The commercial implementation of aqueous Zn-ion batteries is being impeded by the rampant dendrite growth and exacerbated side reactions on the Zn metal anodes. Herein, a 60 nm artificial protective layer with spatial dielectric–metallic gradient composition (denoted as GZH) is developed via Zn and HfO2 cosputtering. In this design, the top HfO2 layer with high permittivity and low electronic conductivity effectively suppresses hydrogen evolution. The intermediate Zn-rich oxide region promotes the dendrite-free Zn deposition and reinforces the contact between Zn and the sputtered layer. This design allows stable battery operation at high currents. Symmetric cells with Zn-GZH exhibit stable voltage separation over 500 h at 10 mA cm–2 with a cutoff capacity of 5 mAh cm–2. When paired with a vanadate cathode, the full-cell battery delivers a capacity retention of around 75% after 2000 cycles. This design concept may apply to other aqueous metal batteries.

Emerging technologies, i.e., spintronics, 2D materials, and memristive devices, have been widely investigated as the building block of neuromorphic computing systems. Three-terminal memristor (3TM) is specifically designed to mitigate the challenges encountered by its two-terminal counterpart as it can concurrently execute signal transmission and memory operations. In this work, we present a complementary metal-oxide-semiconductor-compatible 3TM with highly linear weight update characteristics and a dynamic range of ∼15. The switching mechanism is governed by the migration of oxygen ions and protons in and out of the channel under an external gate electric field. The involvement of the protonic defects in the electrochemical reactions is proposed based on the bipolar pulse trains required to initiate the oxidation process and the device electrical characteristics under different humidity levels. For the synaptic operation, an excellent endurance performance with over 256k synaptic weight updates was demonstrated while maintaining a stable dynamic range. Additionally, the synaptic performance of the 3TM is simulated and implemented into a four-layer neural network (NN) model, achieving an accuracy of ∼92% in MNIST handwritten digit recognition. With such desirable conductance modulation characteristics, our proposed 3T-memristor is a promising synaptic device candidate to realize the hardware implementation of the artificial NN.

The readout margin of the one selector-one RRAM (1S1R) crossbar array architecture is strongly dependent on the nonlinearity of the selector device. In this work, we demonstrated that the nonlinearity of Pt/TiO2/Pt exponential selectors increases with decreasing oxygen vacancy defect density. The defect density is controlled by modulating the sputtering pressure in the oxide deposition process. Our results reveal that the dominant conduction mechanisms of the Pt/TiO2/Pt structure transit from Schottky emission to Poole-Frenkel emission with the increase of sputtering pressure. Such transition is attributed to the rise of oxygen vacancy concentration. In addition, the short-term plasticity feature of the Pt/TiO2/Pt selector is shown to be enhanced with a lower defect density. These results suggest that low defect density is necessary for improved exponential selector performances.