Search Results (112)

Co–Mg–Fe oxide systems are promising candidates for thermally stable deep oxidation catalysts because they potentially combine redox-active cobalt and iron components with stabilizing magnesium-containing phases. In this work, phase formation in a Co–Mg–Fe oxide system obtained by thermal decomposition of nitrate precursors with a Co:Mg:Fe ratio of 1:1:1 was studied over a wide range of heat-treatment temperatures from 400 to 1300 °C. The samples were characterized by X-ray diffraction, Mössbauer spectroscopy, Fourier-transform infrared spectroscopy, scanning electron microscopy with energy-dispersive X-ray spectroscopy mapping, and temperature-programmed oxygen desorption. The results show that the system undergoes staged phase evolution. At 400 °C, α-Fe₂O₃, including Mg-modified hematite-like states, cobalt-containing spinel phases, and a rocksalt oxide phase, is formed. Starting from 550 °C, a mixed ferrite spinel phase appears and its content increases with temperature. The transition through 800–900 °C is accompanied by decomposition of cobalt-containing spinels, a sharp change in the inversion parameter of the mixed ferrite, and formation of a stable high-temperature combination of ferrite spinel and rocksalt oxide solid solution. Oxygen desorption is most pronounced for the low- and medium-temperature samples and decreases strongly after high-temperature treatment. The obtained results provide the basis for the design of thermally stable Co–Mg–Fe oxide catalysts for deep oxidation processes. Full article

Methane combustion over palladium-based catalysts is a critical process for reducing greenhouse gas emissions from lean-burn engines and natural gas installations, yet the role of oxide support in controlling both the population and the intrinsic reactivity of Pd active centres remains incompletely understood. In this work, Pd catalysts at two series of higher and lower loading were prepared on five oxide supports—Al₂O₃, CeO₂, SiO₂, TiO₂, and ZrO₂—and characterised by a complementary suite of techniques including SEM-EDX, XRD, BET, AAS, in situ CO-FTIR, DRIFTS with methanol as a probe molecule, and Raman spectroscopy. Catalytic activity testing revealed the order Pd/CeO₂ > Pd/ZrO₂ > Pd/Al₂O₃ > Pd/TiO₂ > Pd/SiO₂. In situ CO-FTIR site quantification showed that active site density spans nearly an order of magnitude across the series, with Pd/CeO₂ reaching 105.44 µmol g⁻¹ and Pd/Al₂O₃ only 11.63 µmol g⁻¹. Turnover frequency analysis revealed a striking inversion: Pd/Al₂O₃ exhibited the highest TOF (0.1327 s⁻¹), approximately six times greater than Pd/CeO₂ (0.0226 s⁻¹). DRIFTS/methanol profiling demonstrated that CeO₂ and ZrO₂ expose cooperative redox and basic centres that promote methane activation, while SiO₂ supports only weakly bound methoxy species, consistent with its lowest activity. These results establish that the oxide support simultaneously governs Pd dispersion—and hence site density—and the electronic environment of each Pd centre, thereby modulating intrinsic reactivity. High specific surface area alone does not guarantee catalytic performance, and rational support selection is therefore the decisive lever for optimising methane combustion catalysts at ultra-low Pd loadings. In all, our findings provide a quantitative, molecular-level framework that disentangles support-controlled site density from intrinsic site reactivity under identical reaction conditions. By combining in situ CO-FTIR, DRIFTS, and Raman spectroscopy with kinetic analysis on well-defined, high-purity oxide supports, this work transforms previously qualitative “support effects” in Pd-catalysed methane combustion into predictive structure–activity relationships. Full article

The electrochemical performance of hydrogen compressors (EHCs) depends critically on the hierarchical microstructure of their catalyst layers (CLs), where platinum, carbon, and ionomer phases govern coupled charge and mass transport across nanometric (Nano) and mesoporous (Meso) scales, the latter characterized by agglomerate and pore phases. This work presents an experimental–computational framework to establish quantitative microstructure–transport–performance relationships in EHC CLs. CLs were fabricated by electrospray deposition on Nafion^® 117 membranes and characterized by scanning electron microscopy, from which 33 representative Meso MCs were extracted and used to assemble an EHC cell for experimental polarization curves. Statistically equivalent Nano MCs resolved phase connectivity within the agglomerate phase and determined the effective catalyst area from neighboring phase configurations. Effective transport coefficients for electronic conductivity, protonic conductivity, and H₂ diffusivity were computed via the finite volume method and multiscale-coupled into an analytical polarization model. Electronic and protonic conductivities are controlled by conductive-phase connectivity at the Nano scale, while H₂ diffusivity is governed by the pore fraction and spatial distribution at the Meso scale, with variations exceeding three orders of magnitude. Multiscale transport coupling factors obtained via inverse calibration reduced model–experiment discrepancies to 0.05 V, validating the framework for EHC electrode design. Full article

Fe–carbon catalysts (FCCs) are extensively used for persulfate activation in advanced oxidation processes (PS-AOPs), an approach regarded as an efficient and cost-effective strategy for removing emerging contaminants (ECs). However, the quantitative structure–activity relationship between the degradation efficiency of ECs with diverse molecular characteristics and the microstructure of FCCs has not been clearly elucidated. This hinders the widespread practical implementation of FCCs. Herein, density functional theory (DFT)-derived molecular-descriptor-assisted machine learning models were employed to accurately predict the reaction rate constants for EC degradation in FCC-PS AOPs, mainly focusing on three aspects: performance prediction, operating condition optimization and mechanism interpretation. Additionally, DFT-derived descriptors are integrated with fabrication and operational parameters to facilitate the generative design of FCCs. The excellent fitting performance of the overall XGB model in predicting the reaction constants for EC degradation (Test R² = 0.813) highlights the notable advantages of customized hyperparameter tuning for improving predictive accuracy. Subsequently, the submodels trained using different EC clusters (derived from t-SNE and K-means clustering methods) can offer specific strategies for selecting optimal parameters of FCC-PS AOPs that target ECs with distinct properties. The interpretability of the model was improved by using SHAP values and partial-dependence plots to clarify the internal relationships of the ML “black box”. Overall, a feasible and generalizable ML model is proposed to facilitate a paradigm shift in the inverse design of FCCs for the degradation of specific ECs. Full article

Ventilation air methane (VAM) has an extremely low concentration, making its abatement exceptionally challenging. Catalytic oxidation offers a promising route for VAM treatment, but industrial application requires integrated catalysts with high activity and efficient mass transfer. In this study, a novel straight-channel NiO/CeO₂ ceramic reactor was fabricated via mesh-assisted phase inversion, with NiO content systematically optimized to screen the optimal ratio. The 60 wt% NiO was the optimal composition, exhibiting excellent VAM oxidation performance. Brunauer–Emmett–Teller (BET) analysis confirmed that this optimal ratio yielded the largest specific surface area. Furthermore, H₂-temperature-programmed reduction (H₂-TPR) and X-ray photoelectron spectroscopy (XPS) confirmed that this optimal ratio facilitated the formation of abundant NiO–CeO₂ active interfaces, effectively inducing surface Ce³⁺ species and oxygen vacancies. These merits significantly enhanced the reactor’s oxygen adsorption capacity and redox properties, thus realizing efficient methane activation in catalytic oxidation. Moreover, the optimal reactor successfully passed 10 thermal cycle tests, further verifying the thermal stability of the catalytic structure. In addition, it exhibited outstanding long-term stability during a 100 h test, with no carbon deposition or active phase sintering observed. This work develops an optimized straight-channel NiO/CeO₂ ceramic reactor and offers a practical and scalable design strategy for VAM oxidation. Full article

Monolithic ceramic catalysts are a key technology for the industrial treatment of coal mine ventilation air methane (VAM). The preparation of straight-channel NiO/CeO₂ monolithic ceramic catalysts via phase inversion addresses critical bottlenecks for industrial VAM abatement. However, high-temperature sintering leads to irreversible NiO agglomeration and coarsening, severely reducing catalytic activity. In this study, an in situ reduction–oxidation reconstruction method is developed to regenerate sinter-degraded NiO. The reconstructed catalyst increases methane conversion from below 70% after sintering to over 95% at 550 °C and achieves full conversion at 600 °C. The catalyst maintains near 100% conversion during 400 h of continuous operation at 600 °C and shows no performance degradation over 15 thermal cycles. Moreover, the reconstructed catalyst exhibits excellent steam tolerance with fully reversible deactivation. The reconstructed catalyst presents a refined porous structure with BET surface area rising from 4.5 to 11.4 m² g⁻¹, an elevated Ni³⁺/Ni²⁺ ratio (1.47 to 1.97), a higher surface adsorbed oxygen proportion (36.8% to 48.7%) and significantly strengthened NiO-CeO₂ interfacial interaction. This work provides a facile and efficient in situ regeneration strategy, greatly enhancing the VAM oxidation activity and stability of sinter-degraded monolithic ceramic catalysts. Full article

The Lewis basic catalysts were susceptible to poisoning during the activation of peroxymonosulfate, resulting in their transformation into spent catalysts and subsequent secondary environmental contamination. In this work, the chemical constitution of the catalyst’s surface during both the deactivation and regeneration processes was intensively tracked. The mechanistic studies revealed that the reversible bonding of adsorbed hydroxyl groups generated from peroxymonosulfate activation with Lewis basic carbon atoms adjacent to pyridinic nitrogen was identified as the intrinsic mechanism responsible for the catalyst regeneration, accompanied by the reappearance of Lewis basic sites. Following high-temperature or sodium borohydride reduction, the activity of the catalysts was restored to over 90% of the initial activity, enabling the spent catalysts to be reused multiple times. Catalyst deactivation corresponded to an increase in the C–OH content from 24.3% to 35.2%, whereas regeneration reduced it to 25.16%. Furthermore, a strong inverse correlation was observed between the surface hydroxyl density and the catalytic activity. The study elucidates the deactivation and regeneration mechanisms of Lewis basic catalysts at the atomic scale, paving the way for durable applications in advanced oxidation processes. Full article

Oxidative dry reforming of methane (ODRM) in a membrane reactor can become the basis for creating an energy-efficient process for converting greenhouse gases into a sought-after chemical raw material for gas chemistry. The process was carried out in a distribution mode in a reactor with a membrane porous catalyst (MPC) at a temperature of 850 °C. The reagents CH₄ and CO₂ were supplied to the MPC through a volume of retentate, and O₂ mixed with N₂ through a volume of permeate. The mixture of reaction products was removed from the shell side. In the experiment, the effect of the O₂/CO₂ ratio on the conversion of CH₄, CO₂ and O₂, as well as on the thermal effect of the process, was established. When oxygen enters the reactor during dry reforming of methane (DRM), the temperature inversion in the volumes of retentate and permeate occurs, as well as a decrease in electricity consumption in the resistor furnace. The observed effects of the ODRM process in MPC were interpreted using the hypothesis of active mass transfer occurring in pore channels. It is assumed that part of the carbon deposits in MPC will be gasified by oxygen. Full article

Low-temperature methanation technology offers a promising pathway for carbon recycling and sustainable energy storage by enabling near-equilibrium CO₂ conversion under atmospheric pressure. However, efficiently activating CO₂ at low temperatures remains a significant challenge due to the kinetic limitations of hydrogenation intermediates. We construct a composite oxide–metal interface structure by anchoring highly dispersed CeCrO_x nanoclusters onto metallic nickel via an ion-exchange method. This catalyst exhibits superior activity compared to conventional Ni/oxide catalysts with identical composition. Under atmospheric pressure at 220 °C, it achieves nearly 80% CO₂ conversion with over 99% methane selectivity and maintains excellent catalytic performance and structural stability during a 240-h continuous test. Systematic characterizations, including high-resolution transmission electron microscopy, X-ray photoelectron spectroscopy, CO₂ temperature-programmed desorption, and in situ DRIFTS reflectance infrared Fourier-transform spectroscopy, reveal that the synergistic modification by CeO₂ and Cr₂O₃ not only optimizes the electronic structure of Ni to promote CO₂ adsorption and activation, but also enhances H₂ dissociation and intermediate conversion by regulating oxygen vacancy concentration and alkaline site distribution. Mechanistic studies indicate that the reaction follows a synergistic mechanism dominated by the formate pathway and assisted by the CO pathway. Moreover, the interfacial structure effectively stabilizes active sites and inhibits carbon deposition from CH₄ decomposition. This study provides a universal and effective strategy for designing Ni-based CO₂ conversion catalysts suited for mild reaction conditions and characterized by high energy efficiency. Full article

The selective transformation of biomass-derived feedstocks into value-added chemicals via targeted C-O bond cleavage remains challenging due to the presence of multiple reducible bonds and typically low catalytic selectivity. Herein, we report a robust non-noble metal CoCe catalyst for the selective ring-opening hydrogenolysis of 2-furoic acid (2-FA), an industrialized biomass-derived platform molecule, to 5-hydroxypentanoic acid (5-HVA) and its derivatives, which have potential applications as fuel additives. The optimized 90CoCe catalyst with inverse phase demonstrates superior catalytic performance, achieving a total yield of more than 85% for 5-HVA and its derivatives under mild reaction conditions (130 °C, 2 MPa H₂). Extensive characterizations reveal that the inverse-phase 90CoCe catalyst possesses abundant oxygen vacancies at the Co-CeO_x interface, with the formation of Co-Ov-Ce interfacial species. The interfacial Co-Ov-Ce sites serve as specific adsorption centers for the 2-FA molecule, orienting it into a titled adsorption configuration that is highly favorable for the C₂-O₁ bond cleavage in the furan ring. Meanwhile, adjacent Co⁰ sites efficiently dissociate hydrogen into active hydrogen species for the hydrogenolysis of the C₂-O₁ bond to form ring-opening products. The synergistic balance between the hydrogenation Co⁰ sites and the interfacial Co-Ov-Ce adsorption sites is crucial to the high catalytic activity and selectivity of the CoCe catalyst. Moreover, the 90CoCe catalyst maintains stable catalytic performance during a 40 h continuous test in a fixed-bed reactor, demonstrating its great potential for industrial applications. Full article

Catalytic pyrolysis (CP) of biomass is a promising method for producing sustainable hydrogen because lignocellulosic biomass is widely available, renewable, and approximately carbon-neutral. CP of biomass is influenced by complex, interdependent process parameters, making optimization challenging and time-consuming using traditional methods. This study investigated a two-stage machine learning (ML) framework fortified with Bayesian optimization to enhance hydrogen production from CP. The ML models were used to classify and predict hydrogen yield using a dataset of 306 points with 14 input features. The classification stage identified conditions favorable for good hydrogen yield, while the regression model (second stage) quantitatively predicted hydrogen yield. The random forest classifier and regressor demonstrated superior capabilities, achieving R² scores of 1.0 and 0.8, respectively. The model demonstrated strong agreement with experimental data and effectively captured the key factors driving hydrogen production. Shapley Additive exPlanation (SHAP) identified temperature and catalyst properties (nickel loading) as the most influential parameters. The inverse analysis framework validated the model’s ability to determine optimal conditions for predicting targeted hydrogen yields by comparing it to experimental data reported in the literature. This AI-driven approach provides a scalable and data-efficient tool for optimizing processes in sustainable hydrogen production. Full article

The catalytic oxidation of CO is of great technological importance for the treatment of vehicle and industrial exhaust gases. PtCe-catalysts of low-temperature CO oxidation were prepared by the impregnation of ZSM-5 zeolite (Z) with aqueous solutions of H₂PtCl₆ and Ce(NO₃)₃, varying the order of metal deposition and thermal treatment conditions. The relationships between structure transformations and catalyst performance were established based on the SEM, TEM, EDX, DRIFT, and X-ray photoelectron spectroscopies data. For the Ce/Pt/Z sample, in which cerium was deposited after platinum, the 100% CO conversion temperature was only 120 °C. The inverse deposition sequence of metals (Pt/Ce/Z catalyst) resulted in CO oxidation at a higher temperature that can be decreased to 110 °C by redox treatment. The prepared catalysts were also active in the CO oxidation in excess hydrogen (PROX) but were not selective enough. However, the activity of PtCe-modified ZSM-5 enhanced greatly in the repeated cycles of CO oxidation (TOX) after testing in PROX. It is suggested that enhancing the interaction between Pt and Ce is a key factor in tuning the catalyst performance. The 0.2 wt.% Pt catalysts showed the best performance and provided complete CO conversion at 95 °C, which is a pronounced result for low-loaded Pt catalysts. Full article

MnCo₂O₄ and CoMn₂O₄ were successfully synthesized on a stainless-steel substrate using the hydrothermal method. The structural and morphological characteristics of the spinel samples were investigated using X-ray diffraction (XRD) and scanning electron microscopy (SEM). The electronic and vibrational properties were studied through X-ray photoelectron spectroscopy (XPS) and Fourier transform infrared spectroscopy (FTIR). Electrochemical properties were also evaluated using a three-electrode system associated with an electrochemical workstation. The studies revealed that the inversion of Mn and Co cation distribution between the spinel structure sites not only modifies the crystal structure and morphology but also alters specific functional properties. MnCo₂O₄ crystallized in a cubic spinel phase, exhibiting spherical particles, pronounced microstrain, and stronger metal–oxygen bonding. In contrast, CoMn₂O₄ adopted a tetragonal spinel structure with rod-like crystallites, lower microstrain, and more flexible bonding environments. Electrochemical impedance spectroscopy further revealed distinct charge-transfer dynamics, indicating differences in surface redox activity. This comparative analysis elucidates how cation site occupancy governs the performance of the synthesized spinel oxides and underscores their potential as efficient catalysts or catalyst supports for redox and energy-related applications. Full article

This study systematically investigated the influence of catalyst formulation parameters (precious metal loading and Pt/Pd ratio) in diesel oxidation catalysts (DOCs)+catalyzed diesel particulate filter (CDPF)+selective catalytic reduction (SCR) on gaseous pollutant emissions from diesel engines. Results indicate that under varying conditions, the impact of catalyst formulation on DOC system performance—such as temperature rise characteristics, pressure drop, and brake specific fuel consumption (BSFC)—remains limited. Notably, exhaust temperature exerts a decisive influence on carbon monoxide (CO) and hydrocarbon (HC) conversion efficiency, significantly outweighing the impact of exhaust flow rate. Increasing precious metal loading and Pt proportion markedly optimizes CO and HC ignition characteristics by lowering ignition temperatures. However, under high-load conditions, conversion efficiencies across different catalyst formulations tend to converge. Specifically, under low-load conditions, a competitive adsorption mechanism between CO and HC causes HC conversion efficiency to exhibit an inverse trend relative to CO. Furthermore, higher precious metal loading and Pt content significantly enhance the catalyst’s NO₂ formation capacity at equilibrium temperatures, while higher Pd content contributes to improved thermal stability. Higher precious metal loading and Pt content increase nitrogen oxides (NO_x) conversion efficiency. CDPF possesses the ability to further oxidize NO. Full article

This study presents the development of Cu-doped NiMo/TiO₂ photoelectrocatalysts for simultaneous green hydrogen production and pharmaceutical pollutant removal under simulated solar irradiation. The catalysts were synthesized via wet impregnation (15 wt.% total metal loading with 0.6 wt.% Cu) and thermally treated at 400 °C and 900 °C to investigate structural transformations and catalytic performance. Comprehensive characterization (XRD, BET, SEM, XPS) revealed phase transitions, enhanced crystallinity, and redistribution of redox states upon Cu incorporation, particularly the formation of NiTiO₃ and an increase in oxygen vacancies. Crystallite sizes for anatase, rutile, and brookite ranged from 21 to 47 nm at NiMoCu400, while NiMoCu900 exhibited only the rutile phase with 55 nm crystallites. BET analysis showed a surface area of 44.4 m²·g⁻¹ for NiMoCu400, and electrochemical measurements confirmed its higher electrochemically active surface area (ECSA, 2.4 cm²), indicating enhanced surface accessibility. In contrast, NiMoCu900 exhibited a much lower BET surface area (1.4 m²·g⁻¹) and ECSA (1.4 cm²), consistent with its inferior photoelectrocatalytic performance. Compared to previously reported binary NiMo/TiO₂ systems, the ternary NiMoCu/TiO₂ catalysts demonstrated significantly improved hydrogen production activity and more efficient photoelectrochemical degradation of paracetamol. Specifically, NiMoCu400 showed an anodic peak current of 0.24 mA·cm⁻² for paracetamol oxidation, representing a 60% increase over NiMo400 and a cathodic current of −0.46 mA·cm⁻² at −0.1 V vs. RHE under illumination, nearly six times higher than the undoped counterpart (–0.08 mA·cm⁻²). Mott–Schottky analysis further revealed that NiMoCu400 retained n-type behavior, while NiMoCu900 exhibited an unusual inversion to p-type, likely due to Cu migration and rutile-phase-induced realignment of donor states. Despite its higher photosensitivity, NiMoCu900 showed negligible photocurrent, confirming that structural preservation and surface redox activity are critical for photoelectrochemical performance. This work provides mechanistic insight into Cu-mediated photoelectrocatalysis and identifies NiMoCu/TiO₂ as a promising bifunctional platform for integrated solar-driven water treatment and sustainable hydrogen production. Full article