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In this issue, we focus on the combination of techniques such as machine learning, artificial intelligence, robotics and automation for the synthesis of chemicals and materials.
Automated experiments with integrated characterization techniques greatly accelerate materials synthesis and provide data to be used by machine learning algorithms. We reflect on the current use of data-driven automated experimentation in materials synthesis and consider the future of this approach.
Automation and real-time reaction monitoring have enabled data-rich experimentation, which is critically important in navigating the complexities of chemical synthesis. Linking real-time analysis with machine learning and artificial intelligence tools provides the opportunity to accelerate the identification of optimal reaction conditions and facilitate error-free autonomous synthesis. This Comment provides a viewpoint underscoring the growing significance of data-rich experiments and interdisciplinary approaches in driving future progress in synthetic chemistry.
Andrew Cooper, a professor at the University of Liverpool and Academic Director of the Materials Innovation Factory, talks to Nature Synthesis about the use of robotics and artificial intelligence for the synthesis and discovery of materials and chemicals.
King Kuok (Mimi) Hii, a professor at Imperial College London and director of the Centre for Rapid Online Analysis of Reactions (ROAR) and the Engineering and Physical Sciences Research Council (EPSRC) Centre of Doctoral Training in Next Generation Synthesis & Reaction Technology (rEaCt), talks to Nature Synthesis about reaction monitoring in automated workflows as well as the challenges to be overcome in automated synthesis.
Paul Chirik, Edwards S. Sanford Professor of Chemistry at Princeton University, talks to Nature Synthesis about how organometallic catalysis can be used to form weak chemical bonds.
Suzanne Zamany Andersen, future founding CEO of Nitrofix Solutions, talks to Nature Synthesis about lithium-mediated ammonia synthesis and a career path through academia and beyond.
