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Liu et al. J Mater Inf 2024;4:33 https://dx.doi.org/10.20517/jmi.2024.48 Page 15 of 33

Table 4. List of popular databases available for photocatalyst design
Name Database details Data source
ICSD Inorganic Crystal Structure Database Published structures
CSD Crystal structure data of small molecule organic compounds and metal-organic Experiments
compounds
COD Organic, inorganic, metal-organic, and mineral structures Published and unpublished
structures
Materials Project Provide material crystal structure and physicochemical properties, as well as other Calculation using standard
calculation tools such as structures and phase diagrams calculation scheme
Chem Spider The structure of chemical organic materials Calculation and experiments
AFLOW Structure and properties High-throughput calculation
Harvard Clean Energy Properties of organic solar compounds High-throughput calculation
Project
Springer Materials High quality numerical database on material properties Published structures
MatWeb Material physical and chemical properties, grades Experiments
MatNavi Phase diagrams and properties of metals, inorganic non-metals, polymers, Calculation and experiments
superconductors, and other materials
Materials Cloud Open and seamless sharing of computing science resources Computational science
Khazana Structure and property, tools to design materials by learning from the data Calculation
NREL Materials Properties of materials for renewable energy applications Calculation
Database
Open Materials Electronic structure database for 3D organic crystals Calculation
Database
Open Quantum Thermodynamic and structural properties DFT calculation
Materials Database
Topological Materials Topology Material Database High-throughput computation
Database

DFT: Density functional theory.

Table 5. Typical descriptors for photocatalysts in deep-learning approach
Material Application Descriptors Ref.
MOFs Water splitting Morphology, pore structure, band structure, bandgap, VBM, CBM, carrier mobility [105]
Conjugated Hydrogen Morphology, surface functional groups, band structure, bandgap, VBM, CBM [106]
Polyelectrolytes production
Bi TiO Cefixime removal Morphology, size, specific surface area, space group, stoichiometry, band structure, [107]
12 20
bandgap
Bi O /MnO Acetaminophen Morphology, size, specific surface area, porous structure, surface functional groups, crystal [108]
2 3 2
degradation planes, band structure, light absorption coefficient, carrier mobility, carrier lifetime
g-C N NO removal Specific surface area, pore structure, doping atoms, bandgap, absorption wavelength [109]
3 4
TiO 2 Phenazopyridine Morphology, size, specific surface area, porous structure, surface functional groups, crystal [110]
ozonation face, band structure, light absorption coefficient, carrier mobility, carrier lifetime,
photocurrent density, absorption wavelength
ZnO Dye degradation Morphology, size, specific surface area, surface functional groups, crystal plane, lattice [111]
symmetry, space group, band structure, carrier mobility, carrier lifetime, light absorption
coefficient, absorption wavelength
TiO -biochar BB41 degradation Morphology, size, specific surface area, pore structure, surface functional groups, crystal [112]
2
plane, lattice symmetry, band structure, carrier mobility, light absorption coefficient,
absorption wavelength
2D materials Water splitting Size, band structure, bandgap, VBM, CBM, carrier mobility, carrier lifetime [113]
Co O /TiO MB degradation Morphology, size, surface functional groups [114]
3 4 2
VBM: Valence band maximum; CBM: conduction band minimum; MOFs: metal organic frameworks; MB: methylene blue; BB41: Basic Blue 41.

pore structure and surface functional groups. These features help establish nonlinear correlations between