Tunable capacitive resistance switching with low-power synaptic bionic potential in (1–x)Bi0.88Nd0.12FeO3–xCaBi4Ti4O15 thin films

A memristor with a low power consumption, non-volatility, and adaptive abilities complex has a promising prospect in neural network computing systems due to its unique nonlinearity, memory, and local activity. Here, the Au/(1-x)Bi 0.88 Nd 0.12 FeO 3 -xCaBi 4 Ti 4 O 15 (BNFO-CBTO, x = 0.1, 0.2, 0.3,...

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Veröffentlicht in:	Journal of materials science. Materials in electronics 2025, Vol.36 (2), p.138, Article 138
Hauptverfasser:	Liu, Wenlong, Zong, Jin, Li, Di, Wei, Jiahua, Tan, Guoqiang, Yuan, Qibin, Liu, Dinghan, Xia, Ao
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptive systems Behavior Bionics Characterization and Evaluation of Materials Chemistry and Materials Science Data storage Materials Science Memory devices Mimicry Neural networks Optical and Electronic Materials Power management Sol-gel processes Thin films
Online-Zugang:	Volltext
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