Structures, fundamental properties, and potential applications of low-dimensional C60 polymers and other nanocarbons: a review.

Since carbon (C) atom has a variety of chemical bonds via hybridization between s and p atomic orbitals, it is well known that there are robust carbon materials. In particular, discovery of C60 has been an epoch making to cultivate nanocarbon fields. Since then, nanocarbon materials such as nanotube and graphene have been reported. It is interesting to note that C60 is soluble and volatile unlike nanotube and graphene. This indicates that C60 film is easy to be produced on any kinds of substrates, which is advantage for device fabrication. In particular, electron-/photo-induced C60 polymerization finally results in formation of one-dimensional (1D) metallic peanut-shaped and 2D dumbbell-shaped semiconducting C60 polymers, respectively. This enables us to control the physicochemical properties of C60 films using electron-/photo-lithography techniques. In this review, we focused on the structures, fundamental properties, and potential applications of the low-dimensional C60 polymers and other nanocarbons such as C60 peapods, wavy-structured graphene, and penta-nanotubes with topological defects. We hope this review will provide new insights for producing new novel nanocarbon materials and inspire broad readers to cultivate new further research in carbon materials.

We review the structures, fundamental properties, and applications of low-dimensional C₆₀ polymers and other related nanocarbons such as C₆₀ peapods, wavy-structured graphene, and penta-nanotubes from a standpoint of topological defects.

Neuromorphic learning, working memory, and metaplasticity in nanowire networks.

Nanowire networks (NWNs) mimic the brain's neurosynaptic connectivity and emergent dynamics. Consequently, NWNs may also emulate the synaptic processes that enable higher-order cognitive functions such as learning and memory. A quintessential cognitive task used to measure human working memory is the n-back task. In this study, task variations inspired by the n-back task are implemented in a NWN device, and external feedback is applied to emulate brain-like supervised and reinforcement learning. NWNs are found to retain information in working memory to at least n = 7 steps back, remarkably similar to the originally proposed "seven plus or minus two" rule for human subjects. Simulations elucidate how synapse-like NWN junction plasticity depends on previous synaptic modifications, analogous to "synaptic metaplasticity" in the brain, and how memory is consolidated via strengthening and pruning of synaptic conductance pathways.

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.

Self-Organizing, Environmentally Stable, and Low-Cost Copper-Nickel Complex Inks for Printed Flexible Electronics.

Cost-effective copper conductive inks are considered as the most promising alternative to expensive silver conductive inks for use in printed electronics. However, the low stability and high sintering temperature of copper inks hinder their practical application. Herein, we develop rapidly customizable and stable copper-nickel complex inks that can be transformed in situ into uniform copper@nickel core-shell nanostructures by a self-organized process during low-temperature annealing and immediately sintered under photon irradiation to form copper-nickel alloy patterns on flexible substrates. The complex inks are synthesized within 15 min via a simple mixing process and are particle-free, air-stable, and compatible with large-area screen printing. The manufactured patterns exhibit a high conductivity of 19-67 µΩ·cm, with the value depending on the nickel content, and can maintain high oxidation resistance at 180 °C even when the nickel content is as low as 6 wt %. In addition, the printed copper-nickel alloy patterns exhibit high flexibility as a consequence of the local softening and mechanical anchoring effect between the metal pattern and the flexible substrate, showing strong potential in the additive manufacturing of highly reliable flexible electronics, such as flexible radio-frequency identification (RFID) tags and various wearable sensors.

Information dynamics in neuromorphic nanowire networks.

Neuromorphic systems comprised of self-assembled nanowires exhibit a range of neural-like dynamics arising from the interplay of their synapse-like electrical junctions and their complex network topology. Additionally, various information processing tasks have been demonstrated with neuromorphic nanowire networks. Here, we investigate the dynamics of how these unique systems process information through information-theoretic metrics. In particular, Transfer Entropy (TE) and Active Information Storage (AIS) are employed to investigate dynamical information flow and short-term memory in nanowire networks. In addition to finding that the topologically central parts of networks contribute the most to the information flow, our results also reveal TE and AIS are maximized when the networks transitions from a quiescent to an active state. The performance of neuromorphic networks in memory and learning tasks is demonstrated to be dependent on their internal dynamical states as well as topological structure. Optimal performance is found when these networks are pre-initialised to the transition state where TE and AIS are maximal. Furthermore, an optimal range of information processing resources (i.e. connectivity density) is identified for performance. Overall, our results demonstrate information dynamics is a valuable tool to study and benchmark neuromorphic systems.

Avalanches and edge-of-chaos learning in neuromorphic nanowire networks.

The brain's efficient information processing is enabled by the interplay between its neuro-synaptic elements and complex network structure. This work reports on the neuromorphic dynamics of nanowire networks (NWNs), a unique brain-inspired system with synapse-like memristive junctions embedded within a recurrent neural network-like structure. Simulation and experiment elucidate how collective memristive switching gives rise to long-range transport pathways, drastically altering the network's global state via a discontinuous phase transition. The spatio-temporal properties of switching dynamics are found to be consistent with avalanches displaying power-law size and life-time distributions, with exponents obeying the crackling noise relationship, thus satisfying criteria for criticality, as observed in cortical neuronal cultures. Furthermore, NWNs adaptively respond to time varying stimuli, exhibiting diverse dynamics tunable from order to chaos. Dynamical states at the edge-of-chaos are found to optimise information processing for increasingly complex learning tasks. Overall, these results reveal a rich repertoire of emergent, collective neural-like dynamics in NWNs, thus demonstrating the potential for a neuromorphic advantage in information processing.

Dual Surface Architectonics for Directed Self-Assembly of Ultrahigh-Resolution Electronics.

The directed self-assembly of electronic circuits using functional metallic inks has attracted intensive attention because of its high compatibility with extensive applications ranging from soft printed circuits to wearable devices. However, the typical resolution of conventional self-assembly technologies is not sufficient for practical applications in the rapidly evolving additively manufactured electronics (AMEs) market. Herein, an ultrahigh-resolution self-assembly strategy is reported based on a dual-surface-architectonics (DSA) process. Inspired by the Tokay gecko, the approach is to endow submicrometer-scale surface regions with strong adhesion force toward metallic inks via a series of photoirradiation and chemical polarization treatments. The prepared DSA surface enables the directed self-assembly of electronic circuits with unprecedented 600 nm resolution, suppresses the coffee-ring effect, and results in a reliable conductivity of 14.1 ± 0.6 µΩ cm. Furthermore, the DSA process enables the layer-by-layer fabrication of fully printed organic thin-film transistors with a short channel length of 1 µm, which results in a large on-off ratio of 106 and a high field-effect mobility of 0.5 cm2  V-1  s-1 .

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.

Topological Properties of Neuromorphic Nanowire Networks.

Graph theory has been extensively applied to the topological mapping of complex networks, ranging from social networks to biological systems. Graph theory has increasingly been applied to neuroscience as a method to explore the fundamental structural and functional properties of human neural networks. Here, we apply graph theory to a model of a novel neuromorphic system constructed from self-assembled nanowires, whose structure and function may mimic that of human neural networks. Simulations of neuromorphic nanowire networks allow us to directly examine their topology at the individual nanowire-node scale. This type of investigation is currently extremely difficult experimentally. We then apply network cartographic approaches to compare neuromorphic nanowire networks with: random networks (including an untrained artificial neural network); grid-like networks and the structural network of C. elegans. Our results demonstrate that neuromorphic nanowire networks exhibit a small-world architecture similar to the biological system of C. elegans, and significantly different from random and grid-like networks. Furthermore, neuromorphic nanowire networks appear more segregated and modular than random, grid-like and simple biological networks and more clustered than artificial neural networks. Given the inextricable link between structure and function in neural networks, these results may have important implications for mimicking cognitive functions in neuromorphic nanowire networks.

Sub-monolayer Au9 cluster formation via pulsed nozzle cluster deposition.

Submonolayer coverages of chemically synthesised triphenylphosphine-protected Au9 clusters on mica and TiO2 substrates were achieved through the development of a Pulsed Nozzle Cluster Deposition (PNCD) technique under high vacuum conditions. This method offers the deposition of pre-prepared, solvated clusters directly onto substrates in a vacuum without the potential for contamination from the atmosphere. AFM and TEM were used to investigate the rate of gold cluster deposition as a function of cluster solution concentration and the number of pulses, with pulse number showing the most effective control of the final deposition conditions. TEM and XPS were used to determine that the clusters retained their unique properties through the deposition process. Methanol solvent deposited in the PNCD process has been shown to be removable through post-deposition treatments. A physical model describing the vapour behaviour and solvent evaporation in a vacuum is also developed and presented.

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.

Controlled Modification of Superconductivity in Epitaxial Atomic Layer-Organic Molecule Heterostructures.

Self-assembled organic molecules can potentially be an excellent source of charge and spin for two-dimensional (2D) atomic-layer superconductors. Here we investigate 2D heterostructures based on In atomic layers epitaxially grown on Si and highly ordered metal-phthalocyanine (MPc, M = Mn, Cu) through a variety of techniques: scanning tunneling microscopy, electron transport measurements, angle-resolved photoemission spectroscopy, X-ray magnetic circular dichroism, and ab initio calculations. We demonstrate that the superconducting transition temperature (Tc) of the heterostructures can be modified in a controllable manner. Particularly, the substitution of the coordinated metal atoms from Mn to Cu is found to reverse the Tc shift from negative to positive directions. This distinctive behavior is attributed to a competition of charge and spin effects, the latter of which is governed by the directionality of the relevant d-orbitals. The present study shows the effectiveness of molecule-induced surface doping and the significance of microscopic understanding of the molecular states in these 2D heterostructures.

Surfactant-free Fabrication of Fullerene C60 Nanotubules Under Shear.

A method for controlling the self-assembly of fullerene C60 molecules into nanotubules in the fcc phase, devoid of entrapped solvent, has been established in a thin film microfluidic device. The micron length C60 nanotubules, with individual hollow diameters of 100 to 400 nm, are formed under continuous flow processing during high shear micromixing of water and a toluene solution of the fullerene, in the absence of surfactant, and without the need for further down-stream processing. TEM revealed pores on the surface of the nanotubes, and the isolated material has a much higher response to small molecule sensing than that for analogous material formed using multistep batch processing.

Atomically resolved structure of ligand-protected Au9 clusters on TiO2 nanosheets using aberration-corrected STEM.

Triphenylphosphine ligand-protected Au9 clusters deposited onto titania nanosheets show three different atomic configurations as observed by scanning transmission electron microscopy. The configurations observed are a 3-dimensional structure, corresponding to the previously proposed Au9 core of the clusters, and two pseudo-2-dimensional (pseudo-2D) structures, newly found by this work. With the help of density functional theory (DFT) calculations, the observed pseudo-2D structures are attributed to the low energy, de-ligated structures formed through interaction with the substrate. The combination of scanning transmission electron microscopy with DFT calculations thus allows identifying whether or not the deposited Au9 clusters have been de-ligated in the deposition process.

Self-assembled honeycomb lattice in the monolayer of cyclic thiazyl diradical BDTDA (= 4,4'-bis(1,2,3,5-dithiadiazolyl)) on Cu(111) with a zero-bias tunneling spectra anomaly.

Scanning tunneling microscopy (STM) observation reveals that a cyclic thiazyl diradical, BDTDA (= 4,4'-bis(1,2,3,5-dithiadiazolyl)), forms a well-ordered monolayer honeycomb lattice consisting of paramagnetic corners with unpaired electrons on a clean Cu(111) surface. This BDTDA lattice is commensurate with the triangular lattice of Cu(111), with the former being 3 × 3 larger than the latter. The formation of the BDTDA monolayer structure, which is significantly different from its bulk form, is attributed to an interaction with the metal surface as well as the intermolecular assembling forces. STM spectroscopy measurements on the BDTDA molecules indicate the presence of a characteristic zero-bias anomaly centered at the Fermi energy. The origin of this zero-bias anomaly is discussed in terms of the Dirac cones inherent to the honeycomb structure.

Current-Driven Supramolecular Motor with In Situ Surface Chiral Directionality Switching.

Surface-supported molecular motors are nanomechanical devices of particular interest in terms of future nanoscale applications. However, the molecular motors realized so far consist of covalently bonded groups that cannot be reconfigured without undergoing a chemical reaction. Here we demonstrate that a platinum-porphyrin-based supramolecularly assembled dimer supported on a Au(111) surface can be rotated with high directionality using the tunneling current of a scanning tunneling microscope (STM). Rotational direction of this molecular motor is determined solely by the surface chirality of the dimer, and most importantly, the chirality can be inverted in situ through a process involving an intradimer rearrangement. Our result opens the way for the construction of complex molecular machines on a surface to mimic at a smaller scale versatile biological supramolecular motors.

Imaging Josephson vortices on the surface superconductor Si(111)-(√7×√3)-In using a scanning tunneling microscope.

We have studied the superconducting Si(111)-(√7×√3)-In surface using a ³He-based low-temperature scanning tunneling microscope. Zero-bias conductance images taken over a large surface area reveal that vortices are trapped at atomic steps after magnetic fields are applied. The crossover behavior from Pearl to Josephson vortices is clearly identified from their elongated shapes along the steps and significant recovery of superconductivity within the cores. Our numerical calculations combined with experiments clarify that these characteristic features are determined by the relative strength of the interterrace Josephson coupling at the atomic step.

Nanojunction between fullerene and one-dimensional conductive polymer on solid surfaces.

Bottom-up creation of huge molecular complexes by covalently interconnecting functional molecules and conductive polymers is a key technology for constructing nanoscale electronic circuits. In this study, we have created an array of molecule-polymer nanojunctions from C60 molecules and polydiacetylene (PDA) nanowires at designated positions on solid surfaces by controlling self-assemblies and intermolecular chemical reactions of molecular ingredients predeposited onto the surfaces. In the proposed method, the construction of each nanojunction spontaneously proceeds via two types of chemical reactions: a chain polymerization among self-assembled diacetylene compound molecules for creating a single PDA nanowire and a subsequent cycloaddition reaction between the propagating forefront part of the PDA backbone and a single C60 molecule adsorbed on the surface. Scanning tunneling microscopy has proved that the C60 molecule is covalently connected to each end of the π-conjugated PDA backbone. Furthermore, the decrease in the energy gap of the C60 molecule in nanojunctions is observed as compared with that of pristine C60 molecules, which is considered to be due to the covalent interaction between the PDA edge and the C60 molecule.

Double-side-coated nanomechanical membrane-type surface stress sensor (MSS) for one-chip-one-channel setup.

With their capability for real-time and label-free detection of targets ranging from gases to biological molecules, nanomechanical sensors are expected to contribute to various fields, such as medicine, security, and environmental science. For practical applications, one of the major issues of nanomechanical sensors is the difficulty of coating receptor layers on their surfaces to which target molecules adsorb or react. To have measurable deflection, a single-side coating is commonly applied to cantilever-type geometry, and it requires specific methods or protocols, such as inkjet spotting or gold-thiol chemistry. If we can apply a double-side coating to nanomechanical sensors, it allows almost any kind of coating technique including dip coating methods, making nanomechanical sensors more useful with better user experiences. Here we address the feasibility of the double-side coating on nanomechanical sensors demonstrated by a membrane-type surface stress sensor (MSS) and verify its working principle by both finite element analysis (FEA) and experiments. In addition, simple hand-operated dip coating is demonstrated as a proof of concept, achieving practical receptor layers without any complex instrumentation. Because the double-side coating is compatible with batch protocols such as dip coating, double-side-coated MSS represents a new paradigm of one-chip-one-channel (channels on a chip are all coated with the same receptor layers) shifting from the conventional one-chip-multiple-channel (channels on a chip are coated with different receptor layers) paradigm.