Python Materials Genomics (pymatgen): A robust, open-source python library for materials analysis

TL;DR: The pymatgen library as mentioned in this paper is an open-source Python library for materials analysis that provides a well-tested set of structure and thermodynamic analyses relevant to many applications, and an open platform for researchers to collaboratively develop sophisticated analyses of materials data obtained both from first principles calculations and experiments.

About: This article is published in Computational Materials Science.The article was published on 2013-02-01 and is currently open access. It has received 2364 citations till now. The article focuses on the topics: Python (programming language) & Application programming interface.

Summary

Introduction

• 1 by optical spectroscopy and compared to the corresponding mononuclear dyes.
• The large variation in radiative rate constants, and those for the accompanying non-radiative processes, are accountable in terms of electronic coupling and/or intensity borrowing between the two excitonic states.
• The latter include both face-to-face33 and side-byside analogues34 wherein the photophysical properties are controlled by the molecular topology.
• The compounds examined in this work are illustrated in Charts 1-3 and comprise a series of chromophores based on the BODIPY nucleus and their complementary bichromophores.
• Except for B2B, the bichromophores exhibit a smaller Huang-Rhys (S) factor43 than found for the control compound (Ta- ble 2).

EXCITONIC COUPLING WITH THE BICHROMOPHORES

• According to the excitonic coupling theory developed first by Kasha21 but extended by many others,22-25 interaction between the transition dipole moment vectors associated with the two dipyrrin units causes a two-fold splitting of the excited-singlet state.
• Compounds B2A and P1 adopt an oblique geometry and agreement between calculated and observed N values is somewhat improved, but still poor (Table 3).
• This is not to say, however, that there is an important contribution from through-bond excitonic coupling.
• This is evidenced by the observation that the molecular orbitals are clearly associated with each chromophore, rather than being delocalized over the entire super-molecule.
• Replacing the point sources with extended dipoles running the length of the transition dipole moment vector51 gives rise to splitting energies (VXTD) much higher than the experimental results (Table 3).

CONCLUDING REMARKS

• Numerous studies have addressed important issues relating to excitonic coupling in bichromophoric molecules, many of which have been built around the BODIPY nucleus.32-36,58 Related compounds have been proposed for electro-generated chemiluminescent probes.40,59,60.
• In this contribution the authors have examined the optical properties of bichromophores that do not fall naturally into the categories identified by Kasha21 during his pioneering work on excitonic coupling.
• This introduces a strong angular dependence for the optical properties that might be further exploited to optimize the molecular electronic properties.
• An interesting observation to emerge from this work is that the fluorescence quantum yield is sensitive to the extent of splitting of the excitonic bands.

ACKNOWLEDGMENT

• The authors thank Newcastle University for financial support of this work, including the award of a Research Scholarship to PS.
• The authors also thank Dr. Raymond Ziessel (ECPM-Strasbourg) for providing samples of the BODIPY-based derivatives used in this work.

ABBREVIATIONS

• DFT, density functional theory; NMR, nuclear magnetic resonance spectroscopy; TLC, thin-layer chromatography.
• Harriman, A.; Ziessel, R. Making Photoactive Molecular-scale Wires.
• Ziessel, R.; Ulrich, G.; Harriman, A. The Chemistry of Bodipy: A New El Dorado for Fluorescent Tools.

Figures

Fig. 4. The Li–Sn–S phase diagram generated using a single Li4SnS4 calculation and data from the Materials Project using pymatgen’s borg, matproj and phasediagram packages.

Fig. 5. The chemical potential stability map for the Li–Sn–S system generated using a single Li4SnS4 calculation and data from the Materials Project using pymatgen’s borg, matproj and phasediagram packages. l0Li and l0S refers to the calculated bulk energies of lithium and sulfur respectively. This map shows the ranges of lLi and lS for which each phase is stable. Note that chemical potential values to the right of the Li2S line (shaded in grey) are forbidden ranges.

Fig. 2. Bandstructure of Fe2O3, plotted using data from the Materials Project and pymatgen’s electronic_structure package. Up spins are in blue while down spins are in red. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Fig. 3. The CrystalToolkit and PhaseDiagramApp in the Materials Project, utilizing pymatgen’s alchemy and phasediagram packages respectively.

Frequently asked questions

Q1. What contributions have the authors mentioned in the paper "Python materials genomics (pymatgen): a robust, open-source python library for materials analysis" ?

The pymatgen library this paper is a Python library for high-throughput first-principle calculations in materials. 

Q2. What is the main function of the analysis.reaction_calculator module?

The analysis.reaction_calculator module provides classes for the analysis of reactions, including reaction balancing and calculation of reaction energies. 

Q3. What is the main obstacle to performing phase stability analyses on new materials?

One of the main obstacles to performing phase stability analyses on new materials is that the phase stability of a particular material depends on its energy relative to that of competing phases. 

Q4. What can be done with the alchemy package?

Using the alchemy package, a developer can define a sequence of transformations to be applied to a set of structures to generate a corresponding set of new structures. 

Q5. What are the input parameters for the vaspio module?

VASP input parameters based on those used in the Materials Project as well as the originating MIT high-throughput project [6] are provided in the vaspio_set module. 

Q6. What is the role of the first principles in materials design?

A key enabler in high-throughput computational materials science efforts is a robust set of software tools to perform initial setup for calculations (e.g., generation of structures and necessary input files) and post-calculation analysis to derive useful material properties from raw calculated data. 

Q7. What is the recommended class for the Materials Project?

Two Compatibility classes, MaterialsProjectCompatibility and MITCompatibility, are provided, and it is recommended that users use the appropriate class to process their runs prior to other analyses. 

Q8. How did the authors obtain the ground state structure and energy for Li4SnS4?

Using the Materials Project’s CrystalToolkit, the authors performed a Sn for Ge substitution on Li4GeS4, downloaded the necessary input files based on the parameters used in the Materials Project and performed first principles calculations using VASP to obtain the ground state structure and energy for Li4SnS4. 

Q9. What is the basic structure of a ComputedEntry?

At the most basic level, a ComputedEntry comprise a composition and an energy, which are necessary for phase diagram generation (using the phasediagram package) and calculating reaction energies (using the analysis.reaction_calculator package). 

Q10. What are the two types of phase diagrams supported?

Both ‘‘standard’’ compositional and grand canonical phase diagrams (representingphase equilibria in systems open to one or more components) are supported. 

Q11. What is the mature io module for electronic structure codes?

Among the io modules for electronic structure codes, the vaspio module is currently the most mature and supports most Vienna Ab initio Simulation Package (VASP) [1] input and output files. 

Q12. What is the name of the paper?

In this paper, the authors describe the Python Materials Genomics (pymatgen) library, a robust, open-source Python library for materials analysis. 

Q13. What are the different types of structures that can be used in the electronic structure package?

2. The electronic_structure package defines objects representing various electronic structure analyses, including density of states (electronic_structure.dos module) and bandstructures (electronic_structure.bandstructure module). 

Q14. How can the authors analyze the phase stability of a recently synthesized material?

Using pymatgen’s interface to the Materials API and phasediagram package, the authors demonstrate how the phase and electrochemical stability of a recently synthesized material, Li4SnS4, can be analyzed using a minimum of computing resources. 

Q15. What are the main aspects of phase diagrams?

Phase diagrams representing the thermodynamic phase equilibria of multicomponent systems reveal fundamental material aspects regarding the processing and reactions of materials. 

Q16. How many structures are used in the Materials Project?

This determination would otherwise have required the user to obtain all relevant crystal structure, generate the necessary input files, and perform first principles calculations on more than 30 structures (based on the number of Li–Sn–S phases in the Materials Project), incurring significantly greatercomputational expense. 

Q17. What is the scheme for mixing energies calculated using different functionals?

compatibility module implements the scheme for mixing energies calculated using different functionals, in particular, those calculated using the generalized gradient approximation (GGA) and the +U extension to it (GGA + U) [24–26] as outlined by Jain et al. [27] 

Q18. How many inorganic compounds have been used in the Materials Project?

This framework has been used to screen over 80,000 inorganic compounds for a variety of applications, including Li-ion and Na-ion batteries [7–11]. 

Q19. What is the way to calculate the phase stability of Li4SnS4?

There is also significant time savings for the user, in that he/she needs only to obtain initial candidate structures and perform calculations and analysis for the particular phase he/she is interested in (Li4SnS4), while querying the Materials Project for pre-computed data for the other phases.