Synthesis and Electrical Properties of Polyaniline/Polyaniline Grafted Multiwalled Carbon Nanotube Mixture via Suspension Polymerization

Interdisciplinary School of Green EnergyThe mixture of polyaniline (PANi) and PANi-grafted multiwalled carbon nanotube (PANi/PANi-g-MWNT mixture) was prepared by suspension polymerization. MWNT was first functionalizaed with 4-aminobenzoic acid via “direct” Firedel-Crafts acylation in polyphosphoric acid (PPA)/phosphorous pentoxide (P2O5) medium to afford 4-aminobenzoyl-functionalized MWNT (AF-MWNT). The resulting 4-aminobenzoyl-functionalized multiwalled carbon nanotube was then treated with aniline in the presence of ammonium persulfate/aqueous hydrochloric acid to promote a suspension polymerization. The resultant composite was characterized by elemental analysis, Fourier-transform infrared spectroscopy, wide angle x-ray diffraction, scanning electron microscopy, transmission electron microscopy, UV-vis absorption spectroscopy, florescence spectroscopy, cyclic voltammetry, and electrical conductivity measurement. The electrical conductivity of polyaniline grafted multiwalled carbon nanotube composite was improved compared to that of polyaniline control. Specifically, the electrical conductivity of polyaniline grafted multiwalled carbon nanotube was improved 1.5~3500 times depending upon the level of doping of what. The capacitance of the composite was also greatly enhanced.ope

Perceptual consequence of normalization revealed by a novel brightness induction

AbstractThe human brain is renowned for its dynamic regulation of sensory inputs, which enables our brain to operate under an enormous range of physical energy with sensory neurons whose processing range is limited. Here we present a novel and strong brightness induction that reflects neural mechanisms underlying this dynamic regulation of sensory inputs. When physically identical, stationary and moving objects are viewed simultaneously, the stationary and moving objects appear largely different. Experiments reveal that normalization at multiple stages of visual processing provides a plausible account for the large shifts in perceptual experiences, observed in both the stationary and the moving objects. This novel brightness induction suggests that brightness of an object is influenced not only by variations in surrounding light (i.e. simultaneous contrast) but also by dynamically changing neural responses associated with stimulus motion

The concept of translocational regulation

Biological processes are regulated to provide cells with exquisite adaptability to changing environmental conditions and cellular demands. The mechanisms regulating secretory and membrane protein translocation into the endoplasmic reticulum (ER) are unknown. A conceptual framework for translocational regulation is proposed based on our current mechanistic understanding of ER protein translocation and general principles of regulatory control

Lawrence Livermore National Laboratory capabilities in multiphase dynamics

The computer codes at LLNL with capabilities for numerical analysis for multiphase flow; phenomenology and constitutive theory and modeling; advanced diagnostics, advanced test beds, facilities, and data bases; and multiphase flow applications are listed, with brief descriptions

Endoplasmic Reticulum Stress in the β-Cell Pathogenesis of Type 2 Diabetes

Type 2 diabetes is a complex metabolic disorder characterized by high blood glucose in the context of insulin resistance and relative insulin deficiency by β-cell failure. Even if the mechanisms underlying the pathogenesis of β-cell failure are still under investigation, recent increasing genetic, experimental, and clinical evidence indicate that hyperactivation of the unfolded protein response (UPR) to counteract metabolic stresses is closely related to β-cell dysfunction and apoptosis. Signaling pathways of the UPR are “a double-edged sword” that can promote adaptation or apoptosis depending on the nature of the ER stress condition. In this paper, we summarized our current understanding of the mechanisms and components related to ER stress in the β-cell pathogenesis of type 2 diabetes

Trustworthiness-Driven Graph Convolutional Networks for Signed Network Embedding

The problem of representing nodes in a signed network as low-dimensional vectors, known as signed network embedding (SNE), has garnered considerable attention in recent years. While several SNE methods based on graph convolutional networks (GCN) have been proposed for this problem, we point out that they significantly rely on the assumption that the decades-old balance theory always holds in the real-world. To address this limitation, we propose a novel GCN-based SNE approach, named as TrustSGCN, which corrects for incorrect embedding propagation in GCN by utilizing the trustworthiness on edge signs for high-order relationships inferred by the balance theory. The proposed approach consists of three modules: (M1) generation of each node's extended ego-network; (M2) measurement of trustworthiness on edge signs; and (M3) trustworthiness-aware propagation of embeddings. Furthermore, TrustSGCN learns the node embeddings by leveraging two well-known societal theories, i.e., balance and status. The experiments on four real-world signed network datasets demonstrate that TrustSGCN consistently outperforms five state-of-the-art GCN-based SNE methods. The code is available at https://github.com/kmj0792/TrustSGCN.Comment: 12 pages, 8 figures, 9 table

CHEMICAL-LOOPING STEAM METHANE REFORMING FOR HYDROGEN PRODUCTION IN A CIRCULATING FLUIDIZED BED REACTOR

Two-step steam methane reforming for hydrogen production using a chemical looping system is proposed to improve the conventional processes. The reaction characteristics with iron oxides as an oxygen carrier was determined in a circulating fluidized bed reactor. From this system, high concentrated hydrogen can be continuously produced without any post treatment