DOI: 10.60732/6ff013d4
title: AENET_liquid_water_dataset_JCP2021

description: The water data set comprises energies and forces of 9,189 condensed-phase structures. The data was obtained in an iterative procedure described in detail in Ref. [4]. The final ANN potential was employed in Refs. [4,5] to analyze temperature-dependent Raman spectra of liquid water. The data set contains structures from four iterations: Initial structures (iteration 0) were obtained from classical and path integral AIMD simulations of bulk liquid water in a cubic box containing 64 water molecules at 300 K as reported in Ref. [6]. Distorted configurations with higher forces were added by randomly displacing the Cartesian coordinates of these configurations. Iteration 1 contains a set of 500 configurations from MD simulations with the fully flexible SPC/E flex water model [7] employing a 25 % increased water density (simulation box with 80 water molecules) and elevated temperatures (T = 500 K) in order to sample highly repulsive configurations. Structures in iteration 2 were obtained by classical MD simulations with preliminary ANN potentials at T = 300 K, 325 K, 350 K, and 370 K employing cubic boxes with 64 molecules and the corresponding experimental densities. The final iteration 3 data contains structures from preliminary ANN simulations with classical and quantum nuclei, respectively, at a wide range of temperatures (T = 258 K, 268 K, 280 K, 290 K, 300 K, 310 K, 320 K, 330 K, 340 K, 350 K, 360 K, and 370 K) using cubic boxes with 64 molecules and the corresponding experimental densities. Energies and atomic forces were calculated with the CP2K program [8,9] using the revPBE exchange-correlation functional [10,11] with D3 dispersion correction [12] following the setup reported in Ref. [4]. Atomic cores were represented using the dual-space Goedecker-Teter-Hutter pseudopotentials [13], Kohn-Sham orbitals were expanded in the TZV2P basis set within the GPW method [14], and the density was represented by an auxiliary plane-wave basis with a cutoff of 400 Ry. [1] A. Kokalj, J. Mol. Graphics Modell. 17, 176–179 (1999). [2] N. Artrith, A. Urban, Comput. Mater. Sci. 114, 135–150 (2016). [3] N. Artrith, A. Urban, G. Ceder, Phys. Rev. B 96, 014112 (2017). [4] T. Morawietz, O. Marsalek, S. R. Pattenaude, L. M. Streacker, D. Ben-Amotz, and T. E. Markland, J. Phys. Chem. Lett. 9, 851 (2018). [5] T. Morawietz, A. S. Urbina, P. K. Wise, X. Wu, W. Lu, D. Ben-Amotz, and T. E. Markland, J. Phys. Chem. Lett. 10, 6067 (2019). [6] Marsalek and T. E. Markland, J. Phys. Chem. Lett. 8, 1545 (2017). [7] X. B. Zhang, Q. L. Liu, and A. M. Zhu, Fluid Ph. Equilibria 262, 210(2007). [8] J. VandeVondele, M. Krack, F. Mohamed, M. Parrinello, T. Chassaing, and J. Hutter, Comput. Phys. Commun. 167, 103 (2005). [9] J. Hutter, M. Iannuzzi, F. Schiffmann, and J. VandeVondele, WIRES Comput. Mol. Sci. 4, 15 (2014). [10] J. P. Perdew, K. Burke, and M. Ernzerhof, Phys. Rev. Lett. 77, 3865 (1996). [11] Y. Zhang and W. Yang, Phys. Rev. Lett. 80, 890 (1998). [12] S. Grimme, J. Antony, S. Ehrlich, and H. Krieg, J. Chem. Phys. 132, 154104 (2010). [13] S. Goedecker, M. Teter, and J. Hutter, Phys. Rev. B 54, 1703 (1996). [14] B. G. Lippert, J. Hutter, and M. Parrinello, Mol. Phys. 92, 477 (1997).