Databases

FigShare based databases

JARVIS databases

Database name	Number of data-points	Description
dft_3d	75993	Various 3D materials properties in JARVIS-DFT database computed with OptB88vdW and TBmBJ methods
dft_2d	1109	Various 2D materials properties in JARVIS-DFT database computed with OptB88vdW
dft_3d_2021	55723	Various 3D materials properties in JARVIS-DFT database computed with OptB88vdW and TBmBJ methods (2021 version)
dft_2d_2021	1079	Various 2D materials properties in JARVIS-DFT database computed with OptB88vdW (2021 version)
cfid_3d	55723	Various 3D materials properties in JARVIS-DFT database computed with OptB88vdW and TBmBJ methods with CFID
jff	2538	Various 3D materials properties in JARVIS-FF database computed with several force-fields
alignn_ff_db	307113	Energy per atom, forces and stresses for ALIGNN-FF training for 75k materials
edos_pdos	48469	Normalized electron and phonon density of states with interpolated values and fixed number of bins
qe_tb	829574	Various 3D materials properties in JARVIS-QETB database
supercon_3d	1058	3D superconductor DFT dataset
supercon_2d	161	2D superconductor DFT dataset
vacancydb	464	Vacancy formation energy dataset
surfacedb	607	Surface property dataset
interfacedb	593	Interface property dataset
ramandb	5000	Raman spectra dataset
raw_files	144895	Figshare links to download raw calculations VASP files from JARVIS-DFT
stm	1132	2D materials STM images in JARVIS-STM database
wtbh_electron	1440	3D and 2D materials Wannier tight-binding Hamiltonian database for electrons with spin-orbit coupling in JARVIS-WTB (Keyword: 'WANN')
wtbh_phonon	15502	3D and 2D materials Wannier tight-binding Hamiltonian for phonons at Gamma with finite difference (Keyword: FD-ELAST)

Alexandria databases

Database name	Number of data-points	Description
alex_pbe_hull	116k	Alexandria DB convex hull stable materials with PBE functional
alex_pbe_3d_all	5 million	Alexandria DB all 3D materials with PBE
alex_pbe_2d_all	200k	Alexandria DB all 2D materials with PBE
alex_pbe_1d_all	100k	Alexandria DB all 1D materials with PBE
alex_scan_3d_all	500k	Alexandria DB all 3D materials with SCAN
alex_pbesol_3d_all	500k	Alexandria DB all 3D materials with PBEsol
alex_supercon	8253	Alexandria superconductor database

RRUFF databases

Database name	Number of data-points	Description
rruff_powder_xrd	1362	RRUFF powder XRD dataset
rruff_raman_excellent	7688	RRUFF Raman spectra dataset
rruff_ir	824	RRUFF IR spectra dataset

Materials Project databases

Database name	Number of data-points	Description
mp_3d_2020	127k	CFID descriptors for materials project (2020)
mp_3d	84k	CFID descriptors for 84k materials project
megnet	69239	Formation energy and bandgaps of 3D materials properties in Materials project database as on 2018, used in megnet
megnet2	133k	133k materials and their formation energy in MP
m3gnet_mpf	168k	168k structures and their energy, forces and stresses in MP
m3gnet_mpf_1.5mil	1.5 million	1.5 million structures and their energy, forces and stresses in MP

OQMD databases

Database name	Number of data-points	Description
oqmd_3d	460k	CFID descriptors for 460k materials in OQMD
oqmd_3d_no_cfid	817636	Formation energies and bandgaps of 3D materials from OQMD database

Open Catalyst databases

Database name	Number of data-points	Description
ocp_all	510214	Open Catalyst 460328 training, rest validation and test dataset
ocp100k	149886	Open Catalyst 100000 training, rest validation and test dataset
ocp10k	59886	Open Catalyst 10000 training, rest validation and test dataset

Catalyst databases

Database name	Number of data-points	Description
AGRA_O	1000	AGRA Oxygen catalyst dataset
AGRA_OH	875	AGRA OH catalyst dataset
AGRA_COOH	280	AGRA COOH catalyst dataset
AGRA_CHO	214	AGRA CHO catalyst dataset
AGRA_CO	193	AGRA CO catalyst dataset
tinnet_N	329	TinNet Nitrogen catalyst dataset
tinnet_O	747	TinNet Oxygen catalyst dataset
tinnet_OH	748	TinNet OH group catalyst dataset

QM9 and molecular databases

Database name	Number of data-points	Description
qm9_std_jctc	130829	Various properties of molecules in QM9 database (standardized)
qm9_dgl	130829	Various properties of molecules in QM9 dgl database
qm9	134k	Various properties of molecules in QM9 database with CFID
hopv	4855	Various properties of molecules in HOPV15 dataset
pdbbind	11189	Bio-molecular complexes database from PDBBind v2015
pdbbind_core	195	Bio-molecular complexes database from PDBBind core
cccbdb	1333	NIST CCCBDB computational chemistry dataset

MOF databases

Database name	Number of data-points	Description
qmof	20425	Bandgaps and total energies of metal organic frameworks in QMOF database
hmof	137651	Hypothetical MOF database

2D materials databases (external)

Database name	Number of data-points	Description
c2db	3514	Various properties in C2DB database
twod_matpd	6351	Formation energy and bandgaps of 2D materials properties in 2DMatPedia database
mxene275	275	MXene dataset

Other materials databases

Database name	Number of data-points	Description
aflow2	400k	AFLOW dataset
cod	431778	Atomic structures from crystallographic open database
snumat	10481	Bandgaps with hybrid functional
polymer_genome	1073	Electronic bandgap and dielectric constants of crystalline polymers in polymer genome database
omdb	12500	Bandgaps for organic polymers in OMDB database
halide_peroskites	229	Halide perovskite dataset
supercon_chem	16414	Superconductor chemical formula dataset
mag2d_chem	226	Magnetic 2D materials chemical formula dataset
ssub	1726	SSUB formation energy for chemical formula dataset
mlearn	1730	Machine learning force-field for elements datasets
foundry_ml_exp_bandgaps	2069	Foundry ML experimental bandgaps dataset

Text and NLP databases

Database name	Number of data-points	Description
arXiv	1796911	arXiv dataset 1.8 million title, abstract and id dataset
arxiv_summary	137927	arXiv summary dataset (cond-mat)
cord19	223k	CORD-19 COVID-19 research articles dataset

All these datasets can be obtained using jarvis-tools as follows, exception to stm, wtbh_electron, wtbh_phonon which have their own modules in jarvis.db.figshare:

from jarvis.db.figshare import data
d = data('dft_3d') #choose a name of dataset from above
# See available keys
print (d[0].keys())
# Dataset size
print(len(d))

# Visualize an atoms object
from jarvis.core.atoms import Atoms
a = Atoms.from_dict(d[0]['atoms'])
#You can visualize this in VESTA or other similar packages
print(a)

# If pandas framework needed
import pandas as pd
df = pd.DataFrame(d)
print(df)