open data sets for machine learning pertaining to porous materials.
- MOF = metal-organic framework
- COF = covalent organic framework
- MOFs: B&W (Paper, Database), ToBaCCo (Paper, Database, Code), hMOFs (Paper, Database), Anderson et al. (Paper, Database), MOF-5 analogues (Paper, Database), PORMAKE (Paper, Code)
- COFs: Mercado et al. (Paper, Database), Haranczyk's 3D COF database (Paper, Database)
labeled porous materials for supervised learning
material class |
target y |
features x provided? |
Reference |
size of data set |
MOFs (hypothetical) |
CO2, N2 adsorption (sim) |
yes |
Paper, Database |
ca. 325,000 |
MOFs (experimental and hypothetical) |
Band gaps, density of states, charge densities (sim) |
yes |
Paper, Database |
ca. 18,000 |
MOFs (experimental) |
Color (exp) |
yes |
Paper, Database |
? |
COFs (hypothetical) |
CH4 deliverable capacity (sim) |
yes, hand-crafted features provided. |
Paper, Database |
ca. 70,000 |
COFs (experimental) |
CH4, H2, O2, Xe, Kr, H2S adsorption (sim) |
? |
Paper |
ca. 500 |
labeled nodes for supervised learning
material class |
target y |
Reference |
size of data set (# materials) |
MOFs (experimental) |
DDEC6 charges on atoms (sim) |
Paper, Database |
ca. 3,000 |
MOFs (experimental and hypothetical) |
DDEC6/CM5/Bader charges on atoms (sim) |
Paper, Database |
ca. 18,000 (DDEC6/CM5), ca. 5,000 (Bader) |
MOFs (experimental and hypothetical) |
Effective bond orders on atoms (sim) |
Paper, Database |
ca. 18,000 |
MOFs (experimental) |
Formal oxidation states on atoms (exp) |
Paper, Database |
? |