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Carbon number functionality effects

The effective carbon number neff is helpful in characterizing surfactants with an inner functional group. Surfactants with isomeric structures can be compared by means of the hydrophobicity index / [69], which indicates the influence of the effective length of the alkane chain on cM ... [Pg.193]

Fig. 9. Effect of the chain length of hydrocarbons on the adsorption enthalpy and rates of desorption. (A) Hydrocarbon in interaction with zeolite framework. Methyl groups interact with the framework oxygen protons exhibit an additional attractive force. (B) Heat of adsorption as a function of carbon number for zeolites MFI and FAU in the acidic and non-acidic form. (C) Relative desorption rates of a C12, Ci6, and C20 alkane compared to octane at 348 K. Values calculated from the linear extrapolation of the heat of adsorption values shown in (B). Fig. 9. Effect of the chain length of hydrocarbons on the adsorption enthalpy and rates of desorption. (A) Hydrocarbon in interaction with zeolite framework. Methyl groups interact with the framework oxygen protons exhibit an additional attractive force. (B) Heat of adsorption as a function of carbon number for zeolites MFI and FAU in the acidic and non-acidic form. (C) Relative desorption rates of a C12, Ci6, and C20 alkane compared to octane at 348 K. Values calculated from the linear extrapolation of the heat of adsorption values shown in (B).
Extensive manifestations of configurational diffusion can be seen in catalytic zeolites. The landmark measurements by Gorring [16] of the diffusion coefficients of alkanes (in potassium T zeolites) as a function of their carbon number are shown in Fig. 4, indicating over two orders of magnitude of change in diffusivity, with a minimum at C-8 and a maximum at C-12 for unexplained reasons. Similarly, spectacular effects for more complex molecules have been observed by Haag and Chen [17] and are shown in Fig. 5. Although we do not yet have a workable correlation between zeo-... [Pg.244]

Figure 8.8. Effect of chemical interesterification on the relative proportion (w/w) of milk fat triacylglycerols as a function of carbon number (CN). TAG = triacylglycerol. Noninteresterified milk fat (O-O), interesterified milk fat-15 min ( - ), 30 min ( - ), 60 min ( - ), 90 min (A-A), and 120 min (A-A)- (Reproduced with permission from Rousseau et al., 1996a). Figure 8.8. Effect of chemical interesterification on the relative proportion (w/w) of milk fat triacylglycerols as a function of carbon number (CN). TAG = triacylglycerol. Noninteresterified milk fat (O-O), interesterified milk fat-15 min ( - ), 30 min ( - ), 60 min ( - ), 90 min (A-A), and 120 min (A-A)- (Reproduced with permission from Rousseau et al., 1996a).
Still, some conclusions can be drawn. In the mixtures, specific rate of reaction is more a function of carbon number than of degree of branching, and the effect of carbon number in mixtures is not greatly at variance with the conclusions of Ref. 3. Specific rates of individual compounds in the mixtures appear to be somewhat lower than we would predict from Equation 13. This can perhaps be partially attributed to the effects of nitrogen diluent. [Pg.72]

CO reactants and the H2O product of the synthesis step inhibit many of these secondary reactions. As a result, their rates are often higher near the reactor inlet, near the exit of high conversion reactors, and within transport-limited pellets. On the other hand, larger olefins that are selectively retained within transport-limited pellets preferentially react in secondary steps, whether these merely reverse chain termination or lead to products not usually formed in the FT synthesis. In later sections, we discuss the effects of olefin hydrogenation, oligomerization, and acid-type cracking on the carbon number distribution and on the functionality of Fischer-Tropsch synthesis products. We also show the dramatic effects of CO depletion and of low water concentrations on the rate and selectivity of secondary reactions during FT synthesis. [Pg.234]

E. Carbon Number Effects on Chain Growth Probability and Product Functionality... [Pg.253]

Diffiisional restrictions increase the effectiveness of olefin interception sites placed within catalyst pellets. Very high olefin hydrogenation turnover rates or site densities within pellets prevent olefin readsorption and lead to Flory distributions of lighter and more paraffinic hydrocarbons. Identical results can be obtained by introducing a double-bond isomerization function into FT catalyst pellets because internal olefins, like paraffins, are much less reactive than a-olefins in chain initiation reactions. However, light paraffins and internal olefins are not particularly useful end-products in many applications of FT synthesis. Yet, similar concepts can be used to intercept reactive olefins and convert them into more useful products (e.g., alcohols) and to shift the carbon number distribution into a more useful range. In the next section, olefin readsorption model simulations are used to explore these options in the control of FT synthesis selectivity. [Pg.281]

Fig. 27. Effect of diffusion-enhanced a-olefin cracking catalytic function on carbon number distribution (simulations experimental/model parameters as in Fig. 15, 10% CO conversion). (A) FT synthesis without cracking function (B) with intrapellet cracking function, jS = 1.2 (C) with extra pellet cracking function, jS = 1.2. (a) Carbon selectivity vs. carbon number (b) Flory plots. Fig. 27. Effect of diffusion-enhanced a-olefin cracking catalytic function on carbon number distribution (simulations experimental/model parameters as in Fig. 15, 10% CO conversion). (A) FT synthesis without cracking function (B) with intrapellet cracking function, jS = 1.2 (C) with extra pellet cracking function, jS = 1.2. (a) Carbon selectivity vs. carbon number (b) Flory plots.
A series of 8-hydroxy saturated fatty acids were synthesized to explore the effect of chain length on activity. The hydroxyl function was maintained on the eight carbon by starting with 1,8-octanediol and the chain length dictated by a reaction with the appropriate carbon number saturated Grignard reagent. The eighteen carbon 8-hydroxy compound demonstrates the most activity in this series (Fig. 5). [Pg.361]

The use of additive substituent effects to calculate chemical shifts in benzene derivatives has been well documented38. The values obtained for a number of silyl derivatives of benzene are collected in Table 429. The chemical shifts of these compounds are all in the normal range for substituted benzenes (110-150 ppm). The substituent effects differ from those of the analogous carbon containing functional groups and can be differentiated from most other substituents (exceptions are P, Sb, Hg, Bi, Sn, Pb and cationic substituents) by the strong deshielding effect (4-8 ppm) at the ortho position. [Pg.518]

Figure 3(a) is the adsorption effect of modified Activated Carbon on Sb " with increasing pH. The pH was adjusted with HCl, selected room temperature, stirring frequency was lOOr/min, the amount of carbon was 5 g/L and the adsorption time was 1 h. The figure shows that with pH increased, activated carbon adsorption effect on Sb increased first and then decreased. When the pH was 5, the adsorption effect is better, and the remaining Sb " concentration dropped to 0.02 mg/L, removal rate was 99.13%. This is mainly because with the pH value increased, carbon surface functional groups will occur with the dissociation of H, thus exposed a large number of active centers, Sb + occupied the active center and effectively adsorbed, so the adsorption amount increased as the pH increased. However, as the pH increased, the chemical interactions between hydroxyl and the metal ions increased, resulted the relative decline in the amount of adsorption and thus activated carbon adsorption effect on Sb + increased first and then decreased. [Pg.126]


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See also in sourсe #XX -- [ Pg.253 , Pg.254 , Pg.255 , Pg.256 ]




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Carbon function

Carbon functionalization

Carbon functionalized

Carbon functionalizing

Carbon number

Carbonate functionality

Effective carbon number

Effective functionality

Effects function

Number function

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