What are high-throughput methodologies?
High-throughput methodologies are used to increase the discovery speed and formulation of new materials or products. They 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 were first mainly known in pharmaceutical research and the development of new catalysts. Nevertheless, over the past 15-20 years, the interest in high-throughput methodologies has been broadened to other materials research areas.
Why consider high-throughput methodologies?
Traditionally most materials research is based on performing experiments in a sequential way, i.e. one at a time. However, this workflow has to cope with the interplay of many – often interdependent – parameters, making the sequential approach rather inefficient.
Combinatorial experimentation solves this dilemma through automation, robotic handling, miniaturisation and the parallelisation of experiments. Using this strategy, a large number of experiments can be performed simultaneously, speeding up significantly the time-to-discovery and product development.
Statistical analysis, data mining and visualisation tools allow for the harvesting of useful data and a better understanding of the parameters related to the synthesis, formulation and properties of new materials and products. This data can be further used as input for knowledge models.
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