{"title":"VaporFit:用于FTIR光谱精确大气校正的开源软件","authors":"Przemysław Pastwa, Piotr Bruździak","doi":"10.1039/d5cp01007a","DOIUrl":null,"url":null,"abstract":"This paper introduces VaporFit, an open-source software for automated atmospheric interference correction in Fourier-transform infrared (FTIR) spectroscopy, based on a refined correction algorithm. It significantly improves the accuracy and reproducibility of chemical and biological FTIR analysis by effectively removing variable contributions from water vapor and carbon dioxide that often obscure spectral features. Unlike traditional methods relying on subtraction of a single reference spectrum, which struggle with atmospheric variability, VaporFit employs a multispectral least-squares approach to automatically optimize subtraction coefficients based on multiple atmospheric measurements recorded throughout the experiment. The software provides a user-friendly graphical interface (GUI) and built-in tools, including objective smoothness metrics and a Principal Component Analysis (PCA) module, to facilitate parameter selection and intuitively evaluate correction quality. Furthermore, we offer practical recommendations for data acquisition strategies tailored for effective atmospheric correction. VaporFit, the user guide, and sample data sets are freely available at https://zenodo.org/records/15411176 and https://github.com/piobruzdpg/VaporFit/releases/tag/v1.0.","PeriodicalId":99,"journal":{"name":"Physical Chemistry Chemical Physics","volume":"6 1","pages":""},"PeriodicalIF":2.9000,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"VaporFit: An Open-Source Software for Accurate Atmospheric Correction of FTIR Spectra\",\"authors\":\"Przemysław Pastwa, Piotr Bruździak\",\"doi\":\"10.1039/d5cp01007a\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper introduces VaporFit, an open-source software for automated atmospheric interference correction in Fourier-transform infrared (FTIR) spectroscopy, based on a refined correction algorithm. It significantly improves the accuracy and reproducibility of chemical and biological FTIR analysis by effectively removing variable contributions from water vapor and carbon dioxide that often obscure spectral features. Unlike traditional methods relying on subtraction of a single reference spectrum, which struggle with atmospheric variability, VaporFit employs a multispectral least-squares approach to automatically optimize subtraction coefficients based on multiple atmospheric measurements recorded throughout the experiment. The software provides a user-friendly graphical interface (GUI) and built-in tools, including objective smoothness metrics and a Principal Component Analysis (PCA) module, to facilitate parameter selection and intuitively evaluate correction quality. Furthermore, we offer practical recommendations for data acquisition strategies tailored for effective atmospheric correction. VaporFit, the user guide, and sample data sets are freely available at https://zenodo.org/records/15411176 and https://github.com/piobruzdpg/VaporFit/releases/tag/v1.0.\",\"PeriodicalId\":99,\"journal\":{\"name\":\"Physical Chemistry Chemical Physics\",\"volume\":\"6 1\",\"pages\":\"\"},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2025-05-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Physical Chemistry Chemical Physics\",\"FirstCategoryId\":\"92\",\"ListUrlMain\":\"https://doi.org/10.1039/d5cp01007a\",\"RegionNum\":3,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"CHEMISTRY, PHYSICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Physical Chemistry Chemical Physics","FirstCategoryId":"92","ListUrlMain":"https://doi.org/10.1039/d5cp01007a","RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"CHEMISTRY, PHYSICAL","Score":null,"Total":0}
VaporFit: An Open-Source Software for Accurate Atmospheric Correction of FTIR Spectra
This paper introduces VaporFit, an open-source software for automated atmospheric interference correction in Fourier-transform infrared (FTIR) spectroscopy, based on a refined correction algorithm. It significantly improves the accuracy and reproducibility of chemical and biological FTIR analysis by effectively removing variable contributions from water vapor and carbon dioxide that often obscure spectral features. Unlike traditional methods relying on subtraction of a single reference spectrum, which struggle with atmospheric variability, VaporFit employs a multispectral least-squares approach to automatically optimize subtraction coefficients based on multiple atmospheric measurements recorded throughout the experiment. The software provides a user-friendly graphical interface (GUI) and built-in tools, including objective smoothness metrics and a Principal Component Analysis (PCA) module, to facilitate parameter selection and intuitively evaluate correction quality. Furthermore, we offer practical recommendations for data acquisition strategies tailored for effective atmospheric correction. VaporFit, the user guide, and sample data sets are freely available at https://zenodo.org/records/15411176 and https://github.com/piobruzdpg/VaporFit/releases/tag/v1.0.
期刊介绍:
Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions.
The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.