Accuracy of ab initio methods in predicting the crystal structures of metals: review of 80 binary alloys

Surrogate machine-learning models are transforming computational materials science by predicting properties of materials with the accuracy of ab initio methods at a fraction of the computational cost. We demonstrate surrogate models that simultaneously interpolate energies of different materials on a dataset of 10 binary alloys (AgCu, AlFe, AlMg, AlNi, AlTi, CoNi, CuFe, CuNi, FeV, NbNi) with 10 different species and all possible fcc, bcc and hcp structures up to 8 atoms in th...

We have developed an efficient and reliable methodology for crystal structure prediction, merging ab initio total-energy calculations and a specifically devised evolutionary algorithm. This method allows one to predict the most stable crystal structure and a number of low-energy metastable structures for a given compound at any P-T conditions without requiring any experimental input. Extremely high success rate has been observed in a few tens of tests done so far, including i...

Tailoring and improving material properties by alloying is a long-known and used concept. Recent research has demonstrated the potential of ab initio calculations in understanding the material properties at the nanoscale. Here we present a systematic overview of alloying trends when early-transition metals (Y, Zr, Nb, Hf, Ta) are added in the Ti$_{1-x}$Al$_x$N system, routinely used as a protective hard coating. The alloy lattice parameters tend to be larger than the correspo...

The temperature dependence of thermodynamic and mechanical properties of six fcc transition metals (Ni, Cu, Ag, Au, Pt, Rh) and the alloying behavior of Ag-Au and Cu-Ni are studied using molecular dynamics (MD). The structures are described at elevated temperatures by the force fields developed by Sutton and co-workers within the context of tight binding approach. MD algorithms are based on the extended Hamiltonian formalism from the works of Andersen, Parinello and Rahman, N...

We use first-principles density functional theory (DFT) within the local density approx- imation (LDA) to ascertain the ground state structure of real and theoretical compounds with the formula ABS3 (A = K, Rb, Cs, Ca, Sr, Ba, Tl, Sn, Pb, and Bi; and B = Sc, Y, Ti, Zr, V, and Nb) under the constraint that B must have a d0 electronic configuration. Our findings indicate that none of these AB combinations prefer a perovskite ground state with corner-sharing BS6 octahedra, but t...

We present example applications of an approach to high-throughput first-principles calculations of the electronic properties of materials implemented within the Exabyte.io platform. We deploy computational techniques based on the Density Functional Theory with both Generalized Gradient Approximation (GGA) and Hybrid Screened Exchange (HSE) in order to extract the electronic band gaps and band structures for a set of 775 binary compounds. We find that for HSE, the average rela...

Rare-earth oxides (REOs) are an important class of materials owing to their unique properties, including high ionic conductivities, large dielectric constants, and elevated melting temperatures, making them relevant to several technological applications such as catalysis, ionic conduction, and sensing. The ability to predict these properties at moderate computational cost is essential to guiding materials discovery and optimizing materials performance. Although density-functi...

We present a novel deep learning (DL) approach to produce highly accurate predictions of macroscopic physical properties of solid solution binary alloys and magnetic systems. The major idea is to make use of the correlations between different physical properties in alloy systems to improve the prediction accuracy of neural network (NN) models. We use multitasking NN models to simultaneously predict the total energy, charge density and magnetic moment. These physical propertie...

We have systematically studied the mechanical stability of all noble metal carbides with the rock-salt structure by calculating their elastic constants within the density function theory scheme. It was found that only four carbides (RuC, PdC, AgC and PtC) are mechanically stable. In particular, we have shown that RuC, PdC, and PtC have very high bulk modulus, which has been remarkably observed by the most recent experiment for the case of PtC. From the calculated density of s...

The discovery of new multicomponent inorganic compounds can provide direct solutions to many scientific and engineering challenges, yet the vast size of the uncharted material space dwarfs current synthesis throughput. While the computational crystal structure prediction is expected to mitigate this frustration, the NP-hardness and steep costs of density functional theory (DFT) calculations prohibit material exploration at scale. Herein, we introduce SPINNER, a highly efficie...