Thermally driven single-electron stochastic resonance.

Stochastic resonance (SR) in a single-electron system is expected to allow information to be correctly carried and processed by single electrons in the presence of thermal fluctuations. Here, we comprehensively study thermally driven single-electron SR. The response of the system to a weak voltage signal is formulated by considering the single-electron tunneling rate, instead of the Kramers' rate generally used in conventional SR models. The model indicates that the response of the system is maximized at finite temperature and that the peak position is determined by the charging energy. This model quantitatively reproduces the results of a single-electron device simulator. Single-electron SR is also demonstrated using a GaAs-based single-electron system that integrates a quantum dot and a high-sensitivity charge detector. The developed model will contribute to our understanding of single-electron SR and will facilitate accurate prediction, design, and control of single-electron systems.

Effect of asymmetric deformation dynamics in amoeboid organism on its search ability.

We investigate the effect of asymmetric deformation dynamics in an amoeboid organism on its search ability using a model amoeba. The model represents the behaviours of the amoeboid organism and its search ability is evaluated by searching for the solution to a Boolean satisfiability problem (SAT). We found that the efficiency of the search is significantly improved by implementing asymmetric delays in response to the feedback signals that increase and decrease the variable under appropriate errors. The results indicate that the model could search around the variable vector space by means of the appropriate combination of the inherent local search in the model and the error-induced global search. The results also show that the asymmetric response delays bias the variable to the values that can satisfy the SAT. We also demonstrate that an analog electronic system implementing the amoeba model with asymmetric dynamics possesses the search characteristics of the model.

Amoeba-inspired analog electronic computing system integrating resistance crossbar for solving the travelling salesman problem.

Combinatorial optimization to search for the best solution across a vast number of legal candidates requires the development of a domain-specific computing architecture that can exploit the computational power of physical processes, as conventional general-purpose computers are not powerful enough. Recently, Ising machines that execute quantum annealing or related mechanisms for rapid search have attracted attention. These machines, however, are hard to map application problems into their architecture, and often converge even at an illegal candidate. Here, we demonstrate an analogue electronic computing system for solving the travelling salesman problem, which mimics efficient foraging behaviour of an amoeboid organism by the spontaneous dynamics of an electric current in its core and enables a high problem-mapping flexibility and resilience using a resistance crossbar circuit. The system has high application potential, as it can determine a high-quality legal solution in a time that grows proportionally to the problem size without suffering from the weaknesses of Ising machines.

Energy gap opening by crossing drop cast single-layer graphene nanoribbons.

Band gap opening of a single-layer graphene nanoribbon (sGNR) sitting on another sGNR, fabricated by drop casting GNR solution on Au(111) substrate in air, was studied by means of scanning tunneling microscopy and spectroscopy in an ultra-high vacuum at 78 K and 300 K. GNRs with a width of ∼45 nm were prepared by unzipping double-walled carbon nanotubes (diameter ∼15 nm) using the ultrasonic method. In contrast to atomically-flat GNRs fabricated via the bottom-up process, the drop cast sGNRs were buckled on Au(111), i.e., some local points of the sGNR are in contact with the substrate (d âˆ¼ 0.5 nm), but other parts float (d âˆ¼ 1-3 nm), where d denotes the measured distance between the sGNR and the substrate. In spite of the fact that the nanoribbons were buckled, dI/dV maps confirmed that each buckled sGNR had a metallic character (∼3.5 Go) with considerable uniform local density of states, comparable to a flat sGNR. However, when two sGNRs crossed each other, the crossed areas showed a band gap between -50 and +200 meV around the Fermi energy, i.e., the only upper sGNR electronic property changed from metallic to p-type semiconducting, which was not due to the bending, but the electronic interactions between the up and down sGNRs.

Room-temperature discrete-charge-fluctuation dynamics of a single molecule adsorbed on a carbon nanotube.

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-effect transistor provides tunable current fluctuation noise. A unique charge-trap state in the vicinity of the CNT surface due to the presence of the single molecule is the origin of the noise, which generates a prominent and unique slow discrete random telegraph signal in the device current. The power spectral density reveals the peculiar frequency limit of the fluctuation for different types of molecules depending on their redox activity and adsorption configuration. These results indicate that the detected noise will provide new opportunities to obtain electronic information for a single molecule combined with a nanotube surface, and that controllability of the noise may contribute to the expansion of noise utilization in future bio-inspired devices.

Method for Controlling Electrical Properties of Single-Layer Graphene Nanoribbons via Adsorbed Planar Molecular Nanoparticles.

A simple method for fabricating single-layer graphene nanoribbons (sGNRs) from double-walled carbon nanotubes (DWNTs) was developed. A sonication treatment was employed to unzip the DWNTs by inducing defects in them through annealing at 500 °C. The unzipped DWNTs yielded double-layered GNRs (dGNRs). Further sonication allowed each dGNR to be unpeeled into two sGNRs. Purification performed using a high-speed centrifuge ensured that more than 99% of the formed GNRs were sGNRs. The changes induced in the electrical properties of the obtained sGNR by the absorption of nanoparticles of planar molecule, naphthalenediimide (NDI), were investigated. The shape of the I-V curve of the sGNRs varied with the number of NDI nanoparticles adsorbed. This was suggestive of the existence of a band gap at the narrow-necked part near the NDI-adsorbing area of the sGNRs.

Design and characterization of nonlinear functions for the transmission of a small signal with non-Gaussian noise.

We design nonlinear functions for the transmission of a small signal with non-Gaussian noise and perform experiments to characterize their responses. Using statistical design theory [A. Ichiki and Y. Tadokoro, Phys. Rev. E 87, 012124 (2013)], a static nonlinear function is estimated from the probability density function of the given noise in order to maximize the signal-to-noise ratio of the output. Using an electronic system that implements the optimized nonlinear function, we confirm the recovery of a small signal from a signal with non-Gaussian noise. In our experiment, the non-Gaussian noise is a mixture of Gaussian noises. A similar technique is also applied to the optimization of the threshold value of the function. We find that, for non-Gaussian noise, the response of the optimized nonlinear systems is better than that of the linear system.

A binary-decision-diagram-based two-bit arithmetic logic unit on a GaAs-based regular nanowire network with hexagonal topology.

A two-bit arithmetic logic unit (ALU) was successfully fabricated on a GaAs-based regular nanowire network with hexagonal topology. This fundamental building block of central processing units can be implemented on a regular nanowire network structure with simple circuit architecture based on graphical representation of logic functions using a binary decision diagram and topology control of the graph. The four-instruction ALU was designed by integrating subgraphs representing each instruction, and the circuitry was implemented by transferring the logical graph structure to a GaAs-based nanowire network formed by electron beam lithography and wet chemical etching. A path switching function was implemented in nodes by Schottky wrap gate control of nanowires. The fabricated circuit integrating 32 node devices exhibits the correct output waveforms at room temperature allowing for threshold voltage variation.