Palwinder Kaur, Isaac K. Stier, Sudeshna Bagchi, V. Pol, A. Bhondekar
{"title":"Impedimetric Early Sensing of Volatile Organic Compounds Released from Li-Ion Batteries at Elevated Temperatures","authors":"Palwinder Kaur, Isaac K. Stier, Sudeshna Bagchi, V. Pol, A. Bhondekar","doi":"10.3390/batteries9120562","DOIUrl":null,"url":null,"abstract":"Lithium-ion batteries prove to be a promising technology for achieving present and future goals regarding energy resources. However, a few cases of lithium-ion battery fires and failures caused by thermal runaway have been reported in various news articles; therefore, it is important to enhance the safety of the batteries and their end users. The early detection of thermal runaway by detecting gases/volatile organic compounds (VOCs) released at the initial stages of thermal runaway can be used as a warning to end users. An interdigitated platinum electrode spin-coated with a sub-micron thick layer of poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT: PSS) showed sensitivity for two VOCs (ethyl-methyl carbonate and methyl formate) released from Li-ion batteries during thermal runaway, as well as their binary mixtures at elevated temperatures, which were measured using impedance spectroscopy over a frequency range of 1 MHz to 1 Hz. The sensor response was tested at three different high temperatures (40 °C, 55 °C, and 70 °C) for single analytes and binary mixtures of two VOCs at 5 ppm, 15 ppm, and 30 ppm concentrations. Equivalent electrical parameters were derived from impedance data. A machine learning approach was used to classify the sensor’s response. Classification algorithms classify the sensor’s response at elevated temperatures for different analytes with an accuracy greater than 70%. The success of the reported sensors will enhance battery safety via the early detection of thermal runaway.","PeriodicalId":8755,"journal":{"name":"Batteries","volume":"6 1","pages":""},"PeriodicalIF":4.6000,"publicationDate":"2023-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Batteries","FirstCategoryId":"92","ListUrlMain":"https://doi.org/10.3390/batteries9120562","RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ELECTROCHEMISTRY","Score":null,"Total":0}
引用次数: 0
Abstract
Lithium-ion batteries prove to be a promising technology for achieving present and future goals regarding energy resources. However, a few cases of lithium-ion battery fires and failures caused by thermal runaway have been reported in various news articles; therefore, it is important to enhance the safety of the batteries and their end users. The early detection of thermal runaway by detecting gases/volatile organic compounds (VOCs) released at the initial stages of thermal runaway can be used as a warning to end users. An interdigitated platinum electrode spin-coated with a sub-micron thick layer of poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT: PSS) showed sensitivity for two VOCs (ethyl-methyl carbonate and methyl formate) released from Li-ion batteries during thermal runaway, as well as their binary mixtures at elevated temperatures, which were measured using impedance spectroscopy over a frequency range of 1 MHz to 1 Hz. The sensor response was tested at three different high temperatures (40 °C, 55 °C, and 70 °C) for single analytes and binary mixtures of two VOCs at 5 ppm, 15 ppm, and 30 ppm concentrations. Equivalent electrical parameters were derived from impedance data. A machine learning approach was used to classify the sensor’s response. Classification algorithms classify the sensor’s response at elevated temperatures for different analytes with an accuracy greater than 70%. The success of the reported sensors will enhance battery safety via the early detection of thermal runaway.