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.
