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Informatics for Materials Science and Engineering
Materials informatics: a 'hot topic' area in materials science, aims to combine traditionally bio-led informatics with computational methodologies, supporting more efficient research by identifying strategies for time- and cost-effective analysis. The discovery and maturation of new materials has been outpaced by the thicket of data created by new combinatorial and high throughput analytical techniques. The elaboration of this "quantitative avalanche"—and the resulting complex, multi-factor analyses required to understand it—means that interest, investment, and research are revisiting informatics approaches as a solution. This work, from Krishna Rajan, the leading expert of the informati...
Hen Frigates
A hen frigate is any boat with the captain's wife on board. This is their story of life on the high seas.
Combinatorial Materials Science
Combinatorial Materials Science describes new developments and research results in catalysts, biomaterials, and nanomaterials, together with informatics approaches to the analysis of Combinatorial Science (CombiSci) data. CombiSci has been used extensively in the pharmaceutical industry, but there is enormous potential in its application to materials design and characterization. Addressing advances and applications in both fields, Combinatorial Materials Science: Integrates the scientific fundamentals and interdisciplinary underpinnings required to develop and apply CombiSci concepts Discusses the development and use of CombiSci for the systematic and accelerated investigation of new phenome...
Materials Science and Engineering
Design of combinatorial and high-throughput experiments has continued to build on the progress of the last two decades. New variations of factorial and mixture designs have expanded their capability. Increasing attention is being paid to adapting designs to the constraints of the physical apparatus, in the form of split-plot methods or conscious understanding of the statistical penalties to be paid. Rapidly increasing computer power has allowed the use of more sophisticated algorithmic designs and evolutionary methods. Finally, descriptor-based design and analysis of data is making steady progress and there are hopes of its reaching a mature state in the coming decade.
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Contributions
Contains reprints of articles published by members of the department.
