Stable retention in SrTiO3/SrRuO3 heterostructure-based memristive devices

The switching dynamics in memristive devices resembles biological synapses, which makes these devices promising candidates for the development of artificial neural networks. The retention of the synaptic weight is a key parameter in performing artificial intelligent tasks, particularly the inference...

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Veröffentlicht in:	Science China materials 2023-03, Vol.66 (3), p.1140-1147
Hauptverfasser:	Wang, Ting-Ze, Xia, Jian, Yang, Rui, Miao, Xiangshui
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial neural networks Chemistry and Materials Science Chemistry/Food Science Electrodes Heterostructures Materials Science Memory devices Neural networks Oxygen Retention Strontium titanates Switching Synapses
Online-Zugang:	Volltext
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