Abstract
High-level ab initio quantum chemical (QC) molecular potential energy surfaces (PESs) are crucial for accurately simulating molecular rotation-vibration spectra. Machine learning (ML) can help alleviate the cost of constructing such PESs, but requires access to the original ab initio PES data, namely potential energies computed on high-density grids of nuclear geometries. In this work, we present a new structured PES database called VIB5, which contains high-quality ab initio data on 5 small polyatomic molecules of astrophysical significance (CH3Cl, CH4, SiH4, CH3F, and NaOH). The VIB5 database is based on previously used PESs, which, however, are either publicly unavailable or lacking key information to make them suitable for ML applications. The VIB5 database provides tens of thousands of grid points for each molecule with theoretical best estimates of potential energies along with their constituent energy correction terms and a data-extraction script. In addition, new complementary QC calculations of energies and energy gradients have been performed to provide a consistent database, which, e.g., can be used for gradient-based ML methods.
Highlights
Many physical and chemical processes of molecular systems are governed by potential energy surfaces (PESs) that are functions of potential energy with respect to the molecular geometry defined by the nuclei[1]
This can be achieved by defining the PES on a high-density grid of nuclear geometries with no holes and having the theoretical best estimate (TBE) of energies computed at a very high quantum chemical (QC) level of theory
The choice of QC level for TBE calculations is determined by the trade-off between accuracy and computational cost, but typically requires going well beyond the gold-standard[17–19] CCSD(T)17/complete basis set (CBS) limit and needs many QC corrections on top of it
Summary
Many physical and chemical processes of molecular systems are governed by potential energy surfaces (PESs) that are functions of potential energy with respect to the molecular geometry defined by the nuclei[1]. It is necessary to have a global PES covering all relevant regions of nuclear configurations allowing to simulate rotation-vibration (rovibrational) spectra approaching the coveted spectroscopic accuracy of 1 cm−1 in a broad range of temperatures This can be achieved by defining the PES on a high-density grid of nuclear geometries with no holes and having the theoretical best estimate (TBE) of energies computed at a very high QC level of theory. PESs generated from MD are, likely to have limited coverage of high-energy geometries and many holes, making them inapplicable to some kinds of accurate simulations such as diffusion Monte Carlo calculations as was pointed out recently[47] In contrast to these databases, our database provides reliable, global PESs with QC energies and energy gradients at different levels including very accurate TBEs of energies going beyond CCSD(T)/CBS, which can be used for ML models trained on data from several levels of theory, such as hML, Δ-learning, etc. Our database comes with a convenient data-extraction script that can be used to pull the required information in a suitable format for, e.g., ML
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
