机器学习辅助元结构智能设计综述

IF 3.3 3区 物理与天体物理 Q2 PHYSICS, CONDENSED MATTER
Liangshu He, Yan Li, D. Torrent, X. Zhuang, T. Rabczuk, Y. Jin
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引用次数: 1

摘要

近年来,基于数据驱动或环境交互的机器学习(ML)快速发展,为元结构设计领域注入了新的活力。作为传统基于物理公式和规则的分析方法的补充,ML的加入大大加快了元结构性能探索和优化的步伐。本文从带结构、波传播特性和静力特性等方面综述了机器学习在声学、弹性和力学元结构方面的最新进展。最后对机器学习在元结构领域的一些潜在研究方向进行了总结和展望。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Machine learning assisted intelligent design of meta structures: a review
In recent years, the rapid development of machine learning (ML) based on data-driven or environment interaction has injected new vitality into the field of meta-structure design. As a supplement to the traditional analysis methods based on physical formulas and rules, the involvement of ML has greatly accelerated the pace of performance exploration and optimization for meta-structures. In this review, we focus on the latest progress of ML in acoustic, elastic, and mechanical meta-structures from the aspects of band structures, wave propagation characteristics, and static characteristics. We finally summarize and envisage some potential research directions of ML in the field of meta-structures.
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来源期刊
Superlattices and Microstructures
Superlattices and Microstructures 物理-物理:凝聚态物理
CiteScore
6.10
自引率
3.20%
发文量
35
审稿时长
2.8 months
期刊介绍: Micro and Nanostructures is a journal disseminating the science and technology of micro-structures and nano-structures in materials and their devices, including individual and collective use of semiconductors, metals and insulators for the exploitation of their unique properties. The journal hosts papers dealing with fundamental and applied experimental research as well as theoretical studies. Fields of interest, including emerging ones, cover: • Novel micro and nanostructures • Nanomaterials (nanowires, nanodots, 2D materials ) and devices • Synthetic heterostructures • Plasmonics • Micro and nano-defects in materials (semiconductor, metal and insulators) • Surfaces and interfaces of thin films In addition to Research Papers, the journal aims at publishing Topical Reviews providing insights into rapidly evolving or more mature fields. Written by leading researchers in their respective fields, those articles are commissioned by the Editorial Board. Formerly known as Superlattices and Microstructures, with a 2021 IF of 3.22 and 2021 CiteScore of 5.4
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