High throughput, materials research, coatings, characterization, data-management

Introduction to high throughput research with a special attention for metallic materials and coatings.

• Introduction
• Design of experiment
• High-throughput synthesis
• High-throughput screening
• Data-management: Storage, analysis, visualisation

Elementary knowledge of materials science

CONCEPTS: Combinatorial, high-throughput; Factorial design, Takeuchi method, D-optimal design, split-and-pool; Polymers, coatings, catalysts, bulk materials; Catalytic properties, mechanical properties, chemical properties, structural properties; Databases, principle components analysis, artificial neural networks, support vector machines, holographic strategies, quantitative structure-properties relation

INSIGHTS: Knowledge about definitions regarding combinatorial materials research; Notion of possible design of experiment strategies; Possibility to reduce the number of experiments by a scientific approach; Notion of data-management techniques for combinatorial materials research

ATTITUDE: critical attitude

copies of powerpoint-slides completed with copies of articles

• "Combinatorial materials synthesis", Takeuchi I., Lauterbach J., Fasolka M.J., Materials Today, October 2005
• "Combinatorial Materials Synthesis", Xiang X.-D., Takeuchi I. (eds.), Marcel Dekker, (2003).
• "Experimental Design for Combinatorial and High-Throughput Materials Development", Cawse J.N., Wiley-VCH, Hoboken, NJ, (2003).
• "High-Throughput Analysis: A Tool of Combinatorial Materials Science", Potyrailo R.A., Amis E.J. (eds.), Kluwer, New York, (2003).
• http://www.flamac.be

Classroom lectures

Evaluation during examination period

During examination period: oral closed-book exam, written preparation