Reconfigurable Cascaded Thermal Neuristors for Neuromorphic Computing

While the complementary metal‐oxide semiconductor (CMOS) technology is the mainstream for the hardware implementation of neural networks, an alternative route is explored based on a new class of spiking oscillators called “thermal neuristors”, which operate and interact solely via thermal processes. Utilizing the insulator‐to‐metal transition (IMT) in vanadium dioxide, a wide variety of reconfigurable electrical dynamics mirroring biological neurons is demonstrated. Notably, inhibitory functionality is achieved just in a single oxide device, and cascaded information flow is realized exclusively through thermal interactions. To elucidate the underlying mechanisms of the neuristors, a detailed theoretical model is developed, which accurately reflects the experimental results. This study establishes the foundation for scalable and energy‐efficient thermal neural networks, fostering progress in brain‐inspired computing. Targeting a scalable and energy‐efficient thermal neural network, a novel class of spiking oscillators termed “thermal neuristors” is engineered based on the insulator‐to‐metal transition (IMT) in vanadium dioxide. Solely through thermal interactions, a wide variety of reconfigurable functionalities mirroring biological neurons are demonstrated, including cascaded information flow, as well as excitatory and inhibitory interactions, without relying on traditional CMOS‐based circuits.