Screening Design Composition-Property

It is evident that components levels-ratios are not independent and that the level of one component depends on levels of q-1 components. Screening experiments are recommended in situations when the number of components is q 6. For five or 

Design of Experiments in Chemical Engineering. Zivorad R. Lazic Copyright 2004 WILEY-VCH Verlag GmbH Co. KGaA, Weinheim ISBN 3-527-31142-4 

Constant p0 is omitted due to the limitation that the sum of ratios of all components is equal to one. Screening out of components is brought down to finding components Xi that have no effects and/or have the same effects on the property-response of the mixture  

Examples of response surfaces for the two mentioned cases are shown in Figs. 3.1 and 3.2. 

The response surface in Fig, 3.1 is defined by the regression model = 80Xj + 90X2 + IOOX3, where we can see that there is no variation of y in direction X2  

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Topliss tree and Craig plot Factorial, central composite and D-optimal designs Principal properties of substituents Drug-like properties Combinatorial libraries Virtual screens IV Determining relationships between chemical and biological data A Overview... 

Current experiments uniformly tend to perform a grid search on the composition and noncomposition variables. It is preferable, however, to choose the variables statistically from the allowed values. It is also possible to consider choosing the variables in a fashion that attempts to maximize the amount of information gained from the limited number of samples screened, via a quasi-random, low-discrepancy sequence (Niederreiter, 1992 Bratley et al., 1994). Such sequences attempt to eliminate the redundancy that naturally occurs when a space is searched statistically, and they have several favorable theoretical properties. An illustration of these three approaches to materials discovery library design is shown in Fig. 1. 

In principle, the broad range of functional monomers eurrently available makes it possible to design an MIP specific for any type of stable ehemical compound. Currently the selection of the best monomers for polymer preparation is one of the most crucial issues in molecular imprinting. Thermodynamic calculations and combinatorial screening approaches olfer possible solutions, and have already been used successfully for predicting polymer properties and for the optimization of polymer compositions (see Ref. 9,57,58, and Chapter 8), however, in practical terms, application of these methods is not trivial. The problem lies in the technical difiiculty of performing detailed thermodynamic calculations on multicomponent systems and the amount of time and resources required for the combinatorial screening of polymers. To check a simple two-component combination of 100 monomers, for example, one has to synthesize and test more than 5000 polymers, a very difiicult task. This task will be further complicated by the possibility that these monomers could be used in monomer mixtures in dilferent ratios. 

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