Adsorption on Edge-Functionalized Bilayer Graphene Nanoribbons: Assessing the Role of Functional Groups in Methane Uptake

A combination of ab initio and classical Monte Carlo simulations is used to investigate the effects of functional groups on methane binding. Using Moller-Plesset (MP2) calculations, we obtain the binding energies for benzene functionalized with NH2, OH, CH3, COOH, and H2PO3 and identify the methane binding sites. In all cases, the preferred binding sites are located above the benzene plane in the vicinity of the benzene carbon atom attached to the functional group. Functional groups enhance methane binding relative to benzene (-6.39 kJ/mol), with the largest enhancement observed for H2PO3 (-8.37 kJ/mol) followed by COOH and CH3 (-7.77 kJ/mol). Adsorption isotherms are obtained for edge-functionalized bilayer graphene nanoribbons using grand canonical Monte Carlo simulations with a five-site methane model. Adsorbed excess and heats of adsorption for pressures up to 40 bar and 298 K are obtained with functional group concentrations ranging from 3.125 to 6.25 mol 96 for graphene edges functionalized with OH, NH2, and COOH. The functional groups are found to act as preferred adsorption sites, and in the case of COOH the local methane density in the vicinity of the functional group is found to exceed that of bare graphene. The largest enhancement of 44.5% in the methane excess adsorbed is observed for COOH-functionalized nanoribbons when compared to H terminated ribbons. The corresponding enhancements for OH- and NH2-functionalized ribbons are 10.5% and 3.7%, respectively. The excess adsorption across functional groups reflects the trends observed in the binding energies from MP2 calculations. Our study reveals that specific site functionalization can have a significant effect on the local adsorption characteristics and can be used as a design strategy to tailor materials with enhanced methane storage capacity.

Functional maps within a single neuron

Narayanan R, Johnston D. Functional maps within a single neuron. J Neurophysiol 108: 2343-2351, 2012. First published August 29, 2012; doi:10.1152/jn.00530.2012.-The presence and plasticity of dendritic ion channels are well established. However, the literature is divided on what specific roles these dendritic ion channels play in neuronal information processing, and there is no consensus on why neuronal dendrites should express diverse ion channels with different expression profiles. In this review, we present a case for viewing dendritic information processing through the lens of the sensory map literature, where functional gradients within neurons are considered as maps on the neuronal topograph. Under such a framework, drawing analogies from the sensory map literature, we postulate that the formation of intraneuronal functional maps is driven by the twin objectives of efficiently encoding inputs that impinge along different dendritic locations and of retaining homeostasis in the face of changes that are required in the coding process. In arriving at this postulate, we relate intraneuronal map physiology to the vast literature on sensory maps and argue that such a metaphorical association provides a fresh conceptual framework for analyzing and understanding single-neuron information encoding. We also describe instances where the metaphor presents specific directions for research on intraneuronal maps, derived from analogous pursuits in the sensory map literature. We suggest that this perspective offers a thesis for why neurons should express and alter ion channels in their dendrites and provides a framework under which active dendrites could be related to neural coding, learning theory, and homeostasis.

Design and Synthesis of a Functional Derivative of the Triazinium Cation and Its Rhodium Complex that Shows Photoinduced DNA Cleavage Activity and Photocytotoxicity

The design and synthesis of an intensely blue rhodium(III) complex 3]+ of a new N,N-donor ligand, 8-(quinolin-8-ylamino)pyrido2,1-c]1,2,4]benzotriazin-11-ium, 2]+, which contains a planar pendant triazinium arm, is described. Structural characterization for 3]+ was carried out by using various spectroscopic techniques and single-crystal X-ray crystallography. The organometallic rhodium(III) compound shows a ligand-based reversible reduction at 0.65 V. The electrochemically reduced compound displays a single-line EPR spectrum that signifies the formation of ligand-based free radicals. Compound 3]+ shows a binding propensity to calf thymus DNA to give a Kapp value of 6.05X105 M1. The parent triazinium salt, pyrido2,1-c]1,2,4]benzotriazin-11-ium 1]+ and the ligand salt 2]+ exhibit photoinduced cleavage of DNA in UV-A light, whereas the reference Rh complex 3]+ photocleaves DNA with red light (647.1 nm). The compounds show photonuclease activities under both aerobic and anaerobic conditions. Mechanistic investigations under aerobic conditions with several inhibitors indicate the formation of hydroxyl radicals by means of a photoredox pathway. Under anaerobic conditions, it is believed that a photoinduced oxidation of DNA mechanism is operative. Compound 3]+ exhibits photocytotoxicity in HeLa cervical cancer cells to give IC50 values of (12+/-0.9) mu M in UV-A light at 365 nm and (31.4+/-1.1) mu M in the dark.

Vaporization dynamics of functional droplets in a hot laminar air jet

The vaporization characteristics of pendant droplets of various chemical compositions (like conventional fuels, alternative fuels and nanosuspensions) subjected to convective heating in a laminar air jet have been analyzed. Different heating conditions were achieved by controlling the air temperature and velocity fields around the droplet. A hybrid timescale has been proposed which incorporates the effects of latent heat of vaporization, saturation vapor pressure and thermal diffusivity. This timescale in essence encapsulates the different parameters that influence the droplet vaporization rate. The analysis further permits the evaluation of the effect of various parameters such as surrounding temperature, Reynolds number, far-field vapor presence, impurity content and agglomeration dynamics (nanosuspensions) in the droplet. Flow visualization has been carried out to understand the role of internal recirculation on the vaporization rate. The visualization indicates the presence of a single vortex cell within the droplet on account of the rotation and oscillation of the droplet due to aerodynamic load. External heating induced agglomeration in nanofluids leads to morphological changes during the vaporization process. These morphological changes and alteration in vaporization behavior have been assessed using high speed imaging of the diameter regression and Scanning Electron Microscopy images of the resultant precipitate. (C) 2012 Elsevier Ltd. All rights reserved.

q-Gaussian based Smoothed Functional Algorithms for Stochastic Optimization

The q-Gaussian distribution results from maximizing certain generalizations of Shannon entropy under some constraints. The importance of q-Gaussian distributions stems from the fact that they exhibit power-law behavior, and also generalize Gaussian distributions. In this paper, we propose a Smoothed Functional (SF) scheme for gradient estimation using q-Gaussian distribution, and also propose an algorithm for optimization based on the above scheme. Convergence results of the algorithm are presented. Performance of the proposed algorithm is shown by simulation results on a queuing model.

Functional characterization, homology modeling and docking studies of beta-glucosidase responsible for bioactivation of cyanogenic hydroxynitrile glucosides from Leucaena leucocephala (subabul)

Glycosyl hydrolase family 1 beta-glucosidases are important enzymes that serve many diverse functions in plants including defense, whereby hydrolyzing the defensive compounds such as hydroxynitrile glucosides. A hydroxynitrile glucoside cleaving beta-glucosidase gene (Llbglu1) was isolated from Leucaena leucocephala, cloned into pET-28a (+) and expressed in E. coli BL21 (DE3) cells. The recombinant enzyme was purified by Ni-NTA affinity chromatography. The optimal temperature and pH for this beta-glucosidase were found to be 45 A degrees C and 4.8, respectively. The purified Llbglu1 enzyme hydrolyzed the synthetic glycosides, pNPGlucoside (pNPGlc) and pNPGalactoside (pNPGal). Also, the enzyme hydrolyzed amygdalin, a hydroxynitrile glycoside and a few of the tested flavonoid and isoflavonoid glucosides. The kinetic parameters K (m) and V (max) were found to be 38.59 mu M and 0.8237 mu M/mg/min for pNPGlc, whereas for pNPGal the values were observed as 1845 mu M and 0.1037 mu M/mg/min. In the present study, a three dimensional (3D) model of the Llbglu1 was built by MODELLER software to find out the substrate binding sites and the quality of the model was examined using the program PROCHEK. Docking studies indicated that conserved active site residues are Glu 199, Glu 413, His 153, Asn 198, Val 270, Asn 340, and Trp 462. Docking of rhodiocyanoside A with the modeled Llbglu1 resulted in a binding with free energy change (Delta G) of -5.52 kcal/mol on which basis rhodiocyanoside A could be considered as a potential substrate.

Smoothed functional and Quasi-Newton algorithms for routing in multi-stage queueing network with constraints

We consider the problem of optimal routing in a multi-stage network of queues with constraints on queue lengths. We develop three algorithms for probabilistic routing for this problem using only the total end-to-end delays. These algorithms use the smoothed functional (SF) approach to optimize the routing probabilities. In our model all the queues are assumed to have constraints on the average queue length. We also propose a novel quasi-Newton based SF algorithm. Policies like Join Shortest Queue or Least Work Left work only for unconstrained routing. Besides assuming knowledge of the queue length at all the queues. If the only information available is the expected end-to-end delay as with our case such policies cannot be used. We also give simulation results showing the performance of the SF algorithms for this problem.

Vibrational spectroscopy and density functional theory analysis of 3-O-caffeoylquinic acid

Density functional theory (DFT) calculations are being performed to investigate the geometric, vibrational, and electronic properties of the chlorogenic acid isomer 3-CQA (1R,3R,4S,5R)-3-{(2E)-3-(3,4-dihydroxyphenyl)prop-2-enoyl]oxy}-1,4, 5-trihydroxycyclohexanecarboxylic acid), a major phenolic compound in coffee. DFT calculations with the 6-311G(d,p) basis set produce very good results. The electrostatic potential mapped onto an isodensity surface has been obtained. A natural bond orbital analysis (NBO) has been performed in order to study intramolecular bonding, interactions among bonds, and delocalization of unpaired electrons. HOMO-LUMO studies give insights into the interaction of the molecule with other species. The calculated HOMO and LUMO energies indicate that a charge transfer occurs within the molecule. (C) 2012 Elsevier B.V. All rights reserved.

Multi-component, Self-assembled, Functional Soft Materials

Supramolecular chemistry is an emerging tool for devising materials that can perform specified functions. The self-assembly of facially amphiphilic bile acid molecules has been extensively utilized for the development of functional soft materials. Supramolecular hydrogels derived from the bile acid backbone act as useful templates for the intercalation of multiple components. Based on this, synthesis of gel-nanoparticle hybrid materials, photoluminescent coating materials, development of a new enzyme assay technique, etc. were achieved in the author's laboratory. The present account highlights some of these achievements.

A practical approach for cross-functional vehicle body weight optimization

The goal of optimization in vehicle design is often blurred by the myriads of requirements belonging to attributes that may not be quite related. If solutions are sought by optimizing attribute performance-related objectives separately starting with a common baseline design configuration as in a traditional design environment, it becomes an arduous task to integrate the potentially conflicting solutions into one satisfactory design. It may be thus more desirable to carry out a combined multi-disciplinary design optimization (MDO) with vehicle weight as an objective function and cross-functional attribute performance targets as constraints. For the particular case of vehicle body structure design, the initial design is likely to be arrived at taking into account styling, packaging and market-driven requirements. The problem with performing a combined cross-functional optimization is the time associated with running such CAE algorithms that can provide a single optimal solution for heterogeneous areas such as NVH and crash safety. In the present paper, a practical MDO methodology is suggested that can be applied to weight optimization of automotive body structures by specifying constraints on frequency and crash performance. Because of the reduced number of cases to be analyzed for crash safety in comparison with other MDO approaches, the present methodology can generate a single size-optimized solution without having to take recourse to empirical techniques such as response surface-based prediction of crash performance and associated successive response surface updating for convergence. An example of weight optimization of spaceframe-based BIW of an aluminum-intensive vehicle is given to illustrate the steps involved in the current optimization process.

Phase synchronization in brain networks derived from correlation between probabilities of recurrences in functional MRI data

It is increasingly being recognized that resting state brain connectivity derived from functional magnetic resonance imaging (fMRI) data is an important marker of brain function both in healthy and clinical populations. Though linear correlation has been extensively used to characterize brain connectivity, it is limited to detecting first order dependencies. In this study, we propose a framework where in phase synchronization (PS) between brain regions is characterized using a new metric ``correlation between probabilities of recurrence'' (CPR) and subsequent graph-theoretic analysis of the ensuing networks. We applied this method to resting state fMRI data obtained from human subjects with and without administration of propofol anesthetic. Our results showed decreased PS during anesthesia and a biologically more plausible community structure using CPR rather than linear correlation. We conclude that CPR provides an attractive nonparametric method for modeling interactions in brain networks as compared to standard correlation for obtaining physiologically meaningful insights about brain function.

Cytochrome P450-mediated metabolism in brain: functional roles and their implications

Introduction: Cytochromes P450 (P450) and associated monooxygenases are a family of heme proteins involved in metabolism of endogenous compounds (arachidonic acid, eicosanoids and prostaglandins) as also xenobiotics including drugs and environmental chemicals. Liver is the major organ involved in P450-mediated metabolism and hepatic enzymes have been characterized. Extrahepatic organs, such as lung, kidney and brain have the capability for biotransformation through P450 enzymes. Brain, including human brain, expresses P450 enzymes that metabolize xenobiotics and endogenous compounds. Areas covered: An overview of P450-mediated metabolism in brain is presented focusing on distinct differences seen in expression of P450 enzymes, generation of unique P450 enzymes in brain through alternate splicing and their consequences in terms of metabolism of psychoactive drugs and inflammatory prompts, such as leukotrienes, thus modulating inflammatory response. Expert opinion: The brain possesses unique P450s that metabolize drugs and endogenous compounds through pathways that are markedly different from that seen in liver indicating that extrapolation directly from liver to brain is not appropriate. It is therefore necessary to characterize the unique brain P450s and their ability to metabolize xenobiotics and endogenous compounds to better understand the functions of this important class of enzymes in brain, especially human brain.

Heat and SDS insensitive NDK dimers are largely stabilised by hydrophobic interaction to form functional hexamer in Mycobacterium smegmatis

The primary structure and function of nucleoside diphosphate kinase (NDK), a substrate non-specific enzyme involved in the maintenance of nucleotide pools is also implicated to play pivotal roles in many other cellular processes. NDK is conserved from bacteria to human and forms a homotetramer or hexamer to exhibit its biological activity. However, the nature of the functional oligomeric form of the enzyme differs among different organisms. The functional form of NDKs from many bacterial systems, including that of the human pathogen, Mycobacterium tuberculosis (MtuNDK), is a hexamer, although some bacterial NDKs are tetrameric in nature. The present study addresses the oligomeric property of MsmNDK and how a dimer, the basic subunit of a functional hexamer, is stabilized by hydrogen bonds and hydrophobic interactions. Homology modeling was generated using the three-dimensional structure of MtuNDK as a template; the residues interacting at the monomer-monomer interface of MsmNDK were mapped. Using recombinant enzymes of wild type, catalytically inactive mutant, and monomer-monomer interactive mutants of MsmNDK, the stability of the dimer was verified under heat, SDS, low pH, and methanol. The predicted residues (Gln17, Ser24 and Glu27) were engaged in dimer formation, however the mutated proteins retained the ATPase and GTPase activity even after introducing single (MsmNDK- Q17A, MsmNDK-E27A, and MsmNDK-E27Q) and double (MsmNDK-E27A/Q17A) mutation. However, the monomer monomer interaction could be abolished using methanol, indicating the stabilization of the monomer-monomer interaction by hydrophobic interaction.

Gap renormalization of molecular crystals from density-functional theory

Fundamental gap renormalization due to electronic polarization is a basic phenomenon in molecular crystals. Despite its ubiquity and importance, all conventional approaches within density-functional theory completely fail to capture it, even qualitatively. Here, we present a new screened range-separated hybrid functional, which, through judicious introduction of the scalar dielectric constant, quantitatively captures polarization-induced gap renormalization, as demonstrated on the prototypical organic molecular crystals of benzene, pentacene, and C-60. This functional is predictive, as it contains system-specific adjustable parameters that are determined from first principles, rather than from empirical considerations.

Energy Hyperspace for Stacking Interaction in AU/AU Dinucleotide Step: Dispersion-Corrected Density Functional Theory Study

Double helical structures of DNA and RNA are mostly determined by base pair stacking interactions, which give them the base sequence-directed features, such as small roll values for the purine-pyrimidine steps. Earlier attempts to characterize stacking interactions were mostly restricted to calculations on fiber diffraction geometries or optimized structure using ab initio calculations lacking variation in geometry to comment on rather unusual large roll values observed in AU/AU base pair step in crystal structures of RNA double helices. We have generated stacking energy hyperspace by modeling geometries with variations along the important degrees of freedom, roll, and slide, which were chosen via statistical analysis as maximally sequence dependent. Corresponding energy contours were constructed by several quantum chemical methods including dispersion corrections. This analysis established the most suitable methods for stacked base pair systems despite the limitation imparted by number of atom in a base pair step to employ very high level of theory. All the methods predict negative roll value and near-zero slide to be most favorable for the purine-pyrimidine steps, in agreement with Calladine's steric clash based rule. Successive base pairs in RNA are always linked by sugar-phosphate backbone with C3-endo sugars and this demands C1-C1 distance of about 5.4 angstrom along the chains. Consideration of an energy penalty term for deviation of C1-C1 distance from the mean value, to the recent DFT-D functionals, specifically B97X-D appears to predict reliable energy contour for AU/AU step. Such distance-based penalty improves energy contours for the other purine-pyrimidine sequences also. (c) 2013 Wiley Periodicals, Inc. Biopolymers 101: 107-120, 2014.