No abstract

In this research, the ability of multilayer perceptron neural networks to estimate vapour-liquid equilibrium data have been studied. Four typical binary refrigerant systems containing R227ea have been investigated in a large range of temperatures and pressures. The systems are categorised into four groups, based on their different deviations from the Raoult's law. The networks with one hidden layer consisted of five neurons are developed as the optimal structure. For these binary systems, uncertainties in the artificial neural networks (ANNs) estimations were not more than 1.03%. In addition, the abilities of ANNs are shown by comparisons with Margules, van Laar, and some other correlations.Dans ce travail de recherche, nous avonsétudié la capacité de réseaux neuraux de perceptron multicoucheà estimer les données d'équilibre vapeur-liquide. Quatre systèmes typiques de réfrigérants binaires contenant du R227ea ontétéétudiés sur de grands intervalles de température et de pression. Les systèmesétaient classés en quatre groupes, en fonction de leurs déviations différentes par rapportà la Loi de Raoult. Les réseaux ayant une couche cachée composée de cinq neurones sont développés comme la structure optimale. Pour ces systèmes binaires, les incertitudes dans les estimations ANN ne dépassaient pas 1,029 %. De plus, les capacités des ANN sont données en comparaison avec Margules, van Laar et certaines autres corrélations.

Homo-and copolymers of 2-(N-phthalimido)ethyl methacrylate (NPEMA) and p-chlorophenyl methacrylate (PCPMA) were prepared in N,N-dimethyl formamide (DMF) solution at 70 °C using 2,2-azo-bisisobutyronitrile (AIBN) as initiator. The nano-CdS-doped polymer composite of NPEMA and PCPMA was prepared via in situ technique. The homo-and copolymers of NPEMA and PCPMA were characterized using FT-IR spectroscopy and gel permeation chromatography (GPC). The polymer nano composites were characterized using FT-IR spectroscopy, X-ray diffraction, and transmission electron microscopy. The reactivity ratios (r 1 and r 2 ) were obtained from the various linear graphical methods. The values of r 1 (NPEMA) = 0.55 and r 2 (PCPMA) = 1.30 were found from the same graphical methods. The copolymer microstructures were found from the mean sequence length, run number, and dyad fraction. Thermal behavior of polymers and polymer nano composites under nitrogen atmosphere was studied. The activation energies of neat polymers were varied in the range of 56-85 kJ/mol, while 28-56 kJ/mol energies were found for nano-CdS-doped polymer composites. The thermodynamic parameters of thermal degradation were also obtained. Kinetic and thermodynamic parameters were confirming the stability of the neat polymers than polymer nano composites. The polymers were assessed on different microorganisms for obtaining the antimicrobial properties. Overall, the polymers permit 10-52, 20-58, and 18-56% growth of bacteria, fungi, and yeast, respectively.