From Single Metals to High‐Entropy Alloys: How Machine Learning Accelerates the Development of Metal Electrocatalysts

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

Published: April 25, 2024

Abstract The rapid advancement of high‐performance computing and artificial intelligence technology has opened up novel avenues for the development various metal electrocatalysts. In particular, dilute high‐entropy alloys have garnered significant attention owing to their unique electronic spatial structures, as well exceptional electrocatalytic performance. Commencing with exploration single‐atom alloy catalysts, latest advancements in machine learning (ML) techniques are presented efficient screening a broad spectrum spaces. Subsequently, review delves into prevailing trend research, focusing specifically on rare‐metal electrocatalysts, offers an overview progress outcomes achieved through application ML these domains. Finally, highlighted promising category electrocatalysts underscore importance potential applications addressing complex challenging research issues underscored.

Language: Английский

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Single-atom catalysts based on two-dimensional metalloporphyrin monolayers for electrochemical nitrate reduction to ammonia by first-principles calculations and interpretable machine learning

International Journal of Hydrogen Energy, Journal Year: 2024, Volume and Issue: 80, P. 586 - 598

Published: July 17, 2024

Language: Английский

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Electronic structure modulation of high entropy materials for advanced electrocatalysis

Green Energy & Environment, Journal Year: 2024, Volume and Issue: unknown

Published: July 1, 2024

High-entropy materials (HEMs) have managed to make their mark in the field of electrocatalysis. The flexibly adjustable component, unique configuration and proprietary core effect endow HEMs with excellent functional feature, superior stability fast reaction kinetics. Recently, relationship between compositions structures high-entropy catalysts electrocatalytic performances has been extensively investigated. Based on this motivation, we comprehensively systematically summarize HEMs, outline intrinsic properties electrochemical advantages, generalize current state-of-the-art synthetic methods, analyze active centers conjunction characterization techniques, utilize theoretical research conduct a high-throughput screening targeted catalyst exploration mechanisms, importantly, focus specially applications propose strategies for regulating electronic structure accelerate kinetics, including morphological control, defect engineering, element regulation, strain engineering so forth. Finally, provide our personal views challenges further technical improvements catalysts. This work can valuable guidance future electrocatalysts.

Language: Английский

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Nanostructured materials derived from high entropy alloys–State-of-the-art and leading technical applications

Results in Physics, Journal Year: 2024, Volume and Issue: 62, P. 107838 - 107838

Published: June 17, 2024

Exceptional category of alloys comprising five or more alloying metals in structures are referred as high entropy alloys. Uniqueness these have been observed due to the combination superior mechanical, thermal, conducting, anticorrosion, and other physical properties. Unlike traditional metallic (two metals), varying elemental compositions led limitless potential possibilities. Recent research has unveiled an important opportunity for based nanostructures like nanoparticles nanocomposites. This state-of-the-art review is basically intended highlight design essential structure, property, applied aspects alloy nanostructures. Consequently, various notable combinations with carbon (graphene, nanotube) inorganic surveyed. In this context, several nanocomposite designs reported using efficient techniques thermal shock, flame spray pyrolysis, plasma spark sintering, mechanical milling, alloying, electrochemical, solution name a few. The resulting derived nanomaterials researched microstructure, nanocrystalline different features (microhardness, modulus, stress–strain, compression properties), wear, range on pointed towards fields energy storage (batteries supercapacitors), radiation shielding, corrosion/wear coatings, biomedical uses.

Language: Английский

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High entropy materials: potential catalysts for electrochemical water Splitting

Green Chemistry, Journal Year: 2024, Volume and Issue: 26(18), P. 9569 - 9598

Published: Jan. 1, 2024

A comprehensive overview of the use HEM as a catalyst for HER, OER, and water splitting was provided.

Language: Английский

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Unveiling the potential of high-entropy materials toward high-energy metal batteries based on conversion reactions: synthesis, structure, properties, and beyond

Energy storage materials, Journal Year: 2025, Volume and Issue: unknown, P. 104054 - 104054

Published: Jan. 1, 2025

Language: Английский

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Spin glass and complex magnetism in a high-entropy spinel oxide with five cations at both tetrahedral and octahedral sites

Applied Physics Letters, Journal Year: 2025, Volume and Issue: 126(5)

Published: Feb. 3, 2025

We report the stabilization and investigation of a hitherto unexplored high-entropy spinel oxide with composition (Mg0.2Co0.2Ni0.2Cu0.2Zn0.2)(Cr0.4Mn0.4Fe0.4Al0.4Ga0.4)O4, representing compound five distinct elements at both tetrahedral octahedral sites in structure. Detailed structural characterization using x-ray diffraction (and scanning electron microscopy) confirms cubic crystal structure, while DC magnetic AC susceptibility measurements reveal complex behavior below 150 K spin glass state 37 K. along zero-field-cooled field-cooled memory effect aging confirm material. The power law Vogel–Fulcher analyses this material's cluster state. This work highlights potential entropy-driven design tailoring multifunctional materials for advanced applications.

Language: Английский

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Bayesian optimization and explainable machine learning for High-dimensional multi-objective optimization of biodegradable magnesium alloys

Journal of Material Science and Technology, Journal Year: 2025, Volume and Issue: unknown

Published: April 1, 2025

Language: Английский

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Machine learning in electrocatalysis - living up to the hype?

Current Opinion in Electrochemistry, Journal Year: 2025, Volume and Issue: unknown, P. 101649 - 101649

Published: Jan. 1, 2025

Language: Английский

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A Practical Inverse Design Approach for High-Entropy Catalysts with Generative AI

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 14, 2025

The vast compositional space of high-entropy materials offers unprecedented opportunities for the development powerful catalysts. However, their inverse design remains unfeasible due to lack robust theoretical frameworks and high-throughput experimental tools. This study demonstrates a practical approach that integrates spectroscopic descriptors, generative machine learning, robotic platform synthesize optimize catalyst composition oxygen evolution reaction (OER). automated system significantly accelerated catalysts validation, reducing time required synthesis, characterization performance testing from approximately 20 hours only 78 minutes per sample. Following rapid screen efficient senary catalysts, model further optimized top-performing candidate, lowering its overpotential at 10 mA/cm² by an additional 32 mV. Our findings are testament potential incorporates descriptors into learning accelerate discovery. Moreover, this is also expected drive intelligent high-performance complex materials.

Language: Английский

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