Autonomous materials discovery platforms have successfully accelerated high-throughput synthesis, yet the manipulation and real-time tracking of complex solid-state synthesis pathways remain a critical challenge. Therefore, we present a fully integrated,...
Self-driving laboratories (SDLs) integrate robotic experimentation and machine learning to autonomously navigate complex chemical and materials search spaces-but their development demands simultaneous mastery of experimental parameterisation, automated measurement, and optimisation...
Automated laboratories increasingly combine automated and cloudified instruments, robotic operation, sample provenance and data infrastructures, and autonomous agents. Yet these capabilities primarily address execution, while planning remain limited to myopic...
Nature provides a rich source of principles for engineering systems capable of operating efficiently and robustly in complex environments [...].
Robotic systems are increasingly expected to operate autonomously, safely, and efficiently in dynamic and uncertain environments [...].
Self-driving laboratories (SDLs) are rapidly changing how chemical and materials research is performed by closing the loop between automated experimentation and data-driven decision making, enabling faster discovery and optimization with...
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