An optoelectronic synaptic device based on the ITO/ Zn 2 SnO 4 (ZTO)/ITO structure is fabricated which integrates the electronic memory and optical sensing properties along with synaptic functions. The fabricated device shows over 80% optical transparency for the entire visible region (400−800 nm). Post-oxide annealing treatment is performed in a nitrogen environment at 200 °C. Significant improvements in bipolar resistive switching properties of the device with low SET voltage (+0.93 V) and long DC endurance cycles (∼12000) are observed in the annealed device. The linearity of such memristive synapse is improved for 350 training epochs with a total number of 175000 pulses. The spike time dependent plasticity learning rule for the annealed device is demonstrated through the electric field. The optical sensing capabilities of this device including photonic potentiation (responsivity: 0.52 μA/W), photonic paired pulse facilitation by adjusting time interval between two identical light pulses, learning experience behavior, and multilevel memory feature by the repetition of optical pulse for ∼10 3 s are demonstrated under the blue light (wavelength "λ" = 405 nm) illumination at 50 mW/cm 2 . Photonic potentiation and electric depression behavior of the device mimic its nonvolatile synaptic plasticity. The linear fitting of I−V curve illustrates the dominance of Schottky emission and Poole−Frenkel conduction mechanisms at high and low resistance states, respectively. The electric response of the device is explained by the oxygen vacancy based filamentary model. The trapping and detrapping of electrons during the adsorption and desorption processes of atmospheric oxygen molecules on the ITO surface are responsible for the photoconduction phenomenon. To train the Hopfield neural network (HNN) model for image processing of 28 × 28 pixels, the normalized experimental data of long-term potentiation/depression are employed to mimic the learning behavior of the human brain. The convergence of electronic data storage and optical sensor has high potential which provides a path toward the future smart invisible optoelectronics for artificial intelligence.

We explore the use of cubic-zinc peroxide (ZnO) as a switching material for electrochemical metallization memory (ECM) cell. The ZnO was synthesized with a simple peroxide surface treatment. Devices made without surface treatment exhibits a high leakage current due to the self-doped nature of the hexagonal-ZnO material. Thus, its switching behavior can only be observed when a very high current compliance is employed. The synthetic ZnO layer provides a sufficient resistivity to the Cu/ZnO/ZnO/ITO devices. The high resistivity of ZnO encourages the formation of a conducting bridge to activate the switching behavior at a lower operation current. Volatile and non-volatile switching behaviors with sufficient endurance and an adequate memory window are observed in the surface-treated devices. The room temperature retention of more than 10 s confirms the non-volatility behavior of the devices. In addition, our proposed device structure is able to work at a lower operation current among other reported ZnO-based ECM cells.

In this study, the effect of oxygen vacancy in the CoMn2O4 on pseudocapacitive characteristics was examined, and two tetragonal CoMn2O4 spinel compounds with different oxygen vacancy concentrations and morphologies were synthesized by controlling the mixing sequence of the Co and Mn precursors. The mixing sequence was changed; thus, morphologies were changed from spherical nanoparticles to nanoflakes and oxygen vacancies were increased. Electrochemical studies have revealed that tetragonal CoMn2O4 spinels with a higher number of oxygen vacancies exhibit a higher specific capacitance of 1709 F g−1 than those with a lower number of oxygen vacancies, which have a higher specific capacitance of 990 F g−1. Oxygen vacancies create an active site for oxygen ion intercalation. Therefore, oxidation–reduction reactions occur because of the diffusion of oxygen ions at octahedral/tetrahedral crystal edges. The solid-state asymmetric pseudocapacitor exhibits a maximum energy density of 32 Wh-kg−1 and an excellent cyclic stability of nearly 100%.

The synaptic linearity of resistive random-access memory (RRAM) based on TiO x /HfO2 improved by inserting an ultrathin Al2O3 layer is investigated. A gradual bipolar switching with a positive set and a negative reset is observed for devices with an Al2O3 layer after an electroforming process. The devices with a 1 nm Al2O3 layer exhibit acceptable reliability with >400 cycles DC endurance with no decrement of the on/off ratio after 104 sec. A remarkable enhancement in the synaptic linearity of potentiation 2.15 and depression 1.52 is achieved in this device. The conduction mechanisms at different current regions of the optimized device are studied. The presence of the Al2O3 layer is confirmed by x-ray photoelectron spectroscopy (XPS) and transmission electron microscopy analyses. About 42% of the oxygen vacancy concentration calculated from the XPS spectra is responsible for the synaptic properties. This synaptic RRAM structure is suitable for upcoming neuromorphic computing devices.

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