Dataset

JARVIS_TinNet_O




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Name :
JARVIS_TinNet_O
ColabFit ID :
Description :
The JARVIS_TinNet dataset is part of the joint automated repository for various integrated simulations (JARVIS) database. This dataset contains configurations from the TinNet-O dataset: a collection assembled to train a machine learning model for the purposes of assisting catalyst design by predicting chemical reactivity of transition-metal surfaces. The adsorption systems contained in this dataset consist of {111}-terminated metal surfaces. JARVIS is a set of tools and collected datasets built to meet current materials design challenges.
Authors :
Shih-Han Wang, Hemanth Somarajan Pillai, Siwen Wang, Luke E. K. Achenie, Hongliang Xin
DOI :
10.60732/9541fb8b https://commons.datacite.org/doi.org/10.60732/9541fb8b https://doi.datacite.org/dois/10.60732%2F9541fb8b https://doi.org/10.60732/9541fb8b Cite as: Wang, S., Pillai, H. S., Wang, S., Achenie, L. E. K., and Xin, H. "JARVIS TinNet O." ColabFit, 2023. https://doi.org/10.60732/9541fb8b.
For other citation formats, see the DataCite Fabrica page for this dataset.
Num. Configurations :
747
Num. Atoms :
12,699
Downloads :
14
Calculated Property Types :
adsorption_energy cauchy_stress
Elements :
Ag (3.32%) Al (0.19%) Au (6.4%) Bi (0.1%) Cd (0.17%) Co (1.05%) Cr (0.74%) Cu (5.98%) Fe (0.44%) Ga (0.32%) Hf (0.11%) In (0.2%) Ir (10.26%) La (0.1%) Mn (0.63%) Mo (1.22%) Nb (0.65%) Ni (6.84%) O (5.88%) Os (3.46%) Pb (0.1%) Pd (8.79%) Pt (13.67%) Re (6.03%) Rh (9.39%) Ru (4.61%) Sc (0.37%) Sn (0.22%) Ta (0.95%) Ti (0.94%) Tl (0.18%) V (1.0%) W (4.25%) Y (0.24%) Zn (0.56%) Zr (0.59%)
Methods :
DFT-PBE
Software :
Quantum ESPRESSO
Configuration Sets by Name :
Configuration Sets by ID :

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