By Gottfried Glockner
The most topic of this publication is the characterization of plastics. To a excessive measure the houses of those polymers rely on the distribution of the molar mass and of different structural good points, and small deviations often have an exceptional impact. consequently the characterization of polymers can't be constrained to the decision of suggest values yet needs to yield info on those distributions. utilizing classical equipment, the analytical fractionation of polymer homologues and structurally isomeric polymers is intensely time-consuming. accordingly, effective chromatographic innovations are being more and more hired in sleek polymer characterization. within the first position, high-performance liquid chromatography is utilized, within the kind of dimension exclusion chromatography. it's also attainable, even though, to exploit different separation modes. more room is dedicated to those different percentages during this quantity than is merited by means of their present diversity of functions, because the writer believes that many separation difficulties may be solved by means of separation strategies of the non-exclusion variety. however, a lot emphasis is put on measurement exclusion chromatography.
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Extra resources for Polymer Characterization by Liquid Chromatography
1. Molar mass and degree of polymerization Macromolecules are built up of relatively simple units which are based on the monomer structures. , is called the degree of polymerization. Thus, a PVC molecule with a degree of polymerization of P = 2000 is built up of 2000 vinyl chloride molecules and could be represented by the symbol Whether or not the end groups ct or w are mentioned depends, last but not least, on whether they play a demonstrable r6le in the context discussed. For many problems they can be neglected to a good approximation.
M: = c mi . M~ (4-6a) (4-7a) If a large number of summands are involved, such calculations are rather troublesome. 2. Distribution of the degrees of polymerization 47 it is customary to freat the MMD as continuous distribution with the limits 0 and co. Then Eqns. (4-2a) through (4-7a) can be written as: r P h ( P ) dP - P, = 0 (4-2 b) r h ( P ) dP 0 m (4-3 b) fP2h(P) dP - P, (4-4 b) = Ph(P) dP 0 [M2h(M) dM - (4-5 b) M,= (jmMh(M)d M [Pah(P) dP - P, = 1 (4-6 b) P2h(P)d P - MZ rM3h(M)dM (4-7 b) m f MZh(M)dM 0 A,,A, and HZor data derived from them give first information about the width of the distribution.
P , plotted according to eqn. (4-23), passes through a maximum. On the other hand, for k > 1 the frequency distribution shows a maximum as well. Substitution of eqn. (4-20) for h(P) in eqns. (4-2b) and (4-4b), respectively, gives: P,, = k ’ c P, = (k + 1 ) c (4-24) (4-25) For the parameters c and k this gives c = - P , - P,, (4-26) (4-27) The parameter k, which was introduced as a degree of coupling in the derivation, turns out to be the reciprocal of non-uniformity U. Thus the meaning of the generalization becomes most obvious : the non-uniformity will only by chance coincide with the reciprocal of an integer.
Polymer Characterization by Liquid Chromatography by Gottfried Glockner