Ultrathin SrTiO3-based oxide memristor with both drift and diffusive dynamics as versatile synaptic emulators for neuromorphic computing
doi: 10.1088/2752-5724/ace3dc
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Abstract: Artificial synapses are electronic devices that simulate important functions of biological synapses, and therefore are the basic components of artificial neural morphological networks for brain-like computing. One of the most important objectives for developing artificial synapses is to simulate the characteristics of biological synapses as much as possible, especially their self-adaptive ability to external stimuli. Here, we have successfully developed an artificial synapse with multiple synaptic functions and highly adaptive characteristics based on a simple SrTiO3/Nb: SrTiO3 heterojunction type memristor. Diverse functions of synaptic learning, such as short-term/long-term plasticity (STP/LTP), transition from STP to LTP, learning-forgetting-relearning behaviors, associative learning and dynamic filtering, are all bio-realistically implemented in a single device. The remarkable synaptic performance is attributed to the fascinating inherent dynamics of oxygen vacancy drift and diffusion, which give rise to the coexistence of volatile- and nonvolatile-type resistive switching. This work reports a multi-functional synaptic emulator with advanced computing capability based on a simple heterostructure, showing great application potential for a compact and low-power neuromorphic computing system.
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Key words:
- memristor /
- artificial synapse /
- synaptic plasticity /
- associative learning /
- learning-experience
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Figure 1. Device structure and the basic electrical characterization. (a) Schematic diagram of Au/Cr/STO/NSTO device. (b) I-V characteristic under positive and negative bias. (c) R-V loops measured with different pulse width. (d) Measured and fitted I-V curves of HRS and LRS for the device. (e) LRS resistance as a function of electrode sizes. (f) Schematic diagram of oxygen vacancy migration and the corresponding energy band diagrams for LRS and HRS. (g) Endurance behavior.
Figure 2. Short-term plasticity of the Au/Cr/STO/NSTO artificial synapse. (a) EPSC triggered by a single pulse of 0.9 V, 100
s. (b) The EPSCs triggered by a pair of positive pulses of 1 V, 100 s. (c) The varying of PPF as a function of the relative pulse interval t. (d) The EPSCs triggered by a pair of negative pulses of -1.2 V, 1 ms. (e) The variation of PPD as a function of t. (f) PTP as a function of t, and (g) EPSC under ten pulse stimulations with different pulse frequencies. 
Figure 3. Long-term plasticity of the Au/Cr/STO/NSTO artificial synapse. (a) and (b) Long-term potentiation and long-term depression, respectively. EPSC response to the pulse sequence with different (c) pulse amplitude, (d) pulse width, (e) pulse interval, and (f) pulse number. (g) The EPSC triggered by 30 consecutive pulses with different frequencies. (h) Frequency dependence of EPSC gain A30/A1 and the fitting results by the sigmoidal-shaped function.
Figure 4. The learning-forgetting-relearning process achieved within a single Au/Cr/STO/NSTO memristor. (a), (c) and (e) Demonstrate the first, second and third learning stage, while (b), (d) and (f) give the first, second and third forgetting process. The amplitude and duration of the voltage pulses are 0.8 V and 100
s, respectively. The conductance responses are monitored with a small voltage of 0.1 V. -
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