Evaluation of the effect of processing on cocoa polyphenols: antiradical activity,anthocyanins and procyanidins profiling from raw beans to chocolate

The content and composition of anthocyanins and procyanidins in fermented cocoa beans (from different geographic origins: Ecuador, Cameroon, Ivory Coast, Ghana and Nigeria), roasted nibs, cocoa mass and chocolate were determined, beside the determination of the total antiradical capacity. Concerning geographic origin, cocoa beans and processed products from Ecuador showed the highest levels of anthocyanins, followed by Nigeria and Cameroon. Generally, as cocoa beans were further processed, the levels of anthocyanins and flavan‐3‐ols decreased. The largest observed losses of phenolics occurred during roasting. A progressive decreasing trend in polyphenol concentration was observed in the other processed samples as well. Despite the original content of polyphenols in raw cocoa beans, technological processes imply a significant impact on cocoa quality, confirming the need of specific optimisation to obtain high value chocolate.     

Behaviour of mesogenic side group polyacrylates in dilute and semidilute regime

The solution behaviour of a new mesogenic side group polyacrylate in tetrahydrofuran and toluene has been investigated by static and dynamic light scattering. In the dilute regime the polymer behaves as typical polydisperse linear chains in good solvent and the dynamics is dominated by a single fast mode. Cluster formation was detected starting at a concentration around 50 g l⁻¹. It seems to be independent of the solvent as well as of polymer molecular weight. In the semidilute regime, the behaviour of the reduced osmotic modulus leads to the conclusion that repulsion between the chains is stronger than in linear macromolecules. The appearance of larger clusters was revealed above a characteristic concentration and is slightly dependent on the polyacrylate molecular weight. The dynamics was generally characterised by a fast mode related to the cooperative diffusion and by a slow mode associated with large clusters. The existence of a network of multiconnected clusters is envisaged with increasing solution concentration.     

CO2 process intensification of algae oil extraction to biodiesel

Algae-to-biodiesel processes are hindered by high costs and low energy return on investment.^1,2. Herein, three foci in research improve algae-to-biodiesel processes by: (1) reducing high installation and energy costs in the CO₂ sequestration, cultivation, and harvesting stages; (2) improving oil extraction and biodiesel generation; and (3) increasing utilization of the proteins in lipid-extracted biomass (e.g., for animal feed), as well as the omega-3 fatty acids for nutraceuticals and food supplements. A process is introduced that uses carbon dioxide to aid in all three of these foci. CO₂ is used first in the form of microbubbles to lyse algae cell walls, releasing triglyceride oils. CO₂ also aids with transesterification of these triglycerides using methanol. At low temperatures (353.15–368.15 K) and intermediate pressures (5–10 MMPa), carbon dioxide causes methanol to dissolve partially in the triglyceride phase and triglyceride to dissolve partially in the methanol phase, increasing the transesterification reaction rate. Due to the nondestructive nature of these processes, other metabolites can also be harvested providing improvements in both mass and economic efficiency with an overall sharp reduction in the modeled price of biodiesel.     

A goal-based framework for contextual requirements modeling and analysis

Requirements engineering (RE) research often ignores or presumes a uniform nature of the context in which the system operates. This assumption is no longer valid in emerging computing paradigms, such as ambient, pervasive and ubiquitous computing, where it is essential to monitor and adapt to an inherently varying context. Besides influencing the software, context may influence stakeholders’ goals and their choices to meet them. In this paper, we propose a goal-oriented RE modeling and reasoning framework for systems operating in varying contexts. We introduce contextual goal models to relate goals and contexts; context analysis to refine contexts and identify ways to verify them; reasoning techniques to derive requirements reflecting the context and users priorities at runtime; and finally, design time reasoning techniques to derive requirements for a system to be developed at minimum cost and valid in all considered contexts. We illustrate and evaluate our approach through a case study about a museum-guide mobile information system.     

CAFES: A framework for intrachip application modeling and communication architecture design

This paper describes CAFES, an extensible, open-source framework supporting several tasks related to high-level modeling and design of applications employing complex intrachip communication infrastructures. CAFES comprises several built-in models, including application, communication architecture, energy consumption and timing models. It also includes a set of generic and specific algorithms and additional supporting tools, which jointly with the cited models allow the designer to describe and evaluate applications requirements and constraints on specified communication architectures. Several examples of the use of CAFES underline the usefulness of the framework. Some of these are approached in this paper: (i) a realistic application captured at high-level that has its computation time estimated after mapping at the clock cycle level; (ii) a multi-application system that is automatically mapped to a large intrachip network with related tasks occupying contiguous areas in the chip layout; (iii) a set of mapping algorithms explored to define trade-offs between run time and energy savings for small to large intrachip communication architectures.     

Residual stress-affected diffusion during plasma nitriding of tool steels

Plasma nitriding of tool materials is common practice to improve the wear resistance and lifetime of tools. Machining-induced compressive residual stresses in shallow layers of some tenths of microns are observed accompanied by other characteristic properties of machined surfaces in these high-strength materials. After plasma nitriding of M2 high-speed steel, previously induced compressive residual stresses remain stable and the depth of diffusion layers decreases with increasing compressive residual stresses. This article reports investigations of plasma nitrided samples with different levels of residual stresses induced prior to the nitriding process. For comparison, experiments with bending load stresses during plasma nitriding have also been carried out. The plasma nitriding treatment was performed at constant temperature of 500 °C with a gas mixture of 5 vol pct N₂ in hydrogen. Nitriding time was varied from 30 to 120 minutes. All samples were characterized before and after plasma nitriding concerning microstructure, roughness, microhardness, chemical composition, and residual stress states. Experimental results are compared with analytical calculations on (residual) stress effects in diffusion and show a clear effect of residual and load stresses in the diffusion of nitrogen in a high-strength M2 tool steel.     

Thermodiffusion‐Assisted Pyroelectrics—Enabling Rapid and Stable Heat and Radiation Sensing

Sensors for monitoring temperature, heat flux, and thermal radiation are essential for applications such as electronic skin. While pyroelectric and thermoelectric effects are suitable candidates as functional elements in such devices, both concepts show individual drawbacks in terms of zero equilibrium signals for pyroelectric materials and small or slow response of thermoelectric materials. Here, these drawbacks are overcome by introducing the concept of thermodiffusion‐assisted pyroelectrics, which combines and enhances the performance of pyroelectric and ionic thermoelectric materials. The presented integrated concept provides both rapid initial response upon heating and stable synergistically enhanced signals upon prolonged exposure to heat stimuli. Likewise, incorporation of plasmonic metasurfaces enables the concept to provide both rapid and stable signals for radiation‐induced heating. The performance of the concept and its working mechanism can be explained by ion–electron interactions at the interface between the pyroelectric and ionic thermoelectric materials.     

Biodiesel production via transesterification: Process safety insights from kinetic modeling

Biodiesel is an alternative non-petroleum based fuel, consisting of alkyl esters obtained either by esterification of free fatty acids with low molecular weight alcohols, or by transesterification of triglycerides. The realization of a biodiesel unit can pose several safety issues and inherent safety application opportunities as the production involves the transport, use and storage of hazardous materials, either flammable or toxic. In the experimental phase, we studied, at laboratory scale, different alkali catalysts and the relevant reaction parameters, considering inherent safety opportunities. An accurate kinetic model of the transesterification process was developed and validated, allowing to provide possible minimization and simplification plant options.     

The orbital minimization method for electronic structure calculations with finite-range atomic basis sets

The implementation of the orbital minimization method (OMM) for solving the self-consistent Kohn–Sham (KS) problem for electronic structure calculations in a basis of non-orthogonal numerical atomic orbitals of finite-range is reported. We explore the possibilities for using the OMM as an exact cubic-scaling solver for the KS problem, and compare its performance with that of explicit diagonalization in realistic systems. We analyze the efficiency of the method depending on the choice of line search algorithm and on two free parameters, the scale of the kinetic energy preconditioning and the eigenspectrum shift. The results of several timing tests are then discussed, showing that the OMM can achieve a noticeable speedup with respect to diagonalization even for minimal basis sets for which the number of occupied eigenstates represents a significant fraction of the total basis size (>15%). We investigate the hard and soft parallel scaling of the method on multiple cores, finding a performance equal to or better than diagonalization depending on the details of the OMM implementation. Finally, we discuss the possibility of making use of the natural sparsity of the operator matrices for this type of basis, leading to a method that scales linearly with basis size.