私密直播全婐app免费大渔直播,国产av成人无码免费视频,男女同房做爰全过程高潮,国产精品自产拍在线观看

當前位置:群英聚首 > 論文著作 > 正文
Machine learning-assisted carbon dots synthesis and analysis: State of the art and future directions
來源:卞?;劢淌趥€人網站 發布日期:2025-01-17
作者:Fanyong Yan*, Ruixue Bai, Juanru Huang, Xihui Bian, Yang Fu*
關鍵字:Carbon dots, Machine learning, Spectroscopy analysis, Optimized synthesis, Mechanistic elaboration
論文來源:期刊
具體來源:TrAC Trends in Analytical Chemistry, 2025, 184, 118141
發表時間:2025年

Carbon dots (CDs) are considered to be one of the key nanomaterials for novel sensors and detection platforms. While the limitations, including long synthesis cycles and complex data handling, still remain. The machine learning (ML), a powerful tool in accelerating analysis and optimizing results, exhibits elevated precision and generalizability, assumes a pivotal role when integrated with CDs. This review summarizes the recent advancements in ML-assisted CDs technologies, encompassing synthesis and analysis. It provides insight into model architecture, where traditional models are used for spectroscopy classification and quantification, while ensemble learning and neural networks improve modelling accuracy. Additionally, interspersed models and density functional theory (DFT) are integrated as needed. Paving the way for the application of ML in the synthesis, analysis, optimization, and elaboration of CDs. Lastly, the challenges and future prospects of the combination are described.

Copyright © 2005 Polymer.cn All rights reserved
中國聚合物網 版權所有
經營性網站備案信息

京公網安備11010502032929號

工商備案公示信息

京ICP證050801號

京ICP備12003651號

主站蜘蛛池模板: 文水县| 绵阳市| 遵化市| 宝兴县| 平利县| 阿克苏市| 德昌县| 南部县| 万山特区| 三亚市| 凭祥市| 博白县| 清水县| 射洪县| 奉化市| 宁武县| 沾益县| 嵊州市| 保德县| 安多县| 当雄县| 九江市| 长宁区| 贡嘎县| 广饶县| 普兰店市| 德格县| 兴国县| 宁陕县| 东安县| 繁峙县| 南澳县| 临江市| 洛扎县| 富锦市| 伊吾县| 东兴市| 宁化县| 莎车县| 永新县| 息烽县|