Advanced materials are the engine to drive high-performing and sustainable technologies. The speed at which promising materials can be generated has been greatly accelerated by the advancement in artificial intelligence and computation. The bottleneck, however, lies in the experimental synthesis, before the newly designed materials can be validated. This is where autonomous laboratories – also known as self-driving labs – can make a difference. Dr. Yan Zeng will talk about the development of an autonomous solid-state synthesis laboratory designed to accelerate the synthesis step with the ultimate goal of accelerating materials development. This laboratory autonomously generates synthesis recipes drawn from the vast historical literature, performs experiments in a robotic system, and utilizes machine learning for data interpretation, with active learning algorithms then steering the subsequent experimental direction.
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