Carbon Nanotubes/Heteroatom‐Doped Carbon Core–Sheath Nanostructures as Highly Active,Metal‐Free Oxygen Reduction Electrocatalysts for Alkaline Fuel Cells

A facile, scalable route to new nanocomposites that are based on carbon nanotubes/heteroatom‐doped carbon (CNT/HDC) core–sheath nanostructures is reported. These nanostructures were prepared by the adsorption of heteroatom‐containing ionic liquids on the walls of CNTs, followed by carbonization. The design of the CNT/HDC composite allows for combining the electrical conductivity of the CNTs with the catalytic activity of the heteroatom‐containing HDC sheath layers. The CNT/HDC nanostructures are highly active electrocatalysts for the oxygen reduction reaction and displayed one of the best performances among heteroatom‐doped nanocarbon catalysts in terms of half‐wave potential and kinetic current density. The four‐electron selectivity and the exchange current density of the CNT/HDC nanostructures are comparable with those of a Pt/C catalyst, and the CNT/HDC composites were superior to Pt/C in terms of long‐term durability and poison tolerance. Furthermore, an alkaline fuel cell that employs a CNT/HDC nanostructure as the cathode catalyst shows very high current and power densities, which sheds light on the practical applicability of these new nanocomposites.     

Mechanical and electrical response variation of the polyurethane–tin oxide–carbon nanotube composite microfiber depending on the chemical solution

Toward the goal of smart sensor systems for wearable electronics, polymer microfiber‐based free‐standing sensors benefit from excellent flexibility, decent ductility, and easy wearability in comparison with thin‐film‐based sensing devices. Herein, we report a hydrophobic and conducting single‐strand microfiber‐based liquid‐phase chemical sensor consisting of polyurethane (PU), tin oxide (SnO₂), and carbon nanotube (CNT) composites with applying a (1H,1H,2H,2H‐heptadecafluorodec‐1‐yl) phosphonic acid (HDF‐PA)‐based self‐assembled monolayer. The free‐standing HDF‐PA‐treated PU–SnO₂–CNT composite microfiber showing selective filtering properties with the repellency of water and the penetration of an organic solvent is electrically and mechanically characterized. Finally, the single‐strand HDF‐PA‐treated PU–SnO₂–CNT composite microfiber‐based chemical sensor, which shows excellent mechanical properties and aqueous stability, is demonstrated to detect the presence of a chemical in pure water or counterfeit gasoline in pure gasoline by observing mechanical changes, especially variations in the length and diameter of the fiber, and monitoring the electrical resistance change. © 2018 Wiley Periodicals, Inc. J. Polym. Sci., Part A: Polym. Chem. 2019 , 57, 495–502     

Development of simultaneous analysis of tryptophan metabolites in serum and gastric juice – an investigation towards establishing a biomarker test for gastric cancer diagnosis

To evaluate changes in tryptophan metabolism and discover diagnostic biomarkers for gastric cancer, a quantitative method was developed for tryptophan and its seven metabolites (indole‐3‐lactic acid, anthranilic acid, serotonin, nicotinic acid, kynurenic acid, kynurenine and 3‐indoxyl sulfate) in both human serum and gastric juice using liquid chromatography–tandem mass spectrometry (LC–MS/MS). Serum and gastric juice were prepared with a simple protein precipitation using aqueous 0.1% formic acid and acetonitrile. As a result, it was found that the kynurenine pathway of tryptophan metabolism was activated in gastric cancer and that the metabolic ratio of kynurenine/tryptophan, which reflects the enzyme activity of indoleamine‐2,3‐dioxygenase, was associated with the observed metabolic changes. Finally, the investigation of tryptophan metabolites, especially kynurenic acid, in serum and gastric juice might serve as biomarkers for gastric cancer. The findings in this study provide critical information of tryptophan metabolism which can be applied to a serum‐based diagnostic test for gastric cancer.     

Efficient and accurate procedure for selecting ground motions matching target response spectrum

Linear and nonlinear response history analyses have become popular in seismic design and seismic performance evaluation procedures. The accuracy of analysis results depends not only on the accurate analytic models for structures but also on the proper selection of input ground motions. The purpose of this study is to develop a computationally efficient and accurate procedure for selecting ground motions considering the target response spectrum mean and variance, and the correlations between response spectra of different periods. In this procedure, a number of response spectra are simulated equal to the number of ground motions to be selected, using a Monte Carlo simulation. Subsequently, ground motions are selected from a ground motion library to individually match the simulated response spectra, using the proposed selection procedure. This procedure is computationally efficient and accurate in selecting a ground motion that best matches a simulated response spectrum and in determining a scaling factor for the selected ground motion. In order to further improve the selection result, multiple sets of simulated response spectra are considered. The accuracy and efficiency of the proposed procedure are verified with numerical examples.     

An answer to a question of A. Lubin: The lifting problem for commuting subnormals

In this paper, we give an answer to a long-standing open question on the lifting problem for commuting subnormals (due to A. Lubin): The subnormality for the sum of commuting subnormal operators does not guarantee the existence of commuting normal extensions.