Dataset

JARVIS_TinNet_OH




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Name :
JARVIS_TinNet_OH
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-OH 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 :
10.60732/401689c1 https://commons.datacite.org/doi.org/10.60732/401689c1 https://doi.datacite.org/dois/10.60732%2F401689c1 https://doi.org/10.60732/401689c1 Cite as: Wang, S., Pillai, H. S., Wang, S., Achenie, L. E. K., and Xin, H. "JARVIS TinNet OH." ColabFit, 2023. https://doi.org/10.60732/401689c1.
For other citation formats, see the DataCite Fabrica page for this dataset.
Num. Configurations :
748
Num. Atoms :
13,464
Downloads :
18
Calculated Property Types :
adsorption_energy cauchy_stress
Elements :
Ag (3.13%) Al (0.18%) Au (6.04%) Bi (0.1%) Cd (0.16%) Co (0.99%) Cr (0.7%) Cu (5.64%) Fe (0.42%) Ga (0.3%) H (5.56%) Hf (0.1%) In (0.19%) Ir (9.68%) La (0.1%) Mn (0.62%) Mo (1.15%) Nb (0.62%) Ni (6.45%) O (5.56%) Os (3.27%) Pb (0.1%) Pd (8.29%) Pt (12.89%) Re (5.69%) Rh (8.86%) Ru (4.35%) Sc (0.44%) Sn (0.21%) Ta (0.9%) Ti (0.88%) Tl (0.17%) V (0.94%) W (4.01%) Y (0.22%) Zn (0.53%) Zr (0.56%)
Methods :
DFT-PBE
Software :
Quantum ESPRESSO
Configuration Sets by Name :
Configuration Sets by ID :

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