ColabFit: Informatics for Advanced Materials and Chemistry

The ColabFit project aims to create a framework to facilitate the training and use of machine learning (ML) models in materials science including interatomic potentials. This includes an online exchange for datasets used to train ML models and a portable format for deploying ML models to simulation platforms using the OpenKIM system.

H
(36,826)
He
(1)
Li
(3)
Be
(2)
B
(5)
C
(36,791)
N
(36,311)
O
(36,743)
F
(2)
Ne
(1)
Na
(1,664)
Mg
(2)
Al
(3,032)
Si
(3,098)
P
(2,291)
S
(5,141)
Cl
(1,976)
Ar
(1)
K
(1,660)
Ca
(2,543)
Sc
(1,795)
Ti
(2,612)
V
(1,661)
Cr
(1,605)
Mn
(2,393)
Fe
(2,196)
Co
(2,368)
Ni
(2,633)
Cu
(2,188)
Zn
(2,033)
Ga
(2,412)
Ge
(2,362)
As
(1,993)
Se
(3,356)
Br
(1)
Kr
(1)
Rb
(937)
Sr
(1,808)
Y
(2,097)
Zr
(2,264)
Nb
(1,850)
Mo
(1,582)
Tc
(556)
Ru
(1,187)
Rh
(1,603)
Pd
(2,091)
Ag
(1,285)
Cd
(1,119)
In
(1,926)
Sn
(2,003)
Sb
(1,823)
Te
(2,471)
I
(1)
Xe
(1)
Cs
(957)
Ba
(1)
Hf
(1,853)
Ta
(1,228)
W
(858)
Re
(492)
Os
(571)
Ir
(1,053)
Pt
(1,611)
Au
(1,363)
Hg
(779)
Tl
(853)
Pb
(967)
Bi
(933)
PoAtRn
FrRaRfDbSgBhHsMtDsRgCnNhFlMcLvTsOg
LaCePrNdPmSmEuGdTbDyHoErTmYbLu
AcThPaUNpPuAmCmBkCfEsFmMdNoLr
Datasets

Dataset Atlas



Datasets
52
Configuration Sets
1,036

Property Instances
565,000,128
Configurations
188,306,722

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