Classification of biodiesel using NIR spectrometry and multivariate techniques

This article describes the classification of biodiesel samples using NIR spectroscopy and chemometric techniques. A total of 108 spectra of biodiesel samples were taken (being three samples each of four types of oil, cottonseed, sunflower, soybean and canola), from nine manufacturers. The measurements for each of the three samples were in the spectral region between 12,500 and 4000 cm⁻¹. The data were preprocessed by selecting a spectral range of 5000-4500 cm⁻¹, and then a Savitzky-Golay second-order polynomial was used with 21 data points to obtain second derivative spectra. Characterization of the biodiesel was done using chemometric models based on hierarchical cluster analysis (HCA), principal component analysis (PCA) and soft independent modeling of class analogy (SIMCA) elaborated for each group of biodiesel samples (cotton, sunflower, soybean and canola). For the HCA and PCA, the formation of clusters for each group of biodiesel was observed, and SIMCA models were built using 18 spectral measurements for each type of biodiesel (training set), and nine spectral measurements to construct a classification set (except for the canola oil which used eight spectra). The SIMCA classifications obtained 100% accurate identifications. Using this strategy, it was feasible to classify biodiesel quickly and nondestructively without the need for various analytical determinations.     

Achieving fast convergence of ab initio free energy perturbation calculations with the adaptive force-matching method

This paper studies the possibility of improving the convergence of ab initio free energy perturbation (FEP) calculations by developing customized force fields with the adaptive force-matching (AFM) method. The ab initio FEP method relies on a molecular mechanics (MM) potential to sample configuration space. If the Boltzmann weight of the MM sampling is close to that of the ab initio method, the efficiency of ab initio FEP will be optimal. The difference in the Boltzmann weights can be quantified by the relative energy difference distribution (REDD). The force field developed through AFM significantly improves the REDD when compared with standard MM models, thus improving the convergence of the ab initio FEP calculation. The static dielectric constant ε_s of ice-Ih was studied with PW-91 through ab initio FEP. With a customized force field developed through AFM, we were able to converge ε_s to 80 ± 4 with 3,600 configurations. A similar ab initio FEP calculation with the TIP4P model would require 220 times more configurations to achieve the same accuracy. Our study indicates that the PW-91 functional underestimates ice-Ih ε_s by about 20%.     

Phosphorus flame retardant polybenzoxazine foams based on renewable diphenolic acid

Flame retardant polybenzoxazine foams were prepared in a two step process, by heating mixtures of the benzoxazine derived from renewable diphenolic acid (DPA-Bz) with 9,10-dihydro-9-oxa-10-phosphaphenanthrene-10-oxide (DOPO) or 9,10-dihydro-9-oxa-10-(1-hydroxy-1-methylethyl) phosphaphenanthrene-10-oxide (DOPO-2Me) as additives. In the first step partial curing was achieved at different times and temperatures. In the second step, these materials underwent self foaming when heated at 220 °C. By means of a factorial design 2³ the effect of curing conditions and type of additive on the foam density were evaluated. DOPO-2Me additive was found to partially react with the DPA-Bz leading to a decrease in the glass transition temperature of the materials. The cellular structure of the foams was characterized by scanning electron microscope in terms of cell size, cell size distribution, closed-cell content and anisotropy ratio. The presence of DOPO-2Me into the solid precursors and foams greatly influenced the thermal degradation and the flame retardancy properties as evaluated by TGA, LOI and UL-94 respectively.     

A novel labdane diterpene from Acritopappus longifolius

A novel labdane diterpene was isolated from the plant Acritopappus longifolius. The structure of this compound was established by 1D- and 2D-nuclear magnetic resonance spectroscopic techniques and mass spectrometry data. N-Methyl-4-hydroxy-trans-proline, stigmasterol-3-O-β-d-glycoside, and the flavonoids quercetin, luteolin, kaempferol, and rutin were also isolated.     

Optimization of spray drying conditions to microencapsulate cupuassu (Theobroma grandiflorum) seed by-product extract

Cupuassu (Theobroma grandiflorum Schum.) is a popular Amazonian fruit because of its intense aroma and nutritional value, whose lipid fraction is alternatively used in cosmetics. To preserve active principles and ensure their controlled release, extract was microencapsulated by spray drying. Influence of spray-drying conditions on microencapsulation of cupuassu seed by-product extract was investigated according to a 3³-Box Behnken factorial design, selecting inlet temperature, maltodextrin concentration and feed flowrate as independent variables, and total polyphenol and flavonoid contents, antiradical power, yields of drying and microencapsulation as responses. Fitting the results by second-order equations and modelling by Response Surface Methodology allowed predicting optimum conditions. Epicatechin and glycosylated quercetin were the major microencapsulated flavonoids. Microparticles showed satisfactory antiradical power and stability at 5 °C or under simulated gastrointestinal conditions, thus they may be used to formulate new foods or pharmaceuticals.     

Vibrational properties of Cu<Subscript>3</Subscript>XY<Subscript>4</Subscript> sulvanites (X = Nb,Ta, and V; and Y = S,and Se) by ab initio molecular dynamics

In this work, we present a structural and dynamic characterisation of six different types of sulvanites Cu₃ X Y ₄ with X = Nb, V and Ta, and Y = S and Se. These materials have been the subject of intense study in recent times primarily as potential candidates for solar cell devices, as well as for their enhanced opto-electrical properties. Here, by means of first-principles calculations, we study the structural and dynamic behaviour of these materials at different temperatures, which is important for use of these materials in high-temperature conditions. In this work the dynamic and structural properties are studied using the Density Functional Theory technique. The simulations were performed at four different temperatures, ranging from room temperature to ~1500 K. By using first-principles molecular dynamics in the microcanonical ensemble, we are able to determine the vibrational spectra of these sulvanites. With this information we report for the first time the partial vibrational density of states of these structures at different temperatures. With these results we determine the vibrational properties of the basic building blocks of those sulvanites and their dynamic behaviour under temperature effects. We also show that the building blocks that which make up these structures, remain stable as the temperature increases.     

The Cu(I)–glutathione complex: factors affecting its formation and capacity to generate reactive oxygen species

Cu²⁺ ions and reduced glutathione (GSH) swiftly interact to form the physiologically occurring Cu(I)–[GSH]₂ complex. Prompted by the recently reported ability of this complex to generate superoxide radicals from molecular oxygen, the present study addressed how the concentration of Cu²⁺ and GSH, the pH, and the temperature affect the formation of the Cu(I)–[GSH]₂ complex and its capacity to generate superoxide radicals and hydrogen peroxide. Increasing concentrations of Cu²⁺ and GSH, added at a fixed molar ratio of 1:3, led to a proportionally greater production of superoxide anions, hydrogen peroxide, and oxidized glutathione (GSSG). GSSG formation was found to closely reflect the formation of Cu(I)–[GSH]₂. Biologically relevant changes in pH (e.g., from 6.8 to 7.7) and temperature (from 22 to 37 °C) did not affect the formation of the Cu(I)–[GSH]₂, as assessed by GSSG production. However, production of superoxide radicals increased as the pH values were incremented. An opposite effect was observed regarding hydrogen peroxide production. The ability of a freshly prepared Cu(I)–[GSH]₂ complex (assayed within a minute from its formation) to generate superoxide radicals was incremented by as the temperature was increased. Such ability, however, correlated inversely with the temperature when, before assaying for superoxide, the earlier referred preparation was incubated during 30 min in the presence of oxygen. Under the latter condition, hydrogen peroxide linearly accumulated in time, suggesting that an increased autodismutation underlies the apparent time-dependent “aging” of the capacity of the complex to generate superoxide.     

Semidefinite relaxations of dynamical programs under discrete constraints

In this work we propose an exact semidefinite relaxation for non-linear, non-convex dynamical programs under discrete constraints in the state variables and the control variables. We outline some theoretical features of the method and workout the solutions of a benchmark problem in cybernetics and the classical inventory problem under discrete constraints.     

PCA and Kriging for the efficient exploration of consistency regions in Uncertainty Quantification

For stationary power sources such as utility boilers, it is useful to dispose of parametric models able to describe their behavior in a wide range of operating conditions, to predict some Quantities of Interest (QOIs) that need to be consistent with experimental observations. The development of predictive simulation tools for large scale systems cannot rely on full-order models, as the latter would lead to prohibitive costs when coupled to sampling techniques in the model parameter space. An alternative approach consists of using a Surrogate Model (SM). As the number of QOIs is often high and many SMs need to be trained, Principal Component Analysis (PCA) can be used to encode the set of QOIs in a much smaller set of scalars, called PCA scores. A SM is then built for each PCA score rather than for each QOI. The advantage of reducing the number of variables is twofold: computational costs are reduced (less SMs need to be trained) and information is preserved (correlation among the original variables).The strategy is applied to a CFD model simulating the Alstom 15 MW_th oxy-pilot Boiler Simulation Facility (BSF). In practice, experiments cannot provide full coverage of the pulverized-coal utility boiler due to both practicality and costs. Values of the model’s parameters which guarantee consistency with the experimental data of this test facility for 121 QOIs are found, by training a SM based on the combination of Kriging and PCA, using only 5 latent variables.