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Villeurbanne, France

Jarne C.,MINES ParisTech | Jarne C.,CSIC - Institute of Carbochemistry | Rivollet F.,Processium | Richon D.,MINES ParisTech
Journal of Chemical and Engineering Data | Year: 2011

Pressure, density, and temperature (PρT) data are presented for two compositions (z1 = 0.2227 and 0.2691) of the hydrogen sulfide (1) + propane (2) binary mixture at three temperatures in vapor and liquid states from a vacuum up to 40 MPa. Experimental work was achieved thanks to a vibrating-tube densimeter using the forced path mechanical calibration model (FPMC). The Lee-Kesler-Plöcker model was chosen with one temperature-dependent binary interaction parameter to represent our experimental data. Observed deviations on liquid and vapor densities (between experimental and calculated data) are less than 2 % on both liquid and vapor phases except for data close to the critical point. © 2010 American Chemical Society. Source


News Article
Site: http://www.greencarcongress.com/

« Audi refreshes A3 with new engines, driver assistance systems, virtual cockpit | Main | U-Michigan, IBM collaborate on data-centric high performance computing system » Global Bioenergies has purified its bio‐isobutene to 99.77%, a polymer‐grade level. Global Bioenergies routinely produces isobutene batches using its industrial pilot located in Pomacle‐Bazancourt, eastern France. Up to now, 95% purity was reached, a level sufficient for several applications, such as fuels and paints. For the first time, with the help of Processium, a chemical engineering company headquartered in Lyon, France, Global Bioenergies was able to purify batches to a much higher level, reaching 99.77%, the remaining 0.23% being mostly composed of CO , an inert gas known to be neutral in most chemical reactions. Several applications in the polymers business (rubbers, plastics...) require high‐purity isobutene, and 99.77% corresponds to the polymer‐grade standard. We expect that our high‐purity bio‐isobutene will meet the specifications of the industrial leaders involved in converting isobutene into polymers, and that they will be able to use their existing polymerization processes, designed for fossil feedstocks, without any significant change. The higher the purity, the higher the value: targeting higher‐value markets is especially important in the present oil and gas environment. Global Bioenergies is developing processes to convert renewable resources into hydrocarbons through fermentation. The company initially focused its efforts on the production of isobutene, one of the most important petrochemical building blocks that can be converted into fuels, plastics, organic glass and elastomers.


Zhang F.,MINES ParisTech | Theveneau P.,MINES ParisTech | El Ahmar E.,MINES ParisTech | Canet X.,Processium | And 2 more authors.
Fluid Phase Equilibria | Year: 2016

An improved apparatus based on the static-analytic method for reliable vapor-liquid equilibrium (VLE) data measurement is presented in this work. It has been applied to investigate systems containing organic sulfur compounds. New sampling mechanisms were combined with ROLSI™ capillary samplers to achieve on-line sampling for both vapor and liquid phases in a pressure range between 0.1 and 10 bar. Phase samples were directly sent to a gas chromatograph for composition analysis. The equipment was tested against other commonly used experimental methods in this pressure range on the (. n-butane + ethanol) and (diethyl sulfide + ethanol) systems. The obtained data were correlated by Wilson model and compared with existing data. The improved apparatus has shown comparable performances to existing methods, while showing some advantages such as complete PTxy phase measurements and less product consumption. After the validation step, additional VLE data for binary systems of interest, (diethyl sulfide + n-butane) and (1-pentanethiol + 1-pentanol), were reported and modeled in this work. © 2015 Elsevier B.V. Source


Barreau A.,French Institute of Petroleum | Brunella I.,French Institute of Petroleum | De Hemptinne J.-C.,French Institute of Petroleum | Coupard V.,French Institute of Petroleum | And 2 more authors.
Industrial and Engineering Chemistry Research | Year: 2010

A good understanding and prediction of the phase equilibrium of the fatty acid methyl ester (FAME) + glycerol + methanol ternary system is needed to design and optimize the separation unit of the biodiesel production process. In this work, new experimental vapor-liquid-liquid data on the ternary system have been measured at temperatures between 333.15 and 473.15 K. In addition, new data have been gathered on the methanol + glycerol [vapor-liquid equilibrium (VLE)] and methanol + methyl oleate (VLE and liquid-liquid equilibrium) binary systems. A group contribution method combined with a statistical associating fluid theory equation of state (GC-PPC-SAFT) proposed earlier by our group (Tamouza, S. Passarello, J.-P. Tobaly, P. and de Hemptinne, J.-C. Group contribution method with SAFT EOS applied to vapor liquid equilibria of various hydrocarbons series. Fluid Phase Equilib. 2004, 222-223, 67-76) and recently extended to predict VLE of heavy esters and their mixtures (Nguyen Huynh, D. Falaix, A. Passarello, J.-P. Tobaly, P. and de Hemptinne, J.-C. Predicting VLE of heavy esters and their mixtures using GC-SAFT. Fluid Phase Equilib. 2008, 264, 184-200) is here applied to model vapor liquid-liquid equilibria of methanol + glycerol + methyl oleate. The SAFT parameters for the glycerol pure component have been regressed using two association schemes (4C and 3X2B). The dispersive binary interaction parameters kij have been regressed on the binary systems. The group contribution scheme was used for predicting the ester properties. © 2010 American Chemical Society. Source


Oprisiu I.,CNRS Strasbourg Institute of Chemistry | Marcou G.,CNRS Strasbourg Institute of Chemistry | Horvath D.,CNRS Strasbourg Institute of Chemistry | Brunel D.B.,Processium | And 2 more authors.
Thermochimica Acta | Year: 2013

Quantitative structure-property models to predict the normal boiling point (Tb) of organic compounds were developed using non-linear ASNNs (associative neural networks) as well as multiple linear regression-ISIDA-MLR and SQS (stochastic QSAR sampler). Models were built on a diverse set of 2098 organic compounds with Tb varying in the range of 185-491 K. In ISIDA-MLR and ASNN calculations, fragment descriptors were used, whereas fragment, FPTs (fuzzy pharmacophore triplets), and ChemAxon descriptors were employed in SQS models. Prediction quality of the models has been assessed in 5-fold cross validation. Obtained models were implemented in the on-line ISIDA predictor at http://infochim.u-strasbg.fr/webserv/VSEngine.html. © 2012 Elsevier B.V. Source

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