About this Abstract |
Meeting |
MS&T22: Materials Science & Technology
|
Symposium
|
AI for Big Data Problems in Advanced Imaging, Materials Modeling and Automated Synthesis
|
Presentation Title |
B-1: Autonomous Closed Loop Synthesis of Gold Nanorods via a Modular Chemical-Handling Robotic Platform |
Author(s) |
Morgan Chen, Ari Fiorino, Aarti Singh, Reeja Jayan |
On-Site Speaker (Planned) |
Morgan Chen |
Abstract Scope |
Materials research campaigns often encounter challenges with navigating complex and high-dimensional parameter spaces to uncover scientific insights. Consequently, productivity can be hindered by the practical limitations of obtaining and analyzing vast or sufficient experimental datasets required to obtain a functional understanding of a phenomenon of interest. We build upon a modular programmable chemical-handling device as a hardware platform to leverage machine learning algorithms to accelerate the pace at which scientific conclusions can be extracted from minimal datasets or large experimental parameter spaces. We present a closed-loop autonomous system to optimize the conditions for targeted synthesis of gold nanorods using in-line UV-Vis spectroscopy. Although they have diverse functions in electronic, optical, and biomedical applications, gold nanomaterials are confronted with suboptimal production reproducibility and yield. Therefore, we harness algorithm-driven mechanization to enhance the precision, fidelity, and yield of gold nanorods. |