Hokkaido University · Engineering
Professor Megumi Akai-Kasaya's research lab specializes in molecular and nanoscale neuromorphic computing, focusing on the development of bio-inspired computing systems using low-dimensional carbon nanomaterials and redox-active molecules. The lab explores physical reservoir computing using electrochemical and molecular systems, such as polyoxometalate-doped carbon nanotube networks and self-assembled polydiacetylene wires, to harness intrinsic nonlinear dynamics for signal processing. A central theme is the integration of molecular complexity and dynamic response in 3D wetware-like environments to mimic brain-like computation. The lab also investigates noise dynamics in nanoscale devices for applications in sensing and adaptive computing.
Figures are computed from collected data and may differ slightly.
Nonlinear dynamical systems serving reservoir computing enrich the physical implementation of computing systems. A method for building physical reservoirs from electrochemical reactions is provided, and the potential of chemical dynamics as computing resources is shown. The essence of signal processing in such systems includes various degrees of ionic currents which pass through the solution as well as the electrochemical current detected based on a multiway data acquisition system to achieve sw
A molecular wire candidate, the polydiacetylene chain, fabricated in a substantial support layer of monomers self-assembled on a highly ordered pyrolytic graphite surface, was studied using scanning tunneling microscopy and spectroscopy. The density of states of individual polymers and constituent monomers were observed on the same surface, and then compared with the calculated results. The spectrum delineating the density of states of the polydiacetylene wire clearly reveals the theoretically p
Abstract Molecular neuromorphic devices are composed of a random and extremely dense network of single-walled carbon nanotubes (SWNTs) complexed with polyoxometalate (POM). Such devices are expected to have the rudimentary ability of reservoir computing (RC), which utilizes signal response dynamics and a certain degree of network complexity. In this study, we performed RC using multiple signals collected from a SWNT/POM random network. The signals showed a nonlinear response with wide diversity
Detection and use of physical noise fluctuations in a signal provides significant advantages in the development of bio- and neuro-sensing and functional mimicking devices. Low-dimensional carbon nanomaterials are a good candidate for use in noise generation due to the high surface sensitivity of these materials, which may themselves serve as the main building blocks of these devices. Here, we demonstrate that the addition of a molecule with high redox activity to a carbon nanotube (CNT) field-ef
Abstract Neural networks in the brain are structured in three-dimensional (3D) space, and the networks evolve through development and learning, whereas two-dimensional (2D) crossbars have essentially been optimized for a fully connected neural network, which results in a significant increase in unused memristors. Here, we present a prototype of molecular neural networks on wetware consisting of a space-free synaptic medium immersed in monomer solution. In the medium, conductive polymer wires are
Electronic transport was investigated in poly(3-hexylthiophene-2,5-diyl) monolayers. At low temperatures, nonlinear behavior was observed in the current-voltage characteristics, and a nonzero threshold voltage appeared that increased with decreasing temperature. The current-voltage characteristics could be best fitted using a power law. These results suggest that the nonlinear conductivity can be explained using a Coulomb blockade (CB) mechanism. A model is proposed in which an isotropic extende
A polydiacetylene nanowire fabricated on a highly ordered pyrolytic graphite surface was studied by scanning tunneling microscopy/spectroscopy (STM/STS). The spectroscopy of individual polydiacetylene nanowires revealed the theoretically predicted π-band and band edge singularities, which are characteristics of a one-dimensional π-conjugated polymer. Furthermore, under a high electric field intensity applied to the polymer wire, the spectrum shows a narrow band gap caused by polaron injection. W
Networks in the human brain are extremely complex and sophisticated. The abstract model of the human brain has been used in software development, specifically in artificial intelligence. Despite the remarkable outcomes achieved using artificial intelligence, the approach consumes a huge amount of computational resources. A possible solution to this issue is the development of processing circuits that physically resemble an artificial brain, which can offer low-energy loss and high-speed processi
We have demonstrated a switching system with a quantized point contact using the silver particle motion. By applying appropriate bias voltages, the silver particles that are positioned between a scanning tunneling microscope tip and a substrate stick and unstick to the tip. The minute motion of the particles is induced by sum of two Coulomb interactions. The typical conductance of the contact formed is constant, which shows low integral multiples of quantized conductance. Reproducible switching
Charge transport anisotropy in π-stacked poly(3-hexylthiophene-2,5-diyl) (P3HT) monolayers was investigated. The monolayers were prepared using a Langmuir–Blodgett technique and were uniaxial but homogeneous two-dimensional sheets. Nanoscale electrical measurements were carried out using metal electrodes with a submicrometre gap between them in order to exclude breaches that occasionally occur along the chains. A remarkable degree of isotropy in both the conductivity and mobility was found. The
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