Publications by authors named "Martin Vondrak"
Article Synopsis
- Vibrational spectroscopy is a key method for analyzing molecular structures, and this study looks at improving how accurately we can predict gas-phase infrared (IR) spectra using advanced computational techniques.
- A new approach combines harmonic vibrational frequencies and molecular dipole moment calculations, allowing flexibility in how we determine IR intensities.
- The study tests various methods, including semiempirical models and machine learning potentials, to find an efficient protocol for predicting IR spectra, with a focus on enhancing the accuracy of existing low-cost computational methods.
Many state-of-the art machine learning (ML) interatomic potentials are based on a local or semi-local (message-passing) representation of chemical environments. They, therefore, lack a description of long-range electrostatic interactions and non-local charge transfer. In this context, there has been much interest in developing ML-based charge equilibration models, which allow the rigorous calculation of long-range electrostatic interactions and the energetic response of molecules and materials to external fields.
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