Emerging optoelectronic memristors are promising candidates to develop neuromorphic computing, owing to the combined advantages of photonics and electronics. However, the reversible modulation on device conductance usually requires complicated operations involving hybrid optical/electrical signals. Herein, we design a fully light-modulated memristor based on ZnO/MoOx heterojunction, which exhibits potentiation and depression behaviors under the irradiation of ultraviolet and visible light, respectively. Several basic synaptic functions have been emulated by utilizing optical signals, including short-term/long-term plasticity and spike-number-dependent plasticity. Based on the all-optical modulation characteristics, low-level image pre-processing (including contrast enhancement and noise reduction) is demonstrated. Furthermore, logic operations (“AND,” “NOTq,” and “NIMP”) can be performed by combining various optical signals in the same device. The memristive switching mechanism under optical stimulus can be attributed to barrier change at the heterojunction interface. This work proposes a fully light-modulated memristor based on ZnO/MoOx heterojunction that may promote the development of neuromorphic computing with high efficiency.

Vertically stacked all-organic active-matrix organic light-emitting diodes are promising candidates for high-quality skin-like displays due to their high aperture ratio, extreme mechanical flexibility, and low-temperature processing ability. However, these displays suffer from process interferences when interconnecting functional layers made of all-organic materials. To overcome this challenge, we present an innovative integration strategy called “discrete preparation-multilayer lamination” based on microelectronic processes. In this strategy, each functional layer was prepared separately on different substrates to avoid chemical and physical damage caused by process interferences. A single interconnect layer was introduced between each vertically stacked functional layer to ensure mechanical compatibility and interconnection. Compared to the previously reported layer-by-layer preparation method, the proposed method eliminates the need for tedious protection via barrier and pixel-defining layer processing steps. Additionally, based on active-matrix display, this strategy allows multiple pixels to collectively display a pattern of “1” with an aperture ratio of 83%. Moreover, the average mobility of full-photolithographic organic thin-film transistors was 1.04 cm² V⁻¹ s⁻¹, ensuring stable and uniform displays. This strategy forms the basis for the construction of vertically stacked active-matrix displays, which should facilitate the commercial development of skin-like displays in wearable electronics.

True random number generator (TRNG) that cannot be arbitrary attacked with predictable software algorithm is a promising data security solution. Memristors, possessing specific intrinsic stochasticity, are just appropriate to be the random sources for encryption applications. In this work, a TRNG system based on the stochastic duration time of double threshold-switching (TS) memristors is proposed. The reliable stochasticity of this system is mainly attributed to the gradual dissolution of Ag conductive channels and the synergistic effect of these two TS memristors. A digital circuit system based on the micro-controller unit is designed to produce stable random “0” and “1” bitstreams. The random data key generated by this double TS memristor TRNG passed the National Institute of Standards and Technology randomness tests without post-processing procedure. Taking advantage of the true random data key, the binary image can be encrypted and decrypted by executing the XNOR logic operation. In addition, the Gaussian noise effect on the decryption stability of image information secure communication is also analyzed. Although 90% Gaussian noise was applied to the original image, the pristine binary image still can be roughly recognized. This work demonstrates that the double TS memristors-based TRNG system has great potential for hardware security applications.

For the design of a horizontal-axis tidal current turbine with adaptive variable-pitch blades, both numerical simulations and physical model experiments were used to study the hydrodynamic performance of symmetrical airfoil blades based on backward swept models. According to the lift–drag ratio of symmetrical airfoils, variable airfoil sections were selected for each part of the blade in the spanwise direction. Then, three kinds of blades were designed by using different swept-back models from wind turbines. A rotation model with a multi-reference frame was employed to conduct a three-dimensional steady numerical simulation of the turbine model based on the CFD method. The axial thrust and energy-capturing efficiency under different tip speed ratios, as well as the corresponding starting torque under different flow rates, were analyzed. The simulation results indicate that model 2 has optimal start-up performance, and model 3 has the largest power coefficient. The thrust coefficient of model 1 is the smallest. In all, model 2 has better comprehensive performance. The experiments of model 2 show that it has suitable hydrodynamic performance to capture bidirectional energy via passively variable pitch. This research provides an important solution for the design and optimization of horizontal-axis turbines to harvest bidirectional tidal current energy.