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Data Mining for Terahertz Generation Crystals

Authors :
Gabriel A. Valdivia‐Berroeta
Zachary B. Zaccardi
Sydney K. F. Pettit
(Enoch) Sin‐Hang Ho
Bruce Wayne Palmer
Matthew J. Lutz
Claire Rader
Brittan P. Hunter
Natalie K. Green
Connor Barlow
Coriantumr Z. Wayment
Daisy J. Ludlow
Paige Petersen
Stacey J. Smith
David J. Michaelis
Jeremy A. Johnson
Source :
2022 47th International Conference on Infrared, Millimeter and Terahertz Waves (IRMMW-THz).
Publication Year :
2022
Publisher :
IEEE, 2022.

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.<br />Comment: 16 pages, 5 figures

Details

Database :
OpenAIRE
Journal :
2022 47th International Conference on Infrared, Millimeter and Terahertz Waves (IRMMW-THz)
Accession number :
edsair.doi.dedup.....9ae3a2d5f6130735f9a20019081585d7