{"title":"利用机器学习算法对乳酸盐和肌钙蛋白 OFET 生物传感器的有效掺杂模型进行实验验证。","authors":"Sameh O. Abdellatif;Hana Mosalam;Salma A. Hussien","doi":"10.1109/TNANO.2024.3396505","DOIUrl":null,"url":null,"abstract":"As the interest in human health and customized medicine has grown recently, many researchers' investigations have concentrated on biosensors to develop a cost-effective device for sensing different medical parameters. Among the wide range of organic electronic devices, organic field effect transistor (OFET) has been used in manufacturing flexible biosensors due to their light weight, flexibility, and lower energy usage. In this study, a carrier transport electronic model, verified with experimental data, simulates the biosensing process in two different biosensors: lactate and troponin. Initially, a random forest machine learning model was used to optimize the OFET device with a new figure of merit. Consequently, the sensor's sensitivity and limit of detection were calculated. Two active layers were investigated: polyaniline and pentacene, where the polyaniline showed better sensitivity for lactate biosensor 220 (nM)\n<sup>-1</sup>\n and troponin 484 (g/ml)\n<sup>-1</sup>\n. Moreover, the polyaniline recorded nearly ten times lower power consumption because of its extremely low threshold voltage of -170 mV.","PeriodicalId":449,"journal":{"name":"IEEE Transactions on Nanotechnology","volume":"23 ","pages":"415-421"},"PeriodicalIF":2.1000,"publicationDate":"2024-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Experimentally Verified Effective Doping Model for Lactate and Troponin OFET Biosensors Using Machine Learning Algorithm\",\"authors\":\"Sameh O. Abdellatif;Hana Mosalam;Salma A. Hussien\",\"doi\":\"10.1109/TNANO.2024.3396505\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As the interest in human health and customized medicine has grown recently, many researchers' investigations have concentrated on biosensors to develop a cost-effective device for sensing different medical parameters. Among the wide range of organic electronic devices, organic field effect transistor (OFET) has been used in manufacturing flexible biosensors due to their light weight, flexibility, and lower energy usage. In this study, a carrier transport electronic model, verified with experimental data, simulates the biosensing process in two different biosensors: lactate and troponin. Initially, a random forest machine learning model was used to optimize the OFET device with a new figure of merit. Consequently, the sensor's sensitivity and limit of detection were calculated. Two active layers were investigated: polyaniline and pentacene, where the polyaniline showed better sensitivity for lactate biosensor 220 (nM)\\n<sup>-1</sup>\\n and troponin 484 (g/ml)\\n<sup>-1</sup>\\n. Moreover, the polyaniline recorded nearly ten times lower power consumption because of its extremely low threshold voltage of -170 mV.\",\"PeriodicalId\":449,\"journal\":{\"name\":\"IEEE Transactions on Nanotechnology\",\"volume\":\"23 \",\"pages\":\"415-421\"},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2024-03-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Nanotechnology\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10518140/\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Nanotechnology","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/10518140/","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Experimentally Verified Effective Doping Model for Lactate and Troponin OFET Biosensors Using Machine Learning Algorithm
As the interest in human health and customized medicine has grown recently, many researchers' investigations have concentrated on biosensors to develop a cost-effective device for sensing different medical parameters. Among the wide range of organic electronic devices, organic field effect transistor (OFET) has been used in manufacturing flexible biosensors due to their light weight, flexibility, and lower energy usage. In this study, a carrier transport electronic model, verified with experimental data, simulates the biosensing process in two different biosensors: lactate and troponin. Initially, a random forest machine learning model was used to optimize the OFET device with a new figure of merit. Consequently, the sensor's sensitivity and limit of detection were calculated. Two active layers were investigated: polyaniline and pentacene, where the polyaniline showed better sensitivity for lactate biosensor 220 (nM)
-1
and troponin 484 (g/ml)
-1
. Moreover, the polyaniline recorded nearly ten times lower power consumption because of its extremely low threshold voltage of -170 mV.
期刊介绍:
The IEEE Transactions on Nanotechnology is devoted to the publication of manuscripts of archival value in the general area of nanotechnology, which is rapidly emerging as one of the fastest growing and most promising new technological developments for the next generation and beyond.