Processing network models of energy/environment systems

Processing networks are a variant of the standard linear programming network model which are especially useful for optimizing industrial energy/environment systems. Modelling advantages include an intuitive diagrammatic representation and the ability to incorporate all forms of energy and pollutants in a single integrated linear network model. Added advantages include increased speed of solution and algorithms supporting formulation. The paper explores their use in modelling the energy and pollution control systems in large industrial plants. The pollution control options in an ethylene production plant are analyzed as an example. PROFLOW, a computer tool for the formulation, analysis, and solution of processing network models, is introduced.

Surface morphology control of immiscible polymer-blend thin films

The effects of the molecular weights (molecular weight of polystyrene, M-w,M-PS, varying from 2.9 to 129 k) on the surface morphologies of spin-coated and annealed polystyrene/poly (methyl methacrylate) (PS/PMMA = 50/50, w/w) blend films were investigated by atomic force microscopy and X-ray photoelectron spectroscopy. For the spin-coated films, when the M-w,M-PS varied from 2.9 to 129 k, three different kinds of surface morphologies (a nanophase-separated morphology, a PMMA cellular or network-like morphology whose meshes filled with PS, a sea-island like morphology) were observed and their formation mechanisms are discussed, respectively. Upon annealing, two different morphology-evolution processes were observed. It is found that a upper PS-rich phase layer is formed when M-w,M-PS < 4 k, and this behavior is mainly attributed to the low interfacial tension between PS and PMMA component. When M-w,M-PS > 4 k, the PS-rich phase forms droplets on top of the PMMA-rich phase layer which wets the SiOx substrate. These results indicate that the surface morphology of the polymer blend films can be controlled by the polymer molecular weight and annealing conditions.