Group-Additivity–Embedded Multiscale Modeling for Electric Field-Enhanced Nanocatalysis

High Resolution Image Download MS PowerPoint Slide Elucidating structure-performance relationships remains a central challenge in field-enhanced catalysis, where nanoparticles exhibit nonuniform surface sites with site-dependent responses to electric fields. Low-coordination sites (edges, corners, and tips) are particularly electric field-sensitive (EF), leading to nonuniform charge distribution, adsorption energies, and catalytic activity. Here, using ammonia decomposition on a ruthenium cluster as a model system, we develop a transferable multiscale framework integrating density functional theory, group additivity (GA), Brønsted-Evans-Polanyi scaling, and microkinetic modeling to predict EF-dependent activity across nonuniform cluster sites. Across sites and fields, the nitrogen adsorption energy ( E N ) emerges as the governing descriptor, yielding robust volcano relationships whose optimum shifts systematically with field: negative fields strengthen N binding via electron accumulation, while positive fields weaken N binding via charge depletion, moving the optimal E N toward weaker binding. Microkinetic analysis shows that N≡N bond formation remains the key kinetic bottleneck over most conditions; positive fields lower the effective barrier and, critically, increase the fraction of near-optimal active sites, leading to a net enhancement in overall activity relative to zero-field and negative-field cases. By capturing EF- and site-dependent energetics with high accuracy and low computational cost, this GA-embedded multi-scale simulation workflow provides a physically interpretable route to predict and design field-enhanced nanocatalysis.

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Publication Details

Journal
ACS Catalysis
Published
2026-07-01
DOI
https://doi.org/10.1021/acscatal.6c01038
Primary Topic
Ammonia Synthesis and Nitrogen Reduction
Type
article
Field-Weighted Citation Impact
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article

Group-Additivity–Embedded Multiscale Modeling for Electric Field-Enhanced Nanocatalysis

Qiang Li, Fanglin Che, Yilang Liu, Runze Zhao
ACS Catalysis
Ammonia Synthesis and Nitrogen Reduction
article

Group-Additivity–Embedded Multiscale Modeling for Electric Field-Enhanced Nanocatalysis

Qiang Li, Fanglin Che, Yilang Liu, Runze Zhao
article en

Abstract

High Resolution Image Download MS PowerPoint Slide Elucidating structure-performance relationships remains a central challenge in field-enhanced catalysis, where nanoparticles exhibit nonuniform surface sites with site-dependent responses to electric fields. Low-coordination sites (edges, corners, and tips) are particularly electric field-sensitive (EF), leading to nonuniform charge distribution, adsorption energies, and catalytic activity. Here, using ammonia decomposition on a ruthenium cluster as a model system, we develop a transferable multiscale framework integrating density functional theory, group additivity (GA), Brønsted-Evans-Polanyi scaling, and microkinetic modeling to predict EF-dependent activity across nonuniform cluster sites. Across sites and fields, the nitrogen adsorption energy ( E N ) emerges as the governing descriptor, yielding robust volcano relationships whose optimum shifts systematically with field: negative fields strengthen N binding via electron accumulation, while positive fields weaken N binding via charge depletion, moving the optimal E N toward weaker binding. Microkinetic analysis shows that N≡N bond formation remains the key kinetic bottleneck over most conditions; positive fields lower the effective barrier and, critically, increase the fraction of near-optimal active sites, leading to a net enhancement in overall activity relative to zero-field and negative-field cases. By capturing EF- and site-dependent energetics with high accuracy and low computational cost, this GA-embedded multi-scale simulation workflow provides a physically interpretable route to predict and design field-enhanced nanocatalysis.

ACS Catalysis
Worcester Polytechnic Institute (US), University of Massachusetts Lowell (US)
Openalex Percentile: Top 21%
Ammonia Synthesis and Nitrogen Reduction
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