Journal of Semiconductors, Volume. 42, Issue 1, 013101(2021)
Towards engineering in memristors for emerging memory and neuromorphic computing: A review
Fig. 1. (Color online) Recent materials used for memristive storage and applied in artificial synapses. (a) The sketch of filamentary-based resistive switching in an inorganic metal oxide (HfO
Fig. 2. (Color online) Memristor and resistive switching characteristics. (a) Atomic force micrograph of 17 × 17 nano-cross bar array: the inset shows the schematic structure of the cross point. Reprinted from Ref. [
Fig. 3. (Color online) Memristor synapse mimicking the representative synaptic functions of biological synapses for neuromorphic computing applications. (a) Synaptic potentiation and depression behavior of biological synapses obtained from a pair of glutamatergic neurons in hippocampal culture. (b) STDP behavior of biological synapse. Reprinted from Ref. [
Fig. 4. (Color online) Memristors with ternary - ABO
Fig. 5. (Color online) Doping effects and modulation of memory oxide storage. (a) Resistive switching effect variations in HfO2–
Fig. 6. (Color online) Bilayer memristors with heterostructured and homostructured switching materials. (a) Cross-sectional TEM image of the IGZO/MnO heterostructured bilayer device. (b) Typical
Fig. 7. (Color online) Tuning switching behaviors by controlling the stacking sequence of the switching layers in bilayer memristors. Typical
Fig. 8. (Color online) Engineering of the switching modes of single-layer memristors using bilayers, and by controlling the composition of the component materials in the bilayer structures. (a) Schematic of a bilayer device structure, with a cross-sectional TEM image.
Fig. 9. (Color online) Tunability of switching behaviors with bilayer and doped switching materials for improved emulation of synaptic functions. (a) Cross-sectional TEM image of a bilayer ZrO2/ZTO memristor device. The realization of a gradual multilevel switching in the bilayer device by controlling (b) compliance current during the SET process and (c) RESET-stop voltage during the RESET process. (d) Synaptic conductance modulation mimicking LTP and LTD behaviors. (e) Successful emulation of inter-spiking interval dependent PPF behavior, evaluated for various pulse intervals. (f) Experimental demonstration of STDP learning rule. Reprinted from Ref. [
Fig. 10. (Color online) Structural engineering of switching materials using rapid thermal annealing (RTA). Cross-sectional TEM images of the (a) as-deposited device without RTA and (b) RTA-processed device. Typical
Fig. 11. (Color online) Artificial synapse characteristics of a cone-shaped n-ZnO based memristor. (a) Schematic of fabricated cone-shaped n-ZnO based memory device. (b) TEM images of n-ZnO cone-shaped profile, equipped with EDS analysis, displaying stoichiometry of n-ZnO in separated regions, (c) low-current analog multi-level resistive switching
Fig. 12. (Color online) Frequency–spike-rate dependent plasticity (SRDP) synapse characteristics of memristors. (a) plasticity modulation of synapse device by frequency in an Ag/PEDOT:PSS/Ta memristor. (b) High-frequency stimulation spiking increases current via Ag/PEDOT:PSS/Ta memristor. Reprinted from Ref. [
Fig. 13. (Color online) Synaptic crossbar arrays with volatile threshold switching for the emulation of synaptic plasticity. (a) SEM image of a fabricated crossbar array, with a magnified image of a single cross-point memristor cell. (b) Cross-sectional TEM image of a single memristor cell with structure Ag/HfO2/Pt. The FFT patterns indicate the morphology of the corresponding thin films. (c) Schematics of a biological synapse and a fabricated electronic synapse, presenting the correlation between the two. (d) Typical
Fig. 14. (Color online) Synaptic memristor based on nitrogen-doped graphene oxide (N-GOQDs). (a) TEM cross-section image of N-GOQDs-based device, in an Ag/N-GOQDs/Pt structure. (b) Schematic of the fabricated device, depicting Ag ion migration via various functional groups in the N-GOQDs matrix. (c)
Fig. 15. (Color online) Organic storage memristor and leaky-integrate and fire (LIF) characteristics. (a) PVK-C60-based memory, switching mechanism of RS behavior, and corresponding
Fig. 16. (Color online) Memristor advances in 2D material devices. (a) Memristor device schematic with 2D (PEA)2PbBr4 perovskite single crystal-based memory storage and TEM cross-section image of the device. (b) Experimentally measured low-current STP & LTP characteristics of memristor synapse device. Reprinted from Ref. [
Fig. 17. (Color online) Advances in memristor devices. (a) Schematic of hetero-synaptic plasticity synapse device, influenced by neuro-modulatory axon. (b) Hetero-synaptic memristor device. (c) Pre-synaptic pulse operation, influenced by modulatory bias. Reprinted from Ref. [
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Andrey S. Sokolov, Haider Abbas, Yawar Abbas, Changhwan Choi. Towards engineering in memristors for emerging memory and neuromorphic computing: A review[J]. Journal of Semiconductors, 2021, 42(1): 013101
Category: Reviews
Received: Jul. 31, 2020
Accepted: --
Published Online: Mar. 19, 2021
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