Optimal prediction of PKS: RSO modified alkyd resin polycondensation process using discrete-delayed observations, ANN and RSM-GA techniques / Chigozie F. Uzoh in JOURNAL OF COATINGS TECHNOLOGY AND RESEARCH, Vol. 14, N° 3 (05/2017)  

[article]  inJOURNAL OF COATINGS TECHNOLOGY AND RESEARCH > Vol. 14, N° 3 (05/2017) . - p. 607-620 Titre : Optimal prediction of PKS: RSO modified alkyd resin polycondensation process using discrete-delayed observations, ANN and RSM-GA techniques Type de document : texte imprimé Auteurs : Chigozie F. Uzoh, Auteur ; Okechukwu D. Onukwuli, Auteur Année de publication : 2017 Article en page(s) : p. 607-620 Note générale : Bibliogr. Langues : Américain (ame) Catégories : Algorithmes génétiques Analyse multivariée Plan d'expérience Polyalkydes Polycondensation Réseaux neuronaux (informatique) Surfaces de réponse (statistique) Index. décimale : 667.9 Revêtements et enduits Résumé : Alkyd resins are widely used in the paint industry and although they have a long history about 70–100 years, today the developments in alkyds are still welcome and innovations are still needed. Artificial neural network (ANN) and response surface methodology based on a 25−1 fractional factorial design were used as tools for simulation and optimization of the polycondensation process for autooxidative drying alkyd resin from palm kernel stearin: rubber seed oil blend of 70:30 ratio. A feed forward neural network model with Levenberg–Marquardt back propagation training algorithm was adapted to predict the responses (conversion Y1, viscosity Y2, and molecular weight average Y3). The studied input variables were reaction time, temperature, catalyst concentration, oil ratio, and stirring rate. The performance of the RSM and ANN model showed adequate prediction of the responses in terms of the process factors, with MRPD of ±4.47% (Y1), ±2.08% (Y2), ±8.92% (Y3) and ±6.50% (Y1), ±3.31% (Y2), ±10.20% (Y3), respectively. The sensitivity analysis showed that while reaction time is the most effective process parameter, the interaction of the five process variables produced the most significant effect on the studied responses with the overall minimum MSE of 0.079. The optimization task performed using a genetic algorithm linked to the RSM model gave a viable, nondominated optimal response and optimum operating conditions regarding the route to high-quality resin at reduced material and operational costs. Overall, coupled RSM-GA was found to be a better tool for modeling and optimization of the alkyd resin production. Note de contenu : - MATERIALS AND METHODS : Materials - Synthesis of alkyd resin from modified palm kernel stearin - System prediction via RSM - Sensitivity analysis and system prediction via artificial neural network (ANN) model - RESULTS AND DISCUSSION : Predictive model for system response aproximation via RSM - Reaction prediction via ANN - Optimization by coupled RSM-GA technique DOI : 10.1007/s11998-016-9881-6 En ligne : https://link.springer.com/content/pdf/10.1007%2Fs11998-016-9881-6.pdf Format de la ressource électronique : Pdf Permalink : https://e-campus.itech.fr/pmb/opac_css/index.php?lvl=notice_display&id=28569 [article]

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Synthesis of rubber seed oil waterborne alkyd resin from glucitol / Chigozie F. Uzoh in JOURNAL OF COATINGS TECHNOLOGY AND RESEARCH, Vol. 16, N° 6 (11/2019)  

[article]  inJOURNAL OF COATINGS TECHNOLOGY AND RESEARCH > Vol. 16, N° 6 (11/2019) . - p. 1727-1735 Titre : Synthesis of rubber seed oil waterborne alkyd resin from glucitol Type de document : texte imprimé Auteurs : Chigozie F. Uzoh, Auteur ; M. C. OBele, Auteur ; U. M. Umennabuife, Auteur ; Okechukwu D. Onukwuli, Auteur Année de publication : 2019 Article en page(s) : p. 1727-1735 Note générale : Bibliogr. Langues : Américain (ame) Catégories : Huile de graine de caoutchouc Polyalkydes Polymères -- Propriétés mécaniques Polymères -- Synthèse Polymérisation Résistance chimique Revêtements organiques Solubilité Sorbitol Index. décimale : 667.9 Revêtements et enduits Résumé : Solubility properties of alkyd resins from phthalic and maleic anhydrides, glucitol and rubber seed oil (RSO) as raw materials were examined. Four types of glucitol-based medium oil length alkyd resins (ALKYD A–D, two for each acid anhydride) samples were formulated with phthalic anhydride, maleic anhydride, glucitol aqueous solution, and RSO. The physical, chemical, and film characteristics of the glucitol-modified alkyd resins were examined, and the result was compared with the standard alkyd resins and soybean-based alkyd resin. It was observed that all samples were soluble in xylene and butoxyethanol but not water. All of the samples have varying solubilities in water/xylene ratio (%) and complete solubility in water/butoxyethanol (%) ratio of 40:60, 50:50, and 60:40, respectively. ALKYD A is soluble in all solvents except water where it was sparingly soluble at room temperature. The spectral analysis revealed the polyesterification reaction and hydrogen-bonding integrity of the alkyd resins and the polybasic acid. The physical and chemical properties and the performance indices of the glucitol-based alkyd resin results show that they possess acceptable drying properties, chemical resistance, and mechanical properties. Performance of ALKYD A and C gave nearly the same result as the standard alkyd resins and soybean-based alkyd resin. It has potential as a choice waterborne binder for alkyd resin paint and can help in reducing VOC. Note de contenu : - MATERIALS AND METHODS - RESULTS AND DISCUSSION : Features of crude, neutralized, and dehydrated RSO - Chemical formation of sorbitol-based alkyd resin and their solubility characteristics - Features of the lkyd resin samples relative to varnishes performance - The film characteristics of glucitol-based waterborne resins DOI : 10.1007/s11998-019-00235-0 En ligne : https://link.springer.com/content/pdf/10.1007%2Fs11998-019-00235-0.pdf Format de la ressource électronique : Pdf Permalink : https://e-campus.itech.fr/pmb/opac_css/index.php?lvl=notice_display&id=33426 [article]

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