125 research outputs found

    Modeling of Free Radical Styrene/Divinylbenzene Copolymerization with the Numerical Fractionation Technique

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    The modeling approach called “numerical fractionation” has been incorporated into a PREDICI model to simulate crosslinking copolymerization. To take into account inhomogeneities of the considered copolymerization, the kinetic parameters of the model are proposed to be different for each generation of the numerical fractionation. Using this approach the chain-length dependence of termination has been incorporated into the model so that even the method of moments could be applied to study crosslinking copolymerization. The styrene/m-divinylbenzene crosslinking copolymerization at low content of crosslinker has been simulated. The chain-length dependence of termination has been found to accelerate the gel point in monovinyl/divinyl copolymerization and must be taken into account for correct description of the gel points

    Monitoring of chicken meat freshness by means of a colorimetric sensor array

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    A new optoelectronic nose to monitor chicken meat ageing has been developed. It is based on 16 pigments prepared by the incorporation of different dyes (pH indicators, Lewis acids, hydrogenbonding derivatives, selective probes and natural dyes) into inorganic materials (UVM-7, silica and alumina). The colour changes of the sensor array were characteristic of chicken ageing in a modi¿ed packaging atmosphere (30% CO2¿70% N2). The chromogenic array data were processed with qualitative (PCA) and quantitative (PLS) tools. The PCA statistical analysis showed a high degree of dispersion, with nine dimensions required to explain 95% of variance. Despite this high dimensionality, a tridimensional representation of the three principal components was able to differentiate ageing with 2-day intervals. Moreover, the PLS statistical analysis allows the creation of a model to correlate the chromogenic data with chicken meat ageing. The model offers a PLS prediction model for ageing with values of 0.9937, 0.0389 and 0.994 for the slope, the intercept and the regression coef¿cient, respectively, and is in agreement with the perfect ¿t between the predicted and measured values observed. The results suggest the feasibility of this system to help develop optoelectronic noses that monitor food freshness.Salinas Soler, Y.; Ros-Lis, JV.; Vivancos, J.; Martínez Mañez, R.; Marcos Martínez, MD.; Aucejo Romero, S.; Herranz, N.... (2012). Monitoring of chicken meat freshness by means of a colorimetric sensor array. Analyst. 137(16):3635-3643. doi:10.1039/C2AN35211GS3635364313716Anang, D. M., Rusul, G., Ling, F. H., & Bhat, R. (2010). Inhibitory effects of lactic acid and lauricidin on spoilage organisms of chicken breast during storage at chilled temperature. International Journal of Food Microbiology, 144(1), 152-159. doi:10.1016/j.ijfoodmicro.2010.09.014HINTON, A., & INGRAM, K. D. (2005). 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Food Chemistry, 121(4), 1274-1282. doi:10.1016/j.foodchem.2010.01.044Bota, G. M., & Harrington, P. B. (2006). Direct detection of trimethylamine in meat food products using ion mobility spectrometry. Talanta, 68(3), 629-635. doi:10.1016/j.talanta.2005.05.001Grau, R., Sánchez, A. J., Girón, J., Iborra, E., Fuentes, A., & Barat, J. M. (2011). Nondestructive assessment of freshness in packaged sliced chicken breasts using SW-NIR spectroscopy. Food Research International, 44(1), 331-337. doi:10.1016/j.foodres.2010.10.011Sahar, A., Boubellouta, T., & Dufour, É. (2011). Synchronous front-face fluorescence spectroscopy as a promising tool for the rapid determination of spoilage bacteria on chicken breast fillet. Food Research International, 44(1), 471-480. doi:10.1016/j.foodres.2010.09.006Lin, M., Al-Holy, M., Mousavi-Hesary, M., Al-Qadiri, H., Cavinato, A. G., & Rasco, B. A. (2004). 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Coordination Chemistry Reviews, 250(11-12), 1451-1470. doi:10.1016/j.ccr.2006.01.006Chen, X., Zhou, Y., Peng, X., & Yoon, J. (2010). Fluorescent and colorimetric probes for detection of thiols. Chemical Society Reviews, 39(6), 2120. doi:10.1039/b925092aMohr, G. J. (2006). New chromogenic and fluorogenic reagents and sensors for neutral and ionic analytes based on covalent bond formation–a review of recent developments. Analytical and Bioanalytical Chemistry, 386(5), 1201-1214. doi:10.1007/s00216-006-0647-3Kerry, J. P., O’Grady, M. N., & Hogan, S. A. (2006). Past, current and potential utilisation of active and intelligent packaging systems for meat and muscle-based products: A review. Meat Science, 74(1), 113-130. doi:10.1016/j.meatsci.2006.04.024Rakow, N. A., & Suslick, K. S. (2000). A colorimetric sensor array for odour visualization. Nature, 406(6797), 710-713. doi:10.1038/35021028Lim, S. H., Kemling, J. W., Feng, L., & Suslick, K. S. (2009). A colorimetric sensor array of porous pigments. The Analyst, 134(12), 2453. doi:10.1039/b916571aPalacios, M. A., Nishiyabu, R., Marquez, M., & Anzenbacher, P. (2007). Supramolecular Chemistry Approach to the Design of a High-Resolution Sensor Array for Multianion Detection in Water. Journal of the American Chemical Society, 129(24), 7538-7544. doi:10.1021/ja0704784Wu, Y., Na, N., Zhang, S., Wang, X., Liu, D., & Zhang, X. (2009). Discrimination and Identification of Flavors with Catalytic Nanomaterial-Based Optical Chemosensor Array. Analytical Chemistry, 81(3), 961-966. doi:10.1021/ac801733kJanzen, M. C., Ponder, J. B., Bailey, D. P., Ingison, C. K., & Suslick, K. S. (2006). Colorimetric Sensor Arrays for Volatile Organic Compounds. Analytical Chemistry, 78(11), 3591-3600. doi:10.1021/ac052111sSuslick, B. A., Feng, L., & Suslick, K. S. (2010). Discrimination of Complex Mixtures by a Colorimetric Sensor Array: Coffee Aromas. Analytical Chemistry, 82(5), 2067-2073. doi:10.1021/ac902823wHuang, X., Xin, J., & Zhao, J. (2011). A novel technique for rapid evaluation of fish freshness using colorimetric sensor array. Journal of Food Engineering, 105(4), 632-637. doi:10.1016/j.jfoodeng.2011.03.034Anzenbacher, Jr., P., Lubal, P., Buček, P., Palacios, M. A., & Kozelkova, M. E. (2010). A practical approach to optical cross-reactive sensor arrays. Chemical Society Reviews, 39(10), 3954. doi:10.1039/b926220mRos-Lis, J. V., García, B., Jiménez, D., Martínez-Máñez, R., Sancenón, F., Soto, J., … Valldecabres, M. C. (2004). Squaraines as Fluoro−Chromogenic Probes for Thiol-Containing Compounds and Their Application to the Detection of Biorelevant Thiols. Journal of the American Chemical Society, 126(13), 4064-4065. doi:10.1021/ja031987iRos-Lis, J. V., Martínez-Máñez, R., Rurack, K., Sancenón, F., Soto, J., & Spieles, M. (2004). Highly Selective Chromogenic Signaling of Hg2+in Aqueous Media at Nanomolar Levels Employing a Squaraine-Based Reporter. Inorganic Chemistry, 43(17), 5183-5185. doi:10.1021/ic049422qRos-Lis, J. V., Marcos, M. D., Mártinez-Máñez, R., Rurack, K., & Soto, J. (2005). A Regenerative Chemodosimeter Based on Metal-Induced Dye Formation for the Highly Selective and Sensitive Optical Determination of Hg2+ Ions. Angewandte Chemie International Edition, 44(28), 4405-4407. doi:10.1002/anie.200500583Ros-Lis, J. V., Martínez-Máñez, R., & Soto, J. (2005). Colorimetric Signaling of Large Aromatic Hydrocarbons via the Enhancement of Aggregation Processes. Organic Letters, 7(12), 2337-2339. doi:10.1021/ol050564dCliment, E., Marcos, M. D., Martínez-Máñez, R., Sancenón, F., Soto, J., Rurack, K., & Amorós, P. (2009). The Determination of Methylmercury in Real Samples Using Organically Capped Mesoporous Inorganic Materials Capable of Signal Amplification. 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    Living Radical Polymerization by the RAFT Process - A Second Update

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    Headspace Analysis: Static ☆

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    Scope for accessing the chain length dependence of the termination rate coefficient for disparate length radicals in acrylate free radical polymerization

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    A method that utilizes reversible addition fragmentation chain transfer (RAFT) chemistry is evaluated on a theoretical basis to deduce the termination rate coefficient for disparate length radicals kts,l in acrylate free radical polymerization, where sand / represent the arbitrary yet disparate chain lengths from either a "short" or "long" RAFT distribution. The method is based on a previously developed method for elucidation of kts,l for the model monomer system styrene. The method was expanded to account for intramolecular chain transfer (i.e., the formation of mid-chain radicals via backbiting) and the free radical polymerization kinetic parameters of methyl acrylate. Simulations show that the method's predictive capability is sensitive to the polymerization rate's dependence on monomer concentration, i.e., the virtual monomer reaction order, which varies with the termination rate coefficient's value and chain length dependence. However, attaining the virtual monomer reaction order is a facile process and once known the method developed here that accounts for mid-chain radicals and virtual monomer reaction orders other than one seems robust enough to elucidate the chain length dependence of kts,l' for the more complex acrylate free radical polymerization. Copyright © 2007 WILEY-VCH Verlag GmbH & Co. KGaA
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