Name: AENET liquid water dataset JCP2021
License: CC-BY-4.0

Dataset

AENET_liquid_water_dataset_JCP2021

Download Dataset XYZ files Download Dataset Parquet files

Name	AENET_liquid_water_dataset_JCP2021
Extended ID	AENET_liquid_water_dataset_JCP2021__Chen-Morawietz-Markland-Artrith__DS_v4bk24pq0had_0
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).
Authors	Michael S. Chen Tobias Morawietz Thomas E. Markland Nongnuch Artrith
DOI	10.60732/6ff013d4 https://commons.datacite.org/doi.org/10.60732/6ff013d4 https://doi.datacite.org/dois/10.60732%2F6ff013d4 https://doi.org/10.60732/6ff013d4 Cite as: Chen, M. S., Morawietz, T., Markland, T. E., and Artrith, N. "AENET liquid water dataset JCP2021." ColabFit, 2020. https://doi.org/10.60732/6ff013d4. For other citation formats, see the DataCite Fabrica page for this dataset.
Calculated Property Types	atomic_forces cauchy_stress energy
Elements	H (66.67%) O (33.33%)
Number of Configurations	9,189
Number of Atoms	1,788,288
Links	https://doi.org/10.24435/materialscloud:dx-ct http://doi.org/10.1063/5.0063880
Configuration Sets by Name	AENET_liquid_water_dataset_JCP2021_iteration_0 — Structures from iteration 0 from AENET_liquid_water_dataset_JCP2021 dataset AENET_liquid_water_dataset_JCP2021_iteration_1 — Structures from iteration 1 from AENET_liquid_water_dataset_JCP2021 dataset AENET_liquid_water_dataset_JCP2021_iteration_2 — Structures from iteration 2 from AENET_liquid_water_dataset_JCP2021 dataset AENET_liquid_water_dataset_JCP2021_iteration_3 — Structures from iteration 3 from AENET_liquid_water_dataset_JCP2021 dataset
Configuration Sets by ID	CS_b1jsrzeodyml_0 CS_f2sdavgkiyt5_0 CS_lgbojgi171m4_0 CS_slmp32xf2mha_0
Calculated Properties	PO_1040730139677730632013090 PO_1049005036174403277357332 PO_1086739005560584207971316 PO_1091881077733946495658032 PO_1131943784988999608210003 PO_1198043471408771927137483 PO_1215545429407698019361211 PO_1239849238870715899874513 PO_1308263714315228432173492 PO_1315193445584094857187562 PO_1456328505939802236961336 PO_2477843826190927200640594 PO_2549097863114072632675177 PO_2953403237699399671354530 PO_3614703540274158172117620 PO_3855431731054867454786062 PO_3881104233756772055623985 PO_4082390717328612903053019 PO_4258861524842066110865565 PO_4564827914021236673063406 PO_4652323649012946035835688 PO_4985794679728157661668343 PO_5452947518468946655662412 PO_5543990184079337684139589 PO_5577866520180558759703292 PO_6041151919324260411553307 PO_6261595347732842596231571 PO_6306115474851673129388593 PO_6476983268146237426345847 PO_6576936014762855995707683 PO_6823143939805679221327055 PO_7062564706778100854947084 PO_7092274200303700587211841 PO_7200891595768645872055544 PO_7311181441772690626263748 PO_7556878409989694291169343 PO_7590725350116678134478125 PO_8304304519555757459399525 PO_8545115444617534321055931 PO_8656343923250406778735549 PO_8823153804291968620787503 PO_9112505062618185882076169 PO_9296403000376024133689005 PO_9754782427677715014412868
ColabFit ID	DS_v4bk24pq0had_0
Files	colabfitspec.json

No uploaded content is transferred in ownership from the original creators to ColabFit. All content is distributed under the license specified by its contributor who has stated that he or she has the authority to share it under the specified license.