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Experimental Factors

Debye gave tables are also graph for P(q) as a function of size factor . Experimentally,... [Pg.120]

Vander Heyden, Y., Questier, R, and Massart, D. L. (1998). A mggedness test strategy for procedure related factors experimental set-up and interpretation. /. Pharm. Biomed. Anal. 17, 153-168. [Pg.220]

Find a report of a two-factor experimental design. Speculate about the shape of the normalized uncertainty and normalized information surfaces for the design. Sketch their shape. [Pg.315]

Wiktor-JedrzeJczak, W., Urbanowska, E., Aukerman, S.E., Pollard, J.W., Stanley, E.R., Ralph, P., Ansari, A.A., Sell, K.W., and Szperl, M. (1991) Correction by CSF-1 of Defects in the Osteopetrotic op/op Mouse Suggests Local, Developmental, and Hnmoral Reqnirements for this Growth Factor. Experimental Hematology 19, 1049-1054. [Pg.103]

Knowledge of the oxygen isotope fractionation between liquid water and water vapor is essential for the interpretation of the isotope composition of different water types. Fractionation factors experimentally determined in the temperature range from 0 to 350°C have been suntunarized by Horita and Wesolowski (1994). This is shown in Fig. 2.13. [Pg.61]

Kubota, N., Temperature Sensitivity of Solid Propellants and Affecting Factors Experimental Results , Nonsteady Burning and Combustion Stability of Solid Propellants (Eds. De Luca, L, Price, E. W, and Summerfield, M.), Progress in Astronautics and Aeronautics, Vol. 143, Chapter 4, AlAA, Washington DC (1990). [Pg.67]

Eq. (1.34) is the simplified version of the Fowler-Nordheim equation. In the original Fowler-Nordheim equation, there is an algebraic prefactor to the exponential factor. Experimentally, the exponential factor always dominates the functional dependence, leaving the existence and the specific form of the algebraic factor hardly distinguishable (see Fowler and Nordheim, 1928 Good and Muller, 1956). In practical units (work function cj> in eV, and the field intensity F in V/A), Eq. (1.34) becomes... [Pg.46]

Finally, the discrepancy between experiment and theory on the ratio between Norrish type I reaction and Norrish type II reaction can be explained by considering the following factors. Experimental conditions in the gas phase allow for collisions between different molecules, a factor that has not been taken into account by the theoretical simulation. In addition, the presence of O2 or N2 in the experiment might additionally affect the ratio. [Pg.12]

Factor Experimental results of studies of human ingestion not available or scanty. Valid results from long-term feeding studies on experimental animals or, in the absence of human studies, on one or more species. No indication of carcinogenicity. [Pg.681]

Can you find an experimental design such that the off-diagonal elements of Equation 8.45 are all equal to zero What would be the covariance between b ) and fej, between b0 and bn, and between bl and bn for such a design [See, for example, Box, G.E.P., and Hunter, J.S. (1957). Multi-Factor Experimental Designs for Exploring Response Surfaces, Ann. Math. Statist., 28, 195.)... [Pg.134]

Fig. 13.3. Rankit plot for the cathodic OSWV copper peak current-density effects of interferents from a Plackett-Burman 7-factor experimental design. The effect is the change in the copper current density upon increasing the metal-ion interferent concentration from its low level (—1, 0.2 pM) to its high level (+1, 5pM). Reprinted from Ref. [5], Copyright (2005) with permission from Elsevier. Fig. 13.3. Rankit plot for the cathodic OSWV copper peak current-density effects of interferents from a Plackett-Burman 7-factor experimental design. The effect is the change in the copper current density upon increasing the metal-ion interferent concentration from its low level (—1, 0.2 pM) to its high level (+1, 5pM). Reprinted from Ref. [5], Copyright (2005) with permission from Elsevier.
The results clearly show that temperature and time at 95% and 99% confidence level respectively have a significant effect on production yield. It is also clear that there is no interaction between temperature and time factors. Experimental error is small with respect to interaction so that the used measurement equipment can be considered satisfactory. [Pg.88]

For a two-level factorial design, only two excipients can be selected for each factor. However, for the filler-binder, a combination of brittle and plastic materials is preferred for optimum compaction properties. Therefore, different combinations such as lactose with MCC or mannitol with starch can count as a single factor. Experimental responses can be powder blend flowability, compactibility, blend uniformity, uniformity of dose unit, dissolution, disintegration, and stability under stressed storage conditions. The major advantage of using a DOE to screen prototype formulations is that it allows evaluation of all potential factors simultaneously, systematically, and efficiently. It helps the scientist understand the effect of each formulation factor on each response, as well as potential interaction between factors. It also helps the scientist identify the critical factors based on statistical analysis. DOE results can define a prototype formulation that will meet the predefined requirements for product performance stability and manufacturing. [Pg.180]

In the case of H-SSZ-24, the values of the pre-exponential factor experimentally obtained (see Table 5.4) do not agree with the values theoretically predicted by the equation for a jump diffusion mechanism of transport in zeolites with linear channels, in the case of mobile adsorption [6,26], Furthermore, the values obtained for the activation energies are not representative of the jump diffusion mechanism. As a result, the jump diffusion mechanism is not established for H-SSZ-24. This affirmation is related to the fact that in the H-SSZ-24 zeolite Bronsted acid sites were not clearly found (see Figure 4.4.) consequently p- and o-xylene do not experience a strong acid-base interaction with acid sites during the diffusion process in the H-SSZ-24 channels, and, therefore, the hopping between sites is not produced. [Pg.269]

Window diagrams and related methods may in principle be applied to optimization problems in more than one dimension. The main difference compared with one-parameter problems is that graphical procedures become much more difficult and that the role of the computer becomes more and more important. Deming et al. [558,559] have applied the window diagram method to the simultaneous optimization of two parameters in RPLC. The volume fraction of methanol and the concentration of ion-pairing reagent (1-octane sulfonic acid) were considered for the optimization of a mixture of 2,6-disubstituted anilines [558]. A five-parameter model equation was used to describe the retention surface for each solute. Data were recorded according to a three-level, two-factor experimental... [Pg.209]

Fig. 8. Variations of viscosity parameter with expansion factor. Experimental data of Schulz (229) (circles) and Krigbaum and Carpenter (146) (crosses) Theoretical curves according to Eqs. (55) and (56) for homogeneous polymers (broken curve and chain curve) and for broad fractions (dotted curve and full curve)... Fig. 8. Variations of viscosity parameter with expansion factor. Experimental data of Schulz (229) (circles) and Krigbaum and Carpenter (146) (crosses) Theoretical curves according to Eqs. (55) and (56) for homogeneous polymers (broken curve and chain curve) and for broad fractions (dotted curve and full curve)...
FIGURE 3.5 Two-level-three-factor experimental design with geometrically balanced tet-rahedric subset (T). [Pg.47]

Using PC A, Cramer [139] found that more than 95% of the variances in six physical properties (activity coefficient, partition coefficient, boiling point, molar refractivity, molar volume, and molar vaporization enthalpy) of 114 pure liquids can be explained in terms of only two parameters, which are characteristic of the solvent molecule. These two factors are correlated with the molecular bulk and cohesiveness of the individual solvent molecules, the interaction of which depends mainly upon nonspeciffc, weak intermolecular forces. This is closely related to nonspeciffc, weak solute/solvent interactions. With these factors, experimental values of 18 common physical properties... [Pg.86]

BioavaUabUity-corrected bioconcentration factor experimentally determined in the guppy by Gobas et al. [91]. [Pg.95]

Figure 10. Real and imaginary part of complex modulus, G and G —cut/j, vs. loor for atactic polystyrene in dilute solution Oj- is shift factor. Experimental points are from refs. 102 and 103 best-fit continuous lines [from Eqn. (34) of ref. 12] superimposed on experimental points after rigid, parallel shift. [Model assumptions and parameters unperturbed periodic chain, N = 8000 (left) and N = 1300 (right), to/to = 47, R ff = 0.125 A.] (Reprinted with permission from ref. 12, Copyright 1981, American Chemical Society.)... Figure 10. Real and imaginary part of complex modulus, G and G —cut/j, vs. loor for atactic polystyrene in dilute solution Oj- is shift factor. Experimental points are from refs. 102 and 103 best-fit continuous lines [from Eqn. (34) of ref. 12] superimposed on experimental points after rigid, parallel shift. [Model assumptions and parameters unperturbed periodic chain, N = 8000 (left) and N = 1300 (right), to/to = 47, R ff = 0.125 A.] (Reprinted with permission from ref. 12, Copyright 1981, American Chemical Society.)...
Base of natural logarithms Packing factor experimentally determined, fr Actual cfm at fan inlet... [Pg.409]


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See also in sourсe #XX -- [ Pg.15 , Pg.133 ]




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Chemometrics experimental factors

Effect of Experimental Factors

Effectiveness factors experimental values

Experimental Nonisothermal Effectiveness Factors

Experimental and Calculated Effectiveness Factors

Experimental blocking factors

Experimental design factor

Experimental design single-factor

Experimental enhancement factor

Experimental factors, effect

Factors affecting experimental

Factors affecting experimental results

Phase factors experimental probing

Thermal analysis experimental factors affecting

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