Multifunctional In-Memory Logics Based on a Dual-Gate Antiambipolar Transistor toward Non-von Neumann Computing Architecture.

In-memory computing may make it possible to realize non-von Neumann computing because the logic circuits are unified in the memory units. We investigated two types of in-memory logic operations, namely, two-input logic circuits and multifunctional artificial synapses. These were realized in a dual-gate antiambipolar transistor (AAT) with a ReS2/WSe2 heterojunction, in which polystyrene with a zinc phthalocyanine core (ZnPc-PS4) was incorporated as a memory layer. Here, reconfigurability is a key concept for both types of device operations and was achieved by merging the Λ-shaped transfer curve of the AAT and the nonvolatile memory effect of ZnPc-PS4. First, we achieved electrically reconfigurable two-input logic circuits. Versatile logic circuits such as AND, OR, NAND, NOR, and XOR circuits were demonstrated by taking advantage of the Λ-shaped transfer curve of the dual-gate AAT. Importantly, the nonvolatile memory function provided the electrical switching of the individual circuits between AND/OR, NAND/NOR, and XOR/NAND circuits with constant input signals. Second, the memory effect was applied to multifunctional artificial synapses. The inhibitory/excitatory and long-term potentiation/depression synaptic operations were electrically reconfigured simply by controlling one parameter (readout voltage), making three distinct responses possible even with the same presynaptic signals. These findings provide hints that may lead to the realization of new in-memory computing architectures beyond the current von Neumann computers.

Few- and single-molecule reservoir computing experimentally demonstrated with surface-enhanced Raman scattering and ion gating.

Molecule-based reservoir computing (RC) is promising for achieving low power consumption neuromorphic computing, although the information-processing capability of small numbers of molecules is not clear. Here, we report a few- and single-molecule RC that uses the molecular vibration dynamics in the para-mercaptobenzoic acid (pMBA) detected by surface-enhanced Raman scattering (SERS) with tungsten oxide nanorod/silver nanoparticles. The Raman signals of the pMBA molecules, adsorbed at the SERS active site of the nanorod, were reversibly perturbated by the application of voltage-induced local pH changes near the molecules, and then used to perform time-series analysis tasks. Despite the small number of molecules used, our system achieved good performance, including >95% accuracy in various nonlinear waveform transformations, 94.3% accuracy in solving a second-order nonlinear dynamic system, and a prediction error of 25.0 milligrams per deciliter in a 15-minute-ahead blood glucose level prediction. Our work provides a concept of few-molecular computing with practical computation capabilities.

Single-molecule detection with enhanced Raman scattering of tungsten oxide nanostructure.

We have found that tungsten oxide nanorods have a very large enhancement effect on Raman scattering. The nanorods with adsorbed 12CO and 13CO at the ratio of 1 : 1 were dispersed on a Si substrate and Raman mapping was performed. The Raman images of 12CO and 13CO were completely different, indicating that a very small number of molecules at the single-molecule level were observed. We also confirmed the characteristic blinking phenomenon when single-molecule detection was performed. The very large enhancement effect of Raman scattering can be attributed to the {001}CS structure of the tungsten oxide nanorods. It was confirmed from the DFT calculation results that the {001}CS structure exhibits two-dimensional electrical conduction properties.

Sleep-Dependent Memory Consolidation in a Neuromorphic Nanowire Network.

A neuromorphic network composed of silver nanowires coated with TiO2 is found to show certain parallels with neural networks in nature such as biological brains. Owing to the memristive properties emerging at nanowire-to-nanowire contacts, where the Ag/TiO2/Ag interface exists, the network can store information in the form of connectivity between nanowires in the network as electrically measured as an increase in conductance. The observed memory arises from an interplay between the topological constraints imposed by a complex network structure and the plasticity of its constituting memristive Ag/TiO2/Ag junctions. Regarding the long-term decay of the connectivity in the network, we further investigate the controllability of the established connectivity. Inspired by the regulated activity cycles of the human brain during sleep, a learning-sleep-recovery cycle was mimicked by applying voltage pulses, with controlling pulse heights and duty ratios, to the nanowire network. Interestingly, even when the conductance was lost during sleep, the network could quickly recover previous states of conductance in the recovery process after sleep. Comparison between results of experiments and theoretical simulations revealed that such a quick recovery of conductance can be realized by sparse voltage pulse application during sleep; in other words, sleep-dependent memory consolidation occurs and can be controlled. The present results provide clues to new learning designs in neuromorphic networks for achieving longer memory retention for future neuromorphic technology.

Emergent dynamics of neuromorphic nanowire networks.

Neuromorphic networks are formed by random self-assembly of silver nanowires. Silver nanowires are coated with a polymer layer after synthesis in which junctions between two nanowires act as resistive switches, often compared with neurosynapses. We analyze the role of single junction switching in the dynamical properties of the neuromorphic network. Network transitions to a high-conductance state under the application of a voltage bias higher than a threshold value. The stability and permanence of this state is studied by shifting the voltage bias in order to activate or deactivate the network. A model of the electrical network with atomic switches reproduces the relation between individual nanowire junctions switching events with current pathway formation or destruction. This relation is further manifested in changes in 1/f power-law scaling of the spectral distribution of current. The current fluctuations involved in this scaling shift are considered to arise from an essential equilibrium between formation, stochastic-mediated breakdown of individual nanowire-nanowire junctions and the onset of different current pathways that optimize power dissipation. This emergent dynamics shown by polymer-coated Ag nanowire networks places this system in the class of optimal transport networks, from which new fundamental parallels with neural dynamics and natural computing problem-solving can be drawn.

Metallic versus Semiconducting SWCNT Chemiresistors: A Case for Separated SWCNTs Wrapped by a Metallosupramolecular Polymer.

As-synthesized single-walled carbon nanotubes (SWCNTs) are a mixture of metallic and semiconducting tubes, and separation is essential to improve the performances of SWCNT-based electric devices. Our chemical sensor monitors the conductivity of an SWCNT network, wherein each tube is wrapped by an insulating metallosupramolecular polymer (MSP). Vapors of strong electrophiles such as diethyl chlorophosphate (DECP), a nerve agent simulant, can trigger the disassembly of MSPs, resulting in conductive SWCNT pathways. Herein, we report that separated SWCNTs have a large impact on the sensitivity and selectivity of chemical sensors. Semiconducting SWCNT (S-SWCNT) sensors are the most sensitive to DECP (up to 10000% increase in conductivity). By contrast, the responses of metallic SWCNT (M-SWCNT) sensors were smaller but less susceptible to interfering signals. For saturated water vapor, increasing and decreasing conductivities were observed for S- and M-SWCNT sensors, respectively. Mixtures of M- and S-SWCNTs revealed reduced responses to saturated water vapor as a result of canceling effects. Our results reveal that S- and M-SWCNTs compensate sensitivity and selectivity, and the combined use of separated SWCNTs, either in arrays or in single sensors, offers advantages in sensing systems.

Development and application of multiple-probe scanning probe microscopes.

In the research of advanced materials based on nanoscience and nanotechnology, it is often desirable to measure nanoscale local electrical conductivity at a designated position of a given sample. For this purpose, multiple-probe scanning probe microscopes (MP-SPMs), in which two, three or four scanning tunneling microscope (STM) or atomic force microscope (AFM) probes are operated independently, have been developed. Each probe in an MP-SPM is used not only for observing high-resolution STM or AFM images but also for forming an electrical contact enabling nanoscale local electrical conductivity measurement. The world's first double-probe STM (DP-STM) developed by the authors, which was subsequently modified to a triple-probe STM (TP-STM), has been used to measure the conductivities of one-dimensional metal nanowires and carbon nanotubes and also two-dimensional molecular films. A quadruple-probe STM (QP-STM) has also been developed and used to measure the conductivity of two-dimensional molecular films without the ambiguity of contact resistance between the probe and sample. Moreover, a quadruple-probe AFM (QP-AFM) with four conductive tuning-fork-type self-detection force sensing probes has been developed to measure the conductivity of a nanostructure on an insulating substrate. A general-purpose computer software to control four probes at the same time has also been developed and used in the operation of the QP-AFM. These developments and applications of MP-SPMs are reviewed in this paper.

Angled long tip to tuning fork probes for atomic force microscopy in various environments.

We expand the range of applications of a tuning fork probe (TFP) in frequency-modulation atomic force microscopy (FM-AFM) by attaching a long metal tip at a certain angle. By the combined flexure of the metal tip and the tuning fork prong, this TFP can change the direction of the detectable force by switching the resonance frequency, which has not been realized with conventional TFPs with short tips. The oscillatory behavior of the tip apex of the TFP is predicted by computer simulations and is experimentally confirmed with scanning electron microscope. FM-AFM operations using this TFP are performed in various environments, i.e., in ultrahigh vacuum, air, and water. FM-AFM images obtained at an atomic step of highly oriented pyrolytic graphite in air show a clear difference depending on the excitation frequency. It is also revealed that the higher order flexural modes of this TFP are advantageous for FM-AFM in water due to the reduction in the degree of hydrodynamic damping.

Functionalization of carbon nanotubes with a pH-responsive molecule to produce a pH sensor.

Carbon nanotubes were functionalized with the ratiometric pH-responsive dye molecule 6,8-dihydroxy-1,3-pyrenedisulfonic acid disodium salt, which enabled them to indicate pH values over the range of pH 5.6-8.3. The nanotubes were coated with a layer of electron-donating ZnPc, which strengthened the CNT-dye interaction. The range of pH response is relevant for biological systems, which makes the nanotubes suitable for a wide range of applications within nanobiotechnology.