VibML

The deposited data sets were used to obtain representations<br> of potential energy surfaces (PESs) for eight representative<br> molecules using a neural network of the PhysNet type [1]. The<br> molecules under investigation are H2CO, trans-HONO, HCOOH,<br> CH3OH, CH3CHO, CH3NO2, CH3COOH and CH3CONH2. Reference data calculated at three different levels of quantum<br> chemical theory (MP2/aug-cc-pVTZ, CCSD(T)/aug-cc-pVTZ and<br> CCSD(T)-F12/aug-cc-pVTZ-F12) was used to train machine learning<br> (ML) models. Data sets at the MP2 level of theory were generated<br> for all molecules, at CCSD(T) level they were generated for<br> molecules with less than 7 atoms, and data sets at the CCSD(T)-F12<br> level of theory were generated for molecules with less than 6<br> atoms. The data sets contain different geometries for each<br> molecule generated using the normal mode sampling approach [2]<br> performed at different temperatures. The ab initio calculations<br> were performed using MOLPRO [3]. The performance of the PhysNet is then examined by considering<br> out-of-sample energy and force errors, harmonic frequencies in<br> comparison to explicit ab initio calculations and anharmonic<br> frequencies (obtained from a second order vibrational perturbation<br> theory (VPT2) analysis [4] as implemented in the Gaussian 09<br> suite [5]) in comparison to ab initio VPT2 calculations at the<br> MP2 level as well as to experiment. <br> For more details, see https://arxiv.org/abs/2103.05491 ---------------------------------------------------------------------------------------<br> HOW TO CITE: When using this dataset, please cite the following paper:<br> Käser, S. and Boittier, E. and Upadhyay, M. and Meuwly, M.<br> "MP2 Is Not Good Enough! Transfer Learning ML Models for<br> Accurate VPT2 Frequencies", arXiv:2103.05491. and the digital object identifier (DOI):<br> Käser, S. and Boittier, E. and Upadhyay, M. and Meuwly, M. (2021).<br> VibML. Zenodo. http://doi.org/10.5281/zenodo.4585449 --------------------------------------------------------------------------------------- [1] Unke, O. T.; Meuwly, M. J. Chem. Theory Comput. 2019, 15, 3678–3693<br> [2] Smith, J. S.; Isayev, O.; Roitberg, A. E. Sci. Data 2017, 4, 170193<br> [3] Werner, H.-J.; Knowles, P. J.; Knizia, G.; Manby, F. R.; Schütz, M.; et al. https://www.molpro.net<br> [4] Barone, V.; J. Chem. Phys. 2005, 122, 014108<br> [5] Frisch, M. J.; Trucks, G. W.; Schlegel, H. B.; Scuseria, G. E.; Robb, M. A.; Cheeseman, J. R.;<br> Scalmani, G.; Barone, V.; Mennucci, B.; Petersson, G. A. et al. Gaussian09 Revision E.01. Gaussian Inc.<br> Wallingford CT 2009