Data Mining for Terahertz Generation Crystals
Abstract
We demonstrate a data mining approach to discover and develop new organic nonlinear optical crystals that produce intense pulses of terahertz radiation. We mine the Cambridge Structural Database for non-centrosymmetric materials and use this structural data in tandem with density functional theory calculations to predict new materials that efficiently generate terahertz radiation. This enables us to (in a relatively short time) discover, synthesize, and grow large, high-quality crystals of four promising materials and characterize them for intense terahertz generation. In a direct comparison to the current state-of-the-art organic terahertz generation crystals, these new materials excel. The discovery and characterization of these novel terahertz generators validates the approach of combining data mining with density functional theory calculations to predict properties of high-performance organic materials, potentially for a host of exciting applications.
Cite
@article{arxiv.2109.04929,
title = {Data Mining for Terahertz Generation Crystals},
author = {Gabriel A. Valdivia-Berroeta and Zachary B. Zaccardi and Sydney K. F. Pettit and Sin-Hang Ho and Bruce Wayne Palmer and Matthew J. Lutz and Claire Rader and Brittan P. Hunter and Natalie K. Green and Connor Barlow and Coriantumr Z. Wayment and Daisy J. Harmon and Paige Petersen and Stacey J. Smith and David J. Michaelis and Jeremy A. Johnson},
journal= {arXiv preprint arXiv:2109.04929},
year = {2021}
}
Comments
16 pages, 5 figures