Clusters of atmospheric relevance: H2O/HCl/HNO3. Prediction of IR & MW spectra
Literature Information
Pedro C. Gómez, Oscar Gálvez, Rafael G. Mosteo, Cristina Puzzarini, R. Escribano
Theoretical calculations at the B3LYP/aug-cc-pVQZ level are performed on ternary clusters of water, hydrogen chloride and nitric acid to predict their IR and MW spectra. The main IR spectral features and their changes in a set of 15 selected clusters are analyzed in terms of the different hydrogen bonding characteristics of the aggregates. The formation of these clusters in laboratory experiments and their possible identification based on their infrared and microwave spectral properties are discussed. Based on a calculation of the Gibbs free-energy of formation of the clusters from their monomers, the population distribution of the molecules at atmospherically relevant temperatures is evaluated, and the IR spectra of the composed mixture are predicted. The variations of specific spectral features with temperature are assessed, and the possible observation of these features is proposed as a means to detect the existence of these clusters, as well as an indication of the temperature of the corresponding atmospheric sample.
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Physical Chemistry Chemical Physics

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.












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