Polymer Data Base

In conjunction with the preparation of this Handbook a compilation of data for pure polymers and polymer-solvent systems was prepared. This chapter documents these data bases. The actual data are contained on the accompanying disks. 

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Chapter 4 describes the polymer data bases. This chapter is organized into sections discussing the experimental methods available for measuring the thermodynamic data of polymer solutions with an overview of the advantages and disadvantages of each method. The next section, Data Reduction Methods, describes how the experimental measurements from these experiments can be used to calculate the activity coefficients that are necessary for phase equilibria calculations. Finally, a summary of all the systems that are available on the data diskettes is provided. A user can scan this section or use the computer program POLYDATA to find if data are available for a particular system. 

The pure polymer data base contains pressure-volume-temperature data. The data were first entered into a spreadsheet file in the form given by the author. The data were then converted to standard SI units and written to an ASCII file in the standard format developed for these files. 

To illustrate a graphical solution, the following loading and data for nylon from the polymer data base are used ... 

Step 4 deals with physical and chemical properties of compounds and mixtures. Accurate physical and chemical properties ate essential to achieve accurate simulation results. Most simulators have a method of maintaining tables of these properties as well as computet routines for calculations for the properties by different methods. At times these features of simulators make them suitable or not suitable for a particular problem. The various simulators differ ia the number of compounds ia the data base number of methods for estimating unknown properties petroleum fractions characterized electrolyte properties handled biochemical materials present abiUty to handle polymers and other complex materials and the soflds, metals, and alloys handled. 

This chapter has attempted to describe briefly some properties of polymers relevant to product design in terms of molecular behaviour. For in depth consideration the reader should consult more detailed reviews (e.g. refs 4, 5 and 6). There also exist specialist monographs concerned with practical aspects of product design (e.g. refs 7 and 11). Mention should also be made of excellent booklets by materials suppliers (e.g. refs 2 and 8) concerned with design aspects. Some material manufactures now supply comprehensive data books backed by computer data bases for multi-point engineering data (e.g. ref. 12). 

Fig. 111.—Experimental values of the interaction parameter %i plotted against the volume fraction of polymer. Data for polydi-methylsiloxane M =3850) in benzene, A (New-ingi6). polystyrene in methyl ethyl ketone, (Bawn et aV ) and polystyrene in toluene, O (Bawn et alP) are based on vapor pressure measurements. Those for rubber in benzene, T (Gee and Orr ) were obtained using vapor pressure measurements at higher concentrations and isothermal distillation equilibration with solutions of known activities in the dilute range.

Applications of Computer Data Base Management in Polymer and Coatings Research... 

One postulate which does resolve many of the inconsistencies in the present data base is that there is a strong tendency towards alternation in these polymers. Such alternation could result from a combination of an intrinsically greater reactivity of the ortho-relative to para-positions of coordinated phenoxide, coupled with an incibility of radicals of the type 5 to attack coordinated phenoxide at the ortho-position due to steric blocking. (An examination of models shows this to be a plausible assumption). ... 

The lattice models provide useful interpretations of spin relaxation in dissolved polymers and rubbery or amorphous bulk polymers. Very large data bases are required to distinguish the interpretive ability of lattice models from other models, but as yet no important distinction between the lattice models is apparent. In solution, the spectral density at several frequencies can be determined by observing both carbon-13 and proton relaxation processes. However, all the frequencies are rather hl unless T2 data are also included which then involves the prospect of systematic errors. It should be mentioned that only effective rotational motions of either very local or very long range nature are required to account for solution observations. The local... 

In spite of the fact that theoretically the approach of Drago is more sound, the use of the AN and DN numbers of Guttman is more accepted. These numbers can also characterize amphoteric materials and the available data base is much larger for this theory. Schreiber [30], for example, lists these parameters for a large number of polymers and other components used in polymer systems. 

Figure 7.4 Classification and image processing results of a typical situation in polymer waste recycling (a) digital image (b) initial classification result (c) calculation of separation data based on the initial classification result (d) classification result after real-time image processing. A, B Polyethylene terephthalate (PET) bottles with paper labels, C PE bottle with paper label, D PE bottle with PE film label, E PP cup, F PS cup. Classification colour code red high-density PE green PS dark blue PET yellow PP light blue paper.

Separating Force between Rolls in an Experimental Calender A cellulose acetate-based polymeric compound is calendered on a laboratory inverted, L-shaped calender with 16-in-wide rolls of 8 in diameter. The minimum gap between the rolls is 15 mil. The sheet width is 15 in. Calculate the separation force and the maximum pressure between a pair of rolls as a function of exiting film thickness, assuming that film thickness equals the gap separation at the point of detachment. Both rolls turn at 10 rpm. The polymer at the calendered temperature of 90°C follows a Power Law model with m = 3 x 106 dyne.s"/cm2 and n = 0.5. [Data based partly on J. S. Chong, Calendering Thermoplastic Materials, J. Appl. Polym. Sci., 12, 191-212 (1968).]... 

An advantage of defining the problem in this manner is that the partition coefficient has become a central property in quantitative structure-activity relationships (QSAR) and a large data base of P values is available in the medicinal chemistry literature (22-24). In particular, if a correlation (Equation 15) between the polymer-water and octanol-water partition coefficients can be established for a series of solutes, it becomes possible to utilize log P (oc-tanol/water) value as a reference point from which to calculate the polymer-water value. 

Third, a serious need exists for a data base containing transport properties of complex fluids, analogous to thermodynamic data for nonideal molecular systems. Most measurements of viscosities, pressure drops, etc. have little value beyond the specific conditions of the experiment because of inadequate characterization at the microscopic level. In fact, for many polydisperse or multicomponent systems sufficient characterization is not presently possible. Hence, the effort probably should begin with model materials, akin to the measurement of viscometric functions [27] and diffusion coefficients [28] for polymers of precisely tailored molecular structure. Then correlations between the transport and thermodynamic properties and key microstructural parameters, e.g., size, shape, concentration, and characteristics of interactions, could be developed through enlightened dimensional analysis or asymptotic solutions. These data would facilitate systematic... 

Matthew Tirrell It seems to me very likely that, one day, we will be able to compute, a priori, the properties of a conceptual polymer structure before its synthesis is carried out. There exist already large data bases from which one can make group contribution-type estimates. Real theory is a long way off but, I believe, will eventually exist. 

It has been shown by gel permeation chromatography (GPC) and NMR methods that cyclolinear structure of the backbone of synthesized polymers is obtained at the interaction of dichlororgano-cyclosiloxanea and dioxy-derivatives in the presence of HC1 acceptors only. The conclusion about cyclolinear structure of synthesized polymers is based on the data of hydrodynamic studies, MMD values and results of equilibrium rigidity determination. Cyclolinear structure of the backbone is also proved by NMR-spectroscopy method on 29Si nuclei. 

Generally the preferred data source is experimental measurement. Only in rare cases are prediction methods able to give more accurate estimates than a carefully executed experiment. Therefore, one of the major objectives of this Handbook is to provide comprehensive data bases for the phase equilibria of polymer-solvent systems and pressure-volume-temperature behavior of pure polymers. Thus, data have been compiled from extensive literature searches. These data cover a wide range of polymers, solvents, temperatures, and pressures. The data have been converted into consistent units and tabulated in a common format. Methods of evaluating and formatting these data banks have been established by the DIPPR Steering Committee for Project 881 and the Project Investigators. 

Chapter 3 contains the recommended predictive and correlative procedures for the specific volume of pure polymer liquids and the calculation of the vapor liquid equilibria of polymer solutions. These methods have been tested and evaluated with the data bases included in this Handbook. 

The Computer Programs section. Chapter 5, describes the two primary computer programs on the diskettes accompanying this Handbook. POLYPROG is a program which implements the recommended procedures of Chapter 3. POLYDATA provides an easy method of accessing the data contained in the many data bases. Chapter 6, contains the Appendices. The sections included are Glossary of Terms, Standard Polymer Abbreviations, Nomenclature, Units and Conversion Factors, and References. 

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