Sina S. Jamali , Yanfang Wu , Axel M. Homborg , Serge G. Lemay , J. Justin Gooding
{"title":"解释随机电化学数据","authors":"Sina S. Jamali , Yanfang Wu , Axel M. Homborg , Serge G. Lemay , J. Justin Gooding","doi":"10.1016/j.coelec.2024.101505","DOIUrl":null,"url":null,"abstract":"<div><p>Stochastic electrochemical measurement has come of age as a powerful analytical tool in corrosion science, electrophysiology, and single-entity electrochemistry. It relies on the fundamental trait that most electrochemical processes are stochastic and discrete in nature. Stochastic measurement of a single entity probes the charge transfer from a few or even one electroactive species. In corrosion, the stochastic measurements capture either the average amplitude/frequency of many events taking place spontaneously or probe discrete transients, signifying localized dissolution. The measurement principles vary in corrosion, single-entity, and electrophysiology, yet the main quantifiable values are commonly the frequency and amplitude of events. This perspective delves into the methodologies for the analysis and deconvolution of stochastic signals in electrochemistry. Ranging from visual assessment of transients to time/frequency analyses of the data and state-of-the-art machine learning, these methodologies mainly aim at identifying patterns, singular events, and rates of electrochemical processes from stochastic signals.</p></div>","PeriodicalId":11028,"journal":{"name":"Current Opinion in Electrochemistry","volume":null,"pages":null},"PeriodicalIF":7.9000,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2451910324000668/pdfft?md5=822cd80d950c944a1cb1a194964a16a3&pid=1-s2.0-S2451910324000668-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Interpretation of stochastic electrochemical data\",\"authors\":\"Sina S. Jamali , Yanfang Wu , Axel M. Homborg , Serge G. Lemay , J. Justin Gooding\",\"doi\":\"10.1016/j.coelec.2024.101505\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Stochastic electrochemical measurement has come of age as a powerful analytical tool in corrosion science, electrophysiology, and single-entity electrochemistry. It relies on the fundamental trait that most electrochemical processes are stochastic and discrete in nature. Stochastic measurement of a single entity probes the charge transfer from a few or even one electroactive species. In corrosion, the stochastic measurements capture either the average amplitude/frequency of many events taking place spontaneously or probe discrete transients, signifying localized dissolution. The measurement principles vary in corrosion, single-entity, and electrophysiology, yet the main quantifiable values are commonly the frequency and amplitude of events. This perspective delves into the methodologies for the analysis and deconvolution of stochastic signals in electrochemistry. Ranging from visual assessment of transients to time/frequency analyses of the data and state-of-the-art machine learning, these methodologies mainly aim at identifying patterns, singular events, and rates of electrochemical processes from stochastic signals.</p></div>\",\"PeriodicalId\":11028,\"journal\":{\"name\":\"Current Opinion in Electrochemistry\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":7.9000,\"publicationDate\":\"2024-04-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2451910324000668/pdfft?md5=822cd80d950c944a1cb1a194964a16a3&pid=1-s2.0-S2451910324000668-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Current Opinion in Electrochemistry\",\"FirstCategoryId\":\"92\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2451910324000668\",\"RegionNum\":2,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, PHYSICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current Opinion in Electrochemistry","FirstCategoryId":"92","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2451910324000668","RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, PHYSICAL","Score":null,"Total":0}
Stochastic electrochemical measurement has come of age as a powerful analytical tool in corrosion science, electrophysiology, and single-entity electrochemistry. It relies on the fundamental trait that most electrochemical processes are stochastic and discrete in nature. Stochastic measurement of a single entity probes the charge transfer from a few or even one electroactive species. In corrosion, the stochastic measurements capture either the average amplitude/frequency of many events taking place spontaneously or probe discrete transients, signifying localized dissolution. The measurement principles vary in corrosion, single-entity, and electrophysiology, yet the main quantifiable values are commonly the frequency and amplitude of events. This perspective delves into the methodologies for the analysis and deconvolution of stochastic signals in electrochemistry. Ranging from visual assessment of transients to time/frequency analyses of the data and state-of-the-art machine learning, these methodologies mainly aim at identifying patterns, singular events, and rates of electrochemical processes from stochastic signals.
期刊介绍:
The development of the Current Opinion journals stemmed from the acknowledgment of the growing challenge for specialists to stay abreast of the expanding volume of information within their field. In Current Opinion in Electrochemistry, they help the reader by providing in a systematic manner:
1.The views of experts on current advances in electrochemistry in a clear and readable form.
2.Evaluations of the most interesting papers, annotated by experts, from the great wealth of original publications.
In the realm of electrochemistry, the subject is divided into 12 themed sections, with each section undergoing an annual review cycle:
• Bioelectrochemistry • Electrocatalysis • Electrochemical Materials and Engineering • Energy Storage: Batteries and Supercapacitors • Energy Transformation • Environmental Electrochemistry • Fundamental & Theoretical Electrochemistry • Innovative Methods in Electrochemistry • Organic & Molecular Electrochemistry • Physical & Nano-Electrochemistry • Sensors & Bio-sensors •