Modeling and Analysis of a Radiative Thermal Memristor

Featured Application The radiative thermal memristor boasts versatile applications, excelling particularly in contactless thermal sensing, where its unique properties make it ideal for scenarios requiring non-intrusive temperature measurements. Additionally, it holds promise in revolutionizing neuromorphic computing systems, contributing significantly to energy-efficient information processing that mimics the human brain. Furthermore, the integration of radiative thermal memristors into memory devices presents opportunities for optimizing performance, enhancing data storage, and advancing memory device technologies.Abstract This study presents a theoretical framework for a radiative thermal memristor (RTM), utilizing Tungsten-doped vanadium dioxide (WVO) as the phase-change material (PCM) and silicon carbide (SiC) in the far-field regime. The behavior of the RTM is depicted through a Lissajous curve, illustrating the relationship between net flux (Q) and a periodically modulated temperature difference Delta T(t). It is established that temperature variations in the memristance (M) of the RTM form a closed loop, governed by PCM hysteresis. The analysis explores the impact of thermal conductivity contrast (r) and periodic thermal input amplitude (theta) on the Q-Delta T curve and the M-Delta T curve and negative differential thermal resistance (NDTR), revealing notable effects on the curve shapes and the emergence of NDTR. An increasing r leads to changes in the Lissajous curve's shape and enhances the NDTR influence, while variations in both r and (theta) significantly affect the Q values and Lissajous curve amplitudes. In the M-Delta T curve, the height is linked to thermal conductivity contrast (r), with increasing r resulting in higher curve heights.