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Decision trees within a molecular memristor

Author

Listed:
  • Sreetosh Goswami

    (National University of Singapore
    National University of Singapore
    National University of Singapore)

  • Rajib Pramanick

    (Indian Association for the Cultivation of Science (IACS))

  • Abhijeet Patra

    (National University of Singapore
    On Deck)

  • Santi Prasad Rath

    (Indian Association for the Cultivation of Science (IACS))

  • Martin Foltin

    (Hewlett Packard Enterprise)

  • A. Ariando

    (National University of Singapore
    National University of Singapore
    National University of Singapore)

  • Damien Thompson

    (University of Limerick)

  • T. Venkatesan

    (National University of Singapore
    National University of Singapore
    National University of Singapore
    National University of Singapore)

  • Sreebrata Goswami

    (Indian Association for the Cultivation of Science (IACS))

  • R. Stanley Williams

    (Texas A&M University)

Abstract

Profuse dendritic-synaptic interconnections among neurons in the neocortex embed intricate logic structures enabling sophisticated decision-making that vastly outperforms any artificial electronic analogues1–3. The physical complexity is far beyond existing circuit fabrication technologies: moreover, the network in a brain is dynamically reconfigurable, which provides flexibility and adaptability to changing environments4–6. In contrast, state-of-the-art semiconductor logic circuits are based on threshold switches that are hard-wired to perform predefined logic functions. To advance the performance of logic circuits, we are re-imagining fundamental electronic circuit elements by expressing complex logic in nanometre-scale material properties. Here we use voltage-driven conditional logic interconnectivity among five distinct molecular redox states of a metal–organic complex to embed a ‘thicket’ of decision trees (composed of multiple if-then-else conditional statements) having 71 nodes within a single memristor. The resultant current–voltage characteristic of this molecular memristor (a 'memory resistor', a globally passive resistive-switch circuit element that axiomatically complements the set of capacitor, inductor and resistor) exhibits eight recurrent and history-dependent non-volatile switching transitions between two conductance levels in a single sweep cycle. The identity of each molecular redox state was determined with in situ Raman spectroscopy and confirmed by quantum chemical calculations, revealing the electron transport mechanism. Using simple circuits of only these elements, we experimentally demonstrate dynamically reconfigurable, commutative and non-commutative stateful logic in multivariable decision trees that execute in a single time step and can, for example, be applied as local intelligence in edge computing7–9.

Suggested Citation

  • Sreetosh Goswami & Rajib Pramanick & Abhijeet Patra & Santi Prasad Rath & Martin Foltin & A. Ariando & Damien Thompson & T. Venkatesan & Sreebrata Goswami & R. Stanley Williams, 2021. "Decision trees within a molecular memristor," Nature, Nature, vol. 597(7874), pages 51-56, September.
  • Handle: RePEc:nat:nature:v:597:y:2021:i:7874:d:10.1038_s41586-021-03748-0
    DOI: 10.1038/s41586-021-03748-0
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    Citations

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    Cited by:

    1. Shuzhi Liu & Jianmin Zeng & Zhixin Wu & Han Hu & Ao Xu & Xiaohe Huang & Weilin Chen & Qilai Chen & Zhe Yu & Yinyu Zhao & Rong Wang & Tingting Han & Chao Li & Pingqi Gao & Hyunwoo Kim & Seung Jae Baik , 2023. "An ultrasmall organic synapse for neuromorphic computing," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    2. Liying Xu & Jiadi Zhu & Bing Chen & Zhen Yang & Keqin Liu & Bingjie Dang & Teng Zhang & Yuchao Yang & Ru Huang, 2022. "A distributed nanocluster based multi-agent evolutionary network," Nature Communications, Nature, vol. 13(1), pages 1-10, December.

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