Metal-organic framework single crystal for in-memory neuromorphic computing with a light control

AbstractNeuromorphic architectures, expanding the limits of computing from conventional data processing and storage to advanced cognition, learning, and in-memory computing, impose restrictions on materials that should operate fast, energy efficiently, and highly endurant. Here we report on in-memory computing architecture based on metal-organic framework (MOF) single crystal with a light control. We demonstrate that the MOF with inherent memristive behavior (for data storage) changes nonlinearly its electric response when irradiated by light. This leads to three and more electronic states (spikes) with 81 ms duration and 1 s refractory time, allowing to implement 40 bits s−1 optoelectronic data processing. Next, the architecture is switched to the neuromorphic state upon the action of a set of laser pulses, providing the text recognition over 50 times with app. 100% accuracy. Thereby, simultaneous data storage, processing, and neuromorphic computing on MOF, driven by light, pave the way for multifunctional in-memory computing architectures.

Авторы
Bachinin Semyon V.1 , Marunchenko Alexandr1 , Matchenya Ivan1 , Zhestkij Nikolai1 , Shirobokov Vladimir1 , Gunina Ekaterina1 , Novikov Alexander 2, 3 , Timofeeva Maria1 , Povarov Svyatoslav A.1 , Li Fengting4 , Milichko Valentin A.1, 5
Издательство
Springer Nature Limited
Номер выпуска
1
Язык
Английский
Статус
Опубликовано
Том
5
Год
2024
Организации
  • 1 School of Physics and Engineering, ITMO University, Saint Petersburg, 197101, Russia
  • 2 Saint Petersburg State University, Saint Petersburg, 199034, Russia
  • 3 Рeoples’ Friendship University of Russia, Moscow, 117198, Russia
  • 4 Key Laboratory of Climate change and adaptation, China Administration of Meteorology; Shanghai Institute of Pollution Control and Ecological Security; College of Environmental Science and Engineering, Tongji University, 201804, Shanghai, China
  • 5 Institut Jean Lamour, Universit de Lorraine, UMR CNRS 7198, 54011, Nancy, France
Дата создания
21.10.2024
Дата изменения
21.10.2024
Постоянная ссылка
https://repository.rudn.ru/ru/records/article/record/157653/
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