Alkali cation-induced cathodic corrosion in Cu electrocatalysts

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

Published: June 13, 2024

Abstract The reconstruction of Cu catalysts during electrochemical reduction CO 2 is a widely known but poorly understood phenomenon. Herein, we examine the structural evolution nanocubes under reaction and its relevant conditions using identical location transmission electron microscopy, cyclic voltammetry, in situ X-ray absorption fine structure spectroscopy ab initio molecular dynamics simulation. Our results suggest that reconstruct via hitherto unexplored yet critical pathway - alkali cation-induced cathodic corrosion, when electrode potential more negative than an onset value ( e.g ., −0.4 V RHE 0.1 M KHCO 3 ). Having cations electrolyte for such process. Consequently, will inevitably undergo surface reconstructions typical process reaction, resulting dynamic catalyst morphologies. While having these does not necessarily preclude stable electrocatalytic reactions, they indeed prohibit long-term selectivity activity enhancement by controlling morphology pre-catalysts. Alternatively, operating at less potentials reduction, show can provide much advantage over spherical nanoparticles.

Language: Английский

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Rise of machine learning potentials in heterogeneous catalysis: Developments, applications, and prospects

Chemical Engineering Journal, Journal Year: 2024, Volume and Issue: 494, P. 152757 - 152757

Published: June 2, 2024

Language: Английский

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Promotion of C─C Coupling in the CO₂ Electrochemical Reduction to Valuable C₂₊ Products: From Micro‐Foundation to Macro‐Application

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

Published: Feb. 2, 2025

Abstract The electrochemical CO 2 reduction reaction (CO RR) to valuable C 2+ products emerges as a promising strategy for converting intermittent renewable energy into high‐energy‐density fuels and feedstock. Leveraging its substantial commercial potential compatibility with existing infrastructure, the conversion of multicarbon hydrocarbons oxygenates (C ) holds great industrial promise. However, process is hampered by complex multielectron‐proton transfer reactions difficulties in reactant activation, posing significant thermodynamic kinetic barriers commercialization production. Addressing these necessitates comprehensive approach encompassing multiple facets, including effective control C─C coupling electrolyzers using efficient catalysts optimized local environments. This review delves advancements outstanding challenges spanning from microcosmic macroscopic scales, design nanocatalysts, optimization microenvironment, development electrolyzers. By elucidating influence electrolyte environment, exploring flow cells, guidelines are provided future research aimed at promoting coupling, thereby bridging microscopic insights applications field electroreduction.

Language: Английский

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Accelerating Global Optimization of Cerium Oxide Nanocluster Structures with High-Dimensional Neural Network Potential

The Journal of Physical Chemistry A, Journal Year: 2025, Volume and Issue: 129(9), P. 2190 - 2199

Published: Feb. 25, 2025

CeO2, characterized by its unique 4f electronic structure and high oxygen storage capacity, is widely recognized as an important catalyst support material in energy catalytic applications. Despite importance, the complexity of CeO2 nanoclusters poses challenges for structural characterization. Herein, we present a machine learning approach to accelerate global optimization cerium oxide nanocluster structures using high-dimensional neural network potential (HDNNP). Our methodology integrates active construct versatile HDNNP that enables exploration vast configurational space small medium clusters (CenO2n+x, n = 2-18, x -1, 0, +1). The HDNNP, refined through iterative learning, achieves accuracy comparable first-principles calculations. Results indicate configuration lowest varies across different intervals. At 9 14, there transition from compact multilayered ordered structures, subsequently pyramidal structures. When > almost all are derived core grows continuously. In addition, lowest-energy analyzed. findings provide insights into size-dependent stability behavior nanoclusters.

Language: Английский

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Active phase discovery in heterogeneous catalysis via topology-guided sampling and machine learning

Nature Communications, Journal Year: 2025, Volume and Issue: 16(1)

Published: March 14, 2025

Understanding active phases across interfaces, interphases, and even within the bulk under varying external conditions environmental species is critical for advancing heterogeneous catalysis. Describing these through computational models faces challenges in generation calculation of a vast array atomic configurations. Here, we present framework automatic efficient exploration phases. This approach utilizes topology-based algorithm leveraging persistent homology to systematically sample configurations diverse coordination environments material morphologies. Simultaneously, machine learning force fields enable rapid computations. We demonstrate effectiveness this two systems: hydrogen absorption Pd, where penetrates subsurface layers bulk, inducing "hex" reconstruction CO2 electroreduction, explored 50,000 sampled configurations; oxidation dynamics Pt clusters, oxygen incorporation renders clusters less during reduction reactions, investigated 100,000 In both cases, predicted their impacts on catalytic mechanisms closely align with previous experimental observations, indicating that proposed strategy can model complex systems discovery specific conditions. Discovering heterocatalysis entails configuration sampling optimization. authors developed based topology effectively explore structures, applied electroreduction Oxygen Reduction Reaction

Language: Английский

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Machine Learning Big Data Set Analysis Reveals C–C Electro-Coupling Mechanism

Journal of the American Chemical Society, Journal Year: 2024, Volume and Issue: 146(32), P. 22850 - 22858

Published: Aug. 3, 2024

Carbon-carbon (C-C) coupling is essential in the electrocatalytic reduction of CO

Language: Английский

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Revisiting the Origin of Enhanced C2+ Selectivity on Oxide-Derived Copper toward CO2 Electroreduction

Applied Catalysis B Environment and Energy, Journal Year: 2024, Volume and Issue: 363, P. 124805 - 124805

Published: Nov. 9, 2024

Language: Английский

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Advances in Cu-based Catalysts for Electroreduction of CO2 to C2H4 in Flow Cells

Green Energy & Environment, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 1, 2025

Language: Английский

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Trace Iodine Modified Copper Catalyst Drives Asymmetric C─C Coupling in Stable CO₂ Electroreduction

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

Published: Jan. 23, 2025

Abstract Cu‐based catalysts efficiently catalyze the electrochemical conversion of CO 2 into high‐value multicarbon (C 2+ ) products. However, it remains a challenge to achieve optimal structural stability, product selectivity, and long‐term catalytic durability. In this study, well‐active oxide‐derived Cu surface consisting predominantly O(111) facets is developed, which contains trace amounts iodine (I). The enhances hydrogenation *CO facilitates asymmetric coupling *CHO, while intercalated boosts adsorption CO. During reaction, release excess I increases roughness, remaining controls chemical state Cu. These effects together lead Faradaic efficiency 79.0% cathodic energy 43.5% for C products at current density 300 mA cm −2 . Moreover, found that periodic electrode treatment with iodide prevents agglomeration preserves sufficient active sites, ensuring improved stability production. This study provides new insights synergistic interactions between Cu─O compounds offers promising route development highly durable systems electroreduction.

Language: Английский

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Determining the Magnetic Status of Active Sites on Nanocatalysts

The Journal of Physical Chemistry Letters, Journal Year: 2025, Volume and Issue: 16(6), P. 1447 - 1452

Published: Jan. 31, 2025

Identifying the atomic structure and chemical composition of active sites on nanocatalysts has been a long pursuit in heterogeneous catalysis. Yet, determining magnetic well-defined site is even more challenging. However, explicit morphology reaction temperature have not considered identifying behaviors nanocatalysts, especially theoretical studies. Herein, we determined status nanoscale catalysts at finite temperatures by using atomistic spin models. The size dependence Curie point premelting discussed, indicating that properties over localized center can greatly differ from bulk. Therefore, phase transitions its concomitant magneto-catalytic effect be induced considerably low temperature. Our analysis demonstrated an 8 nm cobalt-based core-shell nanoparticle achieve optimal magnetization with Sabatier activity for ammonia synthesis 523 K, which accord condition Haber-Bosch process. We believe our findings elucidate importance configuration sites. Furthermore, including this unexcavated dimension dynamical simulations catalytic process provide us complete comprehensive understanding mechanism under working conditions.

Language: Английский

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