Modern nanoscience: Convergence of AI, robotics, and colloidal synthesis

Abstract

Autonomous experimentation and chemical discovery strategies are rapidly rising across multiple fields of science. However, closed-loop material development approaches have not been widely employed in colloidal nanoscience mainly due to the challenges in synthesis space size, sensitivity to reaction conditions, and the complexity of monitoring multiple synthesis outputs. Recent advancements in automated reactor designs for controlled and reproducible nanocrystal synthesis and intelligent experiment selection algorithms are leading to wider propagation of artificial intelligence-guided autonomous experimentation techniques in colloidal nanoscience. This review will cover the current literature on closed-loop, autonomous platforms for accelerated development of colloidal nanomaterials and discuss the critical features and strategies for developing autonomous robotic experimentation systems suitable to problems in colloidal nanoscience, while providing the context, effectiveness, and prospects of each technique. Then, we will discuss some immediate opportunities in the field for more rapid technological advancement and colloidal nanomaterial discovery.