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Multifunctional CMOS-integrable and reconfigurable 2D ambipolar tellurene transistors for neuromorphic and in-memory computingopen access

Authors
You, BolimHuh, JihoonKim, YunaYang, MinoKim, UnjeongJoo, Min-KyuHahm, Myung GwanLee, Moonsang
Issue Date
Jul-2025
Publisher
Royal Society of Chemistry
Keywords
Oxide Semiconductors; Reconfigurable Architectures; Ambipolar; Complementary Metal Oxide Semiconductors; Computing Architecture; Cutting Edges; Multifunctionals; Neumann; Neumann Computing; Neuromorphic; Reconfigurable; Two-dimensional; Cmos Integrated Circuits; Metal Oxide; Nanomaterial; Article; Atomic Layer Deposition; Controlled Study; Human; Major Clinical Study; Memory; Semiconductor; Transistor
Citation
Nanoscale Horizons, v.10, no.8, pp 1760 - 1770
Pages
11
Indexed
SCIE
SCOPUS
Journal Title
Nanoscale Horizons
Volume
10
Number
8
Start Page
1760
End Page
1770
URI
https://scholarworks.dongguk.edu/handle/sw.dongguk/58515
DOI
10.1039/d5nh00113g
ISSN
2055-6756
2055-6764
Abstract
Despite significant efforts to eliminate the von Neumann bottleneck with new two-dimensional (2D) nanomaterial-based cutting-edge device structures, there remains room for exploring alternative computing architectures that leverage 2D nanomaterials. This study introduced a groundbreaking strategy featuring a complementary metal-oxide semiconductor (CMOS)-integrable and reconfigurable ambipolar 2D tellurene (Te) transistor toward non-von Neumann computing architecture. The innovative scenario integrated seamlessly with CMOS technology, utilizing the p/n-switchable ambipolar characteristics inherited from precise Fermi-level alignment via thermal atomic layer deposition. Further, the architecture exhibited remarkable synaptic behavior while maintaining the conventional inverter performance within a compact single 2D Te device architecture. Expanding these findings, we demonstrated a compact programmable CMOS inverter with reduced spatial complexity and also visualized the construction of diverse complementary logic-in-memory computing. The results of this study pave the way for revolutionary in-memory computing that transcends the boundaries of the von Neumann architecture based on 2D nanomaterials.
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