Machine learning based insights of seeded congruent crystal growth of LiNbO<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si106.svg" display="inline" id="d1e307"><mml:msub><mml:mrow/><mml:mrow><mml:mn>3</mml:mn></mml:mrow></mml:msub></mml:math> in glass-Reference-Cited by-同舟云学术

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Machine learning based insights of seeded congruent crystal growth of LiNbO3 in glass

Published:2024-09 Issue: Volume:276 Page:120115
ISSN:1359-6454
Container-title:Acta Materialia
language:en
Short-container-title:Acta Materialia

Author:

Thapa R.^ORCID,McKenzie M.E.,Musterman E.^ORCID,Kaman J.^ORCID,Dierolf V.^ORCID,Jain H.

Funder

National Science Foundation

U.S. Department of Energy

Office of Science

Basic Energy Sciences

Publisher

Elsevier BV

Reference42 articles.

1. A new method for measuring the crystallization rate of metals;Czochralski;Z. Phys. Chem.,1918

2. Bulk crystal growth of semiconductors: An overview;Fornari,2011

3. Bulk growth of crystals of III–V compound semiconductors;Dutta,2011

4. Lithium niobate on insulator for nonlinear and quantum applications;Zheng,2023

5. Patterning of two-dimensional planar lithium niobate architectures on glass surface by laser scanning;Honma;Opt. Express,2010

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