Autonomous Synthesis and Characterization Platforms for Parameter Space Mapping for Quantum Dots

<br/>Controlling composition, structure, and thus properties of nanomaterials continues to be of importance to numerous fields, with potential and realized applications for colloidal nanomaterials ranging from quantum dots for displays and bioimaging, to metal nanoparticles for (electro-) catalytic conversions. The vastness of synthesis parameter space, in combination with limited understanding of the nucleation and growth mechanisms for many nanomaterials 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. To no surprise, many research efforts have been devoted to these challenges over the past 20+ years. <br/> <br/>This presentation will focus on our efforts to develop and apply a number of enabling capabilities achieved through reactor engineering, focusing on the synthesis and characterization of quantum dots. We have demonstrated how the use of <i>automated flow reactors</i> 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. In subsequent work, we 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 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 <i>automated batch reactor</i> for parameter space mapping of QD synthesis via hot injection, the most frequently used method in both QD research and in QD 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. <br/>In summary, we developed an integrated approach for the rapid synthesis, purification, and characterization of QDs to determine structural properties, with ongoing work focusing on structural mapping of QD synthesis.