Tibor Furtenbacher, Roland Tóbiás, Jonathan Tennyson, Robert R Gamache, Attila G Császár
{"title":"<ArticleTitle xmlns:ns0=\"http://www.w3.org/1998/Math/MathML\">The W2024 database of the water isotopologue <ns0:math> <ns0:msubsup> <ns0:mrow> <ns0:mrow><ns0:mrow><ns0:mi>H</ns0:mi></ns0:mrow> </ns0:mrow> </ns0:mrow> <ns0:mrow><ns0:mn>2</ns0:mn></ns0:mrow> <ns0:mrow><ns0:mspace /> <ns0:mn>16</ns0:mn></ns0:mrow> </ns0:msubsup> <ns0:mrow><ns0:mrow><ns0:mi>O</ns0:mi></ns0:mrow> </ns0:mrow></ns0:math>.","authors":"Tibor Furtenbacher, Roland Tóbiás, Jonathan Tennyson, Robert R Gamache, Attila G Császár","doi":"10.1038/s41597-024-03847-3","DOIUrl":null,"url":null,"abstract":"<p><p>The rovibrational spectrum of the water molecule is the crown jewel of high-resolution molecular spectroscopy. While its significance in numerous scientific and engineering applications and the challenges behind its interpretation have been well known, the extensive experimental analysis performed for this molecule, from the microwave to the ultraviolet, is admirable. To determine empirical energy levels for <math> <msubsup> <mrow> <mrow><mrow><mi>H</mi></mrow> </mrow> </mrow> <mrow><mn>2</mn></mrow> <mrow><mspace></mspace> <mn>16</mn></mrow> </msubsup> <mrow><mrow><mi>O</mi></mrow> </mrow> </math> , this study utilizes an improved version of the MARVEL (Measured Active Rotational-Vibrational Energy Levels) scheme, which now takes into account multiplet constraints and first-principles energy-level splittings. This analysis delivers 19027 empirical energy values, with individual uncertainties and confidence intervals, utilizing 309 290 transition wavenumbers collected from 189 (mostly experimental) data sources. Relying on these empirical, as well as some computed, energies and first-principles intensities, an extensive composite line list, named CW2024, has been assembled. The CW2024 dataset is compared to lines in the canonical HITRAN 2020 spectroscopic database, providing guidance for future experimental investigations.</p>","PeriodicalId":21597,"journal":{"name":"Scientific Data","volume":null,"pages":null},"PeriodicalIF":5.8000,"publicationDate":"2024-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11439062/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scientific Data","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1038/s41597-024-03847-3","RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
The rovibrational spectrum of the water molecule is the crown jewel of high-resolution molecular spectroscopy. While its significance in numerous scientific and engineering applications and the challenges behind its interpretation have been well known, the extensive experimental analysis performed for this molecule, from the microwave to the ultraviolet, is admirable. To determine empirical energy levels for , this study utilizes an improved version of the MARVEL (Measured Active Rotational-Vibrational Energy Levels) scheme, which now takes into account multiplet constraints and first-principles energy-level splittings. This analysis delivers 19027 empirical energy values, with individual uncertainties and confidence intervals, utilizing 309 290 transition wavenumbers collected from 189 (mostly experimental) data sources. Relying on these empirical, as well as some computed, energies and first-principles intensities, an extensive composite line list, named CW2024, has been assembled. The CW2024 dataset is compared to lines in the canonical HITRAN 2020 spectroscopic database, providing guidance for future experimental investigations.
期刊介绍:
Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data.
The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.