High Throughput Methodologies

High-throughput methodologies are used to increase the speed of discovery and formulation of new materials. It encompass a broad range of advanced experimental and computational tools and techniques which enable fast parallel experimentation resulting in an increased productivity and faster time-to-market. The methodologies are well known in pharmaceutical research and the development of new catalysts. In the last 15-20 years, more interest has been observed in the area of high-throughput materials research.

Traditionally most material research is based on performing experiments in a sequential way, one at a time. However, materials related R&D has to cope with the interplay of many – often interdependent – parameters, making the traditional sequential procedures totally inadequate.

Combinatorial experimentation is an experimental strategy that solves this dilemma through automation, miniaturisation and the parallelisation of experiments. Using this strategy, a large number of experiments can be performed simultaneously or in very rapid sequention, speeding up significantly the time to discovery and product development. Today’s robotic handling in combination with rapid screening (measuring, analysing) methods, miniaturisation of testing, and application of data mining and statistical and visualisation tools, allow for rapid harvesting of useful data and a better understanding of the parameters related to the synthesis of new materials and formulations, their properties and effects.

Another strategy is the use of pragmatic modelling techniques to predict structural and functional properties of materials, based on fundamental, physical and chemical principles. Basic aim here is to enable upfront elimination of experimental domains where little or no success is to be expected, so as to direct combinatorial experimentation towards the potentially most rewarding areas.


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