Kang, Unhyeon Lee, Jaesang Oh, Seungmin Song, Hanchan Park, Jongkil Kim, Jaewook Park, Seongsik Jang, Hyun Jae Kim, Sangbum Yi, Su-in Kumar, Suhas Lee, Suyoun 2026-01-13T07:00:32Z 2026-01-13T07:00:32Z 2026-01-12 2026-01 1530-6984 https://pubs.kist.re.kr/handle/201004/153983 Over the past decade, dendrites of neurons, which were previously thought to perform only information pooling and networking, have now been shown to express complex temporal dynamics, Boolean-like logic, arithmetic, signal discrimination, and edge detection. Mimicking this rich functionality could offer a powerful primitive for neuromorphic computing. Here, using Ovonic threshold switching in Sb–Te-doped GeSe, we demonstrate a single two-terminal component capable of self-sustained dynamics and universal Boolean logic in addition to XOR operations (which is traditionally thought to require a network of active components). We then employed logic-driven dynamics to detect and estimate the gradients of edges in images. The Ovonic switch exhibits properties of a half adder and a full adder in addition to discriminative logic accommodating inhibitory and excitatory signals. We show that this simple computational primitive offers a highly improved energy efficiency. As such, this work paves the path for potentially emulating dendrites for efficient postdigital neuromorphic computing. English American Chemical Society Ovonic Switches Enable Energy-Efficient Dendrite-like Computing Article 10.1021/acs.nanolett.5c04348 1 Nano Letters, v.26, no.2, pp.699 - 706 Nano Letters 26 2 699 706 N scie 001639348000001 Chemistry, Multidisciplinary Chemistry, Physical Nanoscience & Nanotechnology Materials Science, Multidisciplinary Physics, Applied Physics, Condensed Matter Chemistry Science & Technology - Other Topics Materials Science Physics Article MEMRISTORS neuromorphic engineering Ovonic threshold switch dendrite-like computing Boolean logic operation image processing energy-efficient computing