Bimetallic Sites for Catalysis: From Binuclear Metal Sites to Bimetallic Nanoclusters and Nanoparticles

Chemical Reviews, Год журнала: 2023, Номер 123(8), С. 4855 - 4933

Опубликована: Март 27, 2023

Heterogeneous bimetallic catalysts have broad applications in industrial processes, but achieving a fundamental understanding on the nature of active sites at atomic and molecular level is very challenging due to structural complexity catalysts. Comparing features catalytic performances different entities will favor formation unified structure-reactivity relationships heterogeneous thereby facilitate upgrading current In this review, we discuss geometric electronic structures three representative types (bimetallic binuclear sites, nanoclusters, nanoparticles) then summarize synthesis methodologies characterization techniques for entities, with emphasis recent progress made past decade. The supported nanoparticles series important reactions are discussed. Finally, future research directions catalysis based and, more generally, prospective developments both practical applications.

Язык: Английский

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Optimization strategies of high-entropy alloys for electrocatalytic applications

Chemical Science, Год журнала: 2023, Номер 14(45), С. 12850 - 12868

Опубликована: Янв. 1, 2023

This review summarizes the synthesis methods, characterization research progress and regulation strategies of HAEs in field electrocatalytic HER, HOR, OER, ORR, CO 2 RR, NRR AOR, providing deep understanding for future applications.

Язык: Английский

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Advances and challenges in the electrochemical reduction of carbon dioxide

Chemical Science, Год журнала: 2024, Номер 15(21), С. 7870 - 7907

Опубликована: Янв. 1, 2024

This review highlights the structure–activity relationship of ECO 2 RR, provides a detailed summary advanced materials by analyzing electrocatalytic applications and reaction mechanisms, discusses challenges in both devices.

Язык: Английский

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Designing strategies and enhancing mechanism for multicomponent high-entropy catalysts

Chemical Science, Год журнала: 2023, Номер 14(4), С. 771 - 790

Опубликована: Янв. 1, 2023

High-entropy materials (HEMs) are new-fashioned functional in the field of catalysis owing to their large designing space, tunable electronic structure, interesting "cocktail effect", and entropy stabilization effect. Many effective strategies have been developed design advanced catalysts for various important reactions. Herein, we firstly review so far optimizing HEM-based underlying mechanism revealed by both theoretical simulations experimental aspects. In light this overview, subsequently present some perspectives about development provide serviceable guidelines and/or inspiration further studying multicomponent catalysts.

Язык: Английский

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Scalable Synthesis of Multi‐Metal Electrocatalyst Powders and Electrodes and their Application for Oxygen Evolution and Water Splitting

Angewandte Chemie International Edition, Год журнала: 2023, Номер 62(12)

Опубликована: Янв. 14, 2023

Multi-metal electrocatalysts provide nearly unlimited catalytic possibilities arising from synergistic element interactions. We propose a polymer/metal precursor spraying technique that can easily be adapted to produce large variety of compositional different multi-metal catalyst materials. To demonstrate this, 11 catalysts were synthesized, characterized, and investigated for the oxygen evolution reaction (OER). Further investigation most active OER catalyst, namely CoNiFeMoCr, revealed polycrystalline structure, operando Raman measurements indicate multiple sites are participating in reaction. Moreover, Ni foam-supported CoNiFeMoCr electrodes developed applied water splitting flow-through electrolysis cells with electrolyte gaps zero-gap membrane electrode assembly (MEA) configurations. The proposed alkaline MEA-type electrolyzers reached up 3 A cm-2 , 24 h demonstrated no loss current density 1 .

Язык: Английский

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Discovering High Entropy Alloy Electrocatalysts in Vast Composition Spaces with Multiobjective Optimization

Journal of the American Chemical Society, Год журнала: 2024, Номер 146(11), С. 7698 - 7707

Опубликована: Март 11, 2024

High entropy alloys (HEAs) are a highly promising class of materials for electrocatalysis as their unique active site distributions break the scaling relations that limit activity conventional transition metal catalysts. Existing Bayesian optimization (BO)-based virtual screening approaches focus on catalytic sole objective and correspondingly tend to identify unlikely be entropically stabilized. Here, we overcome this limitation with multiobjective BO framework HEAs simultaneously targets activity, cost-effectiveness, entropic stabilization. With diversity-guided batch selection further boosting its data efficiency, readily identifies numerous candidates oxygen reduction reaction strike balance between all three objectives in hitherto unchartered HEA design spaces comprising up 10 elements.

Язык: Английский

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Screening of Cu-Mn-Ni-Zn high-entropy alloy catalysts for CO2 reduction reaction by machine-learning-accelerated density functional theory

Applied Surface Science, Год журнала: 2024, Номер 652, С. 159297 - 159297

Опубликована: Янв. 7, 2024

Язык: Английский

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Machine-Learning-Driven High-Entropy Alloy Catalyst Discovery to Circumvent the Scaling Relation for CO₂ Reduction Reaction

ACS Catalysis, Год журнала: 2022, Номер 12(24), С. 14864 - 14871

Опубликована: Ноя. 22, 2022

To achieve an equitable energy transition toward net-zero 2050 goals, the electrochemical reduction of CO2 (CO2RR) to chemical feedstocks through utilizing both and renewable is particularly attractive. However, catalytic activity CO2RR limited by scaling relation adsorption energies intermediates. Circumventing a potential strategy breakthrough in activity. Herein, based on density functional theory (DFT) calculations, we designed high-entropy alloy (HEA) system FeCoNiCuMo with high for CO2RR. Machine learning models were developed considering 1280 sites predict COOH*, CO*, CHO*. The between CHO* circumvented rotation COOH* HEA surface, resulting outstanding limiting 0.29–0.51 V. This work not only accelerates development catalysts but also provides effective circumvent relation.

Язык: Английский

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Machine-learning-based intelligent framework for discovering refractory high-entropy alloys with improved high-temperature yield strength

npj Computational Materials, Год журнала: 2022, Номер 8(1)

Опубликована: Ноя. 12, 2022

Abstract Refractory high-entropy alloys (RHEAs) show significant elevated-temperature yield strengths and have potential to use as high-performance materials in gas turbine engines. Exploring the vast RHEA compositional space experimentally is challenging, a small fraction of this has been explored date. This work demonstrates development state-of-the-art machine learning framework coupled with optimization methods intelligently explore drive search direction that improves high-temperature strengths. Our strength model shown significantly improved predictive accuracy relative approach, also provides inherent uncertainty quantification through repeated k -fold cross-validation. Upon developing validating robust prediction model, used discover RHEAs superior high temperature strength. We compositions can be customized maximum at specific temperature.

Язык: Английский

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High entropy materials frontier and theoretical insights for logistics CO2 reduction and hydrogenation: Electrocatalysis, photocatalysis and thermo-catalysis

Journal of Alloys and Compounds, Год журнала: 2023, Номер 969, С. 172232 - 172232

Опубликована: Сен. 20, 2023

Язык: Английский

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