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DOE OSTI · 2575760

Reconfigurable Cascaded Thermal Neuristors for Neuromorphic Computing

Qiu, Erbin [Univ. of California, San Diego, CA (United States)] (ORCID:0000000174469248)·Zhang, Yuan‐Hang [Univ. of California, San Diego, CA (United States)]·Ventra, Massimiliano Di [Univ. of California, San Diego, CA (United States)]·Schuller, Ivan K. [Univ. of California, San Diego, CA (United States)]
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Abstract

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. In conclusion, this study establishes the foundation for scalable and energy-efficient thermal neural networks, fostering progress in brain-inspired computing.

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36 MATERIALS SCIENCEChemistryMaterials SciencePhysicsScience & Technology - Other TopicsThermal neuristorscascaded information flowinhibitory functionalityreconfigurable electronics

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Qiu, Erbin [Univ. of California, San Diego, CA (United States)] (ORCID:0000000174469248), Zhang, Yuan‐Hang [Univ. of California, San Diego, CA (United States)], Ventra, Massimiliano Di [Univ. of California, San Diego, CA (United States)], Schuller, Ivan K. [Univ. of California, San Diego, CA (United States)]. 2023-09-28. Reconfigurable Cascaded Thermal Neuristors for Neuromorphic Computing. https://doi.org/10.1002/adma.202306818

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