ArticleSmall (Weinheim an der Bergstrasse, Germany)2026
Deterministic Switching-Path Engineering of CMOS-Integrated 2D Memristors for Neuromorphic Computing.
Jihoon Yang, Sohui Yoon, Jaehong Im, Jaemin Kim, Seonghyeok Park, Jaeeun Park, Seong-Jin Kim, Zonghoon Lee, Joonki Suh, Hongsik Jeong and 3 more
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In one paragraphArticle in Small (Weinheim an der Bergstrasse, Germany), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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13 authors.
Jihoon YangDepartment of Materials Science and Engineering and Graduate School of Semiconductor Materials and Devices Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, Republic of Korea.
Sohui YoonDepartment of Materials Science and Engineering and Graduate School of Semiconductor Materials and Devices Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, Republic of Korea.
Jaehong ImDepartment of Materials Science and Engineering and Graduate School of Semiconductor Materials and Devices Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, Republic of Korea.ORCID https://orcid.org/0009-0002-8108-915X Jaemin KimDepartment of Materials Science and Engineering and Graduate School of Semiconductor Materials and Devices Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, Republic of Korea.ORCID https://orcid.org/0000-0001-8675-7271 Jaeeun ParkDepartment of Materials Science and Engineering and Graduate School of Semiconductor Materials and Devices Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, Republic of Korea.
Zonghoon LeeDepartment of Materials Science and Engineering and Graduate School of Semiconductor Materials and Devices Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, Republic of Korea.ORCID https://orcid.org/0000-0003-3246-4072 Joonki SuhDepartment of Materials Science and Engineering and Graduate School of Semiconductor Materials and Devices Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, Republic of Korea.ORCID https://orcid.org/0000-0002-0221-8447 Hongsik JeongDepartment of Materials Science and Engineering and Graduate School of Semiconductor Materials and Devices Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, Republic of Korea.ORCID https://orcid.org/0000-0003-4367-5625 Dong-Hyeok LimDepartment of Materials Science and Engineering and Graduate School of Semiconductor Materials and Devices Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, Republic of Korea.
Soon-Yong KwonDepartment of Materials Science and Engineering and Graduate School of Semiconductor Materials and Devices Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, Republic of Korea.ORCID https://orcid.org/0000-0002-2432-0418 Funding
Institute for Basic Science IBS-R019-G1Korea Institute for Advancement of Technology P0023703Korea Institute for Advancement of Technology P0028867National Research Foundation of Korea 2021R1C1C2012077National Research Foundation of Korea RS-2021-NR059677National Research Foundation of Korea RS-2023-00218908National Research Foundation of Korea RS-2025-12602968Ulsan National Institute of Science and Technology 1.250004.01Ulsan National Institute of Science and Technology 1.250008.01UNIST ISD program of the Ministry of Science and ICT 1.260011.01
6 · The paper itselfAbstract
Two-dimensional (2D) memristors are promising for low-power and high-speed neuromorphic hardware. However, their performance under circuit-level constraints remains limited because resistive switching relies on native defects, hindering precise control of filament formation. Here, we report 2D MoTe
Indexed as
artificial neural networkdynamic rangeelectronic engineeringmemristornanoelectronicsnanomaterialsneuromorphic engineeringscalabilitytransistor
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