Factors influencing properties

Crystallinity. Is one of the key factors influencing properties. You can think of crystallinity in terms of how well a polymer fits in an imaginary pipe, as in Figure 22-6. Linear, straight chains are highly crystalline and fit very well. Bulky groups, coiled chains, and branched chains are not able to line up to fit in the pipe. They are amorphous, the opposite of crystalline. In a spectrum from totally amorphous, to almost totally crystalline, there is methyl methacrylate, polypropylene, low-density polyethylene, linear low-density polyethylene, high-density polyethylene, and nylon. 

Factors influencing properties of the cake during the cake filtration are particle shape, size, packing and dimensions of the cake in addition to the properties of the fluids, interfacial properties and the other factors such as temperature, pressure gradient and the rate of displacement. Particle shape may be an important factor in determining the drainage characteristics (1). 

General Discussion. The usefulness of polymers depends not only on their properties but also on their abundance and reasonable cost. Polymer properties are related not only to the chemical nature of the polymer, but also to such factors as extent and distribution of crystallinity and distribution of polymer chain lengths. These factors influence properties such as hardness, comfort, chemical resistance, biological response, weather resistance, tear strength, dyeability, flex life, stiffness, electrical properties, and flammability. 

It is necessary to allocate the following factors influencing properties of a composition. Except for above molecule structm-es (AMS) of initial polymer, it is chemical structure PhOC, its volume, a degree of polarity and a way of distribution of the additives- modifiers, changes of defectiveness influencing a degree AMS of polymer. Besides it is necessary to take into accoimt that circumstance, that the mentioned above factors can render various influence on mechanical behavior of a composition at different stages of deformation. 

Liquid Holdup The major factor influencing this property is the liquia flow rate, but the shape, size, and wetting characteristics of the particles and the gas rate and the initial distribution of liquid also enter in. One of the simpler correlations is that of Midoux et al. (J. 

It is particularly interesting to consider the influence of the substituents R and Rj in diphenylol alkanes of the type shown in Figure 20.12. Such variations will influence properties because they affect the flexibility of the molecule about the central C-atom, the spatial symmetry of the molecule and also the interchain attraction, the three principal factors determining the physical nature of a high polymer. 

These complicating factors influence not only the middle composition and composition distribution curves of copolymers, but also the kinetic parameters of copolymerization and the molecular weight of copolymers. An understanding of these complicating factors makes it possible to regulate the prosesses of copolymerization and to obtain copolymers with different characteristics and, therefore, with various properties. 

Non-Newtonian fluids vary significantly in their properties that control flow and pressure loss during flow from the properties of Newtonian fluids. The key factors influencing non-Newtonian fluids are their shear thinning or thickening characteristics and time dependency of viscosity on the stress in the fluid. 

Column diameter for a particular service is a function of the physical properties of the vapor and liquid at the tray conditions, efficiency and capacity characteristics of the contacting mechanism (bubble trays, sieve trays, etc.) as represented by velocity effects including entrainment, and the pressure of the operation. Unfortunately the interrelationship of these is not clearly understood. Therefore, diameters are determined by relations correlated by empirical factors. The factors influencing bubble cap and similar devices, sieve tray and perforated plate columns are somewhat different. 

Such processing-induced residual stresses that influence properties as mechanical, physical, environmental, and aesthetic factors (which also exist in other materials like metals and ceramics) can have favorable or unfavorable effects, depending on the application of the load with respect to the direction of the stresses or orientation. 

Summarizing the discussion above, we can only say that all the relations observed experimentally between the parameters of catalytic activity of metals and parameters of their physicochemical bulk properties are secondary. The primary factor influencing the catalytic activity of all metals and most of their physicochemical parameters are... 

This approach of using 2D and 3D monodisperse nanoparticles in catalytic reaction studies ushers in a new era that will permit the identification of the molecular and structural features of selectivity [4,9]. Metal particle size, nanoparticle surface-structure, oxide-metal interface sites, selective site blocking, and hydrogen pressure have been implicated as important factors influencing reaction selectivity. We believe additional molecular ingredients of selectivity will be uncovered by coupling the synthesis of monodisperse nanoparticles with simultaneous studies of catalytic reaction selectivity as a function of the structural properties of these model nanoparticle catalyst systems. 

The object of the present study was to use in the above mentioned hydrogenations improved carbon supported catalysts, which could compete with the Pd black catalyst. Carbon materials are common supports, their surface properties can be modified easily and it is possible to prepare carbons with different proportion of micro-, meso- and macropores, which can be key factors influencing their performances. A highly mesoporous carbon was synthesised and used as support of Pd catalysts in the enantioselective hydrogenations. To our knowledge this is the first report on the use of highly mesoporous carbon for the preparation of Pd catalysts for liquid-phase hydrogenation. 

The model interpretation is in good agreement with the known molecular factors influencing Caco-2 permeability. In addition - and this outlines the originality of the method - VolSurf allows the relevant 3D molecular properties to be quantified. Once the model is developed, as reported above, simple projection of the compound descriptors into it allows predictions to be made for new compounds. 

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