Linear–Cyclic Isomer Competition in Protonated Ethanol–Methanol Clusters Probed by Infrared Spectroscopy and Deep Learning Structural and Dynamical Simulations
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引用次数: 0
Abstract
The competition between linear and cyclic isomer structures in the protonated ethanol tetramer has been investigated using spectroscopic and theoretical approaches. Infrared spectroscopy of protonated ethanol–methanol mixed tetramers, cooled by the inert gas tagging technique, revealed a significant dependence of the isomer structure competition on the mixing ratio and the tag species. To investigate isomer competition, structure searches were performed using the parallelized Basin-Hopping algorithm with neural network potentials that approximate the accuracy of density functional theory. Spectral simulations were conducted via harmonic vibrational analysis of key stable isomers using density functional theory and power spectral density calculations from molecular dynamics trajectories based on the neural network potentials. Comparison with experimental data reveals that the global minimum of the protonated ethanol tetramer is a linear structure. Additionally, the tag species significantly influences the relative stability of linear and cyclic isomers, as well as the isomerization barrier between these two structures.
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.