Decision trees within a molecular memristor Academic Article uri icon

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 treesĀ (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.

author list (cited authors)

  • Goswami, S., Pramanick, R., Patra, A., Rath, S. P., Foltin, M., Ariando, A., ... Williams, R. S.

publication date

  • January 1, 2021 11:11 AM

published in