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Decision trees within a molecular memristor


Profuse dendritic-synaptic interconnections among neurons in the neocortex embed intricate logic structures enabling sophisticated decision-making that vastly outperforms any artificial electronic analogues1,2,3. 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 environments4,5,6. 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 computing7,8,9.

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Fig. 1: Circuit element structure and I(V) characteristics.
Fig. 2: In situ spectroscopy.
Fig. 3: Decision thicket within a single molecular film circuit element.
Fig. 4: Realization of multivariable decision trees.

Data availability

The data on which the figures are constructed and from which the conclusions are drawn are available from the corresponding authors upon reasonable request.


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This research was supported by the Singapore National Research Foundation (NRF) under the Competitive Research Programs (CRP award no. NRF-CRP15-2015-01). Sreebrata Goswami acknowledges the financial support of SERB, India, through grants SR/S2/JCB-09/2011. R.S.W. acknowledges the X-Grants Program of the President’s Excellence Fund at Texas A&M University. A.A. thanks the Agency for Science, Technology and Research (A*STAR) for its Advanced Manufacturing and Engineering (AME) Individual Research Grant (IRG), A1983c0034. D.T. acknowledges support from Science Foundation Ireland (SFI) under awards 15/CDA/3491 and 12/RC/2275_P2, and supercomputing resources at the SFI/Higher Education Authority Irish Center for High-End Computing (ICHEC). We thank S. Hooda for RBS data, L. Haidong for making the shadow masks, S. Sarkar for helping with the in situ spectroscopic measurement setup, A. Tampèz for tip-induced current and spectroscopic measurements, F. Meyer and S. Demeshko for Mössbauer measurements and D. Deb for inputs regarding the figures. We thank W. Robinett, C. R. Sinha and Q. Xia for their comments and suggestions.

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Authors and Affiliations



Sreetosh Goswami devised the project and performed the electrical and spectroscopic measurements. R.S.W. and Sreetosh Goswami designed the experiments and performed data analysis. Sreebrata Goswami introduced the materials and proposed the molecular mechanism. R.P. and S.P.R. performed molecular synthesis and characterization. M.F. provided insights into circuit design. D.T. conceived and performed the electronic structure calculations. Sreetosh Goswami, T.V., D.T., M.F., A.P., A.A., Sreebrata Goswami and R.S.W. discussed and wrote the paper.

Corresponding authors

Correspondence to Sreetosh Goswami, T. Venkatesan, Sreebrata Goswami or R. Stanley Williams.

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The authors declare no competing interests.

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Peer review information Nature thanks Matthew Marinella, Ilia Valov and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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Supplementary information

Supplementary Information

This document contains 9 sections of Supplementary Discussion, with 47 Supplementary Figures and 4 Supplementary Tables providing additional information on circuit element fabrication, material characterisation, electrical, spectroscopic measurements, and data analysis supporting the main text.

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Goswami, S., Pramanick, R., Patra, A. et al. Decision trees within a molecular memristor. Nature 597, 51–56 (2021).

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