Cost-conscious method helps design automated materials labs before equipment is purchased

A research team from The Hong Kong University of Science and Technology (HKUST) has developed a new modeling and optimization framework that helps researchers design modularized autonomous experimentation (MAE) platforms for new materials by determining the optimal combination of equipment before construction begins, thereby reducing time and cost before the platform is physically built.

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