jarvis.ai.descriptors.cfid ========================== .. py:module:: jarvis.ai.descriptors.cfid .. autoapi-nested-parse:: Classical Force-field Inspired Descriptors (CFID). The CFID provide a complete set of chemo-structural descriptors able to differentiate between structural prototypes. Specifically, the combination of pairwise radial, nearest neighbor, bond-angle, dihedral-angle and core-charge distributions, together with hundreds of chemistry-related descriptors, plays an important role in predicting formation energies, bandgaps, static refractive indices, magnetic properties, and modulus of elasticity for 3D materials as well as exfoliation energies of two-dimensional (2D) layered materials. The 1557 CFID are described in detail below: ============================================== =========== ============ Descriptor name Array_index Total number Chemical (mean_chem) 0-437 438 Simulation cell-size (cell) 438-441 4 Radial charge (mean_chg) 442-819 378 Radial distribution function (rdf) 820-919 100 Angular distribution upto 1st nn cutoff (adfa) 920-1098 179 Angular distribution upto 2nd nn cutoff (adfb) 1099-1277 179 Dihedral distribution upto 1st nn cutoff (ddf) 1278-1456 179 Nearest neighbor distribution (nn) 1457-1556 100 Total - 1557 ============================================== =========== ============ Details of element based chemical descriptors are below: =================== ================================================== Descriptor_name Details jv_enp Energy per atom of an element from JARVIS-DFT KV Bulk modulus of an element from JARVIS-DFT GV Shear modulus of an element from JARVIS-DFT C-m (m=0 to 35) Elastic constants of element from JARVIS-DFT (total 36) op_eg OptB88vdW bandgap during SCF for an element mop_eg OptB88vdW bandgap during linear optics for element voro_coord Voronoi coordination number of an elemental-crystal structure ndunfilled Number of unfilled d-orbitals ndvalence Number of valence d-orbitals nsunfilled Number of unfilled s-orbitals nsunfilled Number of valence s-orbitals npunfilled Number of unfilled p-orbitals npvalence Number of valence p-orbitals nfunfilled Number of unfilled f-orbitals nfvalence Number of valence f-orbitals first_ion First ionization energy of an element oq_bg OQMD bandgap for an element elec_aff Electron affinity vol_pa Volume per atom of an element hfus Heat of fusion of an element oq_enp OQMD energy per atom Polariz Polarizability Z Atomic number X Electronegativity row Row number in the periodic table column Column number in the periodic table max_oxid_s Maximum oxidation state min_oxid_s Minimum oxidation state block s,p,d,f block assigned to 0,1,2,3 blocks is_alkali Is it alkali element 0/1 is_alkaline Is it alkaline element 0/1 is_metalloid Is it metalloid element 0/1 is_noble_gas Is it noble gas element 0/1 is_transition_metal Is it transition element 0/1 is_metalloid Is it metalloid element 0/1 is_halogen Is it halogen element 0/1 is_lanthanoid Is it lanthanoid element 0/1 is_actinoid Is it actinoid element 0/1 atom_mass Atomic mass atom_rad Atomic radii therm_cond Thermal conductivity mol_vol Molar volume bp Boiling point mp Melting point avg_ion_rad Average ionic radii polzbl Polarizability e1 Static dielectric function in x-direction from JARVIS-DFT using OptB88vdW functional e2 Static dielectric function in y-direction from JARVIS-DFT using OptB88vdW functional e3 Static dielectric function in z-direction from JARVIS-DFT using OptB88vdW functional me1 Static dielectric function in x-direction from JARVIS-DFT using TB-mBJ potential me2 Static dielectric function in y-direction from JARVIS-DFT using TB-mBJ potential me3 Static dielectric function in z-direction from JARVIS-DFT using TB-mBJ potential =================== ================================================== Addition (‘add’), multiplications (‘mult’), subtraction (‘subs’) and quotient (‘divi’) of hfus, polzbl, first_ion_en, mol_vol, bp,mp, mol_vol, mol_vol, therm_cond and voro_coord were performed to give additional chemical descriptors. Details of simulation cell-size based descriptors are below: =============== ========================================= Descriptor_name Details cell_0 Volume per atom of the cell cell_1 Logarithm of volume per atom of the cell cell_2 Packing fraction cell_3 Density =============== ========================================= Find details in: https://journals.aps.org/prmaterials/abstract/10.1103/PhysRevMaterials.2.083801 Classes ------- .. autoapisummary:: jarvis.ai.descriptors.cfid.CFID Functions --------- .. autoapisummary:: jarvis.ai.descriptors.cfid.get_chem_only_descriptors jarvis.ai.descriptors.cfid.feat_names Module Contents --------------- .. py:function:: get_chem_only_descriptors(formula='Al2O3', extra=[], mean_only=False, max_only=False, min_only=False, source='cfid') Get jarvis_cfid or magpie descriptors for each formula. .. py:class:: CFID(atoms) Bases: :py:obj:`object` Convert Atoms class into 1557 descriptors. .. py:attribute:: _atoms .. py:method:: get_comp_descp(jcell=True, jmean_chem=True, jmean_chg=True, jrdf=False, jrdf_adf=True, print_names=False) Get chemo-structural CFID decriptors. Args: jcell: whether to use cell-size descriptors jmean_chem: whether to use average chemical descriptors jmean_chg: whether to use average charge distribution descriptors jmean_rdf: whether to use radial distribution descriptors jrdf_adf: whether to use radial and angle distribution descriptors print_names: whether to print names of descriptors Returns: cat: catenated final descriptors .. py:function:: feat_names() Names of the 1557 descriptors.