Control and Characterization of Individual Grains and Grain Boundaries in Graphene Grown by Chemical Vapor Deposition

The strong interest in graphene has motivated the scalable production of high quality graphene and graphene devices. Since large-scale graphene films synthesized to date are typically polycrystalline, it is important to characterize and control grain boundaries, generally believed to degrade graphene quality. Here we study single-crystal graphene grains synthesized by ambient CVD on polycrystalline Cu, and show how individual boundaries between coalescing grains affect graphene's electronic properties. The graphene grains show no definite epitaxial relationship with the Cu substrate, and can cross Cu grain boundaries. The edges of these grains are found to be predominantly parallel to zigzag directions. We show that grain boundaries give a significant Raman "D" peak, impede electrical transport, and induce prominent weak localization indicative of intervalley scattering in graphene. Finally, we demonstrate an approach using pre-patterned growth seeds to control graphene nucleation, opening a route towards scalable fabrication of single-crystal graphene devices without grain boundaries.Comment: New version with additional data. Accepted by Nature Material

Direct Imaging of Graphene Edges: Atomic Structure and Electronic Scattering

We report an atomically-resolved scanning tunneling microscopy (STM) investigation of the edges of graphene grains synthesized on Cu foils by chemical vapor deposition (CVD). Most of the edges are macroscopically parallel to the zigzag directions of graphene lattice. These edges have microscopic roughness that is found to also follow zigzag directions at atomic scale, displaying many ~120 degree turns. A prominent standing wave pattern with periodicity ~3a/4 (a being the graphene lattice constant) is observed near a rare-occurring armchair-oriented edge. Observed features of this wave pattern are consistent with the electronic intervalley backscattering predicted to occur at armchair edges but not at zigzag edges

Thermal Properties of Graphene, Carbon Nanotubes and Nanostructured Carbon Materials

Recent years witnessed a rapid growth of interest of scientific and engineering communities to thermal properties of materials. Carbon allotropes and derivatives occupy a unique place in terms of their ability to conduct heat. The room-temperature thermal conductivity of carbon materials span an extraordinary large range - of over five orders of magnitude - from the lowest in amorphous carbons to the highest in graphene and carbon nanotubes. I review thermal and thermoelectric properties of carbon materials focusing on recent results for graphene, carbon nanotubes and nanostructured carbon materials with different degrees of disorder. A special attention is given to the unusual size dependence of heat conduction in two-dimensional crystals and, specifically, in graphene. I also describe prospects of applications of graphene and carbon materials for thermal management of electronics.Comment: Review Paper; 37 manuscript pages; 4 figures and 2 boxe

Exceptional electronic transport and quantum oscillations in thin bismuth crystals grown inside van der Waals materials

Confining materials to two-dimensional forms changes the behavior of electrons and enables new devices. However, most materials are challenging to produce as uniform thin crystals. Here, we present a new synthesis approach where crystals are grown in a nanoscale mold defined by atomically-flat van der Waals (vdW) materials. By heating and compressing bismuth in a vdW mold made of hexagonal boron nitride (hBN), we grow ultraflat bismuth crystals less than 10 nanometers thick. Due to quantum confinement, the bismuth bulk states are gapped, isolating intrinsic Rashba surface states for transport studies. The vdW-molded bismuth shows exceptional electronic transport, enabling the observation of Shubnikov-de Haas quantum oscillations originating from the (111) surface state Landau levels, which have eluded previous studies. By measuring the gate-dependent magnetoresistance, we observe multi-carrier quantum oscillations and Landau level splitting, with features originating from both the top and bottom surfaces. Our vdW-mold growth technique establishes a platform for electronic studies and control of bismuth's Rashba surface states and topological boundary modes. Beyond bismuth, the vdW-molding approach provides a low-cost way to synthesize ultrathin crystals and directly integrate them into a vdW heterostructure

Beyond microarrays: Finding key transcription factors controlling signal transduction pathways

BACKGROUND: Massive gene expression changes in different cellular states measured by microarrays, in fact, reflect just an "echo" of real molecular processes in the cells. Transcription factors constitute a class of the regulatory molecules that typically require posttranscriptional modifications or ligand binding in order to exert their function. Therefore, such important functional changes of transcription factors are not directly visible in the microarray experiments. RESULTS: We developed a novel approach to find key transcription factors that may explain concerted expression changes of specific components of the signal transduction network. The approach aims at revealing evidence of positive feedback loops in the signal transduction circuits through activation of pathway-specific transcription factors. We demonstrate that promoters of genes encoding components of many known signal transduction pathways are enriched by binding sites of those transcription factors that are endpoints of the considered pathways. Application of the approach to the microarray gene expression data on TNF-alpha stimulated primary human endothelial cells helped to reveal novel key transcription factors potentially involved in the regulation of the signal transduction pathways of the cells. CONCLUSION: We developed a novel computational approach for revealing key transcription factors by knowledge-based analysis of gene expression data with the help of databases on gene regulatory networks (TRANSFAC(® )and TRANSPATH(®)). The corresponding software and databases are available at

Top-oil temperature modelling by calibrating oil time constant for an oil natural air natural distribution transformer

© The Institution of Engineering and Technology 2020. Integration of low carbon technologies poses a technical challenge on distribution transformers due to the dynamic loading and potentially frequent overloading scenarios. Transformer dynamic thermal rating is hence required, which is the most economical approach to tackle this challenge and ensure a safe operation. To reach the aim, it is important to enhance the accuracy of the dynamic thermal model, where the top-oil temperature is a key thermal parameter. In this study, a wide range of constant load temperature-rise tests were carried out on an 11/0.433 kV distribution transformer to study the dynamic thermal behaviour of the top-oil temperature. A model based on the IEC 60076-7 thermal model but with an improved oil time constant calibration was deduced for top-oil temperature modelling. The oil time constant calibration was inspired by IEEE C57.91 and verified by eight temperature-rise tests with load factors ranging from 0.7 to 1.4 pu. In addition, the improved top-oil temperature modelling was further verified in experiments under multiple load profiles

Evolution after Anti-TNF Discontinuation in Patients with Inflammatory Bowel Disease: A Multicenter Long-Term Follow-Up Study

OBJECTIVES:The aims of this study were to assess the risk of relapse after discontinuation of anti-tumor necrosis factor (anti-TNF) drugs in patients with inflammatory bowel disease (IBD), to identify the factors associated with relapse, and to evaluate the overcome after retreatment with the same anti-TNF in those who relapsed.METHODS:This was a retrospective, observational, multicenter study. IBD patients who had been treated with anti-TNFs and in whom these drugs were discontinued after clinical remission was achieved were included.RESULTS:A total of 1, 055 patients were included. The incidence rate of relapse was 19% and 17% per patient-year in Crohn''s disease and ulcerative colitis patients, respectively. In both Crohn''s disease and ulcerative colitis patients in deep remission, the incidence rate of relapse was 19% per patient-year. The treatment with adalimumab vs. infliximab (hazard ratio (HR)=1.29; 95% confidence interval (CI)=1.01-1.66), elective discontinuation of anti-TNFs (HR=1.90; 95% CI=1.07-3.37) or discontinuation because of adverse events (HR=2.33; 95% CI=1.27-2.02) vs. a top-down strategy, colonic localization (HR=1.51; 95% CI=1.13-2.02) vs. ileal, and stricturing behavior (HR=1.5; 95% CI=1.09-2.05) vs. inflammatory were associated with a higher risk of relapse in Crohn''s disease patients, whereas treatment with immunomodulators after discontinuation (HR=0.67; 95% CI=0.51-0.87) and age (HR=0.98; 95% CI=0.97-0.99) were protective factors. None of the factors were predictive in ulcerative colitis patients. Retreatment of relapse with the same anti-TNF was effective (80% responded) and safe.CONCLUSIONS:The incidence rate of inflammatory bowel disease relapse after anti-TNF discontinuation is relevant. Some predictive factors of relapse after anti-TNF withdrawal have been identified. Retreatment with the same anti-TNF drug was effective and safe

A reexamination of information theory-based methods for DNA-binding site identification

<p>Abstract</p> <p>Background</p> <p>Searching for transcription factor binding sites in genome sequences is still an open problem in bioinformatics. Despite substantial progress, search methods based on information theory remain a standard in the field, even though the full validity of their underlying assumptions has only been tested in artificial settings. Here we use newly available data on transcription factors from different bacterial genomes to make a more thorough assessment of information theory-based search methods.</p> <p>Results</p> <p>Our results reveal that conventional benchmarking against artificial sequence data leads frequently to overestimation of search efficiency. In addition, we find that sequence information by itself is often inadequate and therefore must be complemented by other cues, such as curvature, in real genomes. Furthermore, results on skewed genomes show that methods integrating skew information, such as <it>Relative Entropy</it>, are not effective because their assumptions may not hold in real genomes. The evidence suggests that binding sites tend to evolve towards genomic skew, rather than against it, and to maintain their information content through increased conservation. Based on these results, we identify several misconceptions on information theory as applied to binding sites, such as negative entropy, and we propose a revised paradigm to explain the observed results.</p> <p>Conclusion</p> <p>We conclude that, among information theory-based methods, the most unassuming search methods perform, on average, better than any other alternatives, since heuristic corrections to these methods are prone to fail when working on real data. A reexamination of information content in binding sites reveals that information content is a compound measure of search and binding affinity requirements, a fact that has important repercussions for our understanding of binding site evolution.</p