Atomic-Scale Homogeneous RuCu Alloy Nanoparticles for Highly Efficient Electrocatalytic Nitrogen Reduction.

Ruthenium (Ru) is the most widely used metal as an electrocatalyst for nitrogen (N2 ) reduction reaction (NRR) because of the relatively high N2 adsorption strength for successive reaction. Recently, it has been well reported that the homogeneous Ru-based metal alloys such as RuRh, RuPt, and RuCo significantly enhance the selectivity and formation rate of ammonia (NH3 ). However, the metal combinations for NRR have been limited to several miscible combinations of metals with Ru, although various immiscible combinations have immense potential to show high NRR performance. In this study, an immiscible combination of Ru and copper (Cu) is first utilized, and homogeneous alloy nanoparticles (RuCu NPs) are fabricated by the carbothermal shock method. The RuCu homogeneous NP alloys on cellulose/carbon nanotube sponge exhibit the highest selectivity and NH3 formation rate of ≈31% and -73 µmol h-1 cm-2 , respectively. These are the highest values of the selectivity and NH3 formation rates among existing Ru-based alloy metal combinations.

Analysis of Dispersion of Carbon Nanotubes in m-Cresol.

We analyzed the dispersion state of carbon nanotubes (CNTs) in m-cresol using dispersion stability analysis, optical microscopy, and UV-vis spectroscopy. The high dispersion stability of CNT/m-cresol dispersion was observed when it was sufficiently treated with ultrasonication. Despite the high dispersion stability, optical microscopy and UV-vis spectroscopy analysis of various CNT/m-cresol dispersions revealed that CNT bundles in m-cresol were not dispersed into individual CNTs. We also propose that the blue-shift of the G peak of CNTs in m-cresol in the Raman spectrum, which had been reported as evidence of the formation of the charge-transfer complex between m-cresol and CNTs, is rather attributed to the interference of m-cresol's inherent peak at around 1600 cm-1.

A computational framework for optimal control of a self-adjustive neural system with activity-dependent and homeostatic plasticity.

The control of the brain system has received increasing attention in the domain of brain science. Most brain control studies have been conducted to explore the brain network's graph-theoretic properties or to produce the desired state based on neural state dynamics, regarding the brain as a passively responding system. However, the self-adjusting nature of neural system after treatment has not been fully considered in the brain control. In the present study, we propose a computational framework for optimal control of the brain with a self-adjustment process in the effective connectivity after treatment. The neural system is modeled to adjust its outgoing effective connectivity as activity-dependent plasticity after treatment, followed by synaptic rescaling of incoming effective connectivity. To control this neural system to induce the desired function, the system's self-adjustment parameter is first estimated, based on which the treatment is optimized. Utilizing this framework, we conducted simulations of optimal control over a functional hippocampal circuitry, estimated using dynamic causal modeling of voltage-sensitive dye imaging from the wild type and mutant mice, responding to consecutive electrical stimuli. Simulation results for optimal control of the abnormal circuit toward a healthy circuit using a single node treatment, neural-type specific treatment as an analogy of medication, and combined treatments of medication and nodal treatment suggest the plausibility of the current framework in controlling the self-adjusting neural system within a restricted treatment setting. We believe the proposed computational framework of the self-adjustment system would help optimal control of the dynamic brain after treatment.

Composite Microgels Created by Complexation between Polyvinyl Alcohol and Graphene Oxide in Compressed Double-Emulsion Drops.

Microgels, microparticles made of hydrogels, show fast diffusion kinetics and high reconfigurability while maintaining the advantages of hydrogels, being useful for various applications. Here, presented is a new microfluidic strategy for producing polymer-graphene oxide (GO) composite microgels without chemical cues or a temperature swing for gelation. As a main component of microgels, polymers that are able to form hydrogen bonds, such as polyvinyl alcohol (PVA), are used. In the mixture of PVA and GO, GO is tethered by PVA through hydrogen bonding. When the mixture is rapidly concentrated in the core of double-emulsion drops by osmotic-pressure-driven water pumping, PVA-tethered GO sheets form a nematic phase with a planar alignment. In addition, the GO sheets are linked by additional hydrogen bonds, leading to a sol-gel transition. Therefore, the PVA-GO composite remains undissolved when it is directly exposed to water by oil-shell rupture. These composite microgels can be also produced using poly(ethylene oxide) or poly(acrylic acid), instead of PVA. In addition, the microgels can be functionalized by incorporating other polymers in the presence of the hydrogel-forming polymers. It is shown that the multicomponent microgels made from a mixture of polyacrylamide, PVA, and GO show an excellent adsorption capacity for impurities.

Direct spinning and densification method for high-performance carbon nanotube fibers.

Developing methods to assemble nanomaterials into macroscopic scaffolds is of critical significance at the current stage of nanotechnology. However, the complications of the fabrication methods impede the widespread usages of newly developed materials even with the superior properties in many cases. Here, we demonstrate the feasibility of a highly-efficient and potentially-continuous fiber-spinning method to produce high-performance carbon nanotube (CNT) fiber (CNTF). The processing time is <1 min from synthesis of CNTs to fabrication of highly densified and aligned CNTFs. CNTFs that are fabricated by the developed spinning method are ultra-lightweight, strong (specific tensile strength = 4.08 ± 0.25 Ntex-1), stiff (specific tensile modulus = 187.5 ± 7.4 Ntex-1), electrically conductive (2,270 S m2kg-1), and highly flexible (knot efficiency = 48 ± 15%), so they are suitable for various high-value fabric-based applications.

Significantly Increased Solubility of Carbon Nanotubes in Superacid by Oxidation and Their Assembly into High-Performance Fibers.

This study demonstrates that small amount of oxygen incorporated into carbon nanotubes (CNTs) during the purification process greatly increases their solubility in chlorosulfonic acid (CSA). Using as-purchased and unpurified CNT powders, the optimal purification process is established to significantly increase the solubility of CNTs in CSA, and spin CNT fibers with high mechanical strength (0.84 N tex-1 ) and electrical conductivity (1.4 MS m-1 ) from the CNT liquid crystal dope with high concentration of CNTs in CSA. The knowledge obtained here may guide development of a way to dissolve extremely long CNTs at high concentration and thereby to enable production of CNT fibers with ultimate properties.

High-strength carbon nanotube/carbon composite fibers via chemical vapor infiltration.

In this study, we have developed an efficient and scalable method for improving the mechanical properties of carbon nanotube (CNT) fibers. The mechanical properties of as-synthesized CNT fibers are primarily limited by their porous structures and the weak bonding between adjacent CNTs. These result in inefficient load transfer, leading to low tensile strength and modulus. In order to overcome these limitations, we have adopted chemical vapor infiltration (CVI) to efficiently fill the internal voids of the CNT fibers with carbon species which are thermally decomposed from gas phase hydrocarbon. Through the optimization of the processing time, temperature, and gas flow velocity, we have confirmed that carbon species formed by the thermal decomposition of acetylene (C2H2) gas successfully infiltrated into porous CNT fibers and densified them at relatively low temperatures (650-750 °C). As a result, after CVI processing of the as-synthesized CNT fibers under optimum conditions, the tensile strength and modulus increased from 0.6 GPa to 1.7 GPa and from 25 GPa to 127 GPa, respectively. The CVI technique, combined with the direct spinning of CNT fibers, can open up a route to the fast and scalable fabrication of high performance CNT/C composite fibers. In addition, the CVI technique is a platform technology that can be easily adapted into other nano-carbon based yarn-like fibers such as graphene fibers.