Abstract
Combinatorial Materials Science is the rapid synthesis and analysis of large numbers of compositions in parallel, created through many combinations of a relatively small number of starting materials. It is, therefore, essential that for a truly combinatorial approach both synthesis and measurement must be high-throughput, to handle the large number of samples required. Since the first serious attempts at combinatorial searches in Materials Science in the mid 1990s, the technique is still very much in its infancy, falling way behind the progress made in biomedical and organic combinatorial chemistry, despite attracting increasing interest from industry. The most investigated materials by combinatorial methods are catalysts and phosphors, and most work has been on libraries in deposited thin film form. This chapter will give a broad overview of the different synthetic strategies used, with a particular look at the difficulties of producing thick film or bulk ceramic/metal-oxide libraries. A vast number of characteristics can be quantified in combinatorial materials libraries, from compositional, crystal phase, structural and microstructural information, to functional properties including catalytic/photocatalytic, optical/luminescent, electrical/dielectric, piezoelectric/ferroelectric, magnetic, oxygen-conducting, water-splitting, mechanical, thermal/thermoelectric, magnetoelectric/optoelectric/magneto-optic/multiferroic, bioactive/biocompatible, etc. This chapter will cover the range of high-throughput measurements open in combinatorial Materials Science, and especially the challenges in presenting and displaying the large and complex amount of data obtained for functional materials libraries. To this end, the use of glyphs is looked at, glyphs being data points that also contain extra levels of information/data in graphic form.
Keywords
- Pulse Laser Deposition
- Combinatorial Library
- Combinatorial Material
- Magnetic Force Microscopy
- Piezoresponse Force Microscopy
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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The author would firstly like to thank the FCT (Fundação para a Ciência e a Tecnologia in Portugal), and the FCT Ciência 2008 program and grant SFRH/BPD/97115/2013 are acknowledged for funding the author during the writing and publication of this chapter. The author would also like to thank the publishers and copy write holders of all figures from previous sources used in this chapter, which have been referenced in the relevant figure caption.
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Pullar, R.C. (2016). Combinatorial Materials Science, and a Perspective on Challenges in Data Acquisition, Analysis and Presentation. In: Lookman, T., Alexander, F., Rajan, K. (eds) Information Science for Materials Discovery and Design. Springer Series in Materials Science, vol 225. Springer, Cham. https://doi.org/10.1007/978-3-319-23871-5_13
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