{"title":"碳点满足人工智能:在生物医学工程中的应用。","authors":"Yalei Guo, Yige Liu, Jiajin Yang, Yulu Wu, Haosen Lian, Xiufa Tang, Chunjie Li, Weitong Cui, Zhiyong Guo","doi":"10.1039/d5tb00593k","DOIUrl":null,"url":null,"abstract":"<p><p>Carbon dots (CDs) are fluorescent carbon nanomaterials typically less than 10 nm in size with excellent water solubility, low toxicity, high biocompatibility, favorable optical properties, and modifiable surface. CDs have great promise in various fields, including bioimaging, sensing, and drug delivery. With the emergence of artificial intelligence (AI) technologies, particularly machine learning (ML) and deep learning (DL) algorithms, new avenues for synthesis optimization, performance improvement, and accurate detection and diagnosis using CDs in biomedical engineering have been opened up. This article aims to present a comprehensive review of the applications of AI in CD research, from material design and performance optimization to material characterization and data analysis. It also addresses the possible areas of application for AI-assisted CDs in biomedical engineering, highlighting the importance and future directions of this interdisciplinary area of research. In addition, the potential role of CDs in advancing AI technologies such as optoelectronic storage devices and neuromorphic computing is explored, as well as the lasting impact of the convergence of CDs and AI on the future course of technological advancement.</p>","PeriodicalId":94089,"journal":{"name":"Journal of materials chemistry. B","volume":" ","pages":""},"PeriodicalIF":5.7000,"publicationDate":"2025-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Carbon dots meet artificial intelligence: applications in biomedical engineering.\",\"authors\":\"Yalei Guo, Yige Liu, Jiajin Yang, Yulu Wu, Haosen Lian, Xiufa Tang, Chunjie Li, Weitong Cui, Zhiyong Guo\",\"doi\":\"10.1039/d5tb00593k\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Carbon dots (CDs) are fluorescent carbon nanomaterials typically less than 10 nm in size with excellent water solubility, low toxicity, high biocompatibility, favorable optical properties, and modifiable surface. CDs have great promise in various fields, including bioimaging, sensing, and drug delivery. With the emergence of artificial intelligence (AI) technologies, particularly machine learning (ML) and deep learning (DL) algorithms, new avenues for synthesis optimization, performance improvement, and accurate detection and diagnosis using CDs in biomedical engineering have been opened up. This article aims to present a comprehensive review of the applications of AI in CD research, from material design and performance optimization to material characterization and data analysis. It also addresses the possible areas of application for AI-assisted CDs in biomedical engineering, highlighting the importance and future directions of this interdisciplinary area of research. In addition, the potential role of CDs in advancing AI technologies such as optoelectronic storage devices and neuromorphic computing is explored, as well as the lasting impact of the convergence of CDs and AI on the future course of technological advancement.</p>\",\"PeriodicalId\":94089,\"journal\":{\"name\":\"Journal of materials chemistry. B\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":5.7000,\"publicationDate\":\"2025-10-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of materials chemistry. B\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1039/d5tb00593k\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of materials chemistry. B","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1039/d5tb00593k","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Carbon dots meet artificial intelligence: applications in biomedical engineering.
Carbon dots (CDs) are fluorescent carbon nanomaterials typically less than 10 nm in size with excellent water solubility, low toxicity, high biocompatibility, favorable optical properties, and modifiable surface. CDs have great promise in various fields, including bioimaging, sensing, and drug delivery. With the emergence of artificial intelligence (AI) technologies, particularly machine learning (ML) and deep learning (DL) algorithms, new avenues for synthesis optimization, performance improvement, and accurate detection and diagnosis using CDs in biomedical engineering have been opened up. This article aims to present a comprehensive review of the applications of AI in CD research, from material design and performance optimization to material characterization and data analysis. It also addresses the possible areas of application for AI-assisted CDs in biomedical engineering, highlighting the importance and future directions of this interdisciplinary area of research. In addition, the potential role of CDs in advancing AI technologies such as optoelectronic storage devices and neuromorphic computing is explored, as well as the lasting impact of the convergence of CDs and AI on the future course of technological advancement.