Antimony-doped graphene nanoplatelets

Heteroatom doping into the graphitic frameworks have been intensively studied for the development of metal-free electrocatalysts. However, the choice of heteroatoms is limited to non-metallic elements and heteroatom-doped graphitic materials do not satisfy commercial demands in terms of cost and stability. Here we realize doping semimetal antimony (Sb) at the edges of graphene nanoplatelets (GnPs) via a simple mechanochemical reaction between pristine graphite and solid Sb. The covalent bonding of the metalloid Sb with the graphitic carbon is visualized using atomic-resolution transmission electron microscopy. The Sb-doped GnPs display zero loss of electrocatalytic activity for oxygen reduction reaction even after 100,000 cycles. Density functional theory calculations indicate that the multiple oxidation states (Sb3+ and Sb5+) of Sb are responsible for the unusual electrochemical stability. Sb-doped GnPs may provide new insights and practical methods for designing stable carbon-based electrocatalystsclose0

In Situ Synthesis of Reduced Graphene Oxide and Gold Nanocomposites for Nanoelectronics and Biosensing

In this study, an in situ chemical synthesis approach has been developed to prepare graphene–Au nanocomposites from chemically reduced graphene oxide (rGO) in aqueous media. UV–Vis absorption, atomic force microscopy, scanning electron microscopy, transmission electron microscopy, and Raman spectroscopy were used to demonstrate the successful attachment of Au nanoparticles to graphene sheets. Configured as field-effect transistors (FETs), the as-synthesized single-layered rGO-Au nanocomposites exhibit higher hole mobility and conductance when compared to the rGO sheets, promising its applications in nanoelectronics. Furthermore, we demonstrate that the rGO-Au FETs are able to label-freely detect DNA hybridization with high sensitivity, indicating its potentials in nanoelectronic biosensing

Dynamics of mechanical waves in periodic grapheme nanoribbon assemblies

We simulate the natural frequencies and the acoustic wave propagation characteristics of graphene nanoribbons (GNRs) of the type (8,0) and (0,8) using an equivalent atomistic-continuum FE model previously developed by some of the authors, where the C-C bonds thickness and average equilibrium lengths during the dynamic loading are identified through the minimisation of the system Hamiltonian. A molecular mechanics model based on the UFF potential is used to benchmark the hybrid FE models developed. The acoustic wave dispersion characteristics of the GNRs are simulated using a Floquet-based wave technique used to predict the pass-stop bands of periodic mechanical structures. We show that the thickness and equilibrium lengths do depend on the specific vibration and dispersion mode considered, and that they are in general different from the classical constant values used in open literature (0.34 nm for thickness and 0.142 nm for equilibrium length). We also show the dependence of the wave dispersion characteristics versus the aspect ratio and edge configurations of the nanoribbons, with widening band-gaps that depend on the chirality of the configurations. The thickness, average equilibrium length and edge type have to be taken into account when nanoribbons are used to design nano-oscillators and novel types of mass sensors based on periodic arrangements of nanostructures

Robust probabilistic superposition and comparison of protein structures

<p>Abstract</p> <p>Background</p> <p>Protein structure comparison is a central issue in structural bioinformatics. The standard dissimilarity measure for protein structures is the root mean square deviation (RMSD) of representative atom positions such as α-carbons. To evaluate the RMSD the structures under comparison must be superimposed optimally so as to minimize the RMSD. How to evaluate optimal fits becomes a matter of debate, if the structures contain regions which differ largely - a situation encountered in NMR ensembles and proteins undergoing large-scale conformational transitions.</p> <p>Results</p> <p>We present a probabilistic method for robust superposition and comparison of protein structures. Our method aims to identify the largest structurally invariant core. To do so, we model non-rigid displacements in protein structures with outlier-tolerant probability distributions. These distributions exhibit heavier tails than the Gaussian distribution underlying standard RMSD minimization and thus accommodate highly divergent structural regions. The drawback is that under a heavy-tailed model analytical expressions for the optimal superposition no longer exist. To circumvent this problem we work with a scale mixture representation, which implies a weighted RMSD. We develop two iterative procedures, an Expectation Maximization algorithm and a Gibbs sampler, to estimate the local weights, the optimal superposition, and the parameters of the heavy-tailed distribution. Applications demonstrate that heavy-tailed models capture differences between structures undergoing substantial conformational changes and can be used to assess the precision of NMR structures. By comparing Bayes factors we can automatically choose the most adequate model. Therefore our method is parameter-free.</p> <p>Conclusions</p> <p>Heavy-tailed distributions are well-suited to describe large-scale conformational differences in protein structures. A scale mixture representation facilitates the fitting of these distributions and enables outlier-tolerant superposition.</p

Chemical Modification of Graphene Oxide by Nitrogenation: An X-ray Absorption and EmissionSpectroscopy Study

Nitrogen-doped graphene oxides (GO:Nx) were synthesized by a partial reduction of graphene oxide (GO) using urea [CO(NH2)2]. Their electronic/bonding structures were investigated using X-ray absorption near-edge structure (XANES), valence-band photoemission spectroscopy (VB-PES), X-ray emission spectroscopy (XES) and resonant inelastic X-ray scattering (RIXS). During GO:Nx synthesis, different nitrogen-bonding species, such as pyrrolic/graphitic-nitrogen, were formed by replacing of oxygen-containing functional groups. At lower N-content (2.7 at%), pyrrolic-N, owing to surface and subsurface diffusion of C, N and NH is deduced from various X-ray spectroscopies. In contrast, at higher N-content (5.0 at%) graphitic nitrogen was formed in which each N-atom trigonally bonds to three distinct sp2-hybridized carbons with substitution of the N-atoms for C atoms in the graphite layer. Upon nitrogen substitution, the total density of state close to Fermi level is increased to raise the valence-band maximum, as revealed by VB-PES spectra, indicating an electron donation from nitrogen, molecular bonding C/N/O coordination or/and lattice structure reorganization in GO:Nx. The well-ordered chemical environments induced by nitrogen dopant are revealed by XANES and RIXS measurements

Effective mechanical properties of multilayer nano-heterostructures

Two-dimensional and quasi-two-dimensional materials are important nanostructures because of their exciting electronic, optical, thermal, chemical and mechanical properties. However, a single-layer nanomaterial may not possess a particular property adequately, or multiple desired properties simultaneously. Recently a new trend has emerged to develop nano-heterostructures by assembling multiple monolayers of different nanostructures to achieve various tunable desired properties simultaneously. For example, transition metal dichalcogenides such as MoS2 show promising electronic and piezoelectric properties, but their low mechanical strength is a constraint for practical applications. This barrier can be mitigated by considering graphene-MoS2 heterostructure, as graphene possesses strong mechanical properties. We have developed efficient closed-form expressions for the equivalent elastic properties of such multi-layer hexagonal nano-hetrostructures. Based on these physics-based analytical formulae, mechanical properties are investigated for different heterostructures such as graphene-MoS2, graphene-hBN, graphene-stanene and stanene-MoS2. The proposed formulae will enable efficient characterization of mechanical properties in developing a wide range of application-specific nano-heterostructures

Parkinson Phenotype in Aged PINK1-Deficient Mice Is Accompanied by Progressive Mitochondrial Dysfunction in Absence of Neurodegeneration

Background Parkinson's disease (PD) is an adult-onset movement disorder of largely unknown etiology. We have previously shown that loss-of-function mutations of the mitochondrial protein kinase PINK1 (PTEN induced putative kinase 1) cause the recessive PARK6 variant of PD. Methodology/Principal Findings Now we generated a PINK1 deficient mouse and observed several novel phenotypes: A progressive reduction of weight and of locomotor activity selectively for spontaneous movements occurred at old age. As in PD, abnormal dopamine levels in the aged nigrostriatal projection accompanied the reduced movements. Possibly in line with the PARK6 syndrome but in contrast to sporadic PD, a reduced lifespan, dysfunction of brainstem and sympathetic nerves, visible aggregates of alpha-synuclein within Lewy bodies or nigrostriatal neurodegeneration were not present in aged PINK1-deficient mice. However, we demonstrate PINK1 mutant mice to exhibit a progressive reduction in mitochondrial preprotein import correlating with defects of core mitochondrial functions like ATP-generation and respiration. In contrast to the strong effect of PINK1 on mitochondrial dynamics in Drosophila melanogaster and in spite of reduced expression of fission factor Mtp18, we show reduced fission and increased aggregation of mitochondria only under stress in PINK1-deficient mouse neurons. Conclusion Thus, aging Pink1 -/- mice show increasing mitochondrial dysfunction resulting in impaired neural activity similar to PD, in absence of overt neuronal death