Dataset
Matbench_mp_e_form
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137.8 MB
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128.3 MB
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Name :
Matbench_mp_e_form
ColabFit ID :
Files :
Description :
Matbench v0.1 test dataset for predicting DFT formation energy from structure. Adapted from Materials Project database. Entries having formation energy more than 2.5eV and those containing noble gases are removed. Retrieved April 2, 2019. For benchmarking w/ nested cross validation, the order of the dataset must be identical to the retrieved data; refer to the Automatminer/Matbench publication for more details.Matbench is an automated leaderboard for benchmarking state of the art ML algorithms predicting a diverse range of solid materials' properties. It is hosted and maintained by the Materials Project.
Authors :
Alexander Dunn, Qi Wang, Alex Ganose, Daniel Dopp, Anubhav Jain
DOI :
10.60732/3cef7b09
https://commons.datacite.org/doi.org/10.60732/3cef7b09
https://doi.datacite.org/dois/10.60732%2F3cef7b09
https://doi.org/10.60732/3cef7b09
Cite as: Dunn, A., Wang, Q., Ganose, A., Dopp, D., and Jain, A. "Matbench mp e form." ColabFit, 2024. https://doi.org/10.60732/3cef7b09.
For other citation formats, see the DataCite Fabrica page for this dataset.
For other citation formats, see the DataCite Fabrica page for this dataset.
Num. Configurations :
132,741
Num. Atoms :
3,869,238
Downloads :
145
Calculated Property Types :
cauchy_stress
formation_energy
Elements :
Ac (0.02%)
Ag (0.37%)
Al (1.23%)
As (0.55%)
Au (0.21%)
B (1.51%)
Ba (0.79%)
Be (0.17%)
Bi (0.57%)
Br (0.72%)
C (2.32%)
Ca (0.77%)
Cd (0.37%)
Ce (0.32%)
Cl (1.75%)
Co (1.15%)
Cr (0.59%)
Cs (0.4%)
Cu (0.97%)
Dy (0.22%)
Er (0.23%)
Eu (0.15%)
F (3.66%)
Fe (1.59%)
Ga (0.6%)
Gd (0.14%)
Ge (0.77%)
H (5.93%)
Hf (0.19%)
Hg (0.27%)
Ho (0.22%)
I (0.75%)
In (0.4%)
Ir (0.18%)
K (0.93%)
La (0.56%)
Li (2.91%)
Lu (0.16%)
Mg (2.62%)
Mn (1.34%)
Mo (0.66%)
N (2.21%)
Na (1.17%)
Nb (0.47%)
Nd (0.32%)
Ni (1.02%)
Np (0.03%)
O (35.82%)
Os (0.1%)
P (2.79%)
Pa (0.01%)
Pb (0.33%)
Pd (0.31%)
Pm (0.02%)
Pr (0.29%)
Pt (0.24%)
Pu (0.04%)
Rb (0.49%)
Re (0.16%)
Rh (0.27%)
Ru (0.22%)
S (2.99%)
Sb (0.63%)
Sc (0.22%)
Se (1.44%)
Si (1.87%)
Sm (0.26%)
Sn (0.63%)
Sr (0.65%)
Ta (0.29%)
Tb (0.21%)
Tc (0.04%)
Te (0.69%)
Th (0.09%)
Ti (0.71%)
Tl (0.26%)
Tm (0.16%)
U (0.24%)
V (0.95%)
W (0.41%)
Y (0.4%)
Yb (0.21%)
Zn (0.7%)
Zr (0.36%)
Methods :
DFT-undefined
Software :
VASP
Publication Link :
Data Source Link :
Other Links :
Configuration Sets by Name :
Configuration Sets by ID :
Name: Matbench_mp_e_form
Extended ID: Matbench_mp_e_form__Dunn-Wang-Ganose-Dopp-Jain__DS_5drebe4tktiu_0
Description: Matbench v0.1 test dataset for predicting DFT formation energy from structure. Adapted from Materials Project database. Entries having formation energy more than 2.5eV and those containing noble gases are removed. Retrieved April 2, 2019. For benchmarking w/ nested cross validation, the order of the dataset must be identical to the retrieved data; refer to the Automatminer/Matbench publication for more details.Matbench is an automated leaderboard for benchmarking state of the art ML algorithms predicting a diverse range of solid materials' properties. It is hosted and maintained by the Materials Project.
Authors:
Alexander Dunn
Qi Wang
Alex Ganose
Daniel Dopp
Anubhav Jain
DOI: 10.60732/3cef7b09
Calculated Property Types:
cauchy_stress
formation_energy
Elements:
Ac (0.02%)
Ag (0.37%)
Al (1.23%)
As (0.55%)
Au (0.21%)
B (1.51%)
Ba (0.79%)
Be (0.17%)
Bi (0.57%)
Br (0.72%)
C (2.32%)
Ca (0.77%)
Cd (0.37%)
Ce (0.32%)
Cl (1.75%)
Co (1.15%)
Cr (0.59%)
Cs (0.4%)
Cu (0.97%)
Dy (0.22%)
Er (0.23%)
Eu (0.15%)
F (3.66%)
Fe (1.59%)
Ga (0.6%)
Gd (0.14%)
Ge (0.77%)
H (5.93%)
Hf (0.19%)
Hg (0.27%)
Ho (0.22%)
I (0.75%)
In (0.4%)
Ir (0.18%)
K (0.93%)
La (0.56%)
Li (2.91%)
Lu (0.16%)
Mg (2.62%)
Mn (1.34%)
Mo (0.66%)
N (2.21%)
Na (1.17%)
Nb (0.47%)
Nd (0.32%)
Ni (1.02%)
Np (0.03%)
O (35.82%)
Os (0.1%)
P (2.79%)
Pa (0.01%)
Pb (0.33%)
Pd (0.31%)
Pm (0.02%)
Pr (0.29%)
Pt (0.24%)
Pu (0.04%)
Rb (0.49%)
Re (0.16%)
Rh (0.27%)
Ru (0.22%)
S (2.99%)
Sb (0.63%)
Sc (0.22%)
Se (1.44%)
Si (1.87%)
Sm (0.26%)
Sn (0.63%)
Sr (0.65%)
Ta (0.29%)
Tb (0.21%)
Tc (0.04%)
Te (0.69%)
Th (0.09%)
Ti (0.71%)
Tl (0.26%)
Tm (0.16%)
U (0.24%)
V (0.95%)
W (0.41%)
Y (0.4%)
Yb (0.21%)
Zn (0.7%)
Zr (0.36%)
Methods:
DFT-undefined
Software:
VASP
Number of Configurations: 132,741
Number of Atoms: 3,869,238
Publication Link: https://doi.org/10.1038/s41524-020-00406-3
Data Source Link: https://matbench.materialsproject.org/
Other Links:
https://doi.org/10.1016/j.commatsci.2014.10.037
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