{"title":"Differential impedance analysis — Extensions and applications in machine learning","authors":"","doi":"10.1016/j.electacta.2024.144720","DOIUrl":null,"url":null,"abstract":"<div><p>The technique of differential impedance analysis (DIA) has shown promising results in identifying appropriate model orders when applied to electrochemical impedance spectroscopy (EIS) measurements of a given medium. However, even with this method it remains challenging to reliably deduce general material properties of the medium from impedance data alone. Here, we discuss a number of possible extensions and modifications of the technique and, in particular, an extension of the process from mere model order identification to a complete modelling approach. In addition, the combination of DIA and machine learning methods to predict material properties is explored. Our results were validated with impedance measurements between 20<!--> <!-->Hz and 1<!--> <!-->MHz of moulding sand containing varying amounts of quartz and chromite sand as well as bentonite and carbon.</p></div>","PeriodicalId":305,"journal":{"name":"Electrochimica Acta","volume":null,"pages":null},"PeriodicalIF":5.5000,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0013468624009605/pdfft?md5=1d208c4fad43b381008e183fd0e4f310&pid=1-s2.0-S0013468624009605-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Electrochimica Acta","FirstCategoryId":"88","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0013468624009605","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ELECTROCHEMISTRY","Score":null,"Total":0}
引用次数: 0
Abstract
The technique of differential impedance analysis (DIA) has shown promising results in identifying appropriate model orders when applied to electrochemical impedance spectroscopy (EIS) measurements of a given medium. However, even with this method it remains challenging to reliably deduce general material properties of the medium from impedance data alone. Here, we discuss a number of possible extensions and modifications of the technique and, in particular, an extension of the process from mere model order identification to a complete modelling approach. In addition, the combination of DIA and machine learning methods to predict material properties is explored. Our results were validated with impedance measurements between 20 Hz and 1 MHz of moulding sand containing varying amounts of quartz and chromite sand as well as bentonite and carbon.
期刊介绍:
Electrochimica Acta is an international journal. It is intended for the publication of both original work and reviews in the field of electrochemistry. Electrochemistry should be interpreted to mean any of the research fields covered by the Divisions of the International Society of Electrochemistry listed below, as well as emerging scientific domains covered by ISE New Topics Committee.