Combinatorial methods and high-throughput experimentation in synthetic polymer chemistry
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Combinatorial methods and high-throughput experimentation in synthetic polymer chemistry Richard Hoogenboom, Michael A. R. Meier and Ulrich S. Schubert* Laboratory of Macromolecular Chemistry and Nanoscience, Eindhoven University of Technology and Dutch Polymer Institute (DPI), PO Box 513, 5600 MB Eindhoven, The Netherlands. E-Mail: [email protected]; Internet: www.schubert-group.com.
ABSTRACT Combinatorial chemistry has revolutionized the drug discovery as well as the catalyst discovery and optimization process during the last years. Nowadays, triggered by these developments, combinatorial methods and parallel chemistry also emerge in the field of material and polymer chemistry. Especially the field of polymer research seems to be perfectly suited for these approaches since many parameters can be varied during synthesis, processing, blending, formulation and compounding. Moreover, the screening of interesting parameters, such as molecular weight, polydispersity, polymerization kinetics, viscosity, hardness or stiffness, became feasible only recently. Within this contribution we will describe our strategy to construct a most efficient workflow in the field of combinatorial polymer research. New developments made by our group as well as some general aspects will be discussed.
INTRODUCTION In the last few years combinatorial polymer research has evolved as an independent, challenging and very promising field of research.[1-3] Several examples are known from the open literature where combinatorial methods have been applied to obtain insight information on polymerization procedures, to design, prepare and screen libraries of polymers or to gain information about structure-property relationships. In general, parallel experimentation, highthroughput screening and combinatorial techniques offer very promising approaches in the field of polymer chemistry since it is possible to vary and screen a large number of parameters at the same time. Within this contribution we will describe the setup we have chosen for our combinatorial laboratories in order to achieve a high level of automation as well as to enable a most efficient combinatorial workflow. This general workflow is shown in Figure 1. Starting with design of experiments (DoE) and ending with data mining the iteration cycle also includes the following steps (not necessarily in the given order): Automated synthesis, high-throughput screening (HTS), thin film & dot preparation techniques as well as property investigations. If necessary, this cycle can be re-executed until certain properties of the investigated polymer are obtained. The following chapters will discuss the separate steps of this iteration cycle.
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Figure 1: Typical workflow in combinatorial polymer chemistry.
DESIGN OF EXPERIMENTS Design of Experiments (DoE) can play an important role in all kinds of chemical processes. Examples reach from simple reaction condition optimization[4,5] to the improvement of analytical techniques.[6] A major advantage of using DoE software packages is the
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