Carolina Materials contains structures used to train several machine learning models for the efficient generation of hypothetical inorganic materials. The database is built using structures from OQMD, Materials Project and ICSD, as well as ML generated structures validated by DFT.
Authors :
Yong Zhao, Mohammed Al-Fahdi, Ming Hu, Edirisuriya M. D. Siriwardane, Yuqi Song, Alireza Nasiri, Jianjun Hu
Name: Carolina_Materials
Extended ID: Carolina_Materials__Zhao-Al-Fahdi-Hu-Siriwardane-Song-Nasiri-Hu__DS_r2r8k3fyb6ny_0
Description: Carolina Materials contains structures used to train several machine learning models for the efficient generation of hypothetical inorganic materials. The database is built using structures from OQMD, Materials Project and ICSD, as well as ML generated structures validated by DFT.
Authors:
Yong Zhao
Mohammed Al-Fahdi
Ming Hu
Edirisuriya M. D. Siriwardane
Yuqi Song
Alireza Nasiri
Jianjun Hu
DOI: 10.60732/f2f98394
Calculated Property Types:
cauchy_stress
formation_energy
Elements:
Ag (0.85%)
Al (1.59%)
As (1.62%)
Au (1.24%)
B (1.74%)
Ba (0.48%)
Be (1.88%)
Bi (0.87%)
Br (2.2%)
C (1.53%)
Ca (0.74%)
Cd (1.0%)
Cl (2.32%)
Co (1.45%)
Cr (1.6%)
Cs (0.44%)
Cu (1.27%)
F (2.64%)
Fe (1.81%)
Ga (1.47%)
Ge (1.34%)
H (7.54%)
Hf (0.97%)
Hg (0.98%)
I (1.89%)
In (1.04%)
Ir (1.41%)
K (1.51%)
Li (1.91%)
Mg (1.17%)
Mn (1.41%)
Mo (1.16%)
N (1.79%)
Na (2.25%)
Nb (2.06%)
Ni (1.65%)
O (2.52%)
Os (1.3%)
P (1.93%)
Pb (0.62%)
Pd (1.2%)
Po (0.01%)
Pt (1.32%)
Rb (0.59%)
Re (1.37%)
Rh (1.55%)
Ru (1.37%)
S (2.44%)
Sb (1.33%)
Sc (1.12%)
Se (1.46%)
Si (4.39%)
Sn (1.07%)
Sr (0.54%)
Ta (1.12%)
Tc (1.44%)
Te (1.71%)
Ti (3.15%)
Tl (0.61%)
V (2.32%)
W (1.36%)
Y (0.89%)
Zn (1.25%)
Zr (1.22%)
Methods:
DFT-PBE
Software:
VASP
Number of Configurations: 214,267
Number of Atoms: 3,168,298
Publication Link: https://doi.org/10.1002/advs.202100566
Data Source Link: https://zenodo.org/records/8381476
Other Links:
http://www.carolinamatdb.org/
https://github.com/IntelLabs/matsciml
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