{"title":"基于统一表面电位的对称双栅AlGaN/GaN MOS-HEMT无标记生物传感分析建模","authors":"P. Sriramani, N. Mohankumar, Y. Prasamsha","doi":"10.1109/EDKCON56221.2022.10032952","DOIUrl":null,"url":null,"abstract":"This paper presents an analytical surface potential-based drain current model for strong, weak and moderate inversion regions of AlGaN/GaN symmetrical Double gate Metal oxide semiconductor High electron mobility transistor (DG- MOSHEMT). The developed model considers the first and second sub-bands E0, E1 of the quantum well. The impact of drain bias variation on MOS-HEMT for biomedical applications reported for the first time. The developed model is used to analyze the device behavior for scalable physical parameters. Moreover, the developed model is validated by comparing the results with existing experimental data.","PeriodicalId":296883,"journal":{"name":"2022 IEEE International Conference of Electron Devices Society Kolkata Chapter (EDKCON)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Unified Surface Potential Based Analytical Modeling of Symmetrical Double Gate AlGaN/GaN MOS-HEMT for Label-Free Bio-Sensing\",\"authors\":\"P. Sriramani, N. Mohankumar, Y. Prasamsha\",\"doi\":\"10.1109/EDKCON56221.2022.10032952\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents an analytical surface potential-based drain current model for strong, weak and moderate inversion regions of AlGaN/GaN symmetrical Double gate Metal oxide semiconductor High electron mobility transistor (DG- MOSHEMT). The developed model considers the first and second sub-bands E0, E1 of the quantum well. The impact of drain bias variation on MOS-HEMT for biomedical applications reported for the first time. The developed model is used to analyze the device behavior for scalable physical parameters. Moreover, the developed model is validated by comparing the results with existing experimental data.\",\"PeriodicalId\":296883,\"journal\":{\"name\":\"2022 IEEE International Conference of Electron Devices Society Kolkata Chapter (EDKCON)\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-11-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE International Conference of Electron Devices Society Kolkata Chapter (EDKCON)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EDKCON56221.2022.10032952\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE International Conference of Electron Devices Society Kolkata Chapter (EDKCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EDKCON56221.2022.10032952","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Unified Surface Potential Based Analytical Modeling of Symmetrical Double Gate AlGaN/GaN MOS-HEMT for Label-Free Bio-Sensing
This paper presents an analytical surface potential-based drain current model for strong, weak and moderate inversion regions of AlGaN/GaN symmetrical Double gate Metal oxide semiconductor High electron mobility transistor (DG- MOSHEMT). The developed model considers the first and second sub-bands E0, E1 of the quantum well. The impact of drain bias variation on MOS-HEMT for biomedical applications reported for the first time. The developed model is used to analyze the device behavior for scalable physical parameters. Moreover, the developed model is validated by comparing the results with existing experimental data.