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Published on: June 23, 2017
High-Entropy Alloys: A Review of Emerging Sensing Materials for Next-Generation Flexible Electronics
Huatan Chen1, Zhongyi Yu1, Yang Huang1
1School of Mechanical and Automotive Engineering, Xiamen University of Technology, Xiamen 361024, China.
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High-entropy alloys (HEAs), composed of five or more principal elements in near-equimolar ratios, have emerged as a groundbreaking class of materials for next-generation flexible electronics. This review systematically examines the unique potential of HEAs as sensing materials, moving beyond their traditional role as structural components. We first elucidate the fundamental mechanisms-core effects including lattice distortion, sluggish diffusion, and the cocktail effect-that endow HEAs with an exceptional synergy of high strength, good ductility, tunable electrical resistivity, and superior electrocatalytic activity. Subsequently, we critically analyze the state-of-the-art strategies for processing HEA-based micro/nano structures, including mechanical alloying, wet-chemical synthesis, and non-equilibrium deposition techniques, with an emphasis on their compatibility with flexible substrates. The core of the review categorizes and discusses the latest advances in HEA-based flexible sensors for strain/stress, gas, and electrochemical (e.g., glucose, biomarkers, heavy metals) detection, highlighting the structure-property-performance relationships. Representative studies have demonstrated that HEA flexible strain sensors achieve a temperature coefficient of resistance as low as 45.59 ppm/K with no signal drift over 6000 stretching cycles; room-temperature hydrogen sensors reach a detection limit down to 31 ppb with a response time of 19 s; and non-enzymatic glucose sensors deliver a sensitivity up to 3043 μA·mM-1·cm-2. Finally, we summarize the key challenges-such as manufacturing scalability, long-term stability under dynamic deformation, and cost-effectiveness-and provide a forward-looking perspective on promising research directions, including high-throughput compositional screening, multi-functional sensor arrays, and the integration of machine learning for rational material design.
