Chemistry

Identifying candidate hosts for quantum defects via data mining

A. M. Ferrenti, N. P. D. Leon, et al.

This research systematically evaluates host materials for quantum defects, identifying 541 viable candidates through a detailed screening process. Conducted by Austin M. Ferrenti, Nathalie P. de Leon, Jeff D. Thompson, and Robert J. Cava, this study offers groundbreaking insights applicable across material systems.

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Abstract

This research systematically evaluates the suitability of host materials for quantum defects using a four-stage data mining and manual screening process applied to the Materials Project database. The study identifies 541 viable hosts (16 unary and 74 binary) for quantum defect introduction, representing a significant reduction from the total known inorganic phases. The screening principles are applicable to other materials systems.

Publisher

npj Computational Materials

Published On

Aug 18, 2020

Authors

Austin M. Ferrenti, Nathalie P. de Leon, Jeff D. Thompson, Robert J. Cava