Experimental Design for Combinatorial and High Throughput Materials Development progresses from methods that are now standard, such as gradient arrays, to mathematical developments that are breaking new ground. The former will be particularly useful to researchers entering the field, while the latter should inspire and challenge advanced practitioners.

Also contains over 200 useful charts and drawings.

Industrial chemists, chemical engineers, materials scientists, and physicists working in combinatorial and high throughput chemistry will find this book to be an invaluable resource.

Contents

1. The Combinatorial Challenge
2. The Combinatorial Discovery Array: An Overview of the Chapters
3. Fractional Masking Methods in Combinatorial Synthesis of Functional Materials
4. High Throughput Synthetic Approaches for the Investigation of Inorganic Phase Space
5. Combinatorial Mapping of Polymer Blends Phase Behavior
6. Combinatorial Experimental Design Using the Optimal-Coverage Algorithm
7. Combinatorial Materials Development Using Gradient Arrays: Designs for Efficient Use of Experimental Resources
8. Split-Plot Designs
9. Evolutionary Strategy for the Design and Evaluation of High Throughput Experiments
10. Artificial Neural Networks in Catalyst Development
11. Descriptor Generation, Selection, and Model Building in Quantitative Structure-Property Analysis
12. The Monte Carlo Approach to Library Design and Redesign
13. Exploring a Space of Materials: Spatial Sampling Design and Subset Selection

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