Author: Eunice I. Aissi
Thesis Supervisor: Tonio Buonassisi
Abstract
Materials development is the foundation for innovation in many industries and fields, however, this process is traditionally slow and resource-intensive. Most often, new materials are developed and characterized on the time scale of years which can limit the pace of scientific and industry innovation. I address the material synthesis and characterization bottleneck by presenting a framework that I believe is suitable for smaller labs: Self-built, low-cost automation. The design philosophy is to de-risk the lab automation process by keeping costs low, failing fast, and leveraging common resources in electronic systems and additive manufacturing. I present an improved version of a low-cost but high-throughput inkjet material printer developed by Siemenn et al. and adapted to operation in the glovebox, hood, and benchtop environments. The tool is capable of depositing gradients of droplets with unique compositions at a rate of up to 1000 materials per minute, is self-built and cost around $500. I also present a computer-vision-enabled high-throughput material characterization algorithm for stability quantification through color degradation. The synthesis and characterization methods are validated on a methylammonium lead iodide (MAPbI3) and formamidinium lead iodide (FAPbI3) perovskite material system. X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and hyperspectral imaging measurements show equivalence between high-throughput synthesis and more traditional spin-coating methods. Results obtained through the high-throughput stability characterization method are aligned with stability trends reported in literature and has an accuracy of 96.9% when compared to ground-truth degradation as measured by a domain expert.
Fig 1. The second iteration of Archerfish was developed to address the chemical limitations of the initial proof of concept. Mainly, the system was fitted with wireless communication and a GUI for use with lead containing perovskites inside a glovebox.
Fig 2. (A) FAPbI3 - MAPbI3 hybrid organic-inorganic perovskite droplets printed using the Archerfish system where characterized using X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and hyperspectral imaging. (B) A Δ2θ of 0.152 deg occurs in an XRD peak corresponding in a change of composition from MAPbI3 to FAPbI3. (C) Similarly, a change in the peak corresponding to the C = NH2 double bond found in formamidinium indicates a gradient from MAPbI3 to FAPbI3. (D) Lastly, a gradual change in the reflectance spectra of the droplets obtained using hyperspectral imaging indicate a change in composition from pure MAPbI3 to FAPbI3. This figure and its measurements are reproduced with permission from Siemenn and Aissi et al. [8], the measurements where taken by Fang Sheng and Alexander Siemenn.
Selected Figures
Keywords: High-throughput laboratory automation; scalable computer vision segmentation; perovskite composition engineering; pinch valve