatchem. 11, 1131 (2019). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/cctc.201801401\u003c/span\u003e\u003cspan address=\"10.1002/cctc.201801401\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eX. Li, J. Ma, L. Yang, G. He, C. Zhang, R. Zhang, H. He, Environ. Sci. Technol. 52 12685 (2018). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1021/acs.est.8b04294\u003c/span\u003e\u003cspan address=\"10.1021/acs.est.8b04294\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJ. Chen, D. Yan, Z. Xu, X. Chen, X. Chen, W. Xu, H. Jia, J. Chen, Environ. Sci. Technol. 52 4728 (2018). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1021/acs.est.7b06039\u003c/span\u003e\u003cspan address=\"10.1021/acs.est.7b06039\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\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":"research-on-chemical-intermediates","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"rint","sideBox":"Learn more about [Research on Chemical Intermediates](http://link.springer.com/journal/11164)","snPcode":"11164","submissionUrl":"https://submission.nature.com/new-submission/11164/3","title":"Research on Chemical Intermediates","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Cu/Mn catalyst, precursor, ozone decomposition, post-reaction characterization","lastPublishedDoi":"10.21203/rs.3.rs-2850692/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2850692/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eA simple co-precipitation method was utilized to synthesize Cu/Mn catalysts with different physiochemical properties for high humidity ozone decomposition. The catalysts were then tested for their activity and stability in decomposing ozone, and their physical and chemical properties were analyzed through various characterization techniques. Furthermore, the characterization after stability testing provided insights into the internal mechanism of the ozone reaction process. The Cu/Mn-NN catalyst demonstrated excellent ozone decomposition activity in the temperature of 25\u0026ndash;100\u0026deg;C, maintaining the conversion above 91% for continuous ozone decomposition for 12 hours at room temperature, the relative humidity (RH) of 85%, and the weight space velocity of 300 L\u0026middot;g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u0026middot;h\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. Characterization revealed that the Cu/Mn-NN catalyst, exhibited the larger specific surface area, better reducibility and oxygen storage capacity, richer surface functional groups and oxygen vacancies. Additionally, characterization after the stability test confirmed the accumulation of oxygen intermediate species on the catalyst surface. The findings also suggested that the catalytic environment created by nitrate precursors played a vital role in preventing catalyst particle aggregation, facilitating electron transfer within the catalyst, ensuring uninterrupted migration of lattice oxygen, and timely regeneration of oxygen vacancies.\u003c/p\u003e","manuscriptTitle":"Effect of different structure of Cu/Mn catalysts on ozone decomposition ability","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-04-27 21:41:33","doi":"10.21203/rs.3.rs-2850692/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2023-06-23T06:46:48+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2023-06-13T11:01:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"88610b3f-0d54-4b74-9991-f452a20773fa","date":"2023-06-02T15:29:41+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2023-05-17T09:21:54+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"d690fc1a-cfd8-49dc-9666-430d494ef4b2","date":"2023-05-15T04:14:44+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2023-05-04T08:45:19+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2023-04-24T15:35:40+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2023-04-24T15:35:39+00:00","index":"","fulltext":""},{"type":"submitted","content":"Research on Chemical Intermediates","date":"2023-04-23T10:05:30+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"research-on-chemical-intermediates","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"rint","sideBox":"Learn more about [Research on Chemical Intermediates](http://link.springer.com/journal/11164)","snPcode":"11164","submissionUrl":"https://submission.nature.com/new-submission/11164/3","title":"Research on Chemical Intermediates","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"d801b3c2-8bf1-4a09-ab6d-bbe15adc0028","owner":[],"postedDate":"April 27th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2023-10-16T21:56:41+00:00","versionOfRecord":{"articleIdentity":"rs-2850692","link":"https://doi.org/10.1007/s11164-023-05078-4","journal":{"identity":"research-on-chemical-intermediates","isVorOnly":false,"title":"Research on Chemical Intermediates"},"publishedOn":"2023-07-29 21:46:10","publishedOnDateReadable":"July 29th, 2023"},"versionCreatedAt":"2023-04-27 21:41:33","video":"","vorDoi":"10.1007/s11164-023-05078-4","vorDoiUrl":"https://doi.org/10.1007/s11164-023-05078-4","workflowStages":[]},"version":"v1","identity":"rs-2850692","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2850692","identity":"rs-2850692","version":["v1"]},"buildId":"-HB7Z8yhvgn0wM9Nzuekk","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}

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