Optically addressable spin defects have emerged as the leading platforms for quantum sensing and communication in solid-state systems. While traditional efforts have concentrated on a focused set of well-studied defects, recent advances in high-throughput computational methods have shown promise for large-scale exploration of defects across diverse semiconductor hosts. By cataloging key properties of quantum defects in computational databases, high-throughput screening techniques can systematically suggest and design novel candidates. In this article, we highlight recent advances in data-driven quantum defect design aimed at addressing critical materials science challenges such as host materials selection, defect stability, and desirable electronic and optical properties. We emphasize the importance of electronic-structure-guided searches across various materials and illustrate how high-throughput computations contribute to our understanding of design principles for quantum defects. Additionally, we outline ongoing challenges and emerging opportunities in this rapidly developing field.
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Yihuang Xiong
Yizhi Zhu
Sinéad M. Griffin
MRS Bulletin
Lawrence Berkeley National Laboratory
Rice University
Dartmouth College
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Xiong et al. (Mon,) studied this question.
www.synapsesocial.com/papers/69df2c9ee4eeef8a2a6b1d3a — DOI: https://doi.org/10.1557/s43577-026-01068-0