Thuc Anh Ngo, Tanju Yildirim, Meng-Qun Feng, Kosuke Minami, Kota Shiba, Genki Yoshikawa
{"title":"Empirical Modification of Force Fields for the Development of Peptide-Based Gas Sensors (Adv. Sensor Res. 4/2025)","authors":"Thuc Anh Ngo, Tanju Yildirim, Meng-Qun Feng, Kosuke Minami, Kota Shiba, Genki Yoshikawa","doi":"10.1002/adsr.202570008","DOIUrl":null,"url":null,"abstract":"<p><b>Empirical Force Fields Optimization for Gas Dynamics</b></p><p>In article 2400122, Thuc Anh Ngo, Genki Yoshikawa, and co-workers introduce an innovative artificial nose concept using peptide-based sensors for selective gas molecule detection. Optimized molecular modeling targets gas-phase interactions, enhancing detection accuracy. This approach offers potential applications in medical diagnostics, blending biology with advanced technology.\n\n <figure>\n <div><picture>\n <source></source></picture><p></p>\n </div>\n </figure></p>","PeriodicalId":100037,"journal":{"name":"Advanced Sensor Research","volume":"4 4","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/adsr.202570008","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advanced Sensor Research","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/adsr.202570008","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Empirical Force Fields Optimization for Gas Dynamics
In article 2400122, Thuc Anh Ngo, Genki Yoshikawa, and co-workers introduce an innovative artificial nose concept using peptide-based sensors for selective gas molecule detection. Optimized molecular modeling targets gas-phase interactions, enhancing detection accuracy. This approach offers potential applications in medical diagnostics, blending biology with advanced technology.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
