2019 journal article
An informatics software stack for point defect-derived opto-electronic properties: the Asphalt Project
MRS COMMUNICATIONS, 9(3), 839–845.
TL;DR:
An informatics and simulation suite to computationally accelerate materials discovery via high-throughput screening and machine learning methods will enable faster and more fundamental materials research, and reduce the cost and time associated with the materials development cycle.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
7. Affordable and Clean Energy
(Web of Science)
9. Industry, Innovation and Infrastructure
(OpenAlex)
Source: Web Of Science
Added: October 21, 2019
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.