Apr 26, 2024
10:45am - 11:00am
Room 343, Level 3, Summit
Erbin Qiu1,Yuan-Hang Zhang1,Massimiliano Di Ventra1,Ivan Schuller1
University of California, San Diego1
Erbin Qiu1,Yuan-Hang Zhang1,Massimiliano Di Ventra1,Ivan Schuller1
University of California, San Diego1
In our work, we explore a novel class of spiking oscillators termed "thermal neuristors". These neuristors function and communicate exclusively through thermal processes, utilizing the insulator-to-metal transition in vanadium dioxide. We showcase a diverse range of reconfigurable electrical behaviors that closely resemble those of biological neurons, including phenomena like the all-or-nothing law, type-II neuronal rate coding law, spike-in and DC out effect, spike-in and spike-out effect, and stochastic leaky integrate-and-firing law. Remarkably, inhibitory capabilities are achieved using just a single oxide device, and the transmission of cascaded information occurs solely through thermal interactions without any intricate circuits. This research serves as the groundwork for scalable and energy-efficient thermal neural networks, advancing the field of brain-inspired computing.