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Name JARVIS_TinNet_O
Extended ID JARVIS_TinNet_O_WangPillaiWangAchenieXin__DS_ok9dbnj53zih_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-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

Cite as: Wang, S., Pillai, H. S., Wang, S., Achenie, L. E. K., and Xin, H. "JARVIS TinNet O." ColabFit, 2023.
For other citation formats, see the DataCite Fabrica page for this dataset.
Elements O (5.88%)
Pt (13.67%)
V (1.0%)
Fe (0.44%)
Ni (6.84%)
Ru (4.61%)
Rh (9.39%)
Au (6.4%)
Ta (0.95%)
Mo (1.22%)
Co (1.05%)
Os (3.46%)
Pd (8.79%)
Sc (0.37%)
W (4.25%)
Cd (0.17%)
Cu (5.98%)
Re (6.03%)
Ir (10.26%)
Cr (0.74%)
Mn (0.63%)
Zn (0.56%)
Pb (0.1%)
Sn (0.22%)
Y (0.24%)
Ag (3.32%)
Al (0.19%)
Ga (0.32%)
Bi (0.1%)
Ti (0.94%)
Nb (0.65%)
Tl (0.18%)
Hf (0.11%)
In (0.2%)
La (0.1%)
Zr (0.59%)
Number of Data Objects 747
Number of Configurations 747
Number of Atoms 12,699
Configuration Sets by Name (None)
Configuration Sets by ID (None)
Data Objects
ColabFit ID DS_ok9dbnj53zih_0
Files colabfitspec.json

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