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Neuro-inspired computing architectures are one of the leading candidates to solve complex, large-scale associative learning problems. The two key building blocks for neuromorphic computing are the synapse and the neuron, which form the distributed computing and memory units. Solid state implementations of these units remain an active area of research. Specifically, voltage or current controlled oscillators are considered a minimal representation of neurons for hardware implementations. Such oscillators should demonstrate synchronization and coupling dynamics for demonstrating collective learning behavior, besides the desirable individual characteristics such as scaling, power, and performance. To this end, we propose the use of nanoscale, epitaxial heterostructures of phase change oxides and oxides with metallic conductivity as a fundamental unit of an ultralow power, tunable electrical oscillator capable of operating in the microwave regime. Our simulations show that optimized heterostructure design with low thermal boundary resistance can result in operation frequency of up to 3 GHz and power consumption as low as 15 fJ/cycle with rich coupling dynamics between the oscillators.
Energy-efficient programmable photonic integrated circuits (PICs) are the cornerstone of on-chip classical and quantum optical technologies. Optical phase shifters constitute the fundamental building blocks which enable these programmable PICs. Thus
A technique for rapidly detecting microwave phase has been developed which uses a spintronic device that can directly rectify microwave fields into a dc voltage signal. Use of a voltage-controlled phase shifter enables the development of a spintronic
Phase-change memory devices have found applications in in-memory computing where the physical attributes of these devices are exploited to compute in place without the need to shuttle data between memory and processing units. However, non-idealities
A simple method has been used to synthesize nanostructured La0.5Ba0.5CoO3 (LBCO) powders, by confining chemical precursors into the pores of polycarbonate filters. The proposed method allows us to obtain powders formed by crystallites of different si
Thermal wave crystals based on the dual-phase-lag model are investigated in this paper by both theoretical analysis and numerical simulation to control the non-Fourier heat conduction process. The transfer matrix method is used to calculate the compl