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porous materials AI gym

open data sets for machine learning pertaining to porous materials.

  • MOF = metal-organic framework
  • COF = covalent organic framework

crystal structures

experimental

hypothetical

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 ?