在超表面结构中探索人工智能,以前向和反向设计
Guantai Yang1,2, Qingxiong Xiao2, Zhilin Zhang2
1Frontiers Science Center for Flexible Electronics (FSCFE) Institute of Flexible Electronics (IFE), Northwestern Polytechnical University, Xi'an 710072, China.
iScience
|March 19, 2025
概括
本综述将人工智能 (AI) 支持的超表面设计分为前向和反向方法. 人工智能加速了超表面的设计,克服了传统方法的局限性,以改善电磁反应.
科学领域:
- 地表表面设计设计.
- 在电磁学领域的人工智能
- 计算电磁学的计算.
背景情况:
- 超表面是人工平面装置,产生独特的电磁反应.
- 传统的超表面设计依赖于耗时的数值算法和参数优化.
- 现有的方法往往难以准确匹配所需的性能.
研究的目的:
- 将人工智能 (AI) 支持的超表面设计方法进行分类.
- 为前进和反向AI设计方法提供独特的视角.
- 审查人工智能在超表面设计中的最新进展,原则,优势和应用.
主要方法:
- 基于可变性能映射的AI支持设计的分类为前向和反向方法.
- 审查智能算法,特别是神经网络,用于反向设计.
- 系统检查人工智能驱动的地表设计原则和技术.
主要成果:
- 人工智能支持的设计提供了一种新的超表面开发方法.
- 前进设计是由智能算法驱动的,而神经网络是反向设计的关键.
- 该评论详细介绍了AI在该领域的原则,优势和潜在应用.
结论:
- 人工智能显著提高了地表设计效率和准确性.
- 这一系统性审查提供了整体的理解,并有助于未来的研究.
- 这些发现有助于选择人工智能设计的超表面的实际应用.
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