ABSTRACT
The concept of combinatorial methods is well known in science. For example, combinatorics is a branch of mathematics that studies finite collections of objects that satisfy some predefined criteria, and is concerned with counting the objects in those collections and with deciding whether certain optimal objects exist.1,2 In life sciences, combinatorial methods have found their applications in intelligent and systematic searching of large-parameter spaces for new candidate drug molecules in combination with high-throughput techniques, applied to evaluate activity.3 It has been recognized that to screen all possible combinations of molecular building blocks for their target-binding properties is a time-and resource-consuming effort, even with the availability of ultra-high-throughput screening instrumentation.4,5
In materials science, materials properties depend not only on composition, but also on morphology, microstructure and other parameters that are dependent on material-preparation conditions. A typical example of such dependence is shown in Figure 1.1, which illustrates the large number of parameters important for selectivity, stability, and reproducibility of operation of formulated polymeric6 and metal oxide semiconductor7 sensors.
