Some remarks on equilibrium state in dynamic condition

For dehydration of CaC₂O₄·H₂O and thermal dissociation of CaCO₃ carried out in Mettler Toledo TGA/SDTA-851^e/STAR^e thermobalance similar experimental conditions was applied: 9–10 heating rates, q = 0.2, 0.5, 1, 2, 3, 6, 12, 24, 30, and 36 K min⁻¹, for sample mass 10 mg, in nitrogen atmosphere (100 ml min⁻¹) and in Al₂O₃ crucibles (70 μl). There were analyzed changes of typical TGA quantities, i.e., T, TG and DTG in the form of the relative rate of reaction/process intended to be analyzed on-line by formula (10). For comparative purposes, the relationship between experimental and equilibrium conversion degrees was used (for P = P^\ominus P = P^{{\ominus}} ). It was found that the solid phase decomposition proceeds in quasi-equilibrium state and enthalpy of reaction is easily “obscured” by activation energy. For small stoichiometric coefficients on gas phase side (here: ν = 1) discussed decomposition processes have typical features of phenomena analyzable by known thermokinetic methods.     

Solubility of methane in octane + ethanol at temperatures from 303.15 K to 333.15 K and pressures up to 12.01 MPa

Solubility of methane in octane + ethanol was measured at temperatures ranging from 303.15 K to 333.15 K and pressures ranging from 2.60 MPa to 12.01 MPa. Experimental data were analyzed using the Soave-Redlich-Kwong equation of state with three types of mixing rules, and the estimated average deviation from the experimental solubility data was less than 3.5 %.     

Influence of Field Effects on the Performance of InGaAs-Based Terahertz Radiation Detectors

A detailed electrical characterization of high-performance bow-tie InGaAs-based terahertz detectors is presented along with simulation results. The local surface potential and tunnelling current were scanned over the surfaces of the detectors by means of Kelvin probe force microscopy (KPFM) and scanning tunnelling microscopy (STM), which also enabled the determination of the Fermi level. Current-voltage curves were measured and modelled using the Synopsys Sentaurus TCAD package to gain deeper insight into the processes involved in detector operation. In addition, we performed finite-difference time-domain (FDTD) simulations to reveal features related to changes in the electric field due to the metal detector contacts. The investigation revealed that field-effect-induced conductivity modulation is a possible mechanism contributing to the high sensitivity of the studied detectors.     

Measurement and Modeling of Phase Equilibrium,Volumetric Properties and Molar Refractivity of 2-Methylpropan-2-ol + Ethane-1,2-diol

2-Methylpropan-2-ol, an important fine chemical, may be dehydrated during extractive distillation with glycols as entrainer. Experimental isobaric phase equilibrium studies were carried out on binary mixtures of 2-methylpropan-2-ol with ethane-1,2-diol, as an entrainer, at the local atmospheric pressure of 94.99 kPa and at sub-atmospheric pressures of 19.99, 39.99, 59.99, 78.79 kPa using a Sweitoslawski-type ebulliometer. The Wilson and NRTL activity coefficient models were used to correlate the experimental results and the binary interaction parameters were obtained using the Generalized Reduced Gradient optimization technique. UNIFAC was also used to predict the deviations in bubble temperatures. Moreover, the variation in density, refractive index values and other derived properties (excess molar volumes, partial molar volumes and deviations in molar refractivity) were explored at 303.15, 313.15, 323.15 and 333.15 K to understand the shift of equilibrium with the variation in the mixture composition for the conformational state of the molecules. The Redlich–Kister polynomial equation was used to correlate the excess molar volumes and deviations from molar refractivity. Different theoretical mixing rules (Lorentz–Lorenz, Wiener, Heller, Gladstone–Dale and Arago–Biot) are investigated and reported in terms of average percentage deviation. Furthermore, the Prigogine–Flory–Patterson theory was used to predict the trend of the dependence of excess molar volumes on composition for the present system.     

Random Evolutionary Dynamics Driven by Fitness and House-of-Cards Mutations: Sampling Formulae

We first revisit the multi-allelic mutation-fitness balance problem, especially when mutations obey a house of cards condition, where the discrete-time deterministic evolutionary dynamics of the allelic frequencies derives from a Shahshahani potential. We then consider multi-allelic Wright–Fisher stochastic models whose deviation to neutrality is from the Shahshahani mutation/selection potential. We next focus on the weak selection, weak mutation cases and, making use of a Gamma calculus, we compute the normalizing partition functions of the invariant probability densities appearing in their Wright–Fisher diffusive approximations. Using these results, generalized Ewens sampling formulae (ESF) from the equilibrium distributions are derived. We start treating the ESF in the mixed mutation/selection potential case and then we restrict ourselves to the ESF in the simpler house-of-cards mutations only situation. We also address some issues concerning sampling problems from infinitely-many alleles weak limits.     

Computationally highly efficient mixture of adaptive filters

We introduce a new combination approach for the mixture of adaptive filters based on the set-membership filtering (SMF) framework. We perform SMF to combine the outputs of several parallel running adaptive algorithms and propose unconstrained, affinely constrained and convexly constrained combination weight configurations. Here, we achieve better trade-off in terms of the transient and steady-state convergence performance while providing significant computational reduction. Hence, through the introduced approaches, we can greatly enhance the convergence performance of the constituent filters with a slight increase in the computational load. In this sense, our approaches are suitable for big data applications where the data should be processed in streams with highly efficient algorithms. In the numerical examples, we demonstrate the superior performance of the proposed approaches over the state of the art using the well-known datasets in the machine learning literature.     

Interactions between cellulose nanofibers and retention systems in flocculation of recycled fibers

Although the positive effect that cellulose nanofibers (CNF) can have on paper strength is known, their effect on flocculation during papermaking is not well understood, and most relevant studies have been carried out in presence of only cationic starch. Flocculation is the key to ensuring retention of fibers, fines, and fillers, and furthermore floc properties have a great influence on paper quality. The aim of this research is to study the interactions between CNF and flocculants by assessing the effect of two types of CNF, from eucalyptus and corn, on the flocculation process induced by three different retention systems [a dual system, polyvinylamine (PVA), and cationic starch as reference]. The results showed that CNF interacted with the flocculants in different ways, affecting flocculation efficiency and floc properties. In general, addition of CNF increased floc stability and minimized overdosing effects. Moreover, presence of CNF increased floc size for given PVA dose; therefore, CNF addition could contribute to improve the wet end in the paper machine if combined with the optimal flocculant and dose.