Abstract
Aside from recent advances in artificial intelligence (AI) models, specialized AI hardware is crucial for addressing large volumes of unstructured and dynamic data. Conventional complementary metal-oxide-semiconductor (CMOS)-based AI hardware faces several critical challenges including scaling limitations, the separation of computation and memory units, and overall system energy efficiency. While emerging materials have been proposed to overcome these limitations, issues such as scalability, reproducibility, and compatibility remain critical obstacles. Here, we demonstrate polymorphic electronic devices with programmable transistor, memristor, and memcapacitor functionalities by manipulating the quasi-two-dimensional electron gas in LaAlO3/SrTiO3 heterostructures using lateral gates. A circuit utilizing transistor and memcapacitor functionalities exhibits digit recognition, enabling implementation in physical reservoir computing. An integrated circuit incorporating transistor and memristor functionalities performs logic operations with in-situ output storage and supports advanced reconfigurable synaptic logic operations for multi-input decision-making tasks such as patient monitoring. Our findings pave the way for oxide-based monolithic integrated circuits in a scalable, silicon-compatible, energy-efficient single platform for polymorphic and neuromorphic computing.
Data availability
The data that support the findings of this study are available from the corresponding authors upon request.
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Acknowledgments
The authors gratefully acknowledge financial support by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) through the Würzburg-Dresden Cluster of Excellence ctd.qmat - Complexity, Topology and Dynamics in Quantum Matter (EXC 2147, project-id 390858490) as well as through the Collaborative Research Center SFB 1170 “ToCoTronics” (project-id 258499086). VLR acknowledges the support from Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq-Brasil), Proj. 311536/2022-0 and FAPESP Projs. 2025/04805-0 and 2025/00677-8.
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F.H. and S.H. initiated and guided the study. M.Spring, J.G., and B.L. grew the sample in discussion with M.Sing and R.C., S.K., and M.K. fabricated the devices. K.M. initiated the experiment, S.P. designed and conducted all the experimental work in discussion with F.H.. S.P, F.H., V.L., and S.H. analyzed and interpreted the experimental results. S.P. and F.H. wrote the manuscript, with input from all coauthors.
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Nature Communications thanks Dewei Chu, Ho Won Jang, Hyungwoo Lee and the other anonymous reviewer(s) for their contribution to the peer review of this work. A peer review file is available.
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Pradhan, S., Miller, K., Hartmann, F. et al. Oxide interface-based polymorphic electronic devices for neuromorphic computing. Nat Commun (2026). https://doi.org/10.1038/s41467-026-71642-2
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DOI: https://doi.org/10.1038/s41467-026-71642-2
