The primary photophysics of the Avena sativa phototropin 1 LOV2 domain observed with time-resolved emission spectroscopy

The phototropins are blue-light receptors that base their light-dependent action on the reversible formation of a covalent bond between a flavin mononucleotide (FMN) cofactor and a conserved cysteine in light, oxygen or voltage (LOV) domains. The primary reactions of the Avena sativa phototropin 1 LOV2 domain were investigated by means of time-resolved and low-temperature fluorescence spectroscopy. Synchroscan streak camera experiments revealed a fluorescence lifetime of 2.2 ns in LOV2. A weak long-lived component with emission intensity from 600 to 650 nm was assigned to phosphorescence from the reactive FMN triplet state. This observation allowed determination of the LOV2 triplet state energy level at physiological temperature at 16600 cm(-1). FMN dissolved in aqueous solution showed pH-dependent fluorescence lifetimes of 2.7 ns at pH 2 and 3.9-4.1 ns at pH 3-8. Here, too, a weak phosphorescence band was observed. The fluorescence quantum yield of LOV2 increased from 0.13 to 0.41 upon cooling the sample from 293 to 77 K. A pronounced phosphorescence emission around 600 nm was observed in the LOV2 domain between 77 and 120 K in the steady-state emission.     

Time-resolved ultrathin cobalt film growth on a colloidal polymer template

Cobalt (Co) sputter deposition onto a colloidal polymer template is investigated using grazing incidence small-angle X-ray scattering (GISAXS), scanning electron microscopy (SEM), and atomic force microscopy (AFM). SEM and AFM data picture the sample topography, GISAXS the surface and near-surface film structure. A two-phase model is proposed to describe the time evolution of the Co growth. The presence of the colloidal template results in the correlated deposition of an ultrathin Co film on the sample surface and thus in the creation of Co capped polystyrene (PS) colloids. Well below the percolation threshold, the radial growth is restricted and only height growth is observed.     

Exact on-lattice stochastic reaction-diffusion simulations using partial-propensity methods

Stochastic reaction-diffusion systems frequently exhibit behavior that is not predicted by deterministic simulation models. Stochastic simulation methods, however, are computationally expensive. We present a more efficient stochastic reaction-diffusion simulation algorithm that samples realizations from the exact solution of the reaction-diffusion master equation. The present algorithm, called partial-propensity stochastic reaction-diffusion (PSRD) method, uses an on-lattice discretization of the reaction-diffusion system and relies on partial-propensity methods for computational efficiency. We describe the algorithm in detail, provide a theoretical analysis of its computational cost, and demonstrate its computational performance in benchmarks. We then illustrate the application of PSRD to two- and three-dimensional pattern-forming Gray-Scott systems, highlighting the role of intrinsic noise in these systems.     

Fluoroalcohols as novel buffer components for basic buffer solutions for liquid chromatography electrospray ionization mass spectrometry: retention mechanisms

Two fluoroalcohols--1,1,1,3,3,3-hexafluoro-2-propanol (HFIP) and 1,1,1,3,3,3-hexafluoro-2-methyl-2-propanol (HFTB)--were evaluated as volatile buffer acids in basic mobile phases for LC-ESI-MS determination of acidic and basic compounds. HFIP and HFTB as acidic buffer components offer interesting possibilities to adjust retention behavior of different analytes and expand the currently rather limited range of ESI-compatible buffer systems for basic mobile phases. Comparing with commonly used basic buffer components the fluoroalcohols did not suppress the ionization of the analytes, for several analytes ionization enhancement was observed. RP chromatographic retention mechanisms were evaluated and compared to traditional buffer system. All trends in retention of the acidic and basic analytes can be interpreted by the following model: the neutral fluoroalcohols are quite strongly retained by the stationary phase whereas their anions are less retained, thus their amount on the stationary phase is dependent on mobile phase pH; the anions of the fluoroalcohols form ion pairs in the mobile phase with the basic analytes; the fluoroalcohols on the stationary phase surface compete with acidic analytes thereby hindering their retention; the fluoroalcohols on the stationary phase bind basic analytes thereby favoring their retention.     

Photochemical preparation of ZnO nanoparticles

Preparation of zinc oxide nanoparticles from aqueous solutions containing zinc nitrate or formate using UV irradiation was investigated. Analysis of solid phase formed during irradiation confirmed the presence of zinc oxide or zinc peroxide nanoparticles ranging in size from 1 to 70 nm, depending on initial precursors. Annealing at temperatures 650–1000 °C results in forming of rice-like zinc oxide particles, up to hundreds of nm in size. Photochemical method yields material with high chemical purity and uniform particle size distribution. In addition, photo-induced doping of zinc oxide with lanthanum was studied. Presence of lanthanum in zinc oxide crystal lattice and post-preparation treatment in reduction atmosphere significantly increase the UV excitonic luminescence at 395 nm in radioluminescence spectra.     

Anchor points for the unified Brønsted acidity scale: the rCCC model for the calculation of standard Gibbs energies of proton solvation in eleven representative liquid media

The COSMO cluster-continuum (CCC) solvation model is introduced for the calculation of standard Gibbs solvation energies of protons. The solvation sphere of the proton is divided into an inner proton-solvent cluster with covalent interactions and an outer solvation sphere that interacts electrostatically with the cluster. Thus, the solvation of the proton is divided into two steps that are calculated separately: 1) The interaction of the proton with one or more solvent molecules is calculated in the gas phase with high-level quantum-chemical methods (modified G3 method). 2) The Gibbs solvation energy of the proton-solvent cluster is calculated by using the conductor-like screening model (COSMO). For every solvent, the solvation of the proton in at least two (and up to 11) proton-solvent clusters was calculated. The resulting Gibbs solvation energies of the proton were weighted by using Boltzmann statistics. The model was evaluated for the calculation of Gibbs solvation energies by using experimental data of water, MeCN, and DMSO as a reference. Allowing structural relaxation of the proton-solvent clusters and the use of structurally relaxed Gibbs solvation energies improved the accordance with experimental data especially for larger clusters. This variation is denoted as the relaxed COSMO cluster-continuum (rCCC) model, for which we estimate a 1σ error bar of 10 kJ mol(-1) . Gibbs solvation energies of protons in the following representative solvents were calculated: Water, acetonitrile, sulfur dioxide, dimethyl sulfoxide, benzene, diethyl ether, methylene chloride, 1,2-dichloroethane, sulfuric acid, fluorosulfonic acid, and hydrogen fluoride. The obtained values are absolute chemical standard potentials of the proton (pH=0 in this solvent). They are used to anchor the individual solvent specific acidity (pH) scales to our recently introduced absolute acidity scale.     

Allan J. Bard and Cynthia G. Zoski (Eds): Electroanalytical Chemistry

Coupled with evaporative light scattering detection, a high-speed counter-current chromatography (HSCCC) method was applied to the separation and purification of three tauro-conjugated cholic acids of taurochenodeoxycholic acid (TCDCA), taurohyodeoxycholic acid (THDCA) and taurohyocholic acid (THCA) from Pulvis Fellis Suis (Pig gallbladder bile) for the first time. The two-phase solvent system composed of chloroform-methanol-water-acetic acid (4:4:2:0.3, v/v/v/v) was selected for the one-step separation where the lower phase was used as the mobile phase in the head to tail elution mode. The revolution speed of the separation column, flow rate of the mobile phase and separation temperature were 800 rpm, 1.5 ml/min and 25°C respectively. From 100 mg of the crude extract, 10.2 mg of TCDCA, 11.8 mg of THDCA and 5.3 mg of THCA were obtained with the purity of 94.6%, 96.5% and 95.4%, respectively. in one step separation The HSCCC fractions were analyzed by high-performance liquid chromatography (HPLC) and the structures of the three tauro-conjugated cholic acids were identified by ESI-MS, (1)H NMR and (13)C NMR.     

Sensitivity Analysis and Quantification of the Role of Governing Transport Mechanisms and Parameters in a Gas Flow Model for Low-Permeability Porous Media

Recent models represent gas (methane) migration in low-permeability media as a weighted sum of various contributions, each associated with a given flow regime. These models typically embed numerous chemical/physical parameters that cannot be easily and unambiguously evaluated via experimental investigations. In this context, modern sensitivity analysis techniques enable us to diagnose the behavior of a given model through the quantification of the importance and role of model input uncertainties with respect to a target model output. Here, we rely on two global sensitivity analysis approaches and metrics (i.e., variance-based Sobol’ indices and moment-based AMA indices) to assess the behavior of a recent interpretive model that conceptualizes gas migration as the sum of a surface diffusion mechanism and two weighted bulk flow components. We quantitatively investigate the impact of (i) each uncertain model parameter and (ii) the type of their associated probability distribution on the evaluation of methane flow. We then derive the structure of an effective diffusion coefficient embedding all complex mechanisms of the model considered and allowing quantification of the relative contribution of each flow mechanism to the overall gas flow.

     

Fast calculation of multiobjective probability of improvement and expected improvement criteria for Pareto optimization

The use of surrogate based optimization (SBO) is widely spread in engineering design to reduce the number of computational expensive simulations. However, “real-world” problems often consist of multiple, conflicting objectives leading to a set of competitive solutions (the Pareto front). The objectives are often aggregated into a single cost function to reduce the computational cost, though a better approach is to use multiobjective optimization methods to directly identify a set of Pareto-optimal solutions, which can be used by the designer to make more efficient design decisions (instead of weighting and aggregating the costs upfront). Most of the work in multiobjective optimization is focused on multiobjective evolutionary algorithms (MOEAs). While MOEAs are well-suited to handle large, intractable design spaces, they typically require thousands of expensive simulations, which is prohibitively expensive for the problems under study. Therefore, the use of surrogate models in multiobjective optimization, denoted as multiobjective surrogate-based optimization, may prove to be even more worthwhile than SBO methods to expedite the optimization of computational expensive systems. In this paper, the authors propose the efficient multiobjective optimization (EMO) algorithm which uses Kriging models and multiobjective versions of the probability of improvement and expected improvement criteria to identify the Pareto front with a minimal number of expensive simulations. The EMO algorithm is applied on multiple standard benchmark problems and compared against the well-known NSGA-II, SPEA2 and SMS-EMOA multiobjective optimization methods.