Experiment planning for combinatorial materials discovery

The introduction of combinatorial methods into materials discovery and optimization presents new challenges for experiment planning. The need for new or adapted experimental design approaches in combinatorial materials discovery stems from the dramatic expansion in numbers of materials and experimental variables that can be considered using combinatorial approaches. This paper presents an overview of some of the experimental design strategies being developed and used for combinatorial discovery and characterization of materials. Parallels between materials versus drug discovery are drawn and various modes of combinatorial experimentation are outlined: mapping, screening and optimization. Specific methods for incorporation of prior knowledge into experimental design include statistical design of experiments, diversity techniques, hierarchical and hybrid approaches such as neural networks, and search techniques like Monte Carlo optimization and genetic algorithms. (C) 2003 Kluwer Academic Publishers.