{"title":"映射信息与光：人工智能元光子学的发展趋势","authors":"Seokho Lee , Cherry Park , Junsuk Rho","doi":"10.1016/j.cossms.2024.101144","DOIUrl":null,"url":null,"abstract":"<div><p>A dynamic convergence between metaphotonics and artificial intelligence (AI) is underway. In this review, AI is conceptualized as a tool for mapping input and output data. From this perspective, an analysis is conducted on how input and output data are set, aiming to discern the following three key trends in the utilization of AI within the field of metaphotonics. 1. The advancement of forward modeling and inverse design, utilizing AI for mapping metaphotonic device design and the corresponding optical properties. 2. Optical neural networks (ONNs), an emerging field that implements AI using metaphotonics by processing information within electromagnetic waves. 3. The field of metasensors, employing metamaterials to encode optical information for measurement and processing using AI to demonstrate high performance sensing. We round up the review with our perspectives on AI and metaphotonics research and discuss the future trends, challenges, and developments.</p></div>","PeriodicalId":295,"journal":{"name":"Current Opinion in Solid State & Materials Science","volume":"29 ","pages":"Article 101144"},"PeriodicalIF":12.2000,"publicationDate":"2024-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Mapping information and light: Trends of AI-enabled metaphotonics\",\"authors\":\"Seokho Lee , Cherry Park , Junsuk Rho\",\"doi\":\"10.1016/j.cossms.2024.101144\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>A dynamic convergence between metaphotonics and artificial intelligence (AI) is underway. In this review, AI is conceptualized as a tool for mapping input and output data. From this perspective, an analysis is conducted on how input and output data are set, aiming to discern the following three key trends in the utilization of AI within the field of metaphotonics. 1. The advancement of forward modeling and inverse design, utilizing AI for mapping metaphotonic device design and the corresponding optical properties. 2. Optical neural networks (ONNs), an emerging field that implements AI using metaphotonics by processing information within electromagnetic waves. 3. The field of metasensors, employing metamaterials to encode optical information for measurement and processing using AI to demonstrate high performance sensing. We round up the review with our perspectives on AI and metaphotonics research and discuss the future trends, challenges, and developments.</p></div>\",\"PeriodicalId\":295,\"journal\":{\"name\":\"Current Opinion in Solid State & Materials Science\",\"volume\":\"29 \",\"pages\":\"Article 101144\"},\"PeriodicalIF\":12.2000,\"publicationDate\":\"2024-02-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Current Opinion in Solid State & Materials Science\",\"FirstCategoryId\":\"88\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S135902862400010X\",\"RegionNum\":2,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MATERIALS SCIENCE, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current Opinion in Solid State & Materials Science","FirstCategoryId":"88","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S135902862400010X","RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATERIALS SCIENCE, MULTIDISCIPLINARY","Score":null,"Total":0}
Mapping information and light: Trends of AI-enabled metaphotonics
A dynamic convergence between metaphotonics and artificial intelligence (AI) is underway. In this review, AI is conceptualized as a tool for mapping input and output data. From this perspective, an analysis is conducted on how input and output data are set, aiming to discern the following three key trends in the utilization of AI within the field of metaphotonics. 1. The advancement of forward modeling and inverse design, utilizing AI for mapping metaphotonic device design and the corresponding optical properties. 2. Optical neural networks (ONNs), an emerging field that implements AI using metaphotonics by processing information within electromagnetic waves. 3. The field of metasensors, employing metamaterials to encode optical information for measurement and processing using AI to demonstrate high performance sensing. We round up the review with our perspectives on AI and metaphotonics research and discuss the future trends, challenges, and developments.
期刊介绍：
Title: Current Opinion in Solid State & Materials Science
Journal Overview:
Aims to provide a snapshot of the latest research and advances in materials science
Publishes six issues per year, each containing reviews covering exciting and developing areas of materials science
Each issue comprises 2-3 sections of reviews commissioned by international researchers who are experts in their fields
Provides materials scientists with the opportunity to stay informed about current developments in their own and related areas of research
Promotes cross-fertilization of ideas across an increasingly interdisciplinary field
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