Autonomous Nanocrystal Doping by Self‐Driving Fluidic Micro‐Processors

Abstract

Lead halide perovskite (LHP) nanocrystals (NCs) are considered an emerging class of advanced functional materials with numerous outstanding optoelectronic characteristics. Despite their success in the field, their precision synthesis and fundamental mechanistic studies remain a challenge. The vast colloidal synthesis and processing parameters of LHP NCs in combination with the batch‐to‐batch and lab‐to‐lab variation problems further complicate their progress. In response, a self‐driving fluidic micro‐processor is presented for accelerated navigation through the complex synthesis and processing parameter space of NCs with multistage chemistries. The capability of the developed autonomous experimentation strategy is demonstrated for a time‐, material‐, and labor‐efficient search through the sequential halide exchange and cation doping reactions of LHP NCs. Next, a machine learning model of the modular fluidic micro‐processors is autonomously built for accelerated fundamental studies of the in‐flow metal cation doping of LHP NCs. The surrogate model of the sequential halide exchange and cation doping reactions of LHP NCs is then utilized for five closed‐loop synthesis campaigns with different target NC doping levels. The precise and intelligent NC synthesis and processing strategy, presented herein, can be further applied toward the autonomous discovery and development of novel impurity‐doped NCs with applications in next‐generation energy technologies.

Metal-doping of halide perovskite nanocrystals for energy and environmental photocatalysis: challenges and prospects

“…Thus, this strategy has become one of the most effective ways to optimize photocatalytic performance further by boosting many unique properties to solve the problems of HPNCs mentioned above. 39…”

An Object-Oriented Framework to Enable Workflow Evolution across Materials Acceleration Platforms

“…Considerable research has been conducted on using MAPs for metal halide perovskite research, such as for investigating anti-solvents [29][30][31] , solution synthesis of perovskites [32][33][34][35] , thin film processing of perovskites 36,37 , and device fabrication. Perovskites are amenable to solution processing, and the vast compositional space for exploration makes them an ideal candidate for HT studies.…”

An Object-Oriented Framework to Enable Workflow Evolution across Materials Acceleration Platforms

“…Considerable research has been conducted on using MAPs for metal halide perovskite research, such as for investigating anti-solvents [29][30][31] , solution synthesis of perovskites [32][33][34][35] , thin film processing of perovskites 36,37 , and device fabrication. Perovskites are amenable to solution processing, and the vast compositional space for exploration makes them an ideal candidate for HT studies.…”