In current memristor-based neuromorphic computing research, several studies face the challenge of realizing only a single function at a time or having isolated functions. This limitation is particularly evident when simulating biological cognition, as the overall synergy between multiple cognitive functions is difficult to represent. In this work, a high-performance heterojunction memristor is presented at first. The memristor-based neural network and functional circuit are further implemented to realize and integrate multiple cognitive functions. Specifically, the proposed photoelectric memristor has the structure of Ag/ZnO-SnO₂/WO_3-x/ITO, it exhibits various synaptic behaviors under external modulations, which are characterized by good stability and repeatability. Based on this device, a neural network is built to realize the basic recognition function in biological cognition. The recognition results are translated into different labelled voltage signals and subsequently fed into a memristor-based functional circuit. By leveraging memory characteristics and tunable conductance of the memristor, and controlling the specific circuit functionalities, the input signals are processed to produce different outputs representing various cognitive functions. This methodology allows the realization and integration of recognition, memory, learning, association, relearning, and forgetting into one single system, thereby enabling a more comprehensive and authentic simulation of biological cognition. This work presents a novel memristor and a method for achieving and integrating multiple neuromorphic computing functions within a single system, providing a successful example for achieving complete biological function.

Developing a cotton fabric sensing layer with good waterproofness and breathability via a low-cost and eco-friendly method is increasingly important for the construction of comfortable and wearable electronic devices. Herein, a waterproof and breathable cotton fabric composite decorated by reduced graphene oxide (rGO) and carbon nanotube (CNT), Cotton/rGO/CNT, is reported by a facile solution infiltration method, and we adopt such Cotton/rGO/CNT composite to develop a layer-by-layer structured multifunctional flexible sensor, enabling the high-sensitivity detection of pressure and temperature stimulus. Particularly, the multifunctional flexible sensor exhibits a high response toward tiny pressure, demonstrating salient superiority in the continuous and reliable monitoring of human physiological information. Concerning temperature sensing, a good linear response for the temperatures ranging from 28 to 40 °C is achieved by the multifunctional flexible sensor and gives rise to be successfully applied to the non-contact real-time monitoring of human respiration signal. Finally, an array consisting of multifunctional flexible sensors further demonstrates its feasibility in perceiving and mapping the pressure and temperature information of contact objects. This work provides a feasible strategy for designing cotton-based sensing layers that can effectively resist liquid water penetration and allow water vapor transmission, and offers reasonable insight for constructing comfort and multifunctional wearable electronics.