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, materialscientists, and
industrial chemists and academics.
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