Ranking phase fields by likelihood with ICSD patterns

Andrij Vasylenko 13.08.2020

Install: >>> pip install . Usage: >>> python ranking_phase_fields.py <input_file>

Supported methods for pattern detection are based on PyOD library

Models:

'AE' : AutoEncoder 'VAE' : Variational AE 'ABOD' : Angle-based outlier detection 'FeatureBagging' : FeatureBagging 'HBOS' : Histogram-Based Outlier Score 'IForest' : Isolation Forest 'KNN' : K-Nearest Neighbours 'LOF' : Local Outlier Factor 'OCSVM' : OCSupport Vector Machine 'PCA' : Principle Component Analysis 'SOS' : SOS(), 'COF' : Connectivity-based OF(), 'CBLOF' : Clustering-Based LOF 'SOD' : SOD(), 'LOCI' : LOCI(), 'MCD' : MCD()

Read more about these methods https://www.pyod.readthedocs.io

[1] Zhao, Y., Nasrullah, Z. and Li, Z., PyOD: A Python Toolbox for Scalable Outlier Detection. Journal of machine learning research 20(96), pp.1-7 (2019).

Supported elemental features:

TABLES/AtomicVolume.table TABLES/AtomicWeight.table TABLES/BCCbandgap.table TABLES/BCCefflatcnt.table TABLES/BCCenergy_pa.table TABLES/BCCenergydiff.table TABLES/BCCfermi.table TABLES/BCCmagmom.table TABLES/BCCvolume_pa.table TABLES/BCCvolume_padiff.table TABLES/BoilingT.table TABLES/Column.table TABLES/CovalentRadius.table TABLES/Density.table TABLES/Electronegativity.table TABLES/FirstIonizationEnergy.table TABLES/GSbandgap.table TABLES/GSefflatcnt.table TABLES/GSenergy_pa.table TABLES/GSestBCClatcnt.table TABLES/GSestFCClatcnt.table TABLES/GSmagmom.table TABLES/GSvolume_pa.table TABLES/ICSDVolume.table TABLES/MeltingT.table TABLES/MendeleevNumber.table TABLES/MiracleRadius.table TABLES/NUnfilled.table TABLES/NValance.table TABLES/NdUnfilled.table TABLES/NdValence.table TABLES/NfUnfilled.table TABLES/NfValence.table TABLES/NpUnfilled.table TABLES/NpValence.table TABLES/NsUnfilled.table TABLES/NsValence.table TABLES/Number.table TABLES/Pettifor.table TABLES/Polarizability.table TABLES/Row.table

[2] Jha, D., Ward, L., Paul, A. et al. ElemNet: Deep Learning the Chemistry of Materials From Only Elemental Composition. Sci Rep 8, 17593 (2018). https://doi.org/10.1038/s41598-018-35934-y [3] Glawe, H., Sanna, A., Gross, E. K. U., Marques, M. A. L., The optimal one dimensional periodic table: a modified Pettifor chemical scale from data mining. N. J. Phys. 18, 093011 (2016). https://doi.org/10.1088/1367-2630/18/9/093011

Parameters of the input file (default values are in rpp.input file)

icsd_file : (default: icsd2017) ICSD excerpt. A text file, a list of ICSD .cif files
with specified oxidation states for each element.
phase_fields : (default: quaternary) binary, ternary, quaternary - are supported.
Type of phase fields to investigate.
cations_train : (default: all) list of elements constituting a phase field in ICSD.
Elements in the first positions (cations), e.g. elements for M and M' in MM'AA' phase fields.
anions_train : (default: S,O,Cl,Br,F,N,Te,P,Se,As,I) list of elements constituting a phase field in ICSD.
Elements in the last positions (anions) e.g. elements for A and A' in MM'AA' phase fields.
nanions_train : (default: 2) Number of anions (elements with negative oxidation states as specified in icsd_file)
in the training set. Supported values: 0, 1, 2. If 0 - oxidation states are not taken into account.
cation1_test : (default: Li) list of elements for the first position (e.g. M in MM'AA' phase fields)
in the phase fields to explore (no reported associated compositions in ICSD).
cation2_test : (default: all) list of elements for the second position (e.g. M' in MM'AA' phase fields)
in the phase fields to explore (no reported associated compositions in ICSD). Ignored for binary and ternary (type MAA') phase fields.
anion1_test : (default: S,O,Cl,Br,I,F,N) list of elements for the 3rd position (e.g. A in MM'AA' phase fields)
in the phase fields to explore (no reported associated compositions in ICSD). Stands for a 3rd cation in ternary (type MM'M") and quaternary (type MM'M"A) phase fields.
anion2_test : (default: S,O,Cl,Br,I,F,N) list of elements for the 4th position (e.g. A' in MM'AA' phase fields)
in the phase fields to explore (no reported associated compositions in ICSD). Ignored for ternary (type MM'A) phase fields.

method : (default: VAE) See all supported models above. average_runs : (default: 1) Number of runs to average the scores over. Makes sense for not neural network based (AE, VAE)

methods.

features : (default: See rpp.input). See all supported features above.