Optimizing Electrocatalytic Nitrogen Reduction via Interfacial Electric Field Modulation: Elevating d‐Band Center in WS₂‐WO₃ for Enhanced Intermediate Adsorption

Angewandte Chemie International Edition, Journal Year: 2023, Volume and Issue: 62(29)

Published: May 25, 2023

Electrocatalytic nitrogen reduction reaction (ENRR) has emerged as a promising approach to synthesizing green ammonia under ambient conditions. Tungsten (W) is one of the most effective ENRR catalysts. In this reaction, protonation intermediates rate-determining step (RDS). Enhancing adsorption crucial increase intermediates, which can lead improved catalytic performance. Herein, we constructed strong interfacial electric field in WS2 -WO3 elevate d-band center W, thereby strengthening intermediates. Experimental results demonstrated that led significantly Specifically, exhibited high NH3 yield 62.38 μg h-1 mgcat-1 and promoted faraday efficiency (FE) 24.24 %. Furthermore, situ characterizations theoretical calculations showed upshifted W towards Fermi level, leading enhanced -NH2 -NH on catalyst surface. This resulted rate RDS. Overall, our study offers new insights into relationship between provides strategy enhance during process.

Language: Английский

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Activity and Selectivity Roadmap for C–N Electro-Coupling on MXenes

Journal of the American Chemical Society, Journal Year: 2023, Volume and Issue: 145(28), P. 15572 - 15580

Published: July 6, 2023

Electrochemical coupling between carbon and nitrogen species to generate high-value C-N products, including urea, presents significant economic environmental potentials for addressing the energy crisis. However, this electrocatalysis process still suffers from limited mechanism understanding due complex reaction networks, which restricts development of electrocatalysts beyond trial-and-error practices. In work, we aim improve mechanism. This goal was achieved by constructing activity selectivity landscape on 54 MXene surfaces density functional theory (DFT) calculations. Our results show that step is largely determined *CO adsorption strength (Ead-CO), while relies more co-adsorption *N (Ead-CO Ead-N). Based these findings, propose an ideal catalyst should satisfy moderate stable adsorption. Through machine learning-based approach, data-driven formulas describing relationship Ead-CO Ead-N with atomic physical chemistry features were further identified. identified formula, 162 materials screened without time-consuming DFT Several potential catalysts predicted good performance, such as Ta2W2C3. The candidate then verified study has incorporated learning methods first time provide efficient high-throughput screening method selective electrocatalysts, could be extended a wider range electrocatalytic reactions facilitate green chemical production.

Language: Английский

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Progress in Single/Multi Atoms and 2D‐Nanomaterials for Electro/Photocatalytic Nitrogen Reduction: Experimental, Computational and Machine Leaning Developments

Advanced Energy Materials, Journal Year: 2024, Volume and Issue: 14(28)

Published: Feb. 11, 2024

Abstract The conversion of atmospheric nitrogen (N 2 ) into ammonia (NH 3 ), known as fixation, plays a crucial role in sustaining life on Earth, facing innovation with electrocatalytic and photocatalytic methods. These approaches promise gentler conversions from to ammonia, diverging the energy‐intensive Haber‐Bosch process, which requires complex plant infrastructure. Vitality lies eco‐friendly, cost‐effective, energy‐efficient pathways. challenge is that electrocatalysts photocatalysts for reduction have shown low Faraday efficiency, hampered by hydrogen evolution. This work delves recent strides electro/photo‐catalytic fixation/reduction, deciphering mechanisms, catalysts, prospects. By unveiling core principles steering these processes, it dissects efficiency drivers. Experimental theoretical studies, ranging density functional calculations/simulations machine learning‐based catalyst screening, mark path toward highly efficient including single/multi‐atom catalysts embedded 2D materials. journey explores diverse assessing their performance, spotlighting emerging nanomaterials, heterostructures, co‐catalyst techniques. Perspectives future directions potential applications fixation/reduction are offered, emphasizing sustainable management implications global agriculture environmental sustainability.

Language: Английский

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Recent Progress on Computation‐Guided Catalyst Design for Highly Efficient Nitrogen Reduction Reaction

Advanced Functional Materials, Journal Year: 2024, Volume and Issue: 34(34)

Published: April 5, 2024

Abstract Electrochemical nitrogen reduction reaction (NRR) for ammonia synthesis has attracted great interest in recent years, which presents a carbon‐free alternative to the energy‐intensive Haber–Bosch process. Besides, NRR also provides promising coverage route of renewable energy since NH 3 is considered second generation hydrogen while possessing established technologies liquefaction, storage, and transport. However, there are long‐term challenges catalyst design due its low intrinsic activity unsatisfied selectivity. Fortunately, by conducting extensive explorations this field, much progress achieved boosting performance. Herein, from view atomic/electronic level, three promotion effects summarized (i.e., electron effect, geometry ligand effect), tackle Representative studies with taking fully advantages reviewed, realized remarkable Finally, future research directions prospects discussed. It highly expected that review will enable advancement catalysts promote further development electrochemical NRR.

Language: Английский

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Machine learning-assisted dual-atom sites design with interpretable descriptors unifying electrocatalytic reactions

Nature Communications, Journal Year: 2024, Volume and Issue: 15(1)

Published: Sept. 17, 2024

Low-cost, efficient catalyst high-throughput screening is crucial for future renewable energy technology. Interpretable machine learning a powerful method accelerating design by extracting physical meaning but faces huge challenges. This paper describes an interpretable descriptor model to unify activity and selectivity prediction multiple electrocatalytic reactions (i.e., O

Language: Английский

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High‐Throughput Screening and General Synthesis Strategy of Single‐Atom Nanozymes for Oral Squamous Cell Carcinoma Therapy

Advanced Materials, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 5, 2025

Abstract Single‐atom nanozymes (SAzymes), with their superior enzyme‐like catalytic activity, have emerged as promising candidates for oncology therapeutics. The well‐defined structures of SAzymes make them well predictable by experiences and theoretical calculation. However, the effects metal center species coordination environments on activity are variable, screening artificial experiments is challenging. High‐throughput can rapidly select optimal thus better application in tumor therapy highly desirable. Herein, a “high‐throughput screening‐SAzymes structures” system established efficient drug preparation density functional theory oxidase‐like processes screened differences brought about different metals environments. Through this process, transition (Mn, Fe, Co, Ni) active centers synthesized then tested multi‐enzyme activities. It found that SAzyme Co exhibited best further showed good anti‐oral squamous cell carcinoma properties both vitro vivo. This study opens up new avenue rational design oral cancer combining computational experimental validation.

Language: Английский

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The Synergistic Effect between Metal and Sulfur Vacancy to Boost CO₂ Reduction Efficiency: A Study on Descriptor Transferability and Activity Prediction

JACS Au, Journal Year: 2024, Volume and Issue: 4(1), P. 125 - 138

Published: Jan. 10, 2024

Both metal center active sites and vacancies can influence the catalytic activity of a catalyst. A quantitative model to describe synergistic effect between centers is highly desired. Herein, we proposed machine learning evaluate index, PSyn, which learned from possible pathways for CH4 production CO2 reduction reaction (CO2RR) on 26 metal-anchored MoS2 with without sulfur vacancy. The data set consists 1556 intermediate structures MoS2, are used training. 2028 literature, comprising both single site dual sites, external test. XGBoost 3 features, including electronegativity, d-shell valence electrons metal, distance vacancy, exhibited satisfactory prediction accuracy limiting potential. Fe@Sv-MoS2 Os@MoS2 predicted be promising CO2RR catalysts high stability, low potential, selectivity against hydrogen evolution reactions (HER). Based some easily accessible descriptors, transferability achieved porous materials 2D in predicting energy change nitrogen (NRR). Such predictive also applied predict other oxygen tungsten vacancy systems.

Language: Английский

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Coordination environment manipulation of single atom catalysts: Regulation strategies, characterization techniques and applications

Coordination Chemistry Reviews, Journal Year: 2024, Volume and Issue: 515, P. 215952 - 215952

Published: May 20, 2024

Language: Английский

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Automation and machine learning augmented by large language models in a catalysis study

Chemical Science, Journal Year: 2024, Volume and Issue: 15(31), P. 12200 - 12233

Published: Jan. 1, 2024

AI and automation are revolutionizing catalyst discovery, shifting from manual methods to high-throughput digital approaches, enhanced by large language models.

Language: Английский

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High throughput screening for electrocatalysts for nitrogen reduction reaction using metal-doped bilayer borophene: A combined approach of DFT and machine learning

Molecular Catalysis, Journal Year: 2024, Volume and Issue: 557, P. 113972 - 113972

Published: Feb. 28, 2024

Language: Английский

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