High entropy powering green energy: hydrogen, batteries, electronics, and catalysis

A reformation in energy is underway to replace fossil fuels with renewable sources, driven by the development of new, robust, and multi-functional materials. High-entropy materials (HEMs) have emerged as promising candidates for various green energy applications, having unusual chemistries that give rise to remarkable functionalities. This review examines recent innovations in HEMs, focusing on hydrogen generation/storage, fuel cells, batteries, semiconductors/electronics, and catalysis—where HEMs have demonstrated the ability to outperform state-of-the-art materials. We present new master plots that illustrate the superior performance of HEMs compared to conventional systems for hydrogen generation/storage and heat-to-electricity conversion. We highlight the role of computational methods, such as density functional theory and machine learning, in accelerating the discovery and optimization of HEMs. The review also presents current challenges and proposes future directions for the field. We emphasize the need for continued integration of modeling, data, and experiments to investigate and leverage the underlying mechanisms of the HEMs that are powering progress in sustainable energy.

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Publication Details

Journal
npj Computational Materials
Published
2025-05-22
DOI
https://doi.org/10.1038/s41524-025-01594-6
Citations
9
Primary Topic
Electrocatalysts for Energy Conversion
Type
article
Field-Weighted Citation Impact
3.27

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article

High entropy powering green energy: hydrogen, batteries, electronics, and catalysis

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npj Computational Materials
Electrocatalysts for Energy Conversion
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article

High entropy powering green energy: hydrogen, batteries, electronics, and catalysis

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article en
9 citations

Abstract

A reformation in energy is underway to replace fossil fuels with renewable sources, driven by the development of new, robust, and multi-functional materials. High-entropy materials (HEMs) have emerged as promising candidates for various green energy applications, having unusual chemistries that give rise to remarkable functionalities. This review examines recent innovations in HEMs, focusing on hydrogen generation/storage, fuel cells, batteries, semiconductors/electronics, and catalysis—where HEMs have demonstrated the ability to outperform state-of-the-art materials. We present new master plots that illustrate the superior performance of HEMs compared to conventional systems for hydrogen generation/storage and heat-to-electricity conversion. We highlight the role of computational methods, such as density functional theory and machine learning, in accelerating the discovery and optimization of HEMs. The review also presents current challenges and proposes future directions for the field. We emphasize the need for continued integration of modeling, data, and experiments to investigate and leverage the underlying mechanisms of the HEMs that are powering progress in sustainable energy.

npj Computational MaterialsVol. 11(1)
Johns Hopkins University (US)
Maryland Space Grant Consortium, Johns Hopkins University, Advanced Research Projects Agency - Energy, Advanced Research Projects Agency
Affordable and clean energy
Openalex Percentile: Top 8%
Electrocatalysts for Energy Conversion
3.27
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