Through design trends

The color and constitution of cyanine dyes may be understood through detailed consideration of their component parts, ie, chromophoric systems, terminal groups, and solvent sensitivity of the dyes. Resonance theories have been developed to accommodate significant trends very successfully. For an experienced dye chemist, these are useful in the design of dyes with a specified color, band shape, or solvent sensitivity. More recendy, quantitative values for reversible oxidation—reduction potentials have allowed more complete correlation of these dye properties with organic substituent constants. 

In developing these eurves, whieh ineidentally follow the trends illustrated in Figures 5-1 through 5-4, it was assumed dial the plant is either a pre-boost or post-boost design with eonventional gas eomposition and proeess eonditions. For unusual plant designs, the expander manufaeturer should be eontaeted. 

In principle, one can carry out a four-dimensional optimization in which the four parameters are varied subject to constraints (< 1 and P4 < 1 ), to minimize the deposition time with the non-uniformity bounded e.g., MN < 3. However, objective function evaluations involve solutions of the Navier-Stokes and species balance equations and are computationally expensive. Instead, Brass and Lee carry out successive unidirectional optimizations, which show the key trends and lead to excellent designs. A summary of the observed trends is shown in Table 10.4-1. Both the deposition rate and the non-uniformity are monotonic functions of the geometric parameters within the bounds considered, with the exception that the non-uniformity goes through a minimum at optimal values of P3 and P4. 

Experience has followed an iterative pattern in playing the model exercises against field measurements. Usually, the first indication of the relative importance of variables is seen in bodies of observational data. The next step is to build a model on the basis of either intuition or a deterministic physical equation that reflects the trends seen in the data. The model is then used for the range of conditions in the data base, and uncertainties as to the correctness or completeness of the model become evident. The questions that arise can usually be answered only through further field experimentation. Thus, the models themselves are used in the design of both laboratory and field experiments that will ultimately provide a basis for the improvement of the modeling art. 

For a complete picture, however, some critical remarks have to be added. For medium-sized molecules, the obviously successful combination of theoretical prediction and experimental verification rather should be considered as an individually tailored interplay, which is based on numerous assumptions i.e. so-called chemical intuition. Tobeginwith, any hypersurface design confined to a few selected coordinates will only cover the aspects introduced thereby. Even several independent cuts through the (3n-6) dimensional hyperspace cannot unravel the complexity of a molecule in a specific molecular state. And although semiempirical methods - especially MNDO (10)- are not only fast but to quite an extent also reliable, their numerical accuracy should not be overstressed. Thus semiempirical hypersurfaces might better be considered as supplying trends in essential features, which can be compared to and correlated with measurement data to add the numerical accuracy, and, in return, to test and to substantiate all underlying assumptions. 

Miniaturization as a general trend in science and technology has also reached flow-through sensors as regards both design and construction of the sensor proper and the experimental set-up or flow manifold used prior to detection. 

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