1. Exploring the potential of TiO2/ZrO2 memristors for neuromorphic computing: Annealing strategy and synaptic characteristics.
- Author
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Ali, Sarfraz, Hussain, Muhammad, Ismail, Muhammad, Iqbal, Muhammad Waqas, and Kim, Sungjun
- Subjects
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HIGH resolution electron microscopy , *MEMRISTORS , *ARTIFICIAL neural networks , *ZIRCONIUM oxide , *CYCLING - Abstract
Artificial Neural Networks (ANNs) have reshaped computing paradigms, transcending traditional methods. Leveraging oxide-based bilayer RRAM memristors, specifically TiO2/ZrO2 deposited via sputtering, offers remarkable potential for RS memory and neuromorphic computing. This study pioneers an extensive annealing approach to counteract variability challenges in LRS and HRS during endurance tests. The Pt/TiO 2 /ZrO 2 /Pt memristor device's structural aspects are validated through cross-sectional high resolution transmission electron microscopy (HRTEM) analysis. Systematic XPS examination investigates the impact of annealing on oxygen vacancies. Successful bipolar resistive switching is unveiled through I-V characteristics, with 550°C annealing optimizing stable endurance cycling (1000 dc cycles). Conduction mechanisms during set/reset are illuminated, corroborated by Schottky emission fitting. Synaptic behavior emulation, Spike-Timing-Dependent Plasticity (STDP), and theoretical simulations with a 28×28 MNIST dataset underscore the ANN's 84.6% average recognition rate. The amalgamation of MNIST-based artificial learning and the innovative annealing strategy holds exciting potential for memory applications and advanced neuromorphic explorations. • Enhanced synaptic behavior in ZrO 2 /TiO 2 memristive synapses via extensive annealing strategy. • Annealing impact on oxygen vacancies assessed by XPS, improving electrical properties. • Optimal 550°C annealing ensures stable endurance cycling, minimal resistance state variations. • Long-term synaptic traits emulated via weight updates using matching pulse sequences. • ANN using 28×28 MNIST data attains 84.6% average recognition rate. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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