Optimal Catalyst Research Articles

CO-Tolerant Heterogeneous Ruthenium Catalysts for Efficient Formic Acid Dehydrogenation.

The development of improved and less costly catalysts for dehydrogenation of formic acid (HCOOH) is of general interest for renewable energy technologies involving hydrogen storage and release. Theoretical calculations reveal that ruthenium (Ru) nanoparticles supported on nitrogen-doped carbon should be appropriate catalysts for such transformations. It is predicted that nitrogen doping significantly decreases the formation of CO, but at the same time increases CO tolerance of the catalysts. To prove these hypotheses heterogeneous ruthenium catalysts supported on porous nitrogen-doped carbon (Rux/CN) with hierarchical structure were synthesized using carbon nitride (C3N4) as template and phenanthroline (Phen) as ligand. Experimental tests in HCOOH dehydrogenation revealed that the optimal catalyst Ru7/CN exhibited good thermal stability at 140 °C and a high turnover frequency (TOF >1300 h-1), which is more than one order of magnitude higher than that of the commercial Ru5/C catalyst.

Revealing Activity of Symmetrical and Asymmetrical Ag2O‐MOx (M = Cu, Fe, Zn) Catalysts via DFT Calculations for Direct Propylene Epoxidation

AbstractDirect propylene epoxidation (DPE) with molecular oxygen is an effective process of conversion of propylene into propylene oxide (PO), which is an essential intermediate compound for many petrochemical products such as propylene glycol, propylene carbonate, polyurethane foams, etc. The modification of Ag‐based catalysts which prevents overoxidation and improves catalytic activity for PO production is studied by simulating Ag2O and mixed metal oxides of Ag2O‐CuO (Ag2CuO2), Ag2O‐ZnO (Ag2ZnO2) and Ag2O‐Fe2O3 (Ag2Fe2O4) catalysts using density functional theory (DFT). Instantaneous adsorption of propylene was observed over Ag2ZnO2 and Ag2CuO2. DPE with oxygen via the Mars‐Van Krevelen mechanism (MVKM) was investigated considering propylene and oxygen as alternatively adsorbed species and molecular species. DPE with molecular oxygen and adsorbed propylene required 1.7 times more activation energy than DPE with molecular propylene and adsorbed oxygen. DPE with oxygen via the Lagmuir‐Hinshelwood mechanism (LHM) required 3–4 times more activation energy than MVKM for Ag2O and Ag2CuO2, whereas it is comparable for Ag2ZnO2. This showed that both mechanisms are followed for DPE over Ag2ZnO2. Ag2ZnO2 was found to be the optimum catalyst for DPE with instantaneous adsorption of propylene and instantaneous desorption of PO.

CO‐tolerant heterogeneous ruthenium catalysts for efficient formic acid dehydrogenation

The development of improved and less costly catalysts for dehydrogenation of formic acid (HCOOH) is of general interest for renewable energy technologies involving hydrogen storage and release. Theoretical calculations reveal that ruthenium (Ru) nanoparticles supported on nitrogen‐doped carbon should be appropriate catalysts for such transformations. It is predicted that nitrogen doping significantly decreases the formation of CO, but at the same time increases CO tolerance of the catalysts. To prove these hypotheses heterogeneous ruthenium catalysts supported on porous nitrogen‐doped carbon (Rux/CN) with hierarchical structure were synthesized using carbon nitride (C3N4) as template and phenanthroline (Phen) as ligand. Experimental tests in HCOOH dehydrogenation revealed the optimal catalyst Ru7/CN exhibiting good thermal stability and a high turnover frequency (TOF > 1300 h‐1), which is more than one order of magnitude higher than that of the commercial Ru5/C catalyst.

Machine learning-based techno-econo-environmental analysis of CO2-to-olefins process for screening the optimal catalyst and hydrogen color

CO2 to light olefins (CTLO) is an attractive strategy for CO2 fixation to obtain high-value-added chemical products. Selecting the optimal catalyst and hydrogen source for the process has become increasingly challenging due to the wide range of developed catalysts and diverse hydrogen sources available. Herein, this study proposes a machine learning-based techno-econo-environmental analysis framework for screening catalysts and hydrogen colors for the CTLO process. The preferred machine learning model is employed to screen the most promising catalyst for the CTLO process, which is then applied to accomplish the conceptual design of the entire process to obtain essential material and energy balance results by process modeling and simulation. Finally, the techno-econo-environmental performance of the CTLO processes using various colored hydrogen are compared to provide more informed choices. The results indicate the extreme gradient boosting model exhibits superior predictive accuracy, making it suitable for integrating with the genetic algorithm to screen the optimal catalyst for the CTLO process. After multi-objective optimization, an optimal Fe-based catalyst is screened and used for the modeling and simulation of the CTLO process due to its highest light olefins yield (36.43%). The carbon, hydrogen, and exergy utilization efficiencies of the CTLO process considering solely the target light olefins are 59.58%, 21.71%, and 40.41%, respectively. After evaluating the impact of different H2 colors on the total operating cost, unit production cost, and minimum selling price of the CTLO process, it was found the CTLO process using gray H2 generated by coke oven gas and coal gasification technologies exhibits the most favorable cost-effectiveness and optimal market price compared to alternative production scenarios. However, using green H2 proves highly advantageous for the CTLO process in attaining comprehensive negative carbon emissions throughout its lifecycle. Moreover, it anticipates the influence of technological advancements and market fluctuations on the market competitiveness of CTLO processes with diverse hydrogen colors.

Monomer production from supercritical ethanol depolymerization of PET plastic waste using Ni-ZnO/Al2O3 catalyst

Plastic waste poses a serious threat to the global environment, with recycled polyethylene terephthalate (PET) plastic accounting for a considerable portion. The application of supercritical ethanol depolymerization technology presents an effective method for recycling PET waste. This study investigated using Ni as an additive to enhance the catalytic activity of ZnO/Al2O3 catalyst for PET waste depolymerization. The effects of different catalysts, catalyst dosage, reaction temperature, and reaction time on PET waste depolymerization were studied using the single-factor controlled variable method. The results showed that the 3Ni-ZnO/Al2O3 was the optimal catalyst, and under the optimal conditions with catalyst dosage of 4 %, reaction temperature of 260 °C, and reaction time of 60 min, the depolymerization efficiency of PET waste could reach 100 %, with the highest yields of diethyl terephthalate (DET) and ethylene glycol (EG) of 93.6 % and 90.2 %, respectively. Response surface methodology (RSM) was used to optimize the operating conditions to obtain the highest monomer yields. The predicted optimal parameters from RSM were as follows: reaction temperature = 262.8 °C, reaction time = 63.2 min, catalyst dosage = 3.8 wt%, with the predicted highest DET and EG yields of 95.9 % and 90.7 %, respectively. The analysis of variance (ANOVA) results for DET and EG possessed the R2 values of 0.9921 and 0.9885, respectively, with p-values < 0.0001, indicating a good fit for the models. Furthermore, after five times reuse, the 3Ni-ZnO/Al2O3 catalyst still exhibited good catalytic activity and stability. In conclusion, this study offers a clean, green, and sustainable alternative to recycling plastic waste.

Bimetallic nickel‑cobalt sulfide derived from lignin-MOFs hybrid as a high-efficiency heterogeneous catalyst for hydrogenolysis of lignin dimers.

Lignin represents a significant source of aromatic hydrocarbons in the natural world. The production of high-value chemicals from lignin has the great potential to effectively address the issue of fossil energy scarcity. In this study, complex sulfides of nickel‑cobalt bimetallic catalysts were prepared via hydrothermal synthesis and subsequently employed in the catalytic hydrogenolysis of CO bonds present in lignin. A series of complex sulfides Ni3S2/Co3S4-CSn-x-T derived from lignin-MOF (n = 0.5, 1, 1.5 and 2; x = 2, 4 and 6; T = 400, 500, 600 and 700 °C), were prepared under different conditions and subsequently employed in the catalytic hydrogenolysis of lignin model compounds. The optimal catalyst Ni3S2/Co3S4-CS1-4-500 exhibited the highest conversion rate of benzyl phenyl ether (BPE) (about 97.3 %), and the yields of toluene and phenol produced were 49.5 % and 43.6 %, respectively with isopropanol as the reaction solvent and no external H2. The introduction of element sulfur in catalysts could effectively inhibit the further hydrogenation of generated aromatic chemicals. The catalysts were well characterized, and the results demonstrated that the catalysts exhibited high catalytic activity with an increased loading of active components. This study provided some novel findings for the construction of biomass-based catalysts and the production lignin-derived aromatic chemicals.

Room temperature oxygenated groups addition in carbon materials via ozone oxidation for boosting electrochemical H2O2 production

The crucial yet delicate 2e− oxygen reduction reaction (ORR) for producing the green chemical H2O2 relies on the uniform coordination environment of the active sites, such as oxygenated groups in metal-free carbon material catalysts. However, conventional harsh carbon material synthesis methods inevitably introduce structural defects and alter morphology, hindering the precise control of active site formation. Herein, we developed the ozone oxidation method under controlled reaction conditions to precisely modify carbon materials at room temperature. Through controlling the ozonation of reaction time, concentration, temperature, and relative humidity, we find the mild method allows us to precisely add active carboxyl group (–COOH) without forming structural defects. Electrochemical tests reveal that the optimal catalyst with the highest –COOH content exhibits the most outstanding mass activity of 164 A/g at 0.65 V and the highest H2O2 selectivity of 91 %. The density functional theory calculations demonstrate that the carbon sites directly connected to –COOH possess the optimized binding strength of *OOH intermediate to favor the two-electron oxygen reduction process. This work offers a novel approach to precisely and gently control carbon surface groups while preserving the structural morphology through ozone gas treatment, which can be readily applied to other material designs.

Novel MOF-derived hexagonal starfish-shaped hollow prismatic cone-loaded metal complexes for electrocatalytic water decomposition study

Exploring efficient and stable bifunctional electrocatalysts for oxygen evolution reaction/hydrogen evolution reaction (OER/HER) is an urgent need and challenge for sustainable energy. Non-noble metal-based catalysts have attracted more and more attention due to their low cost and high catalytic performance. The construction of heterostructures is considered to be one of the most promising strategies for revealing the efficient performance for OER and HER. As a result, we prepared a nanomaterial catalyst based on the combination of three non-precious metals, which were simultaneously used for efficient OER, HER and integral water splitting techniques. We first prepared a very novel hollow hexagram star-shaped metal-organic frameworks (MOFs) by a one-step hydrothermal method, then used it as the substrate material, introduced Mo6+ and Fe3+ through ion exchange reaction, and finally formed a composite system of Co3Fe7 and Mo2C through high-temperature calcination, and the product with hexagonal starfish morphology was named as hexagonal starfish-shaped hollow prismatic cone-loaded metal complexes (HSHP-Mo2C/Co3Fe7). Taking advantage of the synergistic effect of the Co3Fe7 site and the Mo2C site, HSHP-Mo2C/Co3Fe7 not only exhibit excellent OER and HER properties, but also exhibit good stability and durability. Specifically, the optimal catalyst HSHP-Mo2C/Co3Fe7-1 shows a Tafel slope of only 46mV dec-1 for OER and 99mV dec-1 fort HER, an overpotential of only 324 and 371mV and the stability is even up to 60h. This work provides a promising strategy for the development of cost-effective, efficient and stable catalysts for energy area.

Carbonate-mediated Mars-van Krevelen mechanism on CuxO/CeO2 catalysts for boosting CO oxidation

Copper-cerium-based catalysts have gained considerable attention for their excellent performance in low-temperature CO oxidation applications. In this context, the carbonate-mediated Mars-van Krevelen (M−vK) pathway stands out as a promising route for enhancing catalytic performance. Herein, we prepared three CuxO/CeO2 nanocatalysts with varying copper content using Cu2O nanocrystals (Cu2O NCs) and Ce-BTC metal–organic frameworks (MOFs) as dual precursors. The optimal catalyst exhibits excellent performance (T100 value of 110 °C) comparable to the precious metal catalyst. Through integrating in-depth experimental results and density functional theory (DFT) calculations, we reveal the intricate interplay of interfacial synergistic catalysis and carbonate-mediated M−vK mechanisms, confirming that carbonate species generated under mild conditions significantly promote CO oxidation on CuxO/CeO2 nanocatalysts. Based on the comparison of the transition state (TS) energy barrier between the traditional and the carbonate-mediated M−vK mechanism reaction paths, we found that carbonate species is easier to form and establish the rate-determining step (viz., carbonate → CO2, the energy barrier of 1.51 eV). This study sheds light on the importance of carbonate species in modulating the catalytic behaviour of copper-cerium catalysts and provides valuable insights for designing efficient catalysts for CO oxidation applications.

Modeling Heterogeneous Catalysis Using Quantum Computers: An Academic and Industry Perspective.

Heterogeneous catalysis plays a critical role in many industrial processes, including the production of fuels, chemicals, and pharmaceuticals, and research to improve current catalytic processes is important to make the chemical industry more sustainable. Despite its importance, the challenge of identifying optimal catalysts with the required activity and selectivity persists, demanding a detailed understanding of the complex interactions between catalysts and reactants at various length and time scales. Density functional theory (DFT) has been the workhorse in modeling heterogeneous catalysis for more than three decades. While DFT has been instrumental, this review explores the application of quantum computing algorithms in modeling heterogeneous catalysis, which could bring a paradigm shift in our approach to understanding catalytic interfaces. Bridging academic and industrial perspectives by focusing on emerging materials, such as multicomponent alloys, single-atom catalysts, and magnetic catalysts, we delve into the limitations of DFT in capturing strong correlation effects and spin-related phenomena. The review also presents important algorithms and their applications relevant to heterogeneous catalysis modeling to showcase advancements in the field. Additionally, the review explores embedding strategies where quantum computing algorithms handle strongly correlated regions, while traditional quantum chemistry algorithms address the remainder, thereby offering a promising approach for large-scale heterogeneous catalysis modeling. Looking forward, ongoing investments by academia and industry reflect a growing enthusiasm for quantum computing's potential in heterogeneous catalysis research. The review concludes by envisioning a future where quantum computing algorithms seamlessly integrate into research workflows, propelling us into a new era of computational chemistry and thereby reshaping the landscape of modeling heterogeneous catalysis.

The 1.3 Å resolution structure of the truncated group Ia type IV pilin from Pseudomonas aeruginosa strain P1.

The type IV pilus is a diverse molecular machine capable of conferring a variety of functions and is produced by a wide range of bacterial species. The ability ofthe pilus to perform host-cell adherence makes it a viable target for the development of vaccines against infection by human pathogens such as Pseudomonas aeruginosa. Here, the 1.3 Å resolution crystal structure of the N-terminally truncated type IV pilin from P. aeruginosa strain P1 (ΔP1) is reported, the first structure of its phylogenetically linked group (group I) to be discussed in the literature. The structure was solved from X-ray diffraction data that were collected 20 years ago with a molecular-replacement search model generated using AlphaFold; the effectiveness of other search models was analyzed. Examination of the high-resolution ΔP1 structure revealed a solvent network that aids in maintaining the fold of the protein. On comparing the sequence and structure of P1 with a variety of type IV pilins, it was observed that there are cases of higher structural similarities between the phylogenetic groups of P.aeruginosa than there are between the same phylogenetic group, indicating that a structural grouping of pilins may be necessary in developing antivirulence drugs and vaccines. These analyses also identified the α-β loop as the most structurally diverse domain of the pilins, which could allow it to serve a role in pilus recognition. Studies of ΔP1 in vitro polymerization demonstrate that the optimal hydrophobic catalyst for the oligomerization of the pilus from strain K122 is not conducive for pilus formation of ΔP1; a model of a three-start helical assembly using the ΔP1 structure indicates that the α-β loop and the D-loop prevent in vitro polymerization.

Understanding Catalyst ‘Volcano’ Dependence Through Fermi-Level Controlled Kinetics Using Electronic Theory

The ubiquitous two-step Michaelis–Menten and Temkin–Boudart reaction mechanisms are extended to include the influence of the catalyst electronic subsystem in a 5-step mechanism. The resulting kinetic equation provides an alternative explanation for the well-known volcano-shaped dependence found in catalysis. The equilibrium constants of fast electronic steps are highlighted for their influence on adsorption and desorption through the relative concentration of charged versus neutral intermediates. This generalized concept can be widely applied to determine the optimal catalyst, based on the Fermi level of the material, for reactions proceeding via this universal reaction.

Cross-Electrophile Coupling: Principles, Methods, and Applications in Synthesis.

Cross-electrophile coupling (XEC), defined by us as the cross-coupling of two different σ-electrophiles that is driven by catalyst reduction, has seen rapid progression in recent years. As such, this review aims to summarize the field from its beginnings up until mid-2023 and to provide comprehensive coverage on synthetic methods and current state of mechanistic understanding. Chapters are split by type of bond formed, which include C(sp3)-C(sp3), C(sp2)-C(sp2), C(sp2)-C(sp3), and C(sp2)-C(sp) bond formation. Additional chapters include alkene difunctionalization, alkyne difunctionalization, and formation of carbon-heteroatom bonds. Each chapter is generally organized with an initial summary of mechanisms followed by detailed figures and notes on methodological developments and ending with application notes in synthesis. While XEC is becoming an increasingly utilized approach in synthesis, its early stage of development means that optimal catalysts, ligands, additives, and reductants are still in flux. This review has collected data on these and various other aspects of the reactions to capture the state of the field. Finally, the data collected on the papers in this review is offered as Supporting Information for readers.

Optimization of Ru/ZSM-5 catalyst for selective d-glucose hydrogenation to sorbitol: A box-behnken design approach

The hydrogenation of D-glucose to sorbitol holds significant importance in biomass biorefineries. With a focus on enhancing the efficiency and selectivity of this reaction, this research investigated various optimization parameters (catalyst dosage, reaction time, and temperature) over 0.5 %Ru/ZSM-5 prepared via impregnation method. The optimization process was carried out using Box-Behnken design (BBD). The results showed accurate predictive equations for all reaction responses, with R2 values exceeding 97 % and no significant errors observed. Additionally, the 2D contour plot revealed the relationship between time and temperature, highlighting that a long reaction time and high temperature could lead to reduced sorbitol yield due to the formation of by-products. Under the optimal catalyst dosage of 0.6 g, reaction time of 100 min, and temperature of 120°C, the D-glucose conversion and sorbitol yield were 99.6 ± 0.35 % and 99.43 ± 0.45 %, respectively. NMR results confirmed the exclusive production of sorbitol under these optimal conditions. Furthermore, the study demonstrated that the catalyst could be reused at least seven times without a significant decrease in D-glucose conversion or sorbitol yield, while ICP-OES analysis confirmed no Ru leaching during the reaction. Therefore, this research provides a biomass valorization strategy by optimizing the production process of sorbitol via D-glucose hydrogenation.

Sodium Carbonate-Modified activated carbon catalysts for enhanced hydrogen production via methane decomposition

Hydrogen is a clean and renewable energy source with significant potential for decarbonizing energy systems. Methane decomposition offers a sustainable method for hydrogen production without the emission of COx gases, making it as an attractive alternative to conventional methods like steam reforming. However, the high energy consumption associated with methane decomposition presents a challenge. To address this challenge, this study explores the modification of activated carbon (AC) with sodium carbonate (Na2CO3) to enhance its catalytic efficiency in methane decomposition. Various concentrations of Na2CO3 were used, and the catalysts were thoroughly characterized using XRD, SEM, and N2 adsorption–desorption techniques to evaluate their porosity, surface area, and crystallinity. The results indicate that Na2CO3-modified AC significantly reduced the degree of graphitization, resulting in a disordered carbon structure with enhanced porosity. This structure effectively enhances the catalytic activity of AC, with the optimal catalyst being AC-2Na2CO3. After 150 min of reaction, the methane conversion rates at 850 °C, 900 °C, and 950 °C are 17.18 %, 20.19 %, and 31.33 %, respectively, representing increases of 5.19 %, 5.69 %, and 5.32 % compared to the unmodified catalyst. These improvements are attributed to the creation of more active sites for methane adsorption and dissociation. Overall, the study demonstrates the potential of Na2CO3-modified AC as an efficient catalyst for methane decomposition, offering a viable pathway for sustainable hydrogen production with reduced energy consumption.

Novel methodology for targeting the optimal reactor and operating parameters based on the chemical system’s overall performance within catalyst lifecycle

Catalyst deactivation affects chemical system performance and reactor operation. A systematic method is proposed for targeting the optimal reactor, operating parameters, system performance, and catalyst service life, considering the catalyst deactivation. Relations between reactor performance, operating parameters, and running time are clarified based on the coupling analysis of the reactions, catalyst deactivation kinetics, and mass/energy balance. The influence of reactor fluctuation on energy cost and product output is explored by topological analysis, pinch analysis, and algebraic reasoning. A reactor-separator-heat exchanger network coupling frame is established to predict system performance and guide the reactor selection, catalyst regeneration, and system adjustments. The proposed method is intuitive and efficient and can be applied in the preparatory/operation stage. For the studied benzene hydrogenation process, the Plug Flow Reactor is suitable; the catalyst’s optimal service life is 2.08 y, achieving 4.4 % and 4.8 % decreases in annual cost and energy demand/carbon emission by real-time adjustments.

Multifunctional ionic covalent triazine framework as heterogeneous catalysts for efficient CO2 cycloaddition

The abundant triazine rings with the good affinity for CO2 molecules in covalent triazine frameworks (CTFs) can capture and activate CO2 molecules, making CTFs a potential candidate for CO2 cycloaddition reaction. However, due to the single active site, the realization of high catalytic performance commonly requires the assistance of cocatalysts or harsh reaction conditions. In this study, several novel ionic covalent triazine frameworks (MCTFs, BCTFs and YCTFs) multifunctional heterogeneous catalysts were synthesized for CO2 cycloaddition reactions. The prepared CTFs catalysts have outstanding pore structure and uniformly distributed active sites (N Lewis basic sites in triazine ring and Cl– nucleophilic sites). The optimal catalyst MCTF-10 has good CO2 enrichment capacity and high adsorption selectivity. In addition, the catalyst shows an outstanding catalytic performance for the coupling reaction of CO2 and propylene oxide, with 96 % of yield and 99 % of selectivity for the product under metal-, solvent- and cocatalyst-free parameters (110 °C, initial CO2 pressure 1 MPa, 4 h). Even under diluted CO2 concentration (15 % CO2, 85 % N2) and mild conditions (80 °C, 0.1 MPa, 24 h), the synthetized CTFs exhibits an outstanding catalytic activity. The excellent catalytic performance, along with the good cycling stability and broad applicability of epoxides, make it a competitive catalyst for catalyzing the CO2 cycloaddition reaction.

Two-dimensional P1 approximation (P1-2D) for the Description of the Radiant Field on Cylindrical Solar Photocatalytic Reactors

The local volumetric rate of photon absorption (LVRPA) was formulated by solving the radiative transfer equation (RTE) in polar coordinates with the P1 approximation approach (P1-2D) for the description of the radiant field in cylindrical solar photocatalytic reactors. A general expression of the LVRPA was formulated that can be employed on cylindrical photocatalytic reactors with an incident radiation constant along the reactor length. CPC and tubular photocatalytic reactors were used as reactor models and Lambert's cosine law (irradiance) was considered when using the boundary conditions. Simulations were carried out using the commercial TiO2-P25, its optical properties taken from the literature. The LVRPA was found to decrease exponentially from the reactor wall to its center. literature rate of photon absorption per unit of reactor length (VRPA/H) increased exponentially with the catalyst loading until a value where no significant increase was observed and was found to increase with reactor radius, information that agrees with the literature. The optimum catalyst loading with the CPC reactor was about 0.364 g/L with a reactor radius equal to 1.65 cm similar to that found in the literature when using the six-flux model in two dimensions (SFM-2D). The apparent optical thickness τ_App1 newly formulated with the P1 approximation was introduced for optimization purposes and was found more reliable than the optical thickness τ. This parameter not only removes the dependence of the optimum catalyst loading on the reactor's radius but also its dependence on catalyst albedo. τ_App1 was found about 9.73 and 14.6 for CPC and tubular reactors respectively and provides the optimum catalyst loading and the reactor radius that optimize the radiation absorption inside both reactors.

The n–π* electronic transition induced by nitrogen vacancies enhances photocatalytic hydrogen production in carbon nitride

In semiconductor catalysts, long-lived excited states can effectually improve the utilization of photogenerated carriers to enhance photocatalytic performance. Herein, we used supramolecular engineering to synthesize a hollow tubular carbon nitride catalyst with N vacancies and an obvious n–π* transition. The unique hollow tubular structure provides abundant active sites, which are favorable for photocatalytic reaction. The presence of N vacancies expands the π-electron delocalization domains in the conjugated system, which excites the n–π* transition and thus triggers the red-shifted absorption edge at approximately 660 nm. Experiments and DFT calculations demonstrated that the N vacancies are beneficial for narrowing the bandgap and promoting the reduction of H+ by photogenerated electrons. Femtosecond transient absorption spectroscopy (fs-TAS) indicated that the n–π* electronic transition in the carbon nitride photocatalyst leads to slower exciton annihilation (lifetime: 38.64 ± 10.6 ps) and extended shallow electron trapping states (lifetime: 325.9 ± 19.3 ps). The appearance of these states adds more photogenerated electrons to the photocatalytic reaction process. The optimal hollow tubular carbon nitride catalyst exhibits a hydrogen production rate of 2664.47 μmol∙g−1∙h−1, which is 31.2 times higher than that of bulk carbon nitride (85.3325 μmol∙g−1∙h−1). This work highlights the ability of the n–π* transition induced by N vacancies to enhance the photocatalytic activity of carbon nitride.

Tuning oxygen vacancy for efficient CO2 electroreduction over CeO2 supported SnO2

CO2 electroreduction is favorable in neutral or alkaline aqueous solutions, where H2O serves as the proton source, suffering from sluggish dynamics. Herein, we synthesize a series of SnO2-CeO2 with different oxygen vacancy (Ov) concentration, regulating the H2O dissociation, to synchronize with the CO2 reduction. The optimal SnO2-CeO2 catalyst, with a moderate Ov concentration, exhibits a formate Faradic efficiency of nearly 93% and maintains for more than 46 h at a current density of 100 mA/cm2. The catalyst with lower Ov concentration results in weak H2O dissociation, thus enhancing the energy barrier of *OCHO generation, while higher Ov concentration leads to excessive proton, exacerbating the hydrogen evolution reaction (HER), as supported by DFT calculation and in situ attenuated total reflection-Fourier transform infrared spectra (ATR-FTIR). This study underscores the significance of Ov concentration in determining the ability of water dissociation over supported electrocatalysts, providing valuable insights for the development of more efficient electrocatalyst.