In the past decade, combinatorial and high throughput experimental methods have revolutionized the pharmaceutical industry, allowing researchers to conduct more experiments in a week than was previously possible in a year. Now high throughput experimentation is rapidly spreading from its origins in the pharmaceutical world to larger industrial research establishments such as GE and DuPont, and even to smaller companies and universities. Consequently, researchers need to know the kinds of problems, desired outcomes, and appropriate patterns for these new strategies. Editor James Cawse′s far–reaching study identifies and applies, with specific examples, these important new principles and techniques.
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. The book′s contents are contributed by leading researchers in their respective fields. Chapters include:
∗ High Throughput Synthetic Approaches for the Investigation of Inorganic Phase Space
∗ Combinatorial Mapping of Polymer Blends Phase Behavior
∗ Split–Plot Designs
∗ Artificial Neural Networks in Catalyst Development
∗ The Monte Carlo Approach to Library Design and Redesign
The text 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 James Cawse′s study to be an invaluable resource.
The Combinatorial Challenge (J. Cawse).
The Combinatorial Discovery Array: An Overview of the Chapters (J. Cawse).
Fractional Masking Methods in Combinatorial Synthesis of Functional Materials (T. Sun).
High Throughput Synthetic Approaches for the Investigation of Inorganic Phase Space (L. Schneemeyer & R. van Dover).
Combinatorial Mapping of Polymer Blends Phase Behavior (A. Karim, et al.).
Combinatorial Experimental Design Using the Optimal–Coverage Algorithm (D. Bem, et al.).
Combinatorial Materials Development Using Gradient Arrays: Designs for Efficient Use of Experimental Resources (J. Cawse & R. Wroczynski).
Split–Plot Designs (M. Gardner & J. Cawse).
Evolutionary Strategy for the Design and Evaluation of High Throughput Experiments (D. Wolf & M. Baerns).
Artificial Neural Networks in Catalyst Development (M. Holeňa & M. Baerns).
Descriptor Generation, Selection, and Model Building in Quantitative Structure–Property Analysis (C. Breneman, et al.).
The Monte Carlo Approach to Library Design and Redesign (M. Deem).
Exploring a Space of Materials: Spatial Sampling Design and Subset Selection (F. Hamprecht & E. Agrell).