Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
91 tokens/sec
Gemini 2.5 Pro Premium
50 tokens/sec
GPT-5 Medium
27 tokens/sec
GPT-5 High Premium
19 tokens/sec
GPT-4o
103 tokens/sec
DeepSeek R1 via Azure Premium
82 tokens/sec
GPT OSS 120B via Groq Premium
458 tokens/sec
Kimi K2 via Groq Premium
209 tokens/sec
2000 character limit reached

Navigating the Complex Compositional Landscape of High-Entropy Alloys (2011.14403v2)

Published 29 Nov 2020 in cond-mat.mtrl-sci and cond-mat.dis-nn

Abstract: High-entropy alloys, which exist in the high-dimensional composition space, provide enormous unique opportunities for realizing unprecedented structural and functional properties. A fundamental challenge, however, lies in how to predict the specific alloy phases and desirable properties accurately. This review article provides an overview of the data-driven methods published to date to tackle this exponentially hard problem of designing high-entropy alloys. Various utilizations of empirical parameters, first-principles and thermodynamic calculations, statistical methods, and machine learning are described. In an alternative method, the effectiveness of using phenomenological features and data-inspired adaptive features in the prediction of the high-entropy solid solution phases and intermetallic alloy composites is demonstrated. The prospect of high-entropy alloys as a new class of functional materials with improved properties is featured in light of entropic effects. The successes, challenges, and limitations of the current high-entropy alloys design are discussed, and some plausible future directions are presented.

Citations (1)

Summary

We haven't generated a summary for this paper yet.

Dice Question Streamline Icon: https://streamlinehq.com

Follow-up Questions

We haven't generated follow-up questions for this paper yet.