MARVEL analysis of high-resolution rovibrational spectra of 16O12C18O

IF 3.4 3区 化学 Q2 CHEMISTRY, MULTIDISCIPLINARY
Dunia Alatoom, Mohammad Taha I. Ibrahim, Tibor Furtenbacher, Attila G. Császár, M. Alghizzawi, Sergei N. Yurchenko, Ala'a A. A. Azzam, Jonathan Tennyson
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引用次数: 0

Abstract

Empirical rovibrational energy levels are presented for the third most abundant, asymmetric carbon dioxide isotopologue, 16O12C18O, based on a compiled dataset of experimental rovibrational transitions collected from the literature. The 52 literature sources utilized provide 19,438 measured lines with unique assignments in the wavenumber range of 2–12,676 cm−1. The MARVEL (Measured Active Rotational-Vibrational Energy Levels) protocol, which is built upon the theory of spectroscopic networks, validates the great majority of these transitions and outputs 8786 empirical rovibrational energy levels with an uncertainty estimation based on the experimental uncertainties of the transitions. Issues found in the literature data, such as misassignment of quantum numbers, typographical errors, and misidentifications, are fixed before including them in the final MARVEL dataset and analysis. Comparison of the empirical energy-level data of this study with those in the line lists CDSD-2019 and Ames-2021 shows good overall agreement, significantly better for CDSD-2019; some issues raised by these comparisons are discussed.

Abstract Image

对 16O12C18O 的高分辨率振动光谱进行 MARVEL 分析。
根据从文献中收集的实验振荡跃迁数据集,介绍了第三种最丰富的不对称二氧化碳同素异形体 16O12C18O 的经验振荡能级。所利用的 52 个文献来源提供了 19,438 条测量线,这些线在 2-12,676 cm-1 波长范围内具有独特的赋值。建立在光谱网络理论基础上的 MARVEL(主动旋转振动能级测量)协议验证了其中绝大多数的跃迁,输出了 8786 个经验旋转振动能级,并根据跃迁的实验不确定性进行了不确定性估计。在将文献数据纳入最终 MARVEL 数据集和分析之前,会对文献数据中发现的问题(如量子号的错误分配、排版错误和错误识别)进行修正。将本研究的经验能级数据与线表 CDSD-2019 和 Ames-2021 中的能级数据进行比较,结果表明两者总体上吻合,CDSD-2019 的吻合程度更高;本文还讨论了这些比较中提出的一些问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
6.60
自引率
3.30%
发文量
247
审稿时长
1.7 months
期刊介绍: This distinguished journal publishes articles concerned with all aspects of computational chemistry: analytical, biological, inorganic, organic, physical, and materials. The Journal of Computational Chemistry presents original research, contemporary developments in theory and methodology, and state-of-the-art applications. Computational areas that are featured in the journal include ab initio and semiempirical quantum mechanics, density functional theory, molecular mechanics, molecular dynamics, statistical mechanics, cheminformatics, biomolecular structure prediction, molecular design, and bioinformatics.
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