Wafer‐Scale 3D Integration for High‐Density Multi‐Valued Neuromorphic Logic
As conventional transistor scaling approaches fundamental limits, multi-valued logic (MVL) has emerged as a promising strategy to enhance information density and reduce circuit complexity beyond binary complementary metal-oxide-semiconductor (CMOS) technology. Here, we present a monolithic three-dimensional (3D) vertically stacked MVL architecture based on a tellurium (Te)/indium-gallium-zinc-oxide (IGZO) heterojunction field-effect transistor (H-FET) integrated with a crystallinity-enhanced Te field-effect transistor (CE-Te FET). Engineered interfacial band alignment in the H-FET induces carrier confinement and gate-tunable electron-dominated transport, enabling intrinsic ternary switching through controlled current modulation. Complementary channel engineering of the CE-Te FET via oxidation and crystallinity recovery suppresses off-state leakage and optimizes transconductance matching, stabilizing the intermediate logic state. Using low-temperature CMOS-compatible processes, we realize wafer-scale vertically stacked ternary circuits exhibiting robust three-level operation, high uniformity, and long-term stability. System-level analysis reveals substantial gains in logic density and area efficiency enabled by H-FET-assisted 3D integration. Furthermore, the ternary voltage characteristics are directly mapped to ternary weight neural networks, enabling high-accuracy handwritten digit classification. This scalable inorganic 3D MVL platform establishes a practical pathway toward high-density logic and multi-valued neuromorphic computing architectures beyond conventional binary planar scaling.
Authors
- Ick-Joon Park (ORCID: https://orcid.org/0000-0001-8053-7008)
- Tae In Kim (ORCID: https://orcid.org/0000-0001-6278-1613)
- Joong Bum Rhim
- Hyuck‐In Kwon (ORCID: https://orcid.org/0000-0002-4332-051X)
- Chang-Hyeon Kim (ORCID: https://orcid.org/0000-0002-9419-7347)
- Min Seok Kim
Institutions
- Inha University (KR)
- Hansung University (KR)
- Massachusetts Institute of Technology (US)
- Chung-Ang University (KR)
Publication Details
- Journal
- Advanced Science
- Published
- 2026-08-25
- DOI
- https://doi.org/10.1002/advs.77437
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Research Foundation
- Hansung University
- Ministry of Trade, Industry and Energy
- Korea Institute for Advancement of Technology
- National Research Foundation of Korea
- Ministry of Science and ICT, South Korea