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An informatics software stack for point defect-derived opto-electronic properties: the Asphalt Project

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Abstract

Computational acceleration of performance metric-based materials discovery via high-throughput screening and machine learning methods is becoming widespread. Nevertheless, development and optimization of the opto-electronic properties that depend on dilute concentrations of point defects in new materials have not significantly benefited from these advances. Here, the authors present an informatics and simulation suite to computationally accelerate these processes. This will enable faster and more fundamental materials research, and reduce the cost and time associated with the materials development cycle. Analogous to the new avenues enabled by current first-principles-based property databases, this type of framework will open entire new research frontiers as it proliferates.

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Acknowledgments

The authors gratefully acknowledge support from the AFOSR via grants FA9550-14-1-0264 and FA9550-17-1-0318, which are in the Aerospace Materials for Extreme Environments program of Dr. Ali Sayir. P.C.B. acknowledges support from the NDSEG. Computer time was provided for the generation of data by NERSC and DoD HPCMP.

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Authors and Affiliations

  1. Department of Materials Science and Engineering, North Carolina State University, 911 Partners Way, Suite 3002, Raleigh, NC, 27695, USA

    Jonathon N. Baker, Preston C. Bowes, Joshua S. Harris & Douglas L. Irving

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  1. Jonathon N. Baker
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  2. Preston C. Bowes
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  3. Joshua S. Harris
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  4. Douglas L. Irving
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Correspondence to Douglas L. Irving.

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Baker, J.N., Bowes, P.C., Harris, J.S. et al. An informatics software stack for point defect-derived opto-electronic properties: the Asphalt Project. MRS Communications 9, 839–845 (2019). https://doi.org/10.1557/mrc.2019.106

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