Multiparameter space

In spite of the high number of potentially active compounds and the considerable number of diverse catalytic systems studied so far [7], the knowledge available on catalytic materials with more than two components is rather limited. To illustrate this point, one can take 75 of the more stable elements of the periodic table, then divide them in subgroups of n members each, which gives 75n possible compounds, that is about 5,600 binary compounds, or 4.2 x 105 ternary, 3.1 x 107 quaternary and about 5.6 x 1018 decanary compositions. In addition, the relative concentrations between two or more elements and the modifications driven by special treatments contribute to increase those numbers [39]. The main point here is that, using traditional R D methods, the possibilities of scanning a substantial portion of the multiparameter space are rather limited, that is why HT and Combinatorial methods become more important. 

On the other hand, significant developments in catalysis arise from the knowledge of reaction kinetics and engineering, which are crucial for designing industrial catalysts and processes [11], Of course, the actual HT and Combinatorial catalysis methods do not override traditional semi-industrial or Pilot Plant tests, but they are complementary and powerful techniques for exploring the multiparameter space under variable conditions and kinetic... 

During optimisation of a compound series, researchers run through a process of hypothesis and trials. The process starts with the design and synthesis of a compound, which after biological testing in a multiparameter space leads to a verified hypothesis and design of compounds until the optimisation goal has been achieved. 

Different reactor networks can give rise to the same residence time distribution function. For example, a CSTR characterized by a space time Tj followed by a PFR characterized by a space time t2 has an F(t) curve that is identical to that of these two reactors operated in the reverse order. Consequently, the F(t) curve alone is not sufficient, in general, to permit one to determine the conversion in a nonideal reactor. As a result, several mathematical models of reactor performance have been developed to provide estimates of the conversion levels in nonideal reactors. These models vary in their degree of complexity and range of applicability. In this textbook we will confine the discussion to models in which a single parameter is used to characterize the nonideal flow pattern. Multiparameter models have been developed for handling more complex situations (e.g., that which prevails in a fluidized bed reactor), but these are beyond the scope of this textbook. [See Levenspiel (2) and Himmelblau and Bischoff (4).]... 

Iterative methods are interpretive methods in which new experiments can be added to the small number of starting experiments in order to refine the surface retention for all the solutes, and to predict more accurately the optimum location in the parameter space. For single-parameter optimization both graphical and mathematical methods can be used, but for multiparameter optimization computerized methods are necessary. 

Recently, Lautenschlager et al. (2010) described a multiparameter model in isolated rat intestinal segments to allow perfusion through the mesenteric artery and the gut lumen. In this model, blood vessels, lymphatics, interstitial space, and lumen are maintained, allowing the assessment of potential effects of drugs on fluid homeostasis, barrier functions, transport mechanisms, immtme responses, and gut motility in situ. 

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