Abstract
Artificial neural network-based machine learning provides foundations for artificial intelligence (AI), yet requires high energy costs for training. Beyond software-level simulation of neural networks, hardware-level implementation via neuromorphic devices becomes the next milestone in nanoscience towards energy-sustainable AI. Single-molecule devices have the potential for ultimate scale and energy efficiency, but challenges remain in achieving programmable multi-conductance states amidst room-temperature thermal fluctuations. Here we fabricated a bio-inspired single-molecule neuromorphic device consuming ~6.34 aJ/operation by electrochemically gating molecule-ion electrostatic interactions. This device realizes biomimetic emulation of neural plasticity from short-term to long-term memory featuring over 10 distinct conductance states, demonstrating the applications in Pavlovian conditioning for associative learning and pattern recognition in Morse code processing. Our approach enables multi-state synaptic emulation using an individual molecule toward energy-sustainable AI.
Data availability
The relevant data used in this study are available in the figshare database under accession code https://doi.org/10.6084/m9.figshare.31528837. The Supplementary Movie 1 used in this study are available in the figshare database under accession code https://doi.org/10.6084/m9.figshare.31534159.
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Acknowledgements
This work was supported by the National Natural Science Foundation of China (Nos. 22325303 (W. Hong), 21933012 (D. Zhang), 92577016 (J. Liu), 22250003 (W. Hong), 22173075 (J. Liu), 22303071 (Y. Zhang)), the National Key Research and Development Program of China (2024YFA1208103) (J. Liu), the Fujian Provincial Department of Science and Technology (2023H6002) (J. Liu), and the Fundamental Research Funds for the Central Universities (Nos. 20720220020 (J. Liu), 20720200068 (W. Hong), and 20720240040 (Y. Zhang)), and the Open Research Fund of Key Laboratory of Precision and Intelligent Chemistry (W. Hong).
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W. Hong, D. Zhang, and J. Liu supervised the project. W. Hong, D. Zhang, J. Liu, and H. Zhang conceived the concept and designed the experiments. H. Zhang synthesized the test molecules with the support by W. Shang and L. Chen; H. Zhang performed the measurements with the support by Y. Jiang; H. Zhang conducted the data analysis with the support by J. Wu, B. Zhang, W. Xu, C. Yan, Z. Li, T. Zeng, X. Li, J. Bai, J. Li, Z. Xiao, J. Shi, Y. Zhang, and G. Zhang; J. Ye and M. Gao conducted the theoretical calculations with the help of Y. Zhou; W. Hong, D. Zhang, J. Liu, and H. Zhang prepared the manuscript with input from other authors.
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Zhang, H., Ye, J., Gao, M. et al. Single-molecule neuromorphic device with aJ-level power consumption per switching. Nat Commun (2026). https://doi.org/10.1038/s41467-026-71127-2
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DOI: https://doi.org/10.1038/s41467-026-71127-2
