Software

sumo

Written by Alex Ganose and Dr Adam Jackson, sumo is a Python package for plotting and analysis of materials chemistry ab initio calculation data. sumo (click here to get the source code) is a set of command-line tools for publication-ready plotting and analysis of ab initio calculation data. The code includes a fully-documented Python module, upon which the command-line scripts are built. sumo currently only supports VASP, however, extending the code to other ab initio calculators is planned for future releases. The code relies on several open-source Python packages for common tasks, including pymatgen for data loading, spglib for symmetry analysis, and Matplotlib for plotting.

The main plotting functionality of sumo includes density of states plots, electronic and phonon band structure diagrams, and optical absorption spectra (as shown in the Figure below). The code has been designed to allow for significant customisation of plots, including the ability to produce projected density of states and orbital resolved band structures. The code additionally supplies a tool for generating k-point paths along high-symmetry directions in the Brillouin zone, with the ability to write the necessary input files required to perform the calculations in VASP. Crucially, this tool allows a single band structure plot to be split into several ab initio calculations, as is essential when dealing with large materials or restrictive batch systems. Lastly, a script is provided to extract information from semiconductor band structures, including direct and indirect band gaps, band edge locations, and parabolic and non-parabolic effective masses.

SUMO

If you do use SUMO, please cite the following paper in your publication:
A.M. Ganose, A. J. Jackson and D. O. Scanlon, sumo: Command-line tools for plotting and analysis of ab initio calculations, Journal of Open Source Software, Submitted (2018) DOI: 10.21105/joss.00682


GALORE

Written by Dr Adam Jackson and Alex Ganose, GALORE simplifies and automates the process of simulating photoelectron spectra from ab initio calculations. This replaces the tedious process of extracting and interpolating crosssectional weights from reference data and generates tabulated data or publication-ready plots as needed. The broadening tools may also be used to obtain realistic simulated spectra from a theoretical set of discrete lines (e.g. infrared or Raman spectroscopy). GALORE is a Materials Design aid, as it can quickly convert calculated data to simulated spectra which can be compared easily with experiment.

GALORE (click here to get the source code) provides a command-line tool and Python API to import data and resample it to a dense, regular X-Y series. This mesh can then be convolved with Gaussian and Lorentzian functions to yield a smooth output, in the form of a plot or data file. Numpy functions are used for data manipulation and convolution on a finite grid and Matplotlib is used for plotting. As well as simple tabular data files, the electronic DOS or PDOS may be imported directly from the output of the VASP or GPAW codes. An example of the GALORE proceedure for generating simulated PES spectra is shown in the Figure below.

GALORE1

Cross-sectional weights are included for some standard energy values (He(II) UPS and Al k-alpha) from tabulated ab initio calculations. Users may provide their own weighting values in the same human-readable JSON file format. Higher-energy (HAXPES) spectra may be simulated using cross-sections from fitted data over an energy range 1-1500 keV. Tabulated data was fitted to an order-8 polynomial on a log-log scale, and coefficients for each element and orbital shape are stored in a database file. The fitting error is generally below 1%, with outliers in the region of 2–3%, as demonstrated in the Figure below. The order-8 fit was selected based on cross-validation in order to avoid over-fitting

GALORE2

If you do use GALORE, please cite the following paper in your publication:
A. J. Jackson, A. M. Ganose, A. Regoutz, R. G. Egdell and D. O. Scanlon, GALORE: Broadening and weighting for simulation of photoelectron spectroscopy, Journal of Open Source Software, Submitted (2018) DOI: 10.21105/joss.00696


CPLAP

Written by Dr John Buckeridge, CPLAP which stands for the Chemical Potential Limits Analysis Program (click here to get the source code), is a program designed to determine the thermodynamical stability of a material, and, if it is stable, to determine the ranges of the constituent elements’ chemical potentials within which it is stable, in comparison with competing phases and the elemental forms. CPLAP is extremely useful for Materials Design, as you can use it for testing the stability of new materials versus competing phases. It can also be used to set the boundaries of chemical potentials for defect Chemistry/Physics analysis (see figure below). For a full explanation, read the paper here.

Example

If you do use CPLAP, please cite the following paper in your publication:
J. Buckeridge, D. O. Scanlon. A. Walsh and C. R. A. Catlow, Automated procedure to determine the thermodynamic stability of a material and the range of chemical potentials necessary for its formation relative to competing phases and compounds, Computer Physics Communications, 185(1), 330-338 (2014)

Publications using CPLAP

    1. M. Quesada-Gonzalez, B. A. D. Williamson, C. Sotelo-Vasquez, A. Kafizas, N. D. Boscher, R. Quesada-Cabrera, D. O. Scanlon, C. J. Carmalt, and I. P. Parkin, A Deeper Understanding of Boron-doped Anatase Thin Films as a Multifunctional Layer through Theory and Experiment, Journal of Physical Chemistry C , 122, 714 (2018) doi: 10.1021/acs.jpcc.7b11142
    1. A. Walsh and A. Zunger, Instilling Defect Tolerance in New Compounds, Nature Materials, 16, 964 (2017) doi:10.1038/nmat4973
    1. A. L. Galvin and G. W. Watson, Modelling Oxygen Defects in Orthorhombic LaMnO3 and its Low Index Surfaces, Physical Chemistry Chemical Physics, 19, 24636 (2017) doi:10.1039/C7CP02905E
    1. Y. G. Yu, X, Zhang and A. Zunger, Natural Off-Stoichiometry Causes Carrier Doping in Half-Heusler Filled Tetrahedral Structures, Physical Review B, 95, 085201 (2017) doi:10.1103/PhysRevB.95.085201
    1. C. N. Savory, A. M. Ganose and D. O. Scanlon, Exploring the PbS-Bi2S3 Series For Next Generation Energy Conversion Materials, Chemistry of Materials, 29, 5156 (2017) doi: 10.1021/acs.chemmater.7b00628
    1. E. Olsson, X. Aparicio-Angles and N. H. de Leeuw, A Computational Study of the Electronic Properties, Ionic Conduction, and Thermal Expansion of Sm1−xAxCoO3 and Sm1−xAxCoO3−(x/2) (A = Ba2+, Ca2+, Sr2+, and x = 0.25, 0.5) as Intermediate Temperature SOFC Cathodes, Physical Chemistry Chemical Physics, 19, 13960 (2017) doi: 10.1039/C7CP01555K
    1. Z. Xie, Y. Sui, J. Buckeridge, C. R. A. Catlow, T. W. Keal, P. Sherwood, A. Walsh, D. O. Scanlon, S. M. Woodley, and A. A. Sokol, Demonstration of the donor characteristics of Si and O defects in GaN using hybrid QM/MM, Physica Status Solidi A, 214, 1600440 (2017) doi: 10.1002/pssa.201600445
    1. J. Kaczkowski and A. Jezierski, Effect of Chemical and Hydrostatic Pressure on Electronic Structure of BiPd2O4: A First-Principles Study, Journal of Alloys and Compounds, 726, 737 (2017) doi: 10.1016/j.jallcom.2017.08.030
    1. S. H. Shah and P. D. Bristowe, Point Defect Formation in M2AlC (M = Zr,Cr) MAX Phases and Their Tendency to Disorder and Amorphize, Scientific Reports, 7, 9667 (2017) doi: 10.1038/s41598-017-10273-6
    1. C. N. Savory, A. Walsh and D. O. Scanlon, Can Pb-free Halide Double Perovskites Support High-efficiency Solar Cells?, ACS Energy Letters , 1, 949 (2016) doi: 10.1021/acsenergylett.6b00471
    1. W. M. Linhart, M. K. Rajpalke, J. Buckeridge, P. A. E. Murgatroyd, J. J. Bomphrey, J. Alaria, C. R. A. Catlow, D. O. Scanlon, M. J. Ashwin and T. D. Veal, Band Gap Reduction in InSbxN1-x Alloys: Optical Absorption, k.P Modeling and Density Functional Theory , Applied Physics Letters, 109, 132104 (2016) doi: 10.1063/1.4963836
    1. M. R. Farow, C. R. A. Catlow, A. A Sokol and S. M. Woodley, Double Bubble Secondary Building Units Used as a Structural Motif for Enhanced Electron–hole Separation in Solids, Materials Science in Semiconductor Processing, 42, 147 (2016) doi: 10.1016/j.mssp.2015.08.023
    1. E. Olsson, X. Aparicio-Angles and N. H. de Leeuw, Ab Initio Study of Vacancy Formation in Cubic LaMnO3 and SmCoO3 as Cathode Materials in Solid Oxide Fuel Cells, The Journal of Chemical Physics, 145, 014703 (2017) doi: 10.1063/1.4954939
    1. F. H. Taylor, J. Buckeridge and C. R. A. Catlow, Defects and Oxide Ion Migration in the Solid Oxide Fuel Cell Cathode Material LaFeO3, Chemistry of Materials, 28, 8210 (2016) doi: 10.1021/acs.chemmater.6b03048
    1. J. Buckeridge, F. H. Taylor and C. R. A. Catlow, Efficient and Accurate Approach to Modeling the Microstructure and Defect Properties of LaCoO3, Physical Review B, 93, 155123 (2016) doi: 10.1103/PhysRevB.93.155123
    1. J. Buckerdige, D. Jevdokimovs, C. R. A. Catlow and A. A. Sokol, Nonstoichiometry and Weyl Fermionic Behavior in TaAs, Physical Review B, 94, 190101 (2016) doi: 10.1103/PhysRevB.94.180101
    1. J. Buckeridge, K. T. Butler, C. R. A. Catlow, A. J. Logsdail, D. O. Scanlon, S. A. Shevlin, A. A. Sokol, S. M. Woodley, and A. Walsh, Polymorph Engineering of TiO2: Demonstrating How Absolute Reference Potentials are Determined by Local Coordination, Chemistry of Materials, 27, 3844 (2015) doi: 10.1021/acs.chemmater.5b00230
    1. Z.-H. Cai, P. Narang, H. A. Atwater, S. Chen, C.-G. Duan, Z.-Q. Zhu and J.-H. Chu, Cation-Mutation Design of Quaternary Nitride Semiconductors Lattice-Matched to GaN, Chemistry of Materials, 7757, (2015) doi: 10.1021/acs.chemmater.5b03536
    1. R. D. Bayliss, S. N. Cook, D. O. Scanlon, S. Fearn, J. Cabana, C. Greaves, J. A. Kilner and S. J. Skinner, Understanding the Defect Chemistry of Alkali Metal Strontium Silicate Solid Solutions: Insights from Experiment and Theory, Journal of Materials Chemistry A, 2, 17919 (2014) doi: 10.1039/c4ta04299a
    1. D. O. Scanlon, J. Buckeridge, C. R. A. Catlow, G. W. Watson, Understanding doping anomalies in degenerate p-type semiconductor LaCuOSe, Journal of Materials Chemistry C, 2, 3429 (2014) doi: 10.1039/c4tc00096j
    1. C. Wang, S. Chen, J.-H. Yang, L. Liang, H.-J. Xiang, X.-G. Gong, A. Walsh and S.-H. Wei, Design of I2–II–IV–VI4 Semiconductors through Element Substitution: The Thermodynamic Stability Limit and Chemical Trend, Chemistry of Materials, 26, 3411 (2014) doi: 10.1021/cm500598x