"Atomic Topping" of MnOx on Al2O3 to Create Electron-Rich, Aperiodic, Lattice Oxygens that Resemble Noble Metals for Catalytic Oxidation.

Enhancing the catalytic oxidation activity of traditional transition-metal oxides to rival that of noble metals has been a prominent focus in the field of catalysis. However, existing synthesis strategies that focus on controlling the electronic states of metal centers have not yet fully succeeded in achieving this goal. Our current research reveals that manipulating the electronic states of oxygen centers can yield unexpected results. By creating electron-rich, aperiodic lattice oxygens through atomic topping of MnOx, we have produced a catalyst with performance that closely resembles supported Pt. Spherical aberration-corrected transmission electron microscopy and X-ray absorption spectra have confirmed that the atomic topping of the MnOx layer on Al2O3 can form an aperiodic arrangement oxide structure. Near-ambient pressure X-ray photoelectron spectroscopy, in situ diffuse reflectance infrared Fourier transform spectroscopy, reaction kinetics test, and theoretical calculations demonstrated that this structure significantly increases the electron density around the oxygen in MnOx, shifting the activation center for CO adsorption from Mn to O, thereby exhibiting catalytic activity and stability close to that of the precious metal Pt. This study presents a fresh perspective on designing efficient oxide catalysts by targeting electron-rich anionic centers, thereby deepening the understanding of how these centers can be altered to enhance catalytic efficiency in oxidation reactions.

Transient-State Self-Bipolarized Organic Frameworks of Single Aromatic Units for Natural Sunlight-Driven Photosynthesis of H2O2.

Constructing π-conjugated polymer structures through covalent bonds dominates the design of organic framework photocatalysts, which significantly depends on the selection of multiple donor-acceptor building blocks to narrow the optical gap and increase the lifetimes of charge carriers. In this work, self-bipolarized organic frameworks of single aromatic units are demonstrated as novel broad-spectrum-responsive photocatalysts for H2O2 production. The preparation of such photocatalysts is only to fix the aromatic units (such as 1,3,5-triphenylbenzene) with alkane linkers in 3D space. Self-bipolarized aromatic units can drive the H2O2 production from H2O and O2 under natural sunlight, wide pH ranges (3.0-10.0) and natural water sources. Moreover, it can be extended to catalyze the oxidative coupling of amines. Experimental and theoretical investigation demonstrate that such a strategy obeys the mechanism of through-space π-conjugation, where the closely face-to-face overlapped aromatic rings permit the electron and energy transfer through the large-area delocalization of the electron cloud under visible light irradiation. This work introduces a novel design concept for the development of organic photocatalysts, which will break the restriction of conventional through-band π-conjugation structure and will open a new way in the synthesis of organic photocatalysts.

Association between Perceived Stress and Motoric Cognitive Risk Syndrome in an Elderly Population: Rugao Longevity and Aging Study.

INTRODUCTION: Previous studies have indicated a correlation between perceived stress and cognitive decline. However, it remains unknown whether high levels of perceived stress can result in motoric cognitive risk (MCR) syndrome. This study investigated the relationship between perceived stress and MCR in a community-based population. METHODS: The study cohort comprised 852 elderly individuals from the Rugao Longitudinal Aging Cohort. Perceived stress was assessed using the 10-item Perceived Stress Scale (PSS-10), while MCR was defined as the coexistence of subjective memory complaints (SMCs) and slow gait speed. RESULTS: The average age of the study participants is 79.84 ± 4.34 years. The mean score of PSS-10 among participants is 10.32 (range = 0-33; [SD] = 5.71), with a median score of 10.00 (6.00, 14.00). The prevalence of MCR is 9.3%. In the logistic regression analysis, for each 1-SD (5.71) increase in the global PSS-10 score, the risk of MCR increased by 40% (95% CI 1.09-1.80). Additionally, in the aspect of two components of MCR, with a 1-SD increase (5.71) in the global PSS-10 score, there was a 50% (95% CI 1.29-1.75) increase in the risk of SMCs and a 27% (95% CI 1.04-1.55) increase in the risk of slow gait speed. In terms of specific walking speed, there was a reverse correlation between the global PSS-10 score and walking speed (r = -0.14, p < 0.001). CONCLUSIONS: This study provided preliminary evidence that high levels of perceived stress were associated with the risk of MCR in a community-dwelling population.

Ischemic stroke prediction using machine learning in elderly Chinese population: The Rugao Longitudinal Ageing Study.

OBJECTIVE: Compared logistic regression (LR) with machine learning (ML) models, to predict the risk of ischemic stroke in an elderly population in China. METHODS: We applied 2208 records from the Rugao Longitudinal Ageing Study (RLAS) for ischemic stroke risk prediction assessment. Input variables included 103 phenotypes. For 3-year ischemic stroke risk prediction, we compared the discrimination and calibration of LR model and ML methods, where ML methods include Random Forest (RF), Gaussian kernel Support Vector Machines (SVM), Multilayer perceptron (MLP), K-Nearest Neighbors Algorithm (KNN), and Gradient Boosting Decision Tree (GBDT) to develop an ischemic stroke risk prediction model. RESULTS: Age, pulse, waist circumference, education level, ß2-microglobulin, homocysteine, cystatin C, folate, free triiodothyronine, platelet distribution width, QT interval, and QTc interval were significant induced predictors of ischemic stroke. For ischemic stroke prediction, the ML approach was able to tap more biochemical and ECG-related multidimensional phenotypic indicators compared to the LR model, which placed more importance on general demographic indicators. Compared to the LR model, SVM provided the best discrimination and calibration (C-index: 0.79 vs. 0.71, 11.27% improvement in model utility), with the best performance in both validation and test data. CONCLUSION: In a comparison of LR with five ML models, the accuracy of ischemic stroke prediction was higher by combining ML with multiple phenotypes. Combined with other studies based on elderly populations in China, ML techniques, especially SVM, have shown good long-term predictive performance, inspiring the potential value of ML use in clinical practice.

Facile Route to Achieve a Hierarchical CuO/Nickel-Cobalt-Sulfide Electrode for Energy Storage.

Herein, a novel self-supporting CuO/nickel-cobalt-sulfide (NCS) electrode was designed in a two-step electrodeposition technique followed by a calcination process. Three-dimensional copper foam (CF) was exploited as the current collector and spontaneous source for the in situ preparation of the CuO nanostructures, which ensured sufficient deposition space for the subsequent NCS layer, thus forming abundant electrochemical active sites. Such a hierarchical structure is conducive to providing a smooth path for promoting electronic transmission. Therefore, the optimized CuO/NCS electrode exhibits outstanding energy storage capability with extremely superior specific capacitance (Cs) of 7.08 F cm-2 at 4 mA cm-2 and coulombic efficiency of up to 94.83%, as well as excellent cycling stability with capacitance retention of 83.33% after 5000 cycles. The results presented in this work extend our horizons to fabricate novel hierarchical structured electrodes applied to energy storage devices.

Hierarchical Design of CuO/Nickel-Cobalt-Sulfide Electrode by a Facile Two-Step Potentiostatic Deposition.

Herein, a scalable electrodeposition strategy is proposed to achieve hierarchical CuO/nickel-cobalt-sulfide (NCS) electrodes using two-step potentiostatic deposition followed by high-temperature calcination. The introduction of CuO provides support for the further deposition of NSC to ensure a high load of active electrode materials, thus generating more abundant active electrochemical sites. Meanwhile, dense deposited NSC nanosheets are connected to each other to form many chambers. Such a hierarchical electrode prompts a smooth and orderly transmission channel for electron transport, and reserves space for possible volume expansion during the electrochemical test process. As a result, the CuO/NCS electrode exhibits superior specific capacitance (Cs) of 4.26 F cm-2 at 20 mA cm-2 and remarkable coulombic efficiency of 96.37%. Furthermore, the cycle stability of the CuO/NCS electrode remains at 83.05% within 5000 cycles. The multistep electrodeposition strategy provides a basis and reference for the rational design of hierarchical electrodes to be applied in the field of energy storage.

Achieving Self-Supported Hierarchical Cu(OH)2/Nickel-Cobalt Sulfide Electrode for Electrochemical Energy Storage.

Herein, nickel-cobalt sulfide (NCS) nanoflakes covering the surface of Cu(OH)2 nanorods were achieved by a facile two-step electrodeposition strategy. The effect of CH4N2S concentration on formation mechanism and electrochemical behavior is investigated and optimized. Thanks to the synergistic effect of the selected composite components, the Cu(OH)2/NCS composite electrode can deliver a high areal specific capacitance (Cs) of 7.80 F cm-2 at 2 mA cm-2 and sustain 5.74 F cm-2 at 40 mA cm-2. In addition, coulombic efficiency was up to 84.30% and cyclic stability remained 82.93% within 5000 cycles at 40 mA cm-2. This innovative work provides an effective strategy for the design and construction of hierarchical composite electrodes for the development of energy storage devices.

Effect of Annealing Temperature on Electrical Properties of ZTO Thin-Film Transistors.

A high-performance ZnSnO (ZTO) thin-film transistor (TFT) was fabricated, with ZTO deposited by rf magnetron sputtering. XPS was used to analyze and study the effects of different annealing temperatures on the element composition and valence state of ZTO films. Then, the influence mechanism of annealing treatment on the electrical properties of ZTO thin films was analyzed. The results show that, with an increase in annealing temperature, the amount of metal bonding with oxygen increases first and then decreases, while the oxygen vacancy decreases first and then increases. Further analysis on the ratio of Sn2+ is presented. Electrical results show that the TFT annealed at 600 °C exhibits the best performance. It exhibits high saturation mobilities (µSAT) up to 12.64 cm2V-1s-1, a threshold voltage (VTH) of -6.61 V, a large on/off current ratio (Ion/Ioff) of 1.87 × 109, and an excellent subthreshold swing (SS) of 0.79 V/Decade.

Fischer-Tropsch synthesis to olefins boosted by MFI zeolite nanosheets.

Catalytic reactions are severely restricted by the strong adsorption of product molecules on the catalyst surface, where promoting desorption of the product and hindering its re-adsorption benefit the formation of free sites on the catalyst surface for continuous substrate conversion1,2. A solution to this issue is constructing a robust nanochannel for the rapid escape of products. We demonstrate here that MFI zeolite crystals with a short b-axis of 90-110 nm and a finely controllable microporous environment can effectively boost the Fischer-Tropsch synthesis to olefins by shipping the olefin molecules. The ferric carbide catalyst (Na-FeCx) physically mixed with a zeolite promoter exhibited a CO conversion of 82.5% with an olefin selectivity of 72.0% at the low temperature of 260 °C. By contrast, Na-FeCx alone without the zeolite promoter is poorly active under equivalent conditions, and shows the significantly improved olefin productivity achieved through the zeolite promoter. These results show that the well-designed zeolite, as a promising promoter, significantly boosts Fischer-Tropsch synthesis to olefins by accelerating escape of the product from the catalyst surface.

System dynamics modeling of lake water management under climate change.

Lake Urmia, the twentieth largest lake in the world, is the most valuable aquatic ecosystem in Iran. The lake water level has decreased in recent years due to human activities and climate change. Several studies have highlighted the significant roles of climatic and anthropogenic factors on the shrinkage of the lake. Management policies for water resources harvesting must be adopted to adapt to climate change and avoid the consequent problems stemming from the drought affecting Lake Urmia, and rationing must be applied to the upstream water demands. This study analyzes strategies and evaluates their effectiveness in overcoming the Urmia Lake crisis. Specifically, system dynamics analysis was performed for simulating the water volume of Lake Urmia, and the Hadley Centre coupled model was applied to project surface temperature and precipitation for two future periods: 2021-2050 and 2051-2080. Six management scenarios were considered for decreasing the allocation of agricultural water demand corresponding to two options: (1) one-reservoir option (Bukan reservoir only), and (2) six-reservoir option. The net inflow of Urmia Lake was simulated for the two future periods with the IHACRES model and with artificial neural network models under the six management scenarios. The annual average volumes of Lake Urmia would be 30 × 109 and 12 × 109 m3 over the first and second future periods, respectively, without considering the management scenarios. The lake volumes would rise by about 50% and 75% for the first and second periods, respectively under the management scenarios that involve strict protective measures and elimination of the effect of all dams and their reservoirs. Implementing strict measures would increase the annual average lake volume to 21 × 109 m3 in the second period; yet, this volume would be less than the long-term average and strategic volume. The human water use would be completely eliminated under Scenario 6. Nevertheless, Lake Urmia would experience a considerable loss of storage because of drought.

Design and Construction of Cu(OH)2/Ni3S2 Composite Electrode on Cu Foam by Two-Step Electrodeposition.

A Cu(OH)2/Ni3S2 composite has been designed and in situ constructed on Cu foam substrate by facile two-step electrodeposition. Cu(OH)2 is achieved on Cu foam by galvanostatic electrodeposition, and the subsequent coating of Ni3S2 is realized by cyclic voltammetric (CV) electrodeposition. The introduction of Cu(OH)2 provides skeleton support and a large specific surface area for the Ni3S2 electrodeposition. Benefiting from the selection of different components and preparation technology, the Cu(OH)2/Ni3S2 composite exhibits enhanced electrochemical properties with a high specific capacitance of 4.85 F cm-2 at 2 mA cm-2 and long-term cyclic stability at 80.84% (4000 cycles).

Activating Surface Lattice Oxygen of a Cu/Zn1-xCuxO Catalyst through Interface Interactions for CO Oxidation.

Surface lattice oxygen in metal oxides is a common participant in many chemical reactions. Given this, the structural design of catalysts to activate lattice oxygen and moreover investigations into the effect of lattice oxygen on reaction pathways are hot topics. With this in mind, herein we prepare CuO-Zn1-xCuxO (ZCO) nanofibers akin to the Trojan horse legend and via an in situ reduction obtain activated Cu/Zn1-xCuxO (Cu/ZCO) nanofibers. X-ray absorption spectroscopy and X-ray photoelectron spectroscopy reveal that surface lattice oxygen of Cu/ZCO is effectively activated from inert O2- to reactive O2-x. This activation stems from the enhanced covalence of metal-oxygen bonds and the electron transfer between Cu and the support. Online mass spectrometry reveals that Cu/ZCO with activated lattice oxygen exhibits a higher Mars-van Krevelen reaction efficiency during the CO oxidation process. This study offers a new avenue to engineer interface interactions, given, as highlighted here, the importance of surface lattice oxygen in oxide supports during the catalytic process.

Intra-crystalline mesoporous zeolite encapsulation-derived thermally robust metal nanocatalyst in deep oxidation of light alkanes.

Zeolite-confined metal nanoparticles (NPs) have attracted much attention owing to their superior sintering resistance and broad applications for thermal and environmental catalytic reactions. However, the pore size of the conventional zeolites is usually below 2 nm, and reactants are easily blocked to access the active sites. Herein, a facile in situ mesoporogen-free strategy is developed to design and synthesize palladium (Pd) NPs enveloped in a single-crystalline zeolite (silicalite-1, S-1) with intra-mesopores (termed Pd@IM-S-1). Pd@IM-S-1 exhibited remarkable light alkanes deep oxidation performances, and it should be attributed to the confinement and guarding effect of the zeolite shell and the improvement in mass-transfer efficiency and active metal sites accessibility. The Pd-PdO interfaces as a new active site can provide active oxygen species to the first C-H cleavage of light alkanes. This work exemplifies a promising strategy to design other high-performance intra-crystalline mesoporous zeolite-confined metal/metal oxide catalysts for high-temperature industrial thermal catalysis.

Synergistic Effects of a CeO2/SmMn2O5-H Diesel Oxidation Catalyst Induced by Acid-Selective Dissolution Drive the Catalytic Oxidation Reaction.

A diesel oxidation catalyst (DOC) is installed upstream of an exhaust after-treatment line to remove CO and hydrocarbons and generate NO2. The catalyst should possess both good oxidation ability and thermal stability because it sits after the engine. We present a novel high-performance DOC with high steam resistance and thermal stability. A selective dissolution method is adopted to modify the surface physicochemical environment of CeO2-SmMn2O5. The X-ray photoelectron spectroscopy, X-ray absorption spectroscopy, Raman, electron paramagnetic resonance, hydrogen temperature-programmed reduction, and temperature-programmed desorption results reveal that surface Sm cations are partially removed with the exposure of more Mn4+ and Ce3+ cations and the presence of active surface oxygen species. This mechanism benefits the oxygen transformation from Ce to Mn and promotes the Ce3+ + Mn4+ ↔ Ce4+ + Mn3+ redox cycle according to the in situ near-ambient pressure X-ray photoelectron spectroscopy and in situ diffuse reflectance infrared Fourier transformation spectroscopy results. Under laboratory-simulated diesel combustion conditions, the catalyst demonstrates excellent low-temperature oxidation catalytic activity (CO and C3H6 conversion: T100 = 250 °C) compared to a Pt-based catalyst (CO and C3H6 conversion: T100 = 310 °C) with a WHSV of 120,000 mL g-1 h-1. Specifically, NO conversion reaches 68% when the temperature is approximately 300 °C.

Tuning Metal-Support Interaction of Pt-CeO2 Catalysts for Enhanced Oxidation Reactivity.

Metal-support interaction (MSI) has been widely recognized to be playing a pivotal role in regulating the catalytic activity of various reactions. In this work, the degree of MSI between Pt and CeO2 support was finely tuned by adjusting the activation condition, and the obtained catalysts were tested for the oxidative abatement of CO and HCHO under ambient conditions. The characterization of catalysts shows that activation of strongly interacting Pt-CeO2 at higher temperatures by H2 leads to a weaker MSI with increased electron density of Pt, and this modification of local electronic properties is demonstrated to result in enhanced O2 adsorption/activation to prevent the CO self-poisoning effect, while it abates the activity of CO adsorption/activation and oxidation of adsorbed CO. The Pt-CeO2 catalyst with a moderate MSI, which is able to balance each step in the catalytic cycle over Pt and Pt-CeO2 interface domains, displays the highest activity for CO/HCHO oxidation under ambient conditions.

A robust multiple-objective decision-making paradigm based on the water-energy-food security nexus under changing climate uncertainties.

From the perspective of the water-energy-food (WEF) security nexus, sustainable water-related infrastructure may hinge on multi-dimensional decision-making, which is subject to some level of uncertainties imposed by internal or external sources such as climate change. It is important to note that the impact of this phenomenon is not solely limited to the changing behavior patterns of hydro-climatic variables since it can also affect the other pillars of the WEF nexus both directly and indirectly. Failing to address these issues can be costly, especially for those projects with long-lasting economic lifetimes such as hydropower systems. Ideally, a robust plan can tolerate these projected changes in climatic behavior and their associated impacts on other sectors, while maintaining an acceptable performance concerning environmental, socio-economic, and technical factors. This study, thus, aims to develop a robust multiple-objective decision-support framework to address these concerns. In principle, while this framework is sensitive to the uncertainties associated with the climate change projections, it can account for the intricacies that are commonly associated with the WEF security network. To demonstrate the applicability of this new framework, the Karkheh River basin in Iran was selected as a case study due to its critical role in ensuring water, energy, and food security of the region. In addition to the status quo, a series of climate change projections (i.e., RCP 2.6, RCP 4.5, and RCP 8.5) were integrated into the proposed decision support framework as well. Resultantly, the mega decision matrix for this problem was composed of 56 evaluation criteria and 27 feasible alternatives. A TOPSIS/Entropy method was used to select the most robust renovation plan for a hydropower system in the basin by creating a robust and objective weighting mechanism to quantify the role of each sector in the decision-making process. Accordingly, in this case, the energy, food, and environment sectors are objectively more involved in the decision-making process. The results revealed that the role of the social aspect is practically negligible. The results also unveiled that while increasing the power plant capacity or the plant factor would be, seemingly, in favor of the energy sector, if all relevant factors are to be considered, the overall performance of the system might resultantly become sub-optimal, jeopardizing the security of other aspects of the water-energy-food nexus.

Uncertainty analysis of model inputs in riverine water temperature simulations.

Simulation models are often affected by uncertainties that impress the modeling results. One of the important types of uncertainties is associated with the model input data. The main objective of this study is to investigate the uncertainties of inputs of the Heat-Flux (HFLUX) model. To do so, the Shuffled Complex Evolution Metropolis Uncertainty Algorithm (SCEM-UA), a Monte Carlo Markov Chain (MCMC) based method, is employed for the first time to assess the uncertainties of model inputs in riverine water temperature simulations. The performance of the SCEM-UA algorithm is further evaluated. In the application, the histograms of the selected inputs of the HFLUX model including the stream width, stream depth, percentage of shade, and streamflow were created and their uncertainties were analyzed. Comparison of the observed data and the simulations demonstrated the capability of the SCEM-UA algorithm in the assessment of the uncertainties associated with the model input data (the maximum relative error was 15%).

Reallocation of water resources according to social, economic, and environmental parameters.

Population growth, urbanization, and industrial development have significantly increased water demands in many countries, raising the concerns about water resources sustainability to meet the needs of humans and the environment. Furthermore, the economy-oriented allocation of water resources has caused many socio-environmental problems. The main goal of this study is to develop a system dynamics modeling framework that integrates economic, social, and environmental dimensions for the decision of water resources allocation. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is used to rank modeling scenarios and identify the best strategy for water allocation. In the application to East Azerbaijan province of Iran, six industry groups (including chemical, food and beverage, non-metal, machinery and equipment, metal, and textile), thirteen water allocation scenarios, and five criteria (including profit index, employment index, return of surface water, groundwater sustainability index, and total allocated water) were considered. The TOPSIS results showed that in the best scenario most water was allocated to the non-metal industry with a relative distance of 0.63 to the ideal solution. On the other hand, the current water allocation scenario ranked seventh, indicating that significant improvements are required to take into account the social, economic, and environmental factors for optimal reallocation of water resources among different industry users.

Association Study of Mitochondrial DNA Haplogroup D and C5178A Polymorphisms with Chronic Kidney Disease.

Objective: To explore the associations of common mitochondrial DNA polymorphisms with chronic kidney disease (CKD). Methods: Data from 286 longevous individuals aged 95 years or older from the longevity arm from the Rugao Longevity and Ageing Study (RuLAS) were used. Twenty-eight common haplogroups defined by 33 single nucleotide polymorphisms were genotyped using SNaPshot minisequencing reaction assays. The creatinine-based estimated glomerular filtration rate (eGFR) was calculated using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation. Results: The prevalence of CKD was 23.6% among the longevous participants aged 95 years and older. The D haplogroup (67.37 ± 14.72 vs. 70.65 ± 11.07, p = 0.045), the D5 haplogroup (60.86 ± 18.36 vs. 70.34 ± 11.53, p = 0.002), and the 5178A allele (67.23 ± 14.48 vs. 70.75 ± 11.10, p = 0.029) were associated with lower eGFR levels compared with noncarriers. The D5 haplogroup (13.8% vs. 3.6%, p = 0.005) was significantly higher, while D haplogroup (35.4% vs. 24%, p = 0.067) and the 5178A allele (36.9% vs. 24.9%, p = 0.056) were borderline significantly higher in CKD individuals than those without CKD. Further, after adjusting for multiple covariates, the D haplogroup, the D5 haplogroup, and the 5178A allele were associated with increased odds of CKD with odds ratios of 1.93 (95% confidence interval [CI]: 1.00-3.72, p = 0.050), 4.76 (95% CI: 1.49-15.22, p = 0.009) and 2.04 (95% CI: 1.05-3.96, p = 0.035), respectively. Conclusions: The D and D5 haplogroups, as well as the 5178A allele are associated with decreased eGFR levels and an increased risk of CKD in a longevous population.

Boosting the Catalytic Performance of CeO2 in Toluene Combustion via the Ce-Ce Homogeneous Interface.

Catalytic combustion is an advanced technology to eliminate industrial volatile organic compounds such as toluene. In order to replace the expensive noble metal catalysts and avoid the aggregation phenomenon occurring in traditional heterogeneous interfaces, designing homogeneous interfaces can become an emerging methodology to enhance the catalytic combustion performance of metal oxide catalysts. A mesocrystalline CeO2 catalyst with abundant Ce-Ce homogeneous interfaces is synthesized via a self-flaming method which exhibits boosted catalytic performance for toluene combustion compared with traditional CeO2, leading to a ∼40 °C lower T90. The abundant Ce-Ce homogeneous interfaces formed by both highly ordered stacking and small grain size endow the CeO2 mesocrystal with superior redox property and oxygen storage capacity via forming various oxygen vacancies. Surface and bulk oxygen vacancies generate and activate crucial oxygen species, while interfacial oxygen vacancies further promote the reaction behavior of oxygen species (i.e., activation, regeneration, and migration), causing the splitting of redox property toward lower temperature. These properties facilitate aromatic ring decomposition, the important rate-determining step, thus contributing to toluene catalytic degradation to CO2. This work may shed insights into the catalytic effects of homogeneous interfaces in pollutant removal and provide a strategy of interfacial defect engineering for catalyst development.