{"title":"利用碳纳米管增强氧化锡气体传感器的室温传感性能:基于监督学习回归算法的高精度氨气分类。","authors":"Pil Gyu Choi, Akihiro Tsuruta, Toshio Itoh, Hirokuni Jintoku, Yoshitake Masuda","doi":"10.1021/acssensors.4c01902","DOIUrl":null,"url":null,"abstract":"<p><p>The sensing properties of tin oxide (SnO<sub>2</sub>) gas sensors, enhanced by the exploitation of carbon nanotubes (CNTs), were explored at room temperature. The CNT/tin oxide hybrid sensors demonstrated superior performance at room temperature compared to single-material sensors, particularly, showing a high response to ammonia gas. A sensor array was utilized for gas classification tests using PCA and various supervised learning regression algorithms. Results indicated that the CNTs/tin oxide hybrid sensors significantly outperformed the CNT sensor, offering lower detection limits and higher classification accuracy, making them highly suitable for practical ammonia gas monitoring applications. These findings indicate the high potential of CNTs/tin oxide hybrid sensors for reliable and efficient gas monitoring in various environments.</p>","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":" ","pages":""},"PeriodicalIF":9.1000,"publicationDate":"2025-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Enhanced Room Temperature Sensing Properties of Tin Oxide Gas Sensors Exploiting Carbon Nanotubes: High-Accuracy Ammonia Gas Classification via Supervised Learning Regression Algorithms.\",\"authors\":\"Pil Gyu Choi, Akihiro Tsuruta, Toshio Itoh, Hirokuni Jintoku, Yoshitake Masuda\",\"doi\":\"10.1021/acssensors.4c01902\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The sensing properties of tin oxide (SnO<sub>2</sub>) gas sensors, enhanced by the exploitation of carbon nanotubes (CNTs), were explored at room temperature. The CNT/tin oxide hybrid sensors demonstrated superior performance at room temperature compared to single-material sensors, particularly, showing a high response to ammonia gas. A sensor array was utilized for gas classification tests using PCA and various supervised learning regression algorithms. Results indicated that the CNTs/tin oxide hybrid sensors significantly outperformed the CNT sensor, offering lower detection limits and higher classification accuracy, making them highly suitable for practical ammonia gas monitoring applications. These findings indicate the high potential of CNTs/tin oxide hybrid sensors for reliable and efficient gas monitoring in various environments.</p>\",\"PeriodicalId\":24,\"journal\":{\"name\":\"ACS Sensors\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":9.1000,\"publicationDate\":\"2025-08-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Sensors\",\"FirstCategoryId\":\"92\",\"ListUrlMain\":\"https://doi.org/10.1021/acssensors.4c01902\",\"RegionNum\":1,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, ANALYTICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Sensors","FirstCategoryId":"92","ListUrlMain":"https://doi.org/10.1021/acssensors.4c01902","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, ANALYTICAL","Score":null,"Total":0}
Enhanced Room Temperature Sensing Properties of Tin Oxide Gas Sensors Exploiting Carbon Nanotubes: High-Accuracy Ammonia Gas Classification via Supervised Learning Regression Algorithms.
The sensing properties of tin oxide (SnO2) gas sensors, enhanced by the exploitation of carbon nanotubes (CNTs), were explored at room temperature. The CNT/tin oxide hybrid sensors demonstrated superior performance at room temperature compared to single-material sensors, particularly, showing a high response to ammonia gas. A sensor array was utilized for gas classification tests using PCA and various supervised learning regression algorithms. Results indicated that the CNTs/tin oxide hybrid sensors significantly outperformed the CNT sensor, offering lower detection limits and higher classification accuracy, making them highly suitable for practical ammonia gas monitoring applications. These findings indicate the high potential of CNTs/tin oxide hybrid sensors for reliable and efficient gas monitoring in various environments.
期刊介绍:
ACS Sensors is a peer-reviewed research journal that focuses on the dissemination of new and original knowledge in the field of sensor science, particularly those that selectively sense chemical or biological species or processes. The journal covers a broad range of topics, including but not limited to biosensors, chemical sensors, gas sensors, intracellular sensors, single molecule sensors, cell chips, and microfluidic devices. It aims to publish articles that address conceptual advances in sensing technology applicable to various types of analytes or application papers that report on the use of existing sensing concepts in new ways or for new analytes.