This study evaluated the memristive switching characteristics of a biomaterial solid polymer electrolyte (SPE) chitosan-based memristor and confirmed its artificial synaptic behavior with analog switching. Despite the potential advantages of organic memristors for high-end electronics, the unstable multilevel states and poor reliability of organic devices must be overcome. The fabricated Ti/SPE-chitosan/Pt-structured memristor has stable bipolar resistive switching (BRS) behavior due to a cation-based electrochemical reaction between a polymeric electrolyte and metal ions and exhibits excellent endurance in 5 × 10² DC cycles. In addition, we achieved multilevel per cell (MLC) BRS I-V characteristics by adjusting the set compliance current (I_cc) for analog switching. The multilevel states demonstrated uniform resistance distributions and nonvolatile retention characteristics over 10⁴ s. These stable MLC properties are explained by the laterally intensified conductive filaments in SPE-chitosan, based on the linear relationship between operating voltage margin (ΔV_switching) and I_cc. In addition, the multilevel resistance dependence on I_cc suggests the capability of continuous analog resistance switching. Chitosan-based SPE artificial synapses ensure the emulation of short- and long-term plasticity of biological synapses, including excitatory postsynaptic current, inhibitory postsynaptic current, paired-pulse facilitation, and paired-pulse depression. Furthermore, the gradual conductance modulations upon repeated stimulation by 10⁴ electric pulses were evaluated in high stability.

In this study, we implemented a high-performance two-terminal memristor device with a metal/insulator/metal (MIM) structure using a solution-derived In-Ga-Zn-Oxide (IGZO)-based nanocomposite as a resistive switching (RS) layer. In order to secure stable memristive switching characteristics, IGZO:N nanocomposites were synthesized through the microwave-assisted nitridation of solution-derived IGZO thin films, and the resulting improvement in synaptic characteristics was systematically evaluated. The microwave-assisted nitridation of solution-derived IGZO films was clearly demonstrated by chemical etching, optical absorption coefficient analysis, and X-ray photoelectron spectroscopy. Two types of memristor devices were prepared using an IGZO or an IGZO:N nanocomposite film as an RS layer. As a result, the IGZO:N memristors showed excellent endurance and resistance distribution in the 10³ repeated cycling tests, while the IGZO memristors showed poor characteristics. Furthermore, in terms of electrical synaptic operation, the IGZO:N memristors possessed a highly stable nonvolatile multi-level resistance controllability and yielded better electric pulse-induced conductance modulation in 5 × 10² stimulation pulses. These findings demonstrate that the microwave annealing process is an effective synthesis strategy for the incorporation of chemical species into the nanocomposite framework, and that the microwave-assisted nitridation improves the memristive switching characteristics in the oxide-based RS layer.

In this study, we evaluated the improved memristive switching characteristics of hydrogen silsesquioxane (HSQ) nanocomposites embedded with a single-walled carbon nanotube (SWCNT) random network. A low-temperature solution process was implemented using a flexible memristor device on a polyethylene naphthalate (PEN) substrate. The difference in the resistive switching (RS) behavior due to the presence of the SWCNT random network was analyzed by the current transport mechanism. Such a random network not only improves the RS operation but also facilitates a stable multilevel RS performance. The multiple-resistance states exhibited highly reliable nonvolatile retention properties over 10⁴ s at room temperature (25 °C) and at a high temperature (85 °C), showing the possibility of an analog synaptic weight modulation. Consequently, the gradual weight potentiation/depression was realized through 3 × 10² synaptic stimulation pulses. These findings suggest that the embedded SWCNT random network can improve the synaptic weight modulation characteristics with high stability for an artificial synapse and hence can be used in future neuromorphic circuits.

We have investigated how the parameters of an input gate voltage (V _g) waveform and a drain voltage (V _d) impact the performance of reservoir computing (RC) using a Hf_0.5Zr_0.5O₂ ferroelectric FET (FeFET). The RC performance is maximized by the high swing amplitude of the V _g and the most symmetrical polarization switching condition in the triangular-shaped input waveform, obtained by the center V _g of 0.5 V, because of the enhanced polarization switching of the FeFETs. Regarding the V _d dependence, the amount of the drain current and polarization switching have a trade-off relationship. As a result, a moderate V _d of 1.0 V becomes optimum in terms of the RC performance because a difference in drain current responses between different gate input patterns is maximized with this V _d. Furthermore, high computing capacities are achieved by combining the above optimal bias condition with drain current responses to both original and inverted gate input patterns.

In this study, we propose a polysilicon (poly-Si) channel thin-film synaptic transistor based on an organic-inorganic hybrid electric-double-layer (EDL) structured gate dielectric. To implement the hybrid EDLs, which play a key role in artificial synaptic transistors, a protonic mobile ion-based bio-inspired chitosan electrolyte and a high-k Ta ₂ O ₅ dielectric thin-film were applied. Synaptic modulation was realized on the poly-Si channels by the polarization reaction of mobile protonic ions in the organic chitosan electrolyte. The chemically and mechanically stable inorganic Ta ₂ O ₅ dielectric capping layer prevented deterioration of the organic electrolyte due to the patterning and etching processes, enabling the fabrication of large-scale integrated circuits. The fabricated EDL field-effect transistors (FETs) verified essential synaptic behavior. Therefore, polarization and depolarization in EDLs, paired-pulse facilitation, and excitatory post-synaptic current modulation were successfully emulated by applying pre-synaptic stimulation spikes. As a result, the proposed CMOS-compatible poly-Si thin-film synaptic FETs based on hybrid EDLs are suitable for emerging neuromorphic systems and compact artificial neural networks.