Pattern recognition as a new strategy in high-resolution spectroscopy: application to methanol OH-stretch overtones
文献信息
Jozef Rakovský, Ondrej Votava
We further develop a strategy for a line-by-line assignment of complex high-resolution overtone spectra. A search for specific line patterns in the spectrum allows to identify upper rotational states by extending the concept of ground state combination differences (GSCD). Simultaneous use of all GSCDs relating to a given upper state significantly reduces a probability of incorrect assignments. To test this approach, we have analysed a newly recorded spectrum of methanol in the first OH-stretch overtone region, 2νOH, between 7170 cm−1 and 7220 cm−1 at temperature of 19 K by combining a tunable-laser-diode absorption spectrometer with a slit-jet supersonic expansion. The spectrum consists of 1002 lines at this low temperature reflecting the fact that methanol is an asymmetric rotor with a hindered internal rotation. In total, 295 lines have been reliably assigned, representing 63% of the total intensity. Rotational energies and rotational quantum numbers for 52 upper states have been determined. Many of these states have the same quantum numbers, suggesting couplings to a manifold of 'dark' vibrational states in this overtone region.
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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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