Carbon nanotubes (CNTs) as a buffer layer in silicon/CNTs composite electrodes for lithium secondary batteries

A core/shell type silicon/carbon nanotubes (Si/CNTs) composite is prepared and its anodic performance in lithium secondary batteries is examined. For the growth of CNTs, a Ni catalyst is loaded on a Si surface by electroless deposition. The growth is performed by chemical vapour deposition at 600 °C using C2H2/H2 but is successful only on smaller and thinner Ni deposits. This is probably due to an easier transformation to small droplets that initiate the growth reaction. The anodic performance of a Si/CNTs composite electrode is superior to that observed with bare Si and Si/CNTs mixed electrodes. This beneficial feature is ascribed to the conductive buffering role of the CNTs layer. It is likely that the void space and the flexible characteristics in the CNTs buffer layer on the Si surface allow volume expansion of the Si core without severe electrode swelling. Because of this, the electric conductive network made among Si particles, carbon network and current-collector is well maintained, which reduces the charge-transfer resistance.This work was supported by KOSEF via the Research Center for Energy Conversion and Storage, and by the Division of Advanced Batteries in NGE Program (Project no. 10016439)

PiB-PET Imaging-Based Serum Proteome Profiles Predict Mild Cognitive Impairment and Alzheimer's Disease

Development of a simple, non-invasive early diagnosis platform of Alzheimer's disease (AD) using blood is urgently required. Recently, PiB-PET imaging has been shown to be powerful to quantify amyloid-β plaque loads leading to pathophysiological alterations in AD brains. Thus, there has been a need for serum biomarkers reflecting PiB-PET imaging data as an early diagnosis platform of AD. Here, using LC-MS/MS analysis coupled with isobaric tagging, we performed comprehensive proteome profiling of serum samples from cognitively normal controls, mild cognitive impairment (MCI), and AD patients, who were selected using PiB-PET imaging. Comparative analysis of the proteomes revealed 79 and 72 differentially expressed proteins in MCI and AD, respectively, compared to controls. Integrated analysis of these proteins with genomic and proteomic data of AD brain tissues, together with network analysis, identified three biomarker candidates representing the altered proteolysis-related process in MCI or AD: proprotein convertase subtilisin/kexin type 9 (PCSK9), coagulation factor XIII, A1 polypeptide (F13A1), and dermcidin (DCD). In independent serum samples of MCI and AD, we confirmed the elevation of the candidates using western blotting and ELISA. Our results suggest that these biomarker candidates can serve as a potential non-invasive early diagnosis platform reflecting PiB-PET imaging for MCI and AD. © 2016 – IOS Press and the authors.1551sciescopu