(Keynote) Automated / Autonomous Platforms for Synthesis, Purification, and Characterization of Quantum Dots

Abstract

Controlling composition, structure, and thus properties of nanomaterials continues to be of importance to numerous fields. For example, applications of quantum dots range from displays and bioimaging, to metal nanoparticles for (electro-) catalytic conversions. The vastness of synthesis parameter space, in combination with still limited understanding of the nucleation and growth mechanisms for many quantum dots systems still hampers progress in identifying nanomaterials with desired properties for existing and newly envisioned purposes. Furthermore, the identification of optimal synthesis recipes for these nanostructures remains a major hurdle.This presentation will report on the development and application a number of enabling capabilities for the synthesis and characterization of quantum dots, achieved through reactor engineering. We demonstrate how the use of automated flow reactors not only helps in run-to-run reproducibility but also in uncovering mechanistic information. Examples include reactors with dedicated nucleation, growth, and shell formation zones, and investigation that revealed mechanistic insight of how water concentration affects QD synthesis outcome. We also employed an autonomous flow reactor system to map synthesis parameter space of specific QD systems, a project that relied on fast, fully automated in-situ characterization using UV-vis or photo-luminescence in combination with multi-step machine learning workflows The utility of flow reactors, however, is limited when considering chemistries with longer reaction times. Hence, more recently we developed a fully automated batch reactor for parameter space mapping of QD synthesis via hot injection, the most frequently used method in both QD research and production at scale. This batch platform is being augmented with purification capabilities, to address some of the challenges of in-line, in-situ characterization of raw reaction mixtures, and to enable using advanced optical and structural characterization methods to provide insight into the actual structure of the QD materials.