Cocoa Butter Saturated with Supercritical Carbon Dioxide: Measurements and Modelling of Solubility, Volumetric Expansion, Density and Viscosity

International audienceThe use of supercritical carbon dioxide technology for lipid processing has recently developed at the expense of traditional processes. For designing new processes the knowledge of thermophysical properties is a prerequisite. This work is focused on the characterization of physical and thermodynamic properties of CO2-cocoa butter (CB) saturated mixture. Measurements of density, volumetric expansion, viscosity and CO2 solubility were carried out on CB-rich phase at 313 and 353 K and pressures up to 40 MPa. The experimental techniques have previously been compared and validated. Density measurements of CB and CB saturated with CO2, were performed using the vibrating tube technology at pressures ranging from 0.1 to 25 MPa. Experimental values correlated well with the modified Tait equation. CO2 solubility measurements were coupled to those of density in the same pressures ranges. At 25 MPa, the solubility of CO2 is 31.4 % and 28.7 % at 313 and 353 K. Phase behaviour was investigated using a view cell in order to follow the expansion of the CB-rich phase with the rise in pressure. Volumetric expansion up to 47 % was measured and correlated to the CO2 solubility. Phase inversion was observed at 313 K and 40 MPa. Lastly, we developed an innovative falling ball viscometer for high pressure measurements. Viscosity measurements were carried out up to 25 MPa showing a viscosity reduction up to 90 % upon CO2 dissolution. These results were correlated with two empirical models. A new model here presented, was favourably compared with the Grunberg and Nissan model. All the experimental results are consistent with the available literature data for the CB-CO2 mixture and other fat systems. This work is a new contribution to the characterization of physical and thermodynamic behaviour of fats in contact with CO2 which is necessary to design supercritical fluid processes for fats processing

Antioxidant and antibacterial effects of natural phenolic compounds on green composite materials

[EN] The aim of this study is to establish the thermal performance of a biocomposite (Arbofill kokos (R)), stabilized with different natural phenolic additives, to check the antioxidant capacity of the resulting compounds. Different phenolic compounds (thymol, carvacrol, a-tocopherol, and tannic acid) were used as biobased additives and the concentrations ranged between 0.5 wt% and 2 wt%. The results obtained were compared with formulations containing a typical industrial petroleum-based antioxidant agent (octadecyl-3-(3,5-di-tert-butyl-4-hydroxyphenyl) propionate). Differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA) were used to characterize the antioxidant performance of the selected natural additives. The antimicrobial effect of these natural phenolic compounds was also studied by analyzing the growth of bacterial colonies. The comparison between the natural phenolic compounds and the petroleum-based antioxidant compound showed good antioxidant action for natural phenolic compounds; in all the mixtures of biocomposite and antioxidant agent the oxidation onset temperature (OOT) increased in a remarkable way, but the highest stabilization effect was achieved with a-tocopherol with provides a % increase on OOT of about 45%. With regard to antibacterial activity of the different natural phenolic compounds, thymol, and carvacrol showed interesting antibacterial properties against Staphylococcus aureus. POLYM. COMPOS., 2012. (c) 2012 Society of Plastics EngineersThis work is part of the project IPT-310000-2010-037, "ECOTEXCOMP: Research and development of textile structures useful as reinforcement of composite materials with marked ecological character" funded by the "Ministerio de Ciencia e Innovacion," with an aid of 189540.20 euros, within the "Plan Nacional de Investigacion Cientifica, Desarrollo e InnovacionTecnologica 2008-2011" and funded by the European Union through FEDER funds, Technology Fund 2007-2013, Operational Programme on R+D+i for and on behalf of the companies." Also, Generalitat Valenciana Ref: ACOMP/2012/087 is acknowledged for financial support. J.M. Espana thanks to the Universitat Politecnica de Valencia (UPV) its financial support through an FPI-UPV grant.España Giner, JM.; Fages, E.; Moriana Torró, R.; Boronat Vitoria, T.; Balart Gimeno, RA. (2012). Antioxidant and antibacterial effects of natural phenolic compounds on green composite materials. Polymer Composites. 33(8):1288-1294. https://doi.org/10.1002/pc.22254S1288129433

Development of Characterization Techniques of Thermodynamic and Physical Properties Applied to the CO2-DMSO Mixture

International audienceThis work is focused on the development of new characterization techniques of physical and thermodynamic properties. These techniques have been validated using the binary system DMSO-CO2 for which several studies of characterization have been well documented. We focused on the DMSO-rich phase and we carried out measurements of volumetric expansion, density, viscosity and CO2 solubility at 298.15, 308.15 and 313.15 K and pressures up to 9 MPa. The experimental procedures were compared and validated with the available literature data on SC-CO2-DMSO system. We made density and CO2 solubility measurements, using respectively the vibrating tube technology and two static analytical methods. Lastly, we developed an innovative falling body viscosimeter for high pressure measurements. All the measurements made are in good agreement with the already published data in spite of very different experimental techniques. This work is a contribution to the understanding of the DMSO-CO2 binary as it implements new viscosity data. Moreover, it opens new perspectives about the determination of the properties of other systems such as polymers-CO2 and fats-CO2, which are essential for supercritical process design such as extraction, crystallization, chromatography and synthesis reaction

The use of wet-laid techniques to obtain flax nonwovens with different thermoplastic binding fibers for technical insulation applications

[EN] In this work, the wet-laid technique has been used to obtain flax nonwovens thermally bonded with different contents of polyvinyl alcohol (PVA) and bicomponent polyamide 6/copolyamide (PA6/CoPA) fibers in the 10-30 wt.% range. Scanning electron microscopy has been used to evaluate the formation of interlock points through melted polymer and flax fibers. Volume porosity has been estimated through determination of thickness and surface mass. Tensile strength and elongation at break have been determined on longitudinal (preferential) and transversal directions to evaluate anisotropy. The sound absorption properties of stacked sheets of flax: PVA and flax: PA6/CoPA nonwovens have been evaluated. In addition, the thermal insulating properties of individual nonwovens have been obtained. Mechanical characterization shows slight anisotropy. The absorption coefficient is interesting in the medium frequencies range, and relatively low thermal conductivity and thermal resistance values are obtained with these nonwovens (in the 0.020-0.025Wm(-1) K-1 range for flax: PVA nonwovens and in the 0.09-0.10Wm(-1) K-1 range for flax: PA6/CoPA nonwovens). By taking into account these features, these nonwoven substrates could find interesting applications as sound absorbers and/or thermal insulation materials in technical applications.This work is part of the project IPT-310000-2010-037, "ECOTEXCOMP: Research and development of textile structures useful as reinforcement of composite materials with marked ecological character", and was supported by the "Ministerio de Ciencia e Innovacion", with a grant of (sic)189,540.20, within the Plan Nacional de Investigacion Cientifica, Desarrollo e Innovacion Tecnologica 2008-2011 and funded by the European Union through FEDER funds, Technology Fund 2007-2013 and Operational Programme on R + D + i for and on behalf of the companies. The project is also known as "WET-TEX: Implementacion de la tecnologia wet-laid en el desarrollo de nuevos textiles medico-sanitario" with expedient number IMIDIC/2010/137 (total grant of (sic)284,400) and the project "WET-TEX II: Implementacion de la tecnologia wet-laid en la investigacion y desarrollo de paneles para aplicaciones tecnicas a partir de residuos procedentes de la industria textil" with expedient number IMDEEA/2011/167 (total grant of (sic)255,000) funded by IMPIVA and cofunded (80%) by the European Union through FEDER funds, Valencian Community Operational 2007-2012.Fages, E.; Cano, MA.; Gironés, S.; Boronat Vitoria, T.; Fenollar Gimeno, OÁ.; Balart Gimeno, RA. (2013). The use of wet-laid techniques to obtain flax nonwovens with different thermoplastic binding fibers for technical insulation applications. Textile Research Journal. 83(4):426-437. https://doi.org/10.1177/0040517512454183S42643783

Therapeutic potential of HMGB1-targeting agents in sepsis

Sepsis refers to a systemic inflammatory response syndrome resulting from a microbial infection. The inflammatory response is partly mediated by innate immune cells (such as macrophages, monocytes and neutrophils), which not only ingest and eliminate invading pathogens but also initiate an inflammatory response upon recognition of pathogen-associated molecular patterns (PAMPs). The prevailing theories of sepsis as a dysregulated inflammatory response, as manifested by excessive release of inflammatory mediators such as tumour necrosis factor and high-mobility group box 1 protein (HMGB1), are supported by extensive studies employing animal models of sepsis. Here we review emerging evidence that support extracellular HMGB1 as a late mediator of experimental sepsis, and discuss the therapeutic potential of several HMGB1-targeting agents (including neutralising antibodies and steroid-like tanshinones) in experimental sepsis

Efficient Parallel Statistical Model Checking of Biochemical Networks

We consider the problem of verifying stochastic models of biochemical networks against behavioral properties expressed in temporal logic terms. Exact probabilistic verification approaches such as, for example, CSL/PCTL model checking, are undermined by a huge computational demand which rule them out for most real case studies. Less demanding approaches, such as statistical model checking, estimate the likelihood that a property is satisfied by sampling executions out of the stochastic model. We propose a methodology for efficiently estimating the likelihood that a LTL property P holds of a stochastic model of a biochemical network. As with other statistical verification techniques, the methodology we propose uses a stochastic simulation algorithm for generating execution samples, however there are three key aspects that improve the efficiency: first, the sample generation is driven by on-the-fly verification of P which results in optimal overall simulation time. Second, the confidence interval estimation for the probability of P to hold is based on an efficient variant of the Wilson method which ensures a faster convergence. Third, the whole methodology is designed according to a parallel fashion and a prototype software tool has been implemented that performs the sampling/verification process in parallel over an HPC architecture

Probably Approximately Correct Learning of Regulatory Networks from Time-Series Data

International audienceAutomating the process of model building from experimental data is a very desirable goal to palliate the lack of modellers for many applications. However, despite the spectacular progress of machine learning techniques in data analytics, classification, clustering and prediction making, learning dynamical models from data time-series is still challenging. In this paper we investigate the use of the Probably Approximately Correct (PAC) learning framework of Leslie Valiant as a method for the automated discovery of influence models of biochemical processes from Boolean and stochastic traces. We show that Thomas' Boolean influence systems can be naturally represented by k-CNF formulae, and learned from time-series data with a number of Boolean activation samples per species quasi-linear in the precision of the learned model, and that positive Boolean influence systems can be represented by monotone DNF formulae and learned actively with both activation samples and oracle calls. We consider Boolean traces and Boolean abstractions of stochastic simulation traces, and study the space-time tradeoff there is between the diversity of initial states and the length of the time horizon, and its impact on the error bounds provided by the PAC learning algorithms. We evaluate the performance of this approach on a model of T-lymphocyte differentiation, with and without prior knowledge, and discuss its merits as well as its limitations with respect to realistic experiments