Ohad Levy

The high-throughput highway to computational materials design

High-throughput computational materials design is an emerging area of materials science. By combining advanced thermodynamic and electronic-structure methods with intelligent data mining and database construction, and exploiting the power of current supercomputer architectures, scientists generate, manage and analyse enormous data repositories for the discovery of novel materials. In this Review we provide a current snapshot of this rapidly evolving field, and highlight the challenges and opportunities that lie ahead.

Thermoelectric properties of a composite medium

We study the thermoelectric properties of a composite medium. Various approximations are developed for calculating the matrix Qe of the bulk effective transport coefficients of the medium, including exact upper and lower bounds for Qe under various conditions. Results are especially detailed for two‐component composites, where a field decoupling transformation is used to reduce the thermoelectric problem to two uncoupled quasi‐conductivity problems. Exact bounds are then obtained for the absolute thermopower αe and the thermoelectric figure of merit Ze in two‐component composites. We prove that Ze of the composite can never exceed the largest value of Z in any component. Some of these results are extended to certain classes of multicomponent composites.

AFLOW: An Automatic Framework for High-throughput Materials Discovery

Abstract Recent advances in computational materials science present novel opportunities for structure discovery and optimization, including uncovering of unsuspected compounds and metastable structures, electronic structure, surface, and nano-particle properties. The practical realization of these opportunities requires systematic generation and classification of the relevant computational data by high-throughput methods. In this paper we present A flow (Automatic Flow), a software framework for high-throughput calculation of crystal structure properties of alloys, intermetallics and inorganic compounds. The A flow software is available for the scientific community on the website of the materials research consortium, aflowlib.org. Its geometric and electronic structure analysis and manipulation tools are additionally available for online operation at the same website. The combination of automatic methods and user online interfaces provide a powerful tool for efficient quantum computational materials discovery and characterization.

High-throughput computational screening of thermal conductivity, Debye temperature, and Grüneisen parameter using a quasiharmonic Debye model

The quasiharmonic Debye approximation has been implemented within the aflow and Materials Project frameworks for high-throughput computational materials science (Automatic Gibbs Library, agl), in order to calculate thermal properties such as the Debye temperature and the thermal conductivity of materials. We demonstrate that the agl method, which is significantly cheaper computationally compared to the fully ab initio approach, can reliably predict the ordinal ranking of the thermal conductivity for several different classes of semiconductor materials. In particular, a high Pearson (i.e., linear) correlation is obtained between the experimental and agl computed values of the lattice thermal conductivity for a set of 75 compounds including materials with cubic, hexagonal, rhombohedral, and tetragonal symmetry.

A RESTful API for exchanging materials data in the AFLOWLIB.org consortium

Abstract The continued advancement of science depends on shared and reproducible data. In the field of computational materials science and rational materials design this entails the construction of large open databases of materials properties. To this end, an A pplication P rogram I nterface (API) following REST principles is introduced for the AFLOWLIB.org materials data repositories consortium. AUIDs ( A flowlib U nique ID entifier) and AURLs ( A flowlib U niform R esource L ocator) are assigned to the database resources according to a well-defined protocol described herein, which enables the client to access, through appropriate queries, the desired data for post-processing. This introduces a new level of openness into the AFLOWLIB repository, allowing the community to construct high-level work-flows and tools exploiting its rich data set of calculated structural, thermodynamic, and electronic properties. Furthermore, federating these tools will open the door to collaborative investigations of unprecedented scope that will dramatically accelerate the advancement of computational materials design and development.

Uncovering compounds by synergy of cluster expansion and high-throughput methods.

Predicting from first-principles calculations whether mixed metallic elements phase-separate or form ordered structures is a major challenge of current materials research. It can be partially addressed in cases where experiments suggest the underlying lattice is conserved, using cluster expansion (CE) and a variety of exhaustive evaluation or genetic search algorithms. Evolutionary algorithms have been recently introduced to search for stable off-lattice structures at fixed mixture compositions. The general off-lattice problem is still unsolved. We present an integrated approach of CE and high-throughput ab initio calculations (HT) applicable to the full range of compositions in binary systems where the constituent elements or the intermediate ordered structures have different lattice types. The HT method replaces the search algorithms by direct calculation of a moderate number of naturally occurring prototypes representing all crystal systems and guides CE calculations of derivative structures. This synergy achieves the precision of the CE and the guiding strengths of the HT. Its application to poorly characterized binary Hf systems, believed to be phase-separating, defines three classes of alloys where CE and HT complement each other to uncover new ordered structures.

Ordered Structures in Rhenium Binary Alloys from First-Principles Calculations

Rhenium is an important alloying agent in catalytic materials and superalloys, but the experimental and computational data on its binary alloys are sparse. Only 6 out of 28 Re transition-metal systems are reported as compound-forming. Fifteen are reported as phase-separating, and seven have high-temperature disordered σ or χ phases. Comprehensive high-throughput first-principles calculations predict stable ordered structures in 20 of those 28 systems. In the known compound-forming systems, they reproduce all the known compounds and predict a few unreported ones. These results indicate the need for an extensive revision of our current understanding of Re alloys through a combination of theoretical predictions and experimental validations. The following systems are investigated: AgRe(★), AuRe(★), CdRe(★), CoRe, CrRe(★), CuRe(★), FeRe, HfRe, HgRe(★), IrRe, MnRe, MoRe, NbRe, NiRe, OsRe, PdRe, PtRe, ReRh, ReRu, ReSc, ReTa, ReTc, ReTi, ReV, ReW(★), ReY, ReZn(★), and ReZr ((★) = systems in which the ab initio method predicts that no compounds are stable).

The New Face of Rhodium Alloys: Revealing Ordered Structures from First Principles

The experimental and computational data on rhodium binary alloys is sparse despite its importance in numerous applications, especially as an alloying agent in catalytic materials. Half of the Rh-transition metal systems (14 out of 28) are reported to be phase separating or are lacking experimental data. Comprehensive high-throughput first-principles calculations predict stable ordered structures in 9 of those 14 binary systems. They also predict a few unreported compounds in the known compound-forming systems. These results indicate the need for an extensive revision of our current understanding of Rh alloys through a combination of theoretical predictions and experimental validations.

Comprehensive Search for New Phases and Compounds in Binary Alloy Systems Based on Platinum-Group Metals, Using a Computational First-Principles Approach

We report a comprehensive study of the binary systems of the platinum group metals with the transition metals, using high-throughput first-principles calculations. These computations predict stability of new compounds in 37 binary systems where no compounds have been reported in the literature experimentally, and a few dozen of as yet unreported compounds in additional systems. Our calculations also identify stable structures at compound compositions that have been previously reported without detailed structural data and indicate that some experimentally reported compounds may actually be unstable at low temperatures. With these results we construct enhanced structure maps for the binary alloys of platinum group metals. These are much more complete, systematic and predictive than those based on empirical results alone.

Structure maps for hcp metals from first-principles calculations

The ability to predict the existence and crystal type of ordered structures of materials from their components is a major challenge of current materials research. Empirical methods use experimental data to construct structure maps and make predictions based on clustering of simple physical parameters. Their usefulness depends on the availability of reliable data over the entire parameter space. Recent development of highthroughput methods opens the possibility to enhance these empirical structure maps by ab initio calculations in regions of the parameter space where the experimental evidence is lacking or not well characterized. In this paper we construct enhanced maps for the binary alloys of hcp metals, where the experimental data leaves large regions of poorly characterized systems believed to be phase separating. In these enhanced maps, the clusters of noncompound-forming systems are much smaller than indicated by the empirical results alone.