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Extended ID JARVIS_TinNet_OH_WangPillaiWangAchenieXin__DS_mk2e641eop9w_0
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

Cite as: Wang, S., Pillai, H. S., Wang, S., Achenie, L. E. K., and Xin, H. "JARVIS TinNet OH." ColabFit, 2023.
For other citation formats, see the DataCite Fabrica page for this dataset.
Elements Al (0.18%)
H (5.56%)
O (5.56%)
Ru (4.35%)
Ir (9.68%)
Pd (8.29%)
Cr (0.7%)
Cu (5.64%)
Pt (12.89%)
Rh (8.86%)
Re (5.69%)
Sc (0.44%)
Os (3.27%)
Ta (0.9%)
Mo (1.15%)
Ni (6.45%)
W (4.01%)
V (0.94%)
Au (6.04%)
Tl (0.17%)
Fe (0.42%)
Zn (0.53%)
Sn (0.21%)
Ag (3.13%)
Pb (0.1%)
Co (0.99%)
Ti (0.88%)
Nb (0.62%)
Y (0.22%)
Mn (0.62%)
Zr (0.56%)
La (0.1%)
Ga (0.3%)
Bi (0.1%)
In (0.19%)
Hf (0.1%)
Cd (0.16%)
Number of Data Objects 748
Number of Configurations 748
Number of Atoms 13,464
Configuration Sets by Name (None)
Configuration Sets by ID (None)
Data Objects
ColabFit ID DS_mk2e641eop9w_0
Files colabfitspec.json

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