journal article·2025-12-09

From Multinary Solid Solutions to High-Entropy Nanomaterials

Hong-Bo Cui, Yiyun Wang, Yi-Chen Wang, Chengjie Chen, Guijian Guan, Ming-Yong Han

ACS Nano· Volume 19· Issue 48
Publisher page

Abstract

High-entropy nanomaterials (HENMs)─nanoscale solid solutions containing multiple principal elements in near-equiatomic ratios─have rapidly evolved from early multinary alloys into a broadly tunable platform spanning alloys, oxides, sulfides, and emerging ceramics such as carbides, nitrides, phosphides, and fluorides. This perspective maps that evolution across compositional expansion, dimensional reduction, and structural diversification (solid, hollow, mesoporous, and layered architectures). We synthesize current knowledge of the thermodynamic and kinetic principles that govern phase formation and metastability at the nanoscale, emphasizing the roles of configurational entropy stabilization versus enthalpy penalties, sluggish diffusion, and rapid quenching. Top-down and bottom-up routes are critically assessed, highlighting how far-from-equilibrium pathways enable homogeneous multielement mixing at the nanoscale. We further highlight high-throughput pipelines that couple continuous synthesis with rapid electrochemical mapping, and machine-learning frameworks that compress the combinatorial search space and reveal composition-structure-property rules. Finally, we outline key challenges and opportunities in component space expansion, predictive synthesis control, operando/high-throughput characterization, interpretable machine learning, device-level integration, and resource sustainability. Together, these advances facilitate the transition from "entropy-stabilized curiosities" to engineered HENMs with programmable performance for catalysis, energy conversion/storage, electronics, and extreme-environment technologies.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: High Entropy Alloys Studies · Machine Learning in Materials Science · Electrocatalysts for Energy Conversion

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Institute of Molecular Plus, Tianjin University, 92 Weijin Road, Tianjin 300072, China

Funding

Ministry of Science and Technology of the People's Republic of China · Tianjin University

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