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The high-throughput highway to computational materials design

Abstract

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.

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Figure 1: High-throughput analysis of binary intermetallics24.
Figure 2: High-throughput screening of light-absorbing materials for photovoltaic applications.
Figure 3: Example of an efficient HT screening of oxide and oxynitride materials for new photoelectrochemical cells with improved light absorption64.
Figure 4: Example of an HT search for nanosintered thermoelectric materials.
Figure 5: High-throughput screening of electrocatalytic materials for a hydrogen evolution reaction.
Figure 6: High-throughput study of safety versus voltage in lithium batteries.

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Acknowledgements

We thank Marco Fornari, Greg Rohrer, Shidong Wang, Kesong Yang, Junkai Xue, Richard Taylor, Camilo Calderon, Cheng-Ing Chia, Omar Knio, Ichiro Takeuchi, Mike Mehl, Harold Stokes, Rodney Forcade, Gerbrand Ceder, Alex Zunger, Wahyu Setyawan and Aleksey Kolmogorov for useful comments. This work was supported in part by DOD-ONR (N00014-11-1-0136, N00014-09-1-0921) and by the Duke University—Center for Materials Genomics. S.S. thanks financial support from CRANN.

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Correspondence to Stefano Curtarolo.

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Curtarolo, S., Hart, G., Nardelli, M. et al. The high-throughput highway to computational materials design. Nature Mater 12, 191–201 (2013). https://doi.org/10.1038/nmat3568

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