No abstract

The Open Quantum Materials Database (OQMD) is a high-throughput database currently consisting of nearly 300,000 density functional theory (DFT) total energy calculations of compounds from the Inorganic Crystal Structure Database (ICSD) and decorations of commonly occurring crystal structures. To maximise the impact of these data, the entire database is being made available, without restrictions, at www.oqmd.org/download. In this paper, we outline the structure and contents of the database, and then use it to evaluate the accuracy of the calculations therein by comparing DFT predictions with experimental measurements for the stability of all elemental ground-state structures and 1,670 experimental formation energies of compounds. This represents the largest comparison between DFT and experimental formation energies to date. The apparent mean absolute error between experimental measurements and our calculations is 0.096 eV/atom. In order to estimate how much error to attribute to the DFT calculations, we also examine deviation between different experimental measurements themselves where multiple sources are available, and find a surprisingly large mean absolute error of 0.082 eV/atom. Hence, we suggest that a significant fraction of the error between DFT and experimental formation energies may be attributed to experimental uncertainties. Finally, we evaluate the stability of compounds in the OQMD (including compounds obtained from the ICSD as well as hypothetical structures), which allows us to predict the existence of~3,200 new compounds that have not been experimentally characterised and uncover trends in material discovery, based on historical data available within the ICSD.

Typically, computational screens for new materials sharply constrain the compositional search space, structural search space, or both, for the sake of tractability. To lift these constraints, we construct a machine learning model from a database of thousands of density functional theory (DFT) calculations. The resulting model can predict the thermodynamic stability of arbitrary compositions without any other input and with six orders of magnitude less computer time than DFT. We use this model to scan roughly 1.6 million candidate compositions for novel ternary compounds (A x B y C z), and predict 4500 new stable materials. Our method can be readily applied to other descriptors of interest to accelerate domain-specific materials discovery.

The use of hydrogen as fuel is a promising avenue to aid in the reduction of greenhouse effect gases released in the atmosphere. In this work, we present a highthroughput density functional theory (HT-DFT) study of 5,329 cubic and distorted perovskites ABO 3 compounds to screen for thermodynamically favorable two-step thermochemical water splitting (TWS) materials. From a dataset of more than 11,000 calculations, we screened materials based on: (a) thermodynamic stability, and (b) oxygen vacancy formation energy that allow favorable TWS. From our screening strategy, we identify 139 materials as potential new candidates for TWS application.Several of these compounds, such as CeCoO 3 and BiVO 3 , have not been experimentally explored yet for TWS and present promising avenues for further research. We show that taking into consideration all phases present in the A-B-O ternary phase, as opposed to only calculating the formation energy of a compound, is crucial to assess correctly the stability of a compound as it reduces the number of potential candidates from 5,329 to 383. Finally, our large dataset of compounds containing stabilites, oxidation states and ionic sizes allowed us to revisit the structural maps for perovskites by showing stable and unstable compounds simultaneously.

Density functional theory is widely used to predict materials properties, but the local density approximation and generalized gradient approximation exchange-correlation functionals are known to poorly predict the energetics of reactions involving molecular species. In this paper, we obtain corrections for the O2, H2, N2, F2, and Cl2 molecules within the Perdew-Burke-Enzerhof GGA, Perdew-Wang GGA, and Perdew-Zunger LDA exchange-correlation functionals by comparing DFTcalculated formation energies of oxides, hydrides, nitrides, fluorides, and chlorides to experimental values. We also show that the choice of compounds used to obtain the correction is significant, and we use a leave one out cross-validation approach to rigorously determine the proper fit set. We report confidence intervals with our correction values, which quantifies the variation caused by the choice of fit set after outlier removal. The remaining variation in the correction values is on the order of 1 kcal/mol, which indicates that chemical accuracy is a realistic goal for these systems.