Yuki Maekawa

Wafer-scale fabrication and growth dynamics of suspended graphene nanoribbon arrays

Adding a mechanical degree of freedom to the electrical and optical properties of atomically thin materials can provide an excellent platform to investigate various optoelectrical physics and devices with mechanical motion interaction. The large scale fabrication of such atomically thin materials with suspended structures remains a challenge. Here we demonstrate the wafer-scale bottom–up synthesis of suspended graphene nanoribbon arrays (over 1,000,000 graphene nanoribbons in 2 × 2 cm2 substrate) with a very high yield (over 98%). Polarized Raman measurements reveal graphene nanoribbons in the array can have relatively uniform-edge structures with near zigzag orientation dominant. A promising growth model of suspended graphene nanoribbons is also established through a comprehensive study that combined experiments, molecular dynamics simulations and theoretical calculations with a phase-diagram analysis. We believe that our results can contribute to pushing the study of graphene nanoribbons into a new stage related to the optoelectrical physics and industrial applications.

Charge Behaviors around Oxide Device/Pseudo-Physiological Solution Interface with Molecular Dynamic Simulations

In this study, we investigated the charge behaviors of ions and water molecules at the oxide device/pseudo-physiological solution interface by use of molecular dynamics (MD) simulations because the detection principle of semiconductor-based biosensors is based on the detection of charge density changes at the oxide sensing surface in physiological environments. In particular, we designed an alpha-quartz (100) surface with some charges corresponding to pH=5.5 so that the ionic behaviors for 500 mM each of Na+ and Cl- around the interface were calculated under the surface condition with charges, considering a real system. As a result of the simulation, we defined the region of Debye length from the calculated potential distribution, in which some parameters such as diffusion coefficient and the vibration of water molecules around the interface differed from those of the bulk solution. The elucidation of the solid/liquid interfacial behaviors by the simulation technique should deepen our understanding of the detection principle of semiconductor-based biosensors and will give guidelines for the design of a bio-interface in the field of biosensing technology, because they cannot be demonstrated experimentally.

Understanding the Molecular Structure of the Sialic Acid-Phenylboronic Acid Complex by using a Combined NMR Spectroscopy and DFT Study: Toward Sialic Acid Detection at Cell Membranes

Abstract The origin of the unusually high stability of the sialic acid (SA) and phenylboronic acid (PBA) complex was investigated by a combined nuclear magnetic resonance (NMR) spectroscopy and density functional theory (DFT) study. SA is a glycan‐terminating monosaccharide, and its importance as a clinical target has long been recognized. Inspired by the fact that the binding properties of SA–PBA complexation are anomalously high relative to those of typical monosaccharides, great effort has been made to build a clinical platform with the use of PBA as a SA‐selective receptor. Although a number of applications have been reported in recent years, the ability of PBA to recognize SA‐terminating surface glycans selectively is still unclear, because high‐affinity SA–PBA complexation might not occur in a physiological environment. In particular, different forms of SA (α‐ and β‐pyranose) were not considered in detail. To answer this question, the combined NMR spectroscopy/DFT study revealed that the advantageous binding properties of the SA–PBA complex arise from ester bonding involving the α‐carboxylate moieties (C1 and C2) of β‐SA but not α‐SA. Moreover, the facts that the C2 atom is blocked by a glycoside bond in a physiological environment and that α‐SA basically exists on membrane‐bound glycans in a physiological environment lead to the conclusion that PBA cannot selectively recognize the SA unit to discriminate specific types of cells. Our results have a significant impact on the field of SA‐based cell recognition.