Department of Earth, Atmospheric, and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, USA.
Phys Chem Chem Phys. 2019 Sep 11;21(35):18970-18987. doi: 10.1039/c8cp07057a.
Unambiguously identifying molecules in spectra is of fundamental importance for a variety of scientific and industrial uses. Interpreting atmospheric spectra for the remote detection of volatile compounds requires information about the spectrum of each relevant molecule. However, spectral data currently exist for a few hundred molecules and only a fraction of those have complete spectra (e.g. H2O, NH3). Consequently, molecular detections in atmospheric spectra remain vulnerable to false positives, false negatives, and missassignments. There is a key need for spectral data for a broad range of molecules. Given how challenging it is to obtain high-resolution molecular spectra, there is great value in creating intermediate approximate spectra that can provide a starting point for the analysis of atmospheric spectra. Using a combination of experimental measurements, organic chemistry, and quantum mechanics, RASCALL (Rapid Approximate Spectral Calculations for ALL) is a computational approach that provides approximate spectral data for any given molecule, including thousands of potential atmospheric gases. RASCALL is a new theoretical chemistry method for the simulation of spectral data. RASCALL 1.0, presented here, is capable of simulating molecular spectral data, in a few seconds, by interpreting functional group data from experimental and theoretical sources to estimate the position and strength of molecular bands. The RASCALL 1.0 spectra consist of approximate band centers and qualitative intensities. RASCALL 1.0 is also able to assess hundreds of molecules simultaneously, which will inform prioritization protocols for future, computationally and experimentally costly, high-accuracy physical chemistry studies. Finally, RASCALL can be used to study spectral patterns between molecules, highlighting ambiguities in molecular detections and also directing observations towards spectral regions that reduce the degeneracy in molecular identification. The RASCALL catalogue, and its preliminary version RASCALL 1.0, contains spectral data for more molecules than any other publicly available database, with applications in all fields interested in the detection of molecules in the gas phase (e.g., medical imaging, petroleum industry, pollution monitoring, astrochemistry). The preliminary catalogue of molecular data and associated documentation are freely available online and will be routinely updated.
明确鉴定光谱中的分子对于各种科学和工业应用都具有重要意义。为了实现对挥发性化合物的远程检测,需要了解每个相关分子的光谱信息。然而,目前仅有几百种分子的光谱数据,并且只有一部分分子具有完整的光谱(例如 H2O、NH3)。因此,大气光谱中的分子检测仍然容易出现假阳性、假阴性和误识别。因此,广泛的分子光谱数据非常重要。由于获得高分辨率分子光谱具有挑战性,因此创建能够为大气光谱分析提供起点的中间近似光谱具有重要价值。RASCALL(用于所有分子的快速近似光谱计算)是一种基于实验测量、有机化学和量子力学的计算方法,可为任何给定分子提供近似的光谱数据,包括数千种潜在的大气气体。RASCALL 是一种新的理论化学方法,用于模拟光谱数据。这里介绍的 RASCALL 1.0 能够通过解释来自实验和理论来源的官能团数据来模拟分子光谱数据,从而在几秒钟内估计分子带的位置和强度。RASCALL 1.0 光谱由近似的带中心和定性强度组成。RASCALL 1.0 还能够同时评估数百种分子,这将为未来计算和实验成本高昂的高精度物理化学研究提供优先级协议。最后,RASCALL 可用于研究分子之间的光谱模式,突出分子检测中的歧义,并指导观测朝向减少分子识别中简并性的光谱区域。RASCALL 目录及其初步版本 RASCALL 1.0 包含的分子光谱数据比任何其他公开数据库都多,适用于所有对气相分子检测感兴趣的领域(例如,医学成像、石油工业、污染监测、天体化学)。分子数据的初步目录及其相关文档可在线免费获取,并将定期更新。