Better, Faster, and Less Biased Machine Learning: Electromechanical Switching in Ferroelectric Thin Films-Reference-Cited by-同舟云学术

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Better, Faster, and Less Biased Machine Learning: Electromechanical Switching in Ferroelectric Thin Films

Published:2020-08-14 Issue:38 Volume:32 Page:2002425
ISSN:0935-9648
Container-title:Advanced Materials
language:en
Short-container-title:Adv. Mater.

Author:

Griffin Lee A.¹²,Gaponenko Iaroslav¹³^ORCID,Bassiri‐Gharb Nazanin¹⁴^ORCID

Affiliation:

1. G. W. Woodruff School of Mechanical Engineering Georgia Institute of Technology Atlanta GA 30332 USA

2. School of Electrical Engineering Georgia Institute of Technology Atlanta GA 30332 USA

3. Department of Quantum Matter Physics University of Geneva Geneva 1204 Switzerland

4. School of Materials Science and Engineering Georgia Institute of Technology Atlanta GA 30332 USA

Funder

National Science Foundation

Defense Threat Reduction Agency

Publisher

Wiley

Subject

Mechanical Engineering,Mechanics of Materials,General Materials Science

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/adma.202002425

Reference52 articles.

1. Ferroelectric Memories

2. Nanoparticulate Functional Materials

3. Miniaturized Battery‐Free Wireless Systems for Wearable Pulse Oximetry

4. Fiber-Based Wearable Electronics: A Review of Materials, Fabrication, Devices, and Applications

5. Stretchable, Skin-Mountable, and Wearable Strain Sensors and Their Potential Applications: A Review

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1. A borate [C₆N₂H₁₅]·[B₅O₆(OH)₄] ferroelectric crystal: synthesis, properties and film fabrication;Journal of Materials Chemistry C;2024

2. Machine learning for automated experimentation in scanning transmission electron microscopy;npj Computational Materials;2023-12-20

3. Mask or Enhance: Data Curation Aiding the Discovery of Piezoresponse Force Microscopy Contributors;Advanced Physics Research;2023-02-02

4. Automatic Ferroelectric Domain Pattern Recognition Based on the Analysis of Localized Nonlinear Optical Responses Assisted by Machine Learning;Advanced Physics Research;2022-12-14

5. Investigation of piezoelectric 0.65Pb(Mg_1/3Nb_2/3)O₃–0.35PbTiO₃ films in cross section using piezo-response force microscopy;Applied Physics Letters;2022-11-07

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