Monolithic three-dimensionally integrated memristor-thin-film transistor for electrically programmable multimode reservoir computing

Article Open access Published: 03 October 2026 Sung Keun Shim ORCID: orcid.org/0009-0008-3718-1833 1 na1 , Wonho Choi 1 na1 , Sunwoo Cheong 1 , Dong Hoon Shin 1 , Jonghoon Shin 1 , Janguk Han 1 , Jiseong Im ORCID: orcid.org/0000-0002-7260-9224 1 , Sungho Kim 1 , Kunhee Son 1 , Hyun Wook Kim ORCID: orcid.org/0009-0003-3345-9264 1 , Jin Hong Kim 1 , Jea Min Cho 1 , Junwoo Park 1 , Byongwoo Park 1 , Yoon Ho Jang 2 & ... Cheol Seong Hwang ORCID: orcid.org/0000-0002-6254-9758 1 Nature Communications ( 2026 ) Cite this article We’re sharing this article early to provide faster access to peer-reviewed, accepted research. It is citable and carries a permanent DOI. This version is subject to further edits and will be replaced automatically by the final Version of Record. All legal disclaimers apply. Abstract Reservoir computing offers an efficient framework for processing temporal information, but most hardware reservoirs exhibit fixed or narrowly tunable dynamics determined by intrinsic material relaxation time. A monolithically integrated memristor-thin-film transistor reservoir kernel of this study enables electrically programmable temporal dynamics across a wide timescale. By vertically and monolithically integrating Ru/HfO 2 /TiN memristors with In 2 O 3 channel thin-film transistors (TFTs), the memristive conductance dynamics are modulated by the TFTs. The temporal response can be actively tuned over three orders of magnitude experimentally and extended to over eight orders of magnitude via circuit configuration, demonstrating temporally unconstrained hardware with general applicability for spatiotemporal data processing. Implemented as an active reservoir array compatible with back-end-of-line integration, the system exhibits reliable spatiotemporal responses. The system demonstrates spatiotemporal computing capability through dynamic motion recognition in vision sensors and ultrasound signal classification, achieving high accuracy with a simple linear readout layer. Funding This work was supported by the National Research Foundation of Korea (Grant No. 2020R1A3B2079882). Author information Author notes These authors contributed equally: Sung Keun Shim, Wonho Choi. Authors and Affiliations Department of Materials Science and Engineering and Inter-university Semiconductor Research Center, Seoul National University, Seoul, 08826, Republic of Korea Sung Keun Shim, Wonho Choi, Sunwoo Cheong, Dong Hoon Shin, Jonghoon Shin, Janguk Han, Jiseong Im, Sungho Kim, Kunhee Son, Hyun Wook Kim, Jin Hong Kim, Jea Min Cho, Junwoo Park, Byongwoo Park & Cheol Seong Hwang Department of Materials Science and Engineering, College of Engineering, Yonsei University, Seoul, 03722, Republic of Korea Yoon Ho Jang Authors Sung Keun Shim Wonho Choi Sunwoo Cheong Dong Hoon Shin Jonghoon Shin Janguk Han Jiseong Im Sungho Kim Kunhee Son Hyun Wook Kim Jin Hong Kim Jea Min Cho Junwoo Park Byongwoo Park Yoon Ho Jang Cheol Seong Hwang Corresponding author Correspondence to Cheol Seong Hwang . Ethics declarations Competing interests The authors declare no competing interests. Additional information Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Rights and permissions Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/ . Reprints and permissions About this article Cite this article Shim, S.K., Choi, W., Cheong, S. et al. Monolithic three-dimensionally integrated memristor-thin-film transistor for electrically programmable multimode reservoir computing. Nat Commun (2026). https://doi.org/10.1038/s41467-026-78364-5 Download citation Received : 27 April 2026 Accepted : 22 September 2026 Published : 03 October 2026 DOI : https://doi.org/10.1038/s41467-026-78364-5