Efficient Composite Infrared Spectroscopy: Combining the Double-Harmonic Approximation with Machine Learning Potentials

Vibrational spectroscopy is a cornerstone technique for molecular characterization and offers an ideal target for the computational investigation of molecular materials. Building on previous comprehensive assessments of efficient methods for infrared (IR) spectroscopy, this study investigates the pr...

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Bibliographic Details
Main Author:	Philipp Pracht (9523414) (author)
Other Authors:	Yuthika Pillai (20420740) (author), Venkat Kapil (5248616) (author), Gábor Csányi (1900057) (author), Nils Gönnheimer (20420743) (author), Martin Vondrák (20420746) (author), Johannes T. Margraf (1707877) (author), David J. Wales (246398) (author)
Published:	2024
Subjects:	Biophysics Biochemistry Space Science Biological Sciences not elsewhere classified Chemical Sciences not elsewhere classified Physical Sciences not elsewhere classified Information Systems not elsewhere classified throughput analytical workflows semiempirical extended tight previous comprehensive assessments diverse data set dipole moment prediction cost quantum mechanical corresponding vibrational modes advancing automated high molecular dipole moment combination squared derivatives efficient computational prediction computational investigation computational efficiency molecular materials molecular dipoles molecular characterization efficient methods unknown compounds systematically tested suitable protocol study investigates study aims reliable identification predictive accuracy particularly focus organic molecules methodical flexibility ideal target harmonic approximation cornerstone technique conventional low composite approach assessed across approach allows accuracy limitations
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Efficient Composite Infrared Spectroscopy: Combining the Double-Harmonic Approximation with Machine Learning Potentials

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