Name: TiO2 CMS2016
License: CC0-1.0

Dataset

TiO2_CMS2016

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Name	TiO2_CMS2016
Extended ID	TiO2_CMS2016__Artrith-Urban__DS_kvjft3au55qb_0
Description	TiO2 dataset that was designed to build atom neural network potentials (ANN) by Artrith et al. using the AENET package. This dataset includes various crystalline phases of TiO2 and MD data that are extracted from ab inito calculations. The dataset includes 7815 structures with 165,229 atomic environments in the stochiometric ratio of 66% O to 34% Ti.
Authors	Nongnuch Artrith Alexander Urban
DOI	10.60732/861c6a25 https://commons.datacite.org/doi.org/10.60732/861c6a25 https://doi.datacite.org/dois/10.60732%2F861c6a25 https://doi.org/10.60732/861c6a25 Cite as: Artrith, N., and Urban, A. "TiO2 CMS2016." ColabFit, 2023. https://doi.org/10.60732/861c6a25. For other citation formats, see the DataCite Fabrica page for this dataset.
Calculated Property Types	atomic_forces cauchy_stress energy
Elements	O (65.68%) Ti (34.32%)
Number of Configurations	7,812
Number of Atoms	165,114
Links	https://github.com/DescriptorZoo/sensitivity-dimensionality-results/tree/master/datasets/TiO2 https://doi.org/10.1016/j.commatsci.2015.11.047
Configuration Sets by Name	(None)
Configuration Sets by ID	(None)
Calculated Properties	PO_1029471457227469774108165 PO_1051756038714464842836384 PO_1068712345789863317676167 PO_1073657662658137173157450 PO_1116867336998344335321773 PO_1165064580801665157767833 PO_1168152334383801786912872 PO_1185509702298951652652768 PO_1201953486744488186240056 PO_1252972185453010217947191 PO_1255450870273596315929614 PO_1275563710761187936678472 PO_1304658536443958404862134 PO_2262799468950652296102294 PO_2295342784720885592824452 PO_2295796293644860277085343 PO_2308673488651977505384304 PO_2363144696187663622144833 PO_3217770460897754082598349 PO_3414654039918559875198083 PO_3506715097642570430137416 PO_3620558454411579959394862 PO_3795541598921643431055042 PO_3887598063231324584055020 PO_4078529412353657418364584 PO_4091279951823465559592415 PO_4130415662734319831549002 PO_4667852449331305952413490 PO_4715679539744465458432070 PO_4877266873549047688926834 PO_5028269490954862475164051 PO_5075490804490133493881101 PO_6068549802629250061742270 PO_6084402850170842168549639 PO_6181175506516182194201769 PO_6367046868562893300132720 PO_6372260877422856110846241 PO_6471749210869338604434163 PO_6473624539856705778120453 PO_6642764044844014066064200 PO_6899874545816331751477449 PO_7743777757571980326048598 PO_7790358199452959610574430 PO_7814191575666892633543173 PO_7999808328113641697921401 PO_8490475190783694109358245 PO_8800675691634133042652604 PO_9293814317148109520663951 PO_9446134551044044689327040 PO_9603625645661270995969347 PO_9908212251192919018246151 PO_9935653813539182740683254
ColabFit ID	DS_kvjft3au55qb_0
Files	colabfitspec.json

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