Liquid li structure and dynamics: A comparison between OFDFT and second nearest‐neighbor embedded‐atom method

The structure and dynamics of liquid lithium are studied using two simulation methods: orbital‐free (OF) first‐principles molecular dynamics (MD), which employs OF density functional theory (DFT), and classical MD utilizing a second nearest‐neighbor embedded‐atom method potential. The properties studied include the dynamic structure factor, the self‐diffusion coefficient, the dispersion relation, the viscosity, and the bond angle distribution function. Simulation results were compared to available experimental data when possible. Each method has distinct advantages and disadvantages. For example, OFDFT gives better agreement with experimental dynamic structure factors, yet is more computationally demanding than classical simulations. Classical simulations can access a broader temperature range and longer time scales. The combination of first‐principles and classical simulations is a powerful tool for studying properties of liquid lithium. © 2015 American Institute of Chemical Engineers AIChE J, 61: 2841–2853, 2015     

Synthesis, characterization and photocatalytic evaluation of visible light activated C-doped TiO2 nanoparticles

We have demonstrated heterogeneous photocatalytic degradation of microcystin-LR (MC-LR) by visible light activated carbon doped TiO(2) (C-TiO(2)) nanoparticles, synthesized by a modified sol-gel route based on the self-assembly technique exploiting oleic acid as a pore directing agent and carbon source. The C-TiO(2) nanoparticles crystallize in anatase phase despite the low calcination temperature of 350 °C and exhibit a highly porous structure that can be optimized by tuning the concentration of the oleic acid surfactant. The carbon modified nanomaterials exhibited enhanced absorption in the broad visible light region together with an apparent red shift in the optical absorption edge by 0.5 eV (2.69 eV), compared to the 3.18 eV of reference anatase TiO(2). Carbon species were identified by x-ray photoelectron spectroscopy analysis through the formation of both Ti-C and C-O bonds, indicative of substitution of carbon for oxygen atoms and the formation of carbonates, respectively. Electron paramagnetic resonance spectroscopy revealed the formation of two carbon related paramagnetic centers in C-TiO(2), whose intensity was markedly enhanced under visible light illumination, pointing to the formation of localized states within the anatase band gap, following carbon doping. The photocatalytic activity of C-TiO(2) nanomaterials was evaluated for the degradation of MC-LR at pH 3.0 under visible light (λ > 420 nm) irradiation. The doped materials showed a higher MC-LR degradation rate than reference TiO(2), behavior that is attributed to the incorporation of carbon into the titania lattice.     

In Situ Polymerisation of Polyamide‐6 Nanocompounds from Caprolactam and Layered Silicates

An in situ process for the production of polyamide‐6 nanocompounds is investigated as an alternative to melt compounding. During the in situ production, the layered silicates are dispersed in the monomer caprolactam before the polymerisation in a twin screw extruder, leading to an intercalation of the silicates. The production of a polyamide compound containing 0, 2 and 4 wt.‐% nanoscale silicates was successful. An improvement of the elastic modulus of approximately 30–60% was reached. The figure shows the TEM micrograph of a nanocompound containing 2 wt.‐% nanoclay at a magnification of 30 000×.

     

Influence of the structure of soft and stiff chain fragments on properties of segmented polyurethanes. I. Phase morphology

Model segmented polyurethanes (SPUs) prepared from either oxypropylene glycol oligomer or butylene adipate glycol oligomer, both of molar mass 2 kg/mol (soft fragments, SFT), and three different diisocyanates (all-trans 4,4'-dicyclohexylmethane diisocyanate, t, t-HMDI-1.0; HMDI with 20% of trans isomers, t, t-HMDI-0.2; and 4, 4'-diphenylmethane diisocyanate, MDI) (stiff fragments, STF) were characterized by specific heat capacity measurements in the temperature interval 140-540 K, and by wide-angle and small-angle X-ray scattering at room temperature. Limited miscibility of SFT and STF chain components resulted in incomplete separation into a regular three-dimensional macrolattice of STF-rich microdomains and SFT-rich microphases. The composition of STF-rich microdomains was estimated by fitting the softening temperatures to the Couchman's equation, whereas the relative contents of SFT-rich and STF-rich microphases were assessed by comparing the specific heat capacity change at the glass transition temperatures to corresponding additive values. The overall degree of microphase separation, as well as the mean macrolattice spacings between STF microdomains decreased in the order, MDI > t, t-HMDI-1.0 ? t, t-HMDI-0.2. The conformation of STF fragments within the STF-rich microdomains changed from nearly extended (for MDI) through slightly contracted (for t, t-HMDI-1.0) to strongly contracted (for t, t-HMDI-0.2).     

Derived components regression using the BACON algorithm

Partial least squares and principal components regression are commonly used regularized regression methods which use derived components instead of original predictors. The components are derived from the estimated variance-covariance matrix and regression is run using the least squares. Therefore, they are not robust and a few outliers may have drastic effects on the obtained results. These regression methods are robustified by using the BACON algorithm which provides robust measures for both dispersion and regression. The proposed methods are illustrated by examples and their properties are investigated using both real data and simulation experiments.     

Adaptively preconditioned Krylov spaces to identify irrelevant predictors

Linear regression methods have problems in estimation when the predictor variables are highly correlated and when their number exceeds the number of available observations. PLS is one well known method for handling such ill-conditioned regression problems. It does so by approximating the regression solution in a low dimensional subspace. While it copes with collinearity and singularity problems, PLS does not have a variable selection procedure intrinsic to the method. However, it is often the case that one needs to decide which predictors, among the numerous and correlated ones, are the more relevant. The PLS coefficient is a good starting point for the identification of relevant variables in ill-conditioned regression settings. We propose to adaptively precondition the space generated by PLS in order to determine the most relevant predictors. The relevant subset is determined by a multiple testing procedure, and preconditioning stops when this set no longer changes. The principal objective is to do regression modelling and to recover solutions that are easy to interpret in the high dimensional regression setting. We use dimension reduction in a PLS fashion, using information on the response to guide the variable selection procedure. A variety of examples is studied with good results.     

Potato: a comparative study of the effect of cultivars and cultivation conditions and genetic modification on the physico-chemical properties of potato tubers in conjunction with multivariate analysis towards authenticity

Potato (Solanum tuberosum L.) is a highly nutritious, mild flavored, easy to blend food that has many possibilities for "building in" desired nutrients. Varietal and environmental differences are known to exist in the shape, size, and nutritional content of potatoes. Different populations opt for varying sensory properties in relation to their diets. Potatoes are a low energy food in comparison to cereals and legumes. The aim of this review was to present an update of the currently conducted studies both on the characterization of several potato varieties (physical, chemical, and sensory analysis) and by means of genetic modification. Towards this target, five comprehensive tables were compiled where all recent data (physicochemical properties) and GM varieties were presented in conjunction with multivariate analysis (chemometrics). The latter was shown to be effectively used towards authenticity purposes (identification of geographical origin, variety, GM).