Catalyst optimization

Chiral Catalyst Optimization 201 Tab. 5.8 Catalyst optimization using 20 in the reaction of Id with 7a... 

Thus, a novel chiral zirconium complex for asymmetric aza Diels-Alder reactions has been developed by efficient catalyst optimization using both solid-phase and liquid-phase approaches. High yields, high selectivity, and low loading of the catalyst have been achieved, and the effectiveness of chiral catalyst optimization using a combination of solid-phase and liquid-phase methods has been demonstrated. 

For supported layered catalysts, optimizing the location of the active sites within the catalyst pellets maximizes the effectiveness or the selectivity or reactor yield. 

Scheme 12.23. Enantioselective test reaction for catalyst optimization.

A comparison of the structures of 4 and 5, both in the crystalline form and in solution, has been carried out [46], The results obtained suggest that the structures are essentially the same in both states of aggregation and that crystal structure data can therefore be used for catalyst optimization. 

In hindsight, the development of bisfoxazolines) (box) from semicorrins seems a logical progression. It is, therefore, no surprise that these ligands were developed for this reaction independently and concurrently in three different laboratories. The finer details of catalyst optimization, however, were slightly different. 

By avoiding the acid catalysis mechanism of the conventional FCC zeolite catalyst (optimized over the years for high octane gasoline), the novel MAB catalyst will produce substantially lower aromatics in the liquid products than is possible by less extreme FCC catalyst adaptations. By changing the FCC reaction system, it is possible to overcome the MAB catalyst low activity drawback and achieve slurry yields compatible with those observed in maximum distillate operation in today s FCC units. 

Figure 2. Iterative approach flowchart for homogeneous catalyst optimization.

In the field of selective hydrogenation two important properties are used to describe the catalytic performance the activity and the selectivity of the catalysts. Their values have to be optimized. The simplest approach is to fix the desired conversion level and ranking the catalysts according to their selectivity data. An alternative way for catalyst optimization is the use of the so called "desirability function" d. Upon using this function different optimization parameters can be combined in a common function Dj. In the combination different optimization parameters (often called as objective functions) can be taken into account with different weights [21]. The single desirability function for the conversion (a) can be described by the following formula ... 

The main steps in catalyst optimization are as follows (see Scheme 1.) ... 

The cross-linked aggregates of MeHNL also showed themselves to be highly active and robust catalysts. Optimized procedures give MeHNL CLEAs with activity recoveries up to 93% measured by a synthetic assay [75]. As observed earlier for PaHNL CLEAs [74], this result is in contrast with the photometric assay, indicating that a fast assay severely underestimates the recovery of initial activity because of rate-limiting diffusion [75]. 

Importantly, the supramolecular strategy revealed a catalyst that outperforms all conventional catalysts known to date. This unambiguously shows that the supramolecular approach to create bidentate ligands is a very powerful tool that brings about new catalysts with properties that surpass those of catalysts already known. Moreover, it shows that these hits can be found in a very short time-frame. In addition, further catalyst optimization will be much faster using the supramolecular approach. The fact the only one hit was obtained from 60 catalysts clearly stresses the need for large numbers of catalysts to address catalytically challenging issues sufficiently. 

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