期刊
JOURNAL OF ALLOYS AND COMPOUNDS
卷 868, 期 -, 页码 -出版社
ELSEVIER SCIENCE SA
DOI: 10.1016/j.jallcom.2021.159194
关键词
Memristor; Titanium dioxide; Nitrogen-doped; Tunable memory lifetime
资金
- Science and Technology Plan Project of Hunan Province [2015TP1007]
- Central South University [202045002]
- National Natural Science Foundation for Young Scientists of China [51802353]
- Graduate innovation project of Central South University [1053320183232]
Titanium dioxide memristors doped with nitrogen exhibit excellent performance in mimicking synaptic functions of the human brain, with bidirectional gradually changing conductance and high endurance over 8000 cycles. This promising approach for neuromorphic computing allows for synaptic features simulation and tunable memory lifetimes through manipulation of stimulation parameters.
Titanium dioxide memristors are promising next generation devices for neuromorphic computing, which can mimic synapses of human brain. With respect to meet satisfactory performance, gradual conductance changes and stability of cycling are essential. In this work, nitrogen-doped titanium dioxide nanorod arrays (N-TiO2 NARs) memristors with high performance have been fabricated using a hydrothermal process. The X-ray photo electron spectra confirm the existence of Ti.N bonds, with uniform distribution of nitrogen confirmed by elemental mapping. The bidirectional gradually changing conductance and endurance of over 8000 cycles have been achieved. The ratio of high resistance state (HRS) and low resistance state (LRS) exceeds 16. The synaptic features, such as potentiation, depression, paired pulse facilitation (PPF), experience-learning and STDP have been achieved using continuous sweeping voltage and pulse trains respectively. It is possible to emulate the learning processes by stimulating the memristor using pulses of different amplitude, duration and interval. By manipulating the stimulation pulse duration, voltage and current compliance, memory lifetimes (MLTs) can be tuned from seconds to tens of thousands of seconds. These transitional processes are associated with anion vacancy creation/accumulation and diffusion. Those synaptic features and tunable MLTs provide a promising approach for neuromorphic computing. (C) 2021 Published by Elsevier B.V.
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