Tactile tribotronic reconfigurable p-n junctions for artificial synapses

Autor:	Mengmeng Jia, Pengwen Guo, Wei Wang, Aifang Yu, Yufei Zhang, Zhong Lin Wang, Junyi Zhai
Rok vydání:	2022
Předmět:	Multidisciplinary Artificial Intelligence Synapses Learning Graphite
Zdroj:	Science Bulletin. 67:803-812
ISSN:	2095-9273
Popis:	The emulation of biological synapses with learning and memory functions and versatile plasticity is significantly promising for neuromorphic computing systems. Here, a robust and continuously adjustable mechanoplastic semifloating-gate transistor is demonstrated based on an integrated graphene/hexagonal boron nitride/tungsten diselenide van der Waals heterostructure and a triboelectric nanogenerator (TENG). The working states (p-n junction or n
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fbb30d0c32d1546b51767cd83133861e https://doi.org/10.1016/j.scib.2021.12.014 Zobrazit plný text záznamu Full Text from ScienceDirect