Rapid Generation of Optimal Generalized Monkhorst-Pack Grids

Computational modeling of the properties of crystalline materials has become an increasingly important aspect of materials research, consuming hundreds of millions of CPU-hours at scientific computing centres around the world each year, if not more. A routine operation in such calculations is the evaluation of integrals over the Brillouin zone. We have previously demonstrated that performing such integrals using generalized Monkhorst-Pack k-point grids can roughly double the speed of these calculations relative to the widely-used traditional Monkhorst-Pack grids, and such grids can be rapidly generated by querying a free, internet-accessible database of pre-generated grids. To facilitate the widespread use of generalized k-point grids, we present new algorithms that allow rapid generation of optimized generalized Monkhorst-Pack grids on the fly, an open-source library to facilitate their integration into external software packages, and an open-source implementation of the database tool that can be used offline. We also present benchmarks of the speed of our algorithms on structures randomly selected from the Inorganic Crystal Structure Database. For grids that correspond to a real-space supercell with at least 50 angstroms between lattice points, which is sufficient to converge density functional theory calculations within 1 meV/atom for nearly all materials, our algorithm finds optimized grids in an average of 0.19 seconds on a single processing core. For 100 angstroms between real-space lattice points, our algorithm finds optimal grids in less than 5 seconds on average

A representation-independent electronic charge density database for crystalline materials

In addition to being the core quantity in density functional theory, the charge density can be used in many tertiary analyses in materials sciences from bonding to assigning charge to specific atoms. The charge density is data-rich since it contains information about all the electrons in the system. With increasing utilization of machine-learning tools in materials sciences, a data-rich object like the charge density can be utilized in a wide range of applications. The database presented here provides a modern and user-friendly interface for a large and continuously updated collection of charge densities as part of the Materials Project. In addition to the charge density data, we provide the theory and code for changing the representation of the charge density which should enable more advanced machine-learning studies for the broader community

High-throughput calculations of charged point defect properties with semi-local density functional theory—performance benchmarks for materials screening applications

Calculations of point defect energetics with Density Functional Theory (DFT) can provide valuable insight into several optoelectronic, thermodynamic, and kinetic properties. These calculations commonly use methods ranging from semi-local functionals with a-posteriori corrections to more computationally intensive hybrid functional approaches. For applications of DFT-based high-throughput computation for data-driven materials discovery, point defect properties are of interest, yet are currently excluded from available materials databases. This work presents a benchmark analysis of automated, semi-local point defect calculations with a-posteriori corrections, compared to 245 “gold standard” hybrid calculations previously published. We consider three different a-posteriori correction sets implemented in an automated workflow, and evaluate the qualitative and quantitative differences among four different categories of defect information: thermodynamic transition levels, formation energies, Fermi levels, and dopability limits. We highlight qualitative information that can be extracted from high-throughput calculations based on semi-local DFT methods, while also demonstrating the limits of quantitative accuracy

OPTIMADE, an API for exchanging materials data

The Open Databases Integration for Materials Design (OPTIMADE) consortium has designed a universal application programming interface (API) to make materials databases accessible and interoperable. We outline the first stable release of the specification, v1.0, which is already supported by many leading databases and several software packages. We illustrate the advantages of the OPTIMADE API through worked examples on each of the public materials databases that support the full API specification

OPTIMADE, an API for exchanging materials data

: The Open Databases Integration for Materials Design (OPTIMADE) consortium has designed a universal application programming interface (API) to make materials databases accessible and interoperable. We outline the first stable release of the specification, v1.0, which is already supported by many leading databases and several software packages. We illustrate the advantages of the OPTIMADE API through worked examples on each of the public materials databases that support the full API specification

OPTIMADE, an API for exchanging materials data.

The Open Databases Integration for Materials Design (OPTIMADE) consortium has designed a universal application programming interface (API) to make materials databases accessible and interoperable. We outline the first stable release of the specification, v1.0, which is already supported by many leading databases and several software packages. We illustrate the advantages of the OPTIMADE API through worked examples on each of the public materials databases that support the full API specification

Measurements to Elucidate the Mechanism of Thermal and Radiation Enhanced Diffusion of Cesium, Europium, and Strontium in Silicon Carbide.

Containment of fission products (FP) within the TRISO fuel particle is critical to the success of the very high temperature reactor (VHTR). Over sixty years of experience developing and testing this fuel has yet to identify the mechanism by which several key fission products (cesium, europium, and strontium) escape through intact SiC at temperatures between 900C and 1,300C. A novel diffusion couple was developed that was successful in making the first measurements of fission product diffusion in SiC. This design allows for the isolation of thermal diffusion and investigation of radiation enhanced diffusion using ion irradiation as a simulant for neutron radiation damage. The thermal and radiation enhanced diffusion of cesium, europium, and strontium were measured between 900C and 1,300C. The ion irradiation significantly enhanced the diffusion of all three fission products with enhancement factors ranging from 100x to 1E7x over thermal diffusion. All three fission products exhibits mixed diffusion kinetics between 900C and 1,300C under purely thermal conditions, and between 900C and 1,100C under ion irradiation. This indicates that both bulk and grain boundary diffusion are active mechanisms for fission product release. A defect reaction model indicates that fission product diffusion can occur on both the silicon or carbon sub-lattices. Comparison of cesium diffusion with the literature suggests that the best quality TRISO fuel should exhibit minimal cesium release and that cesium release is a good indicator of TRISO fuel failure.PhDNuclear Engineering and Radiological SciencesUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/120786/1/shyamd_1.pd

High-throughput computation and evaluation of raman spectra.

Raman spectroscopy is used ubiquitously in the characterization of condensed materials, spanning from biomaterials, minerals to polymers, as it provides a unique fingerprint of local bonding and environment. In this work, we design and demonstrate a robust, automatic computational workflow for Raman spectra that employs first-principle calculations based on density functional perturbation theory. A set of computational results are compared to Raman spectra obtained from established experimental databases to estimate the accuracy of the calculated properties across chemical systems and structures. Details regarding the computational methodology and technical validation are presented along with the format of our publicly available data record