Including nonequilibrium interface kinetics in a continuum model for melting nanoscaled particles

The melting temperature of a nanoscaled particle is known to decrease as the curvature of the solid-melt interface increases. This relationship is most often modelled by a Gibbs--Thomson law, with the decrease in melting temperature proposed to be a product of the curvature of the solid-melt interface and the surface tension. Such a law must break down for sufficiently small particles, since the curvature becomes singular in the limit that the particle radius vanishes. Furthermore, the use of this law as a boundary condition for a Stefan-type continuum model is problematic because it leads to a physically unrealistic form of mathematical blow-up at a finite particle radius. By numerical simulation, we show that the inclusion of nonequilibrium interface kinetics in the Gibbs--Thomson law regularises the continuum model, so that the mathematical blow up is suppressed. As a result, the solution continues until complete melting, and the corresponding melting temperature remains finite for all time. The results of the adjusted model are consistent with experimental findings of abrupt melting of nanoscaled particles. This small-particle regime appears to be closely related to the problem of melting a superheated particle.

Adsorption thermodynamics and kinetics study for the self-assembly of 1,8,15,22-tetraaminophthalocyanatocobalt(II) on glassy carbon surface

Spontaneous adsorption of 1,8,15,22-tetraaminophthalocyanatocobalt(II) (4α-CoIITAPc) on glassy carbon (GC) electrode leads to the formation of a stable self-assembled monolayer (SAM). Since the SAM of 4α-CoIITAPc is redox active, its adsorption on GC electrode was followed by cyclic voltammetry. SAM of 4α-CoIITAPc on GC electrode shows two pairs of well-defined redox peaks corresponding to CoIII/CoII and CoIIIPc−1/CoIIIPc−2. The surface coverage (Γ) value, calculated by integrating the charge under CoII oxidation, was used to study the adsorption thermodynamics and kinetics of 4α-CoIITAPc on GC surface. Cyclic voltammetric studies show that the adsorption of 4α-CoIITAPc on GC electrode has reached the saturation coverage (Γs) within 3 h. The Γs value for the SAM of 4α-CoIITAPc on GC electrode was found to be 2.37 × 10−10 mol cm−2. Gibbs free energy (ΔGads) and adsorption rate constant (kad) for the adsorption of 4α-CoIITAPc on GC surface were found to be −16.76 kJ mol−1 and 7.1 M−1 s−1, respectively. The possible mechanism for the self-assembly of 4α-CoIITAPc on GC surface is through the addition of nucleophilic amines to the olefinic bond on the GC surface in addition to a meager contribution from π stacking. The contribution of π stacking was confirmed from the adsorption of unsubstituted phthalocyanatocobalt(II) (CoPc) on GC electrode. Raman spectra for the SAM of 4α-CoIITAPc on carbon surface shows strong stretching and breathing bands of Pc macrocycle, pyrrole ring and isoindole ring. Raman and CV studies suggest that 4α-CoIITAPc is adopting nearly a flat orientation or little bit tilted orientation.

Development of a pilot-scale bacterial fermentation for plasmid-based biopharmaceutical production using a stoichiometric medium

The recognition of the potential efficacy of plasmid DNA (pDNA) molecules as vectors in the treatment and prevention of emerging diseases has birthed the confidence to combat global pandemics. This is due to the close-to-zero safety concern associated with pDNA vectors compared to viral vectors in cell transfection and targeting. Considerable attention has been paid to the potential of pDNA vectors but comparatively less thought has been given to the practical challenges in producing large quantities to meet current rising demands. A pilot-scale fermentation scheme was developed by employing a stoichiometrically-designed growth medium whose exceptional plasmid yield performance was attested in a shake flask environment for pUC19 and pEGFP-N1 transformed into E. coliDH5α and E. coliJM109, respectively. Batch fermentation of E. coliDH5α-pUC19 employing the stoichiometric medium displayed a maximum plasmid volumetric and specific yield of 62.6 mg/L and 17.1 mg/g (mg plasmid/g dry cell weight), respectively. Fed-batch fermentation of E. coliDH5α-pUC19 on a glycerol substrate demonstrated one of the highest ever reported pilot-scale plasmid specific yield of 48.98 mg/g and a volumetric yield of 0.53 g/L. The attainment of high plasmid specific yields constitutes a decrease in plasmid manufacturing cost and enhances the effectiveness of downstream processes by reducing the proportion of intracellular impurities. The effect of step-rise temperature induction was also considered to maximize ColE1-origin plasmid replication.

Preparation of macroporous methacrylate monolithic material with convective flow properties for bioseparation : Investigating the kinetics of pore formation and hydrodynamic performance

The preparation of macroporous methacrylate monolithic material with controlled pore structures can be carried out in an unstirred mould through careful and precise control of the polymerisation kinetics and parameters. Contemporary synthesis conditions of methacrylate monolithic polymers are based on existing polymerisation schemes without an in-depth understanding of the dynamics of pore structure and formation. This leads to poor performance in polymer usage thereby affecting final product recovery and purity, retention time, productivity and process economics. The unique porosity of methacrylate monolithic polymer which propels its usage in many industrial applications can be controlled easily during its preparation. Control of the kinetics of the overall process through changes in reaction time, temperature and overall composition such as cross-linker and initiator contents allow the fine tuning of the macroporous structure and provide an understanding of the mechanism of pore formation within the unstirred mould. The significant effect of temperature of the reaction kinetics serves as an effectual means to control and optimise the pore structure and allows the preparation of polymers with different pore size distributions from the same composition of the polymerisation mixture. Increasing the concentration of the cross-linking monomer affects the composition of the final monoliths and also decreases the average pore size as a result of pre-mature formation of highly cross-linked globules with a reduced propensity to coalesce. The choice and concentration of porogen solvent is also imperative. Different porogens and porogen mixtures present different pore structure output. Example, larger pores are obtained in a poor solvent due to early phase separation.

Doubly Fed Induction Generators : Overview and Intelligent Control Strategies for Wind Energy Conversion Systems

Adjustable speed induction generators, especially the Doubly-Fed Induction Generators (DFIG) are becoming increasingly popular due to its various advantages over fixed speed generator systems. A DFIG in a wind turbine has ability to generate maximum power with varying rotational speed, ability to control active and reactive by integration of electronic power converters such as the back-to-back converter, low rotor power rating resulting in low cost converter components, etc, DFIG have become very popular in large wind power conversion systems. This chapter presents an extensive literature survey over the past 25 years on the different aspects of DFIG. Application of H8 Controller for enhanced DFIG-WT performance in terms of robust stability and reference tracking to reduce mechanical stress and vibrations is also demonstrated in the chapter.

Behavioral consistency, the homology assumption, and the problems of induction

The ultimate goal of profiling is to identify the major behavioral and personality characteristics to narrow the suspect pool. Inferences about offender characteristics can be accomplished deductively, based on the analysis of discrete offender behaviors established within a particular case. They can also be accomplished inductively, involving prediction based on abstract offender averages from group data (these methods and the logic on which they are based is detailed extensively in Chapters 2 and 4). As discussed, these two approaches are by no means equal.

Effect of functionalized kaolinite on the curing kinetics of cycloaliphatic epoxy/anhydride system

Silane grafted kaolinite (KGS) was prepared through grinding kaolinite and then grafting with 3-aminopropyltriethoxysilane. The influence of KGS on the curing kinetics of cycloaliphatic epoxy resin was studied by non-isothermal differential scanning calorimetry at different heating rates. The reaction activation energy (Ea) was determined based on the Flynn–Wall–Ozawa method. The results of dynamic differential scanning calorimetry (DSC) kinetic analysis show that the surface hydroxyl groups of clay decreases the Ea from 70.6 kJ mol− 1 to 62.8 kJ mol− 1 and accelerates the curing reaction of the epoxy resin. The silane grafting reactions consume the surface hydroxyl groups of kaolinite and lead to a decrease in the catalytic efficiency of KGS in the curing of epoxy resin.

Kinematics and kinetics of the Nordic hamstring curl

This thesis describes, for the first time, the forces involved in the Nordic hamstring exercise, its reliability and the biomechanical effects of extra loading during the movement. The results provide practitioners with valuable information to enhance hamstring injury prevention and rehabilitation programs.

Stochastic linear multistep methods for the simulation of chemical kinetics

In this paper, we introduce the Stochastic Adams-Bashforth (SAB) and Stochastic Adams-Moulton (SAM) methods as an extension of the tau-leaping framework to past information. Using the theta-trapezoidal tau-leap method of weak order two as a starting procedure, we show that the k-step SAB method with k >= 3 is order three in the mean and correlation, while a predictor-corrector implementation of the SAM method is weak order three in the mean but only order one in the correlation. These convergence results have been derived analytically for linear problems and successfully tested numerically for both linear and non-linear systems. A series of additional examples have been implemented in order to demonstrate the efficacy of this approach.

Induction of a Th1 immune response and suppression of IgE via immunotherapy with a recombinant hybrid molecule encapsulated in liposome-protamine-DNA nanoparticles in a model of experimental allergy

Liposome-protamine-DNA nanoparticles (LPD) are safe, effective, and non-toxic adjuvants that induce Th1-like immune responses. We hypothesized that encapsulation of allergens into liposomes could be an appropriate option for immunotherapy. The present study evaluated the immunotherapeutic potential of a recombinant hybrid molecule (rHM) encapsulated in LPD nanoparticles in a murine model of Chenopodium album allergy. BALB/c mice were sensitized with the allergen in alum, and the immunotherapy procedure was performed by subcutaneous injections of LPD-rHM, rHM, or empty LPD at weekly intervals. Sensitized mice developed a Th2-biased immune response characterized by strong specific IgG1 and IgE production, IL-4, and the transcription factor GATA3 in spleen cell cultures. Treatment with the LPD-rHM resulted in a reduction in IgE and a marked increase in IgG2a. The LPD-rHM induced allergen-specific responses with relatively high interferon-gamma production, as well as expression of the transcription factor T-bet in stimulated splenocytes. In addition, lymphoproliferative responses were higher in the LPD-rHM-treated mice than in the other groups. Removal of the nanoparticles from the rHM resulted in a decrease in the allergen's immunogenicity. These results indicate that the rHM complexed with LPD nanoparticles has a marked suppressive effect on the allergic response and caused a shift toward a Th1 pathway.

Analysis of complex molecular systems: The impact of multivariate analysis for resolving the interactions of small molecules with biopolymers - a review

This review is focused on the impact of chemometrics for resolving data sets collected from investigations of the interactions of small molecules with biopolymers. These samples have been analyzed with various instrumental techniques, such as fluorescence, ultraviolet–visible spectroscopy, and voltammetry. The impact of two powerful and demonstrably useful multivariate methods for resolution of complex data—multivariate curve resolution–alternating least squares (MCR–ALS) and parallel factor analysis (PARAFAC)—is highlighted through analysis of applications involving the interactions of small molecules with the biopolymers, serum albumin, and deoxyribonucleic acid. The outcomes illustrated that significant information extracted by the chemometric methods was unattainable by simple, univariate data analysis. In addition, although the techniques used to collect data were confined to ultraviolet–visible spectroscopy, fluorescence spectroscopy, circular dichroism, and voltammetry, data profiles produced by other techniques may also be processed. Topics considered including binding sites and modes, cooperative and competitive small molecule binding, kinetics, and thermodynamics of ligand binding, and the folding and unfolding of biopolymers. Applications of the MCR–ALS and PARAFAC methods reviewed were primarily published between 2008 and 2013.

A rapid and label-free dual detection of Hg (II) and cysteine with the use of fluorescence switching of graphene quantum dots

A simple and rapid method of analysis for mercury ions (Hg2+) and cysteine (Cys) was developed with the use of graphene quantum dots (GQDs) as a fluorescent probe. In the presence of GQDs, Hg2+ cations are absorbed on their negatively charged surface by means of electrostatic interactions. Thus, the fluorescence (FL) of the GQDs would be significantly quenched as a result of the FL charge transfer, e.g. 92% quenching at 450 nm occurs for a 5 μmol L−1 Hg2+ solution. However, when Cys was added, a significant FL enhancement was observed (510% at 450 nm for a 8.0 μmol L−1 Cys solution), and Hg2+ combined with Cys rather than with the GQDs in an aqueous solution. This occurred because a strong metalsingle bondthiol bond formed, displacing the weak electrostatic interactions, and this resulted in an FL enhancement of the GQDs. The limits of detection (LOD) for Hg2+ and Cys were 0.439 nmol L−1 and 4.5 nmol L−1, respectively. Also, this method was used successfully to analyze Hg2+ and Cys in spiked water samples.

Efficient simulation of stochastic chemical kinetics with the Stochastic Bulirsch-Stoer extrapolation method

Background Biochemical systems with relatively low numbers of components must be simulated stochastically in order to capture their inherent noise. Although there has recently been considerable work on discrete stochastic solvers, there is still a need for numerical methods that are both fast and accurate. The Bulirsch-Stoer method is an established method for solving ordinary differential equations that possesses both of these qualities. Results In this paper, we present the Stochastic Bulirsch-Stoer method, a new numerical method for simulating discrete chemical reaction systems, inspired by its deterministic counterpart. It is able to achieve an excellent efficiency due to the fact that it is based on an approach with high deterministic order, allowing for larger stepsizes and leading to fast simulations. We compare it to the Euler τ-leap, as well as two more recent τ-leap methods, on a number of example problems, and find that as well as being very accurate, our method is the most robust, in terms of efficiency, of all the methods considered in this paper. The problems it is most suited for are those with increased populations that would be too slow to simulate using Gillespie’s stochastic simulation algorithm. For such problems, it is likely to achieve higher weak order in the moments. Conclusions The Stochastic Bulirsch-Stoer method is a novel stochastic solver that can be used for fast and accurate simulations. Crucially, compared to other similar methods, it better retains its high accuracy when the timesteps are increased. Thus the Stochastic Bulirsch-Stoer method is both computationally efficient and robust. These are key properties for any stochastic numerical method, as they must typically run many thousands of simulations.