Quantification of gradient energy coefficients using physics-informed neural networks-Reference-Cited by-同舟云学术

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Quantification of gradient energy coefficients using physics-informed neural networks

Published:2024-07 Issue: Volume:273 Page:109210
ISSN:0020-7403
Container-title:International Journal of Mechanical Sciences
language:en
Short-container-title:International Journal of Mechanical Sciences

Author:

Shang Lan^ORCID,Zhao Yunhong,Zheng Sizheng,Wang Jin,Zhang Tongyi,Wang Jie^ORCID

Publisher

Elsevier BV

Reference85 articles.

1. Thin-film ferroelectric materials and their applications;Martin;Nat Rev Mater,2016

2. Ferroelectric or non-ferroelectric: Why so many materials exhibit “ferroelectricity” on the nanoscale;Vasudevan;Appl Phys Rev,2017

3. A theory of domain switch for the nonlinear behaviour of ferroelectrics;Li;Proc R Soc Lond Ser A Math Phys Eng Sci,1999

4. Large electric-field-induced strain in ferroelectric crystals by point-defect-mediated reversible domain switching;Ren;Nat Mater,2004

5. Intrinsic ferroelectric switching from first principles;Liu;Nature,2016

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