Designing polar textures with ultrafast neuromorphic features from atomistic simulations
This review summarizes recent works, all using a specific atomistic approach, that predict and explain the occurrence of key features for neuromorphic computing in three archetypical dipolar materials, when they are subject to THz excitations. The main ideas behind such atomistic approach are provid...
| Main Authors: | , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IOP Publishing
2023-01-01
|
| Series: | Neuromorphic Computing and Engineering |
| Subjects: | |
| Online Access: | https://doi.org/10.1088/2634-4386/acbfd6 |
| _version_ | 1827964970326818816 |
|---|---|
| author | Sergey Prosandeev Sergei Prokhorenko Yousra Nahas Yali Yang Changsong Xu Julie Grollier Diyar Talbayev Brahim Dkhil L Bellaiche |
| author_facet | Sergey Prosandeev Sergei Prokhorenko Yousra Nahas Yali Yang Changsong Xu Julie Grollier Diyar Talbayev Brahim Dkhil L Bellaiche |
| author_sort | Sergey Prosandeev |
| collection | DOAJ |
| description | This review summarizes recent works, all using a specific atomistic approach, that predict and explain the occurrence of key features for neuromorphic computing in three archetypical dipolar materials, when they are subject to THz excitations. The main ideas behind such atomistic approach are provided, and illustration of model relaxor ferroelectrics, antiferroelectrics, and normal ferroelectrics are given, highlighting the important potential of polar materials as candidates for neuromorphic computing. Some peculiar emphases are made in this Review, such as the connection between neuromorphic features and percolation theory, local minima in energy path, topological transitions and/or anharmonic oscillator model, depending on the material under investigation. By considering three different and main polar material families, this work provides a complete and innovative toolbox for designing polar-based neuromorphic systems. |
| first_indexed | 2024-04-09T17:24:33Z |
| format | Article |
| id | doaj.art-131e390b8bfb4a66aa19a04d6b917b3d |
| institution | Directory Open Access Journal |
| issn | 2634-4386 |
| language | English |
| last_indexed | 2024-04-09T17:24:33Z |
| publishDate | 2023-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | Neuromorphic Computing and Engineering |
| spelling | doaj.art-131e390b8bfb4a66aa19a04d6b917b3d2023-04-18T13:52:37ZengIOP PublishingNeuromorphic Computing and Engineering2634-43862023-01-013101200210.1088/2634-4386/acbfd6Designing polar textures with ultrafast neuromorphic features from atomistic simulationsSergey Prosandeev0https://orcid.org/0000-0002-0511-8310Sergei Prokhorenko1Yousra Nahas2Yali Yang3Changsong Xu4Julie Grollier5Diyar Talbayev6Brahim Dkhil7L Bellaiche8Physics Department and Institute for Nanoscience and Engineering, University of Arkansas , Fayetteville, AR 72701, United States of AmericaPhysics Department and Institute for Nanoscience and Engineering, University of Arkansas , Fayetteville, AR 72701, United States of AmericaPhysics Department and Institute for Nanoscience and Engineering, University of Arkansas , Fayetteville, AR 72701, United States of AmericaSchool of Mathematics and Physics, University of Science and Technology Beijing , Beijing 100083, People’s Republic of ChinaKey Laboratory of Computational Physical Sciences (Ministry of Education), Institute of Computational Physical Sciences, State Key Laboratory of Surface Physics, and Department of Physics, Fudan University , Shanghai 200433, People’s Republic of China; Shanghai Qi Zhi Institute , Shanghai 200030, People’s Republic of ChinaUnité Mixte de Physique, CNRS, Thales, Université Paris-Saclay , 91767 Palaiseau, FranceDepartment of Physics and Engineering Physics, Tulane University , 6400 Freret St., New Orleans, LA 70118, United States of AmericaUniversité Paris-Saclay, CentraleSupélec, CNRS-UMR8580, Laboratoire Structures, Propriétés et Modélisation des Solides , 91190 Gif-sur-Yvette, FrancePhysics Department and Institute for Nanoscience and Engineering, University of Arkansas , Fayetteville, AR 72701, United States of AmericaThis review summarizes recent works, all using a specific atomistic approach, that predict and explain the occurrence of key features for neuromorphic computing in three archetypical dipolar materials, when they are subject to THz excitations. The main ideas behind such atomistic approach are provided, and illustration of model relaxor ferroelectrics, antiferroelectrics, and normal ferroelectrics are given, highlighting the important potential of polar materials as candidates for neuromorphic computing. Some peculiar emphases are made in this Review, such as the connection between neuromorphic features and percolation theory, local minima in energy path, topological transitions and/or anharmonic oscillator model, depending on the material under investigation. By considering three different and main polar material families, this work provides a complete and innovative toolbox for designing polar-based neuromorphic systems.https://doi.org/10.1088/2634-4386/acbfd6atomisticsimulationsferroelectricTHz pulsesneuromorphic computing |
| spellingShingle | Sergey Prosandeev Sergei Prokhorenko Yousra Nahas Yali Yang Changsong Xu Julie Grollier Diyar Talbayev Brahim Dkhil L Bellaiche Designing polar textures with ultrafast neuromorphic features from atomistic simulations Neuromorphic Computing and Engineering atomistic simulations ferroelectric THz pulses neuromorphic computing |
| title | Designing polar textures with ultrafast neuromorphic features from atomistic simulations |
| title_full | Designing polar textures with ultrafast neuromorphic features from atomistic simulations |
| title_fullStr | Designing polar textures with ultrafast neuromorphic features from atomistic simulations |
| title_full_unstemmed | Designing polar textures with ultrafast neuromorphic features from atomistic simulations |
| title_short | Designing polar textures with ultrafast neuromorphic features from atomistic simulations |
| title_sort | designing polar textures with ultrafast neuromorphic features from atomistic simulations |
| topic | atomistic simulations ferroelectric THz pulses neuromorphic computing |
| url | https://doi.org/10.1088/2634-4386/acbfd6 |
| work_keys_str_mv | AT sergeyprosandeev designingpolartextureswithultrafastneuromorphicfeaturesfromatomisticsimulations AT sergeiprokhorenko designingpolartextureswithultrafastneuromorphicfeaturesfromatomisticsimulations AT yousranahas designingpolartextureswithultrafastneuromorphicfeaturesfromatomisticsimulations AT yaliyang designingpolartextureswithultrafastneuromorphicfeaturesfromatomisticsimulations AT changsongxu designingpolartextureswithultrafastneuromorphicfeaturesfromatomisticsimulations AT juliegrollier designingpolartextureswithultrafastneuromorphicfeaturesfromatomisticsimulations AT diyartalbayev designingpolartextureswithultrafastneuromorphicfeaturesfromatomisticsimulations AT brahimdkhil designingpolartextureswithultrafastneuromorphicfeaturesfromatomisticsimulations AT lbellaiche designingpolartextureswithultrafastneuromorphicfeaturesfromatomisticsimulations |