The development of parallel synthesis and high-throughput
characterization tools offer scientists a time-efficient and
cost-effective solution for accelerating traditional synthesis
processes and developing the structure-property relationships of
multiple materials under variable conditions. Written by renowned
contributors to the field, Combinatorial and High-Throughput
Discovery and Optimization of Catalysts and Materials documents the
impact of combinatorial methods for inorganic, organic, polymeric,
and biological materials applications over the last several years.
This valuable reference describes techniques for the preparation,
formulation, fabrication, optimization, performance testing, and
evaluation of catalysts, polymeric materials arrays, sensing
materials, fuel cell battery and memory materials, semiconductor
nanoclusters, dielectrics, OLED arrays, additives, organic
coatings, luminescent materials, and phosphors. The book introduces
some of the latest features in the development of combinatorial and
high throughput workflows, including new library designs, the
scale-up of combinatorially discovered materials, and innovative
methods of data storage, data mining and informatics. It also
points to active research in the development of intelligent
software for data mining including multiparameter modeling and
visualization. As combinatorial materials science becomes
increasingly applicable to a growing number of materials and
problems, Combinatorial and High-Throughput Discovery and
Optimization of Catalysts and Materials provides an essential
portrait of the success, challenges, and opportunities in this
field for the next generation of combinatorial chemists, material
scientists, and industrial chemists and academics.
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