Effective molarity values, influencing factors

The positive intercepts in Figure 7 show that post-gel(inelastic) loop formation is influenced by the same factors as pre-gel intramolecular reaction but is not determined solely by them. The important conclusion is that imperfections still occur in the limit of infinite reactant molar masses or very stiff chains (vb - ). They are a demonstration of a law-of-mass-action effect. Because they are intercepts in the limit vb - >, spatial correlations between reacting groups are absent and random reaction occurs. Intramolecular reaction occurs post-gel simply because of the unlimited number of groups per molecule in the gel fraction. The present values of p , (0.06 for f=3 and 0.03 for f=4 are derived from modulus measure- ments, assuming two junction points per lost per inelastic loop in f=3 networks and one junction point lost per loop in f=4 networks. 

A useful plot for identifying factors that are important is a Pareto chart. The graph in Fig. 1 shows the t-test values in the horizontal axis and also includes a vertical line to indicate the p value (an effect that exceeds the vertical line maybe considered significant). As observed in the Pareto chart, enzyme concentration is the most significant variable influencing monolaurin molar fraction. 

Figure 1 shows a family of 2-D slices (Re(n) varied and Im(n) fixed) of a typical error surface obtained from data acquired for a PEG particle. The three independent factors that define the scattering pattern - size, Re(n), and Im(n) - are systematically varied to find the best possible match to the experimental data by locating the minimum in a 4-dimensional error function. From exhaustive analysis of these error surfaces from many different sized particles, we find absolute size uncertainties to be between 2 and 5 nanometers, and the uncertainty in Re(n) to be between lO- and 5 x lO " For materials with a low molar absorptivity (typical of most dielectric liquids), Im(n) is correspondingly small - on the order of lO- to 10 At these values, there is very little (if any) effect on the match to data by varying Im(n). For many polymers (polyvinyl chlorides for example) however, this is not the case and Im(n) can be as large as 10 At this order of magnitude, Im(n) does indeed influence the Mie analysis ofthe data. 

In addition to this there arc two other factors influencing Fj when the ionic valency is altered. To discuss these two factors, we shall compare solutions of a 1—1 valent and a 3—3 valent electrolyte at such concentrations that k has the same value for both solutions. It then follows from the definition of X that the molar concentration of the trivalent electrolyte is one-ninth of that of the monovalent electrolyte. The effect of the valency upon the Fjj curve is then twofold. 

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