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RESEARCH PAPER · Advanced Materials · 2018

Machine Detection of Enhanced Electromechanical Energy Conversion in PbZr0.2Ti0.8O3 Thin Films

Joshua Agar, Ye Cao, Brett Naul, Shishir A. Pandya, Stéfan van der Walt, Aileen Luo, Joshua T. Maher, Nina Balke, Stephen Jesse, Sergei V. Kalinin, Rama Krishnan Vasudevan, Lane W. Martin

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42 direct citing works

Machine Detection of Enhanced Electromechanical Energy Conversion in PbZr0.2Ti0.8O3 Thin FilmsOriginalEffects of thermal strain on electric properties of lead zirconate titanate thin films upon LaNiO3 coated base metal plates9Mechanical-Induced Polarization Switching in Relaxor Ferroelectric Single Crystals14Quantitative investigation of electromechanical coupling of potassium sodium niobate-based thin films1To switch or not to switch – a machine learning approach for ferroelectricity15Strain-Engineered Ferroelastic Structures in PbTiO3 Films and Their Control by Electric Fields23Better, Faster, and Less Biased Machine Learning: Electromechanical Switching in Ferroelectric Thin Films18Application of a long short-term memory for deconvoluting conductance contributions at charged ferroelectric domain walls22Local C–V mapping for ferroelectrics using scanning nonlinear dielectric microscopy13Reducing Time to Discovery: Materials and Molecular Modeling, Imaging, Informatics, and Integration65Ferroelectric/multiferroic self-assembled vertically aligned nanocomposites: Current and future status23High-precision local C – V mapping for ferroelectrics using principal component analysis4Symmetry-aware recursive image similarity exploration for materials microscopy8Interplay of domain structure and phase transitions: theory, experiment and functionality33Thin‐Film Ferroelectrics167Uncovering material deformations via machine learning combined with four-dimensional scanning transmission electron microscopy58Nanoscale mapping to assess the asymmetry of local C – V curves obtained from ferroelectric materials6Atomic-scale analysis of disorder by similarity learning from tunneling spectroscopy3Why it is Unfortunate that Linear Machine Learning “Works” so well in Electromechanical Switching of Ferroelectric Thin Films5Image-based machine learning for materials science54Machine learning for materials classifications from images4Non-Ising domain walls in c -phase ferroelectric lead titanate thin films15Finding the semantic similarity in single-particle diffraction images using self-supervised contrastive projection learning11Direct Measurement of Inverse Piezoelectric Effects in Thin Films Using Laser Doppler Vibrometry15Imaging and structure analysis of ferroelectric domains, domain walls, and vortices by scanning electron diffraction5Machine-Learning-Assisted Materials Discovery from Electronic Band Structure7Quantitative scanning capacitance microscopy enabled by machine learning and electrostatic modeling1

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26 direct citing papers saved.

  1. Effects of thermal strain on electric properties of lead zirconate titanate thin films upon LaNiO3 coated base metal plates

    Ceramics International · 2019-09-19

    Hanting Dong, Maojun Chen, Hongjun Zhu, Ye Huang, Qi Ding, Jun Feng

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  2. Mechanical-Induced Polarization Switching in Relaxor Ferroelectric Single Crystals

    ACS Applied Materials & Interfaces · 2019-10-08

    Jihong Bian, Yuting Wang, Ren Zhu, Lei Wang, Bian Yang, Jianwei Wang, Dawei Zhang, Congcong Xu, Tao Li, Dwight D. Viehland, Yaodong Yang

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  3. Quantitative investigation of electromechanical coupling of potassium sodium niobate-based thin films

    Ceramics International · 2019-12-23

    Lei Wang, Jihong Bian, Fei Shao, Bian Yang, Linglong Li, Zhongshuai Liang, Guohua Lan, Ming Liu, Junqi Gao, Yaodong Yang

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  4. To switch or not to switch – a machine learning approach for ferroelectricity

    Nanoscale Advances · 2020-01-01

    Sabine M. Neumayer, Stephen Jesse, Gabriel A. P. Velarde, Andréi L. Kholkin, Ivan I. Kravchenko, Lane W. Martin, Nina Balke, Petro Maksymovych

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  5. Strain-Engineered Ferroelastic Structures in PbTiO3 Films and Their Control by Electric Fields

    ACS Applied Materials & Interfaces · 2020-04-15

    Eric Langenberg, Hanjong Paik, Eva H. Smith, Hari P. Nair, Isabelle M. Hanke, Steffen Ganschow, Gustau Catalán, Neus Domingo, Darrell G. Schlom

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

    Advanced Materials · 2020-08-14

    Lee A. Griffin, Iaroslav Gaponenko, Nazanin Bassiri‐Gharb

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  7. Application of a long short-term memory for deconvoluting conductance contributions at charged ferroelectric domain walls

    npj Computational Materials · 2020-10-28

    Theodor S. Holstad, Trygve Magnus Ræder, Donald M. Evans, Didrik René Småbråten, S. Krohns, Jakob Schaab, Zewu Yan, Edith D. Bourret, Antonius T. J. van Helvoort, Tor Grande, Sverre M. Selbach, Joshua Agar, Dennis Meier

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  8. Local C–V mapping for ferroelectrics using scanning nonlinear dielectric microscopy

    Journal of Applied Physics · 2020-12-28

    Yoshiomi Hiranaga, Takanori Mimura, Takao Shimizu, Hiroshi Funakubo, Yasuo Cho

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  9. Reducing Time to Discovery: Materials and Molecular Modeling, Imaging, Informatics, and Integration

    ACS Nano · 2021-02-12

    Seungbum Hong, Chi Hao Liow, Jong Min Yuk, Hye Ryung Byon, Yongsoo Yang, EunAe Cho, Jiwon Yeom, Gun Park, Hyeonmuk Kang, Seung-Gu Kim, Yoonsu Shim, Moony Na, Chaehwa Jeong, Gyuseong Hwang, Hongjun Kim, Hoon Kim, Seongmun Eom, Seongwoo Cho, Hosun Jun, Yongju Lee, Arthur Baucour, Kihoon Bang, Myungjoon Kim, Seokjung Yun, Jeongjae Ryu, Youngjoon Han, Albina Jetybayeva, Pyuck‐Pa Choi, Joshua Agar, Sergei V. Kalinin, Peter W. Voorhees, P. B. Littlewood, Hyuck Mo Lee

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  10. Ferroelectric/multiferroic self-assembled vertically aligned nanocomposites: Current and future status

    APL Materials · 2021-03-01

    Oon Jew Lee, Shikhar Misra, Haiyan Wang, Judith L. MacManus‐Driscoll

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  11. High-precision local C – V mapping for ferroelectrics using principal component analysis

    Japanese Journal of Applied Physics · 2021-07-13

    Yoshiomi Hiranaga, Takanori Mimura, Takao Shimizu, Hiroshi Funakubo, Yasuo Cho

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  12. Symmetry-aware recursive image similarity exploration for materials microscopy

    npj Computational Materials · 2021-10-08

    Tri N. M. Nguyen, Yichen Guo, Shuyu Qin, Kylie S. Frew, Ruijuan Xu, Joshua Agar

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  13. Interplay of domain structure and phase transitions: theory, experiment and functionality

    Journal of Physics Condensed Matter · 2021-11-03

    Anna Grünebohm, Madhura Marathe, Ruben Khachaturyan, Raphael Schiedung, Doru Constantin Lupascu, Vladimir V Shvartsman

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  14. Thin‐Film Ferroelectrics

    Advanced Materials · 2022-03-30

    Abel N. Fernandez, Megha Acharya, Han‐Gyeol Lee, Jesse Schimpf, Yizhe Jiang, Djamila Lou, Zishen Tian, Lane W. Martin

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  15. Uncovering material deformations via machine learning combined with four-dimensional scanning transmission electron microscopy

    npj Computational Materials · 2022-05-18

    Chuqiao Shi, Michael C. Cao, Sarah M. Rehn, Sang‐Hoon Bae, Jeehwan Kim, Matthew R. Jones, David Anthony Muller, Yimo Han

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  16. Nanoscale mapping to assess the asymmetry of local C – V curves obtained from ferroelectric materials

    Japanese Journal of Applied Physics · 2022-07-07

    Yoshiomi Hiranaga, Takanori Mimura, Takao Shimizu, Hiroshi Funakubo, Yasuo Cho

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  17. Atomic-scale analysis of disorder by similarity learning from tunneling spectroscopy

    Physical Review Research · 2022-07-19

    Petro Maksymovych, Jiaqiang Yan, Brian C. Sales, Jun Wang

    Read original paper ↗ ·

  18. Why it is Unfortunate that Linear Machine Learning “Works” so well in Electromechanical Switching of Ferroelectric Thin Films

    Advanced Materials · 2022-07-29

    Shuyu Qin, Yichen Guo, Alibek T. Kaliyev, Joshua Agar

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  19. Image-based machine learning for materials science

    Journal of Applied Physics · 2022-09-08

    Lei Zhang, Shaofeng Shao

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  20. Machine learning for materials classifications from images

    Journal of Physics Conference Series · 2022-11-01

    Lei Zhang, Zhenyu Li

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  21. Non-Ising domain walls in c -phase ferroelectric lead titanate thin films

    Physical review. B./Physical review. B · 2022-12-20

    Christian Weymann, S. Cherifi, Céline Lichtensteiger, Iaroslav Gaponenko, Kokou D. Dorkenoo, Aaron B. Naden, Patrycja Paruch

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  22. Finding the semantic similarity in single-particle diffraction images using self-supervised contrastive projection learning

    npj Computational Materials · 2023-02-16

    Julian Zimmermann, Fabien Beguet, Daniel Guthruf, Bruno Langbehn, Daniela Rupp

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  23. Direct Measurement of Inverse Piezoelectric Effects in Thin Films Using Laser Doppler Vibrometry

    Physical Review Applied · 2023-07-11

    Megha Acharya, Djamila Lou, Abel N. Fernandez, Jieun Kim, Zishen Tian, Lane W. Martin

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  24. Imaging and structure analysis of ferroelectric domains, domain walls, and vortices by scanning electron diffraction

    npj Computational Materials · 2024-05-18

    Ursula Ludacka, Jiali He, Shuyu Qin, Manuel Zahn, Emil Christiansen, Kasper A. Hunnestad, Xinqiao Zhang, Zewu Yan, Edith D. Bourret, I. Kézsmárki, Antonius T. J. van Helvoort, Joshua Agar, Dennis Meier

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  25. Machine-Learning-Assisted Materials Discovery from Electronic Band Structure

    Journal of Chemical Information and Modeling · 2024-11-03

    Prashant Sinha, Ablokit Joshi, Rik Dey, Shikhar Misra

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  26. Quantitative scanning capacitance microscopy enabled by machine learning and electrostatic modeling

    Journal of Vacuum Science & Technology B Nanotechnology and Microelectronics Materials Processing Measurement and Phenomena · 2026-02-18

    Sheng‐Zhu Ho, Si-An Wen, Yi‐Chun Chen, Dong Gui, Wei‐Shan Hu

    Read original paper ↗ ·
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