Realization of future neuro-biological architecture in power efficient memristors of Fe₃O₄/WS₂ hybrid nanocomposites

The future generation of digital technology will heavily rely on power efficient non-volatile resistive memory systems as a potential alternative to flash memory due to its limitations in scalability and endurance. To attain the commercial benchmark, memristors have still lacked performance. This study reports a novel and cost-effective solution processable method for growing surface-modified hybrid nanocomposites (Nc) on a large scale, as an active layer. The solution-processed synthesis approach used for Ag/Fe₅₀W₅₀/Pt hybrid nanocomposite memristor device results in the formation of heterophase grain boundaries, which create residual filaments along these boundaries. The device Fe₃O₄-WS₂(Nc) shows excellent performance, having ultra-low energy consumption (0.1fJ), high reproducibility (10 devices), scalability, excellent endurance (10⁶), and excellent environment stability. Density functional theory (DFT) simulations reveal that structural symmetry distortion and interfacial interaction of hybrid nanocomposite at the interface plays a vital role in the switching mechanism. As high-performance electronic synapses, the optimal pulse scheme enables a steady interaction of short- and long-term plasticity principles, such as spike -time dependent plasticity (STDP) and pulse pair facilitation (PPF), essential for learning and neuromorphic computing analogous to human brain. Moreover, by using Modified National Institute of Standards and Technology (MINST), the memristor device attained a high learning accuracy of 95.4% under convolution neural network (CNN) simulations. The present study revealed that the performance of hybrid-nanocomposite memristors could lead to efficient future neuromorphic architecture.