{"title":"Baseline matching preprocessing of temperature perturbation infrared spectra.","authors":"Robert L White","doi":"10.1039/d5ay00196j","DOIUrl":null,"url":null,"abstract":"<p><p>An infrared spectrum baseline matching procedure that compensates for measurement drift and eliminates sloping baselines from sequentially acquired spectra is described. The theory underlying this procedure is provided and examples are given for three implementations based on infrared spectrum data sets containing at least 100 successively measured spectra. Consecutive spectra were acquired when the infrared beam contained: no sample, poly(styrene) powder, and a poly(styrene) film. The first two data sets consisted of 120 spectra and were used to characterize instrument reproducibility and identify short- and long-term measurement drifts. The 200 infrared spectra obtained while heating and then cooling a poly(styrene) film were subjected to baseline matching to reveal subtle temperature-dependent changes that are not evident when overlayed spectra are displayed. Baseline matching preprocessing is easily implemented on large numbers of similar spectra by using macro programming.</p>","PeriodicalId":64,"journal":{"name":"Analytical Methods","volume":" ","pages":""},"PeriodicalIF":2.7000,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Analytical Methods","FirstCategoryId":"92","ListUrlMain":"https://doi.org/10.1039/d5ay00196j","RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CHEMISTRY, ANALYTICAL","Score":null,"Total":0}
引用次数: 0
Abstract
An infrared spectrum baseline matching procedure that compensates for measurement drift and eliminates sloping baselines from sequentially acquired spectra is described. The theory underlying this procedure is provided and examples are given for three implementations based on infrared spectrum data sets containing at least 100 successively measured spectra. Consecutive spectra were acquired when the infrared beam contained: no sample, poly(styrene) powder, and a poly(styrene) film. The first two data sets consisted of 120 spectra and were used to characterize instrument reproducibility and identify short- and long-term measurement drifts. The 200 infrared spectra obtained while heating and then cooling a poly(styrene) film were subjected to baseline matching to reveal subtle temperature-dependent changes that are not evident when overlayed spectra are displayed. Baseline matching preprocessing is easily implemented on large numbers of similar spectra by using macro programming.
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