A framework for fully autonomous design of materials via multiobjective optimization and active learning: challenges and next steps

1 code implementation • 15 Apr 2023 • Tyler H. Chang, Jakob R. Elias, Stefan M. Wild, Santanu Chaudhuri, Joseph A. Libera

In order to deploy machine learning in a real-world self-driving laboratory where data acquisition is costly and there are multiple competing design criteria, systems need to be able to intelligently sample while balancing performance trade-offs and constraints.

Active Learning Multiobjective Optimization

Flame Stability Analysis of Flame Spray Pyrolysis by Artificial Intelligence

no code implementations • 22 Oct 2020 • Jessica Pan, Joseph A. Libera, Noah H. Paulson, Marius Stan

This research has the potential to autonomously track and manage flame spray pyrolysis as well as other flame technologies by monitoring and classifying the flame stability.

BIG-bench Machine Learning

Towards Online Steering of Flame Spray Pyrolysis Nanoparticle Synthesis

1 code implementation • 16 Oct 2020 • Maksim Levental, Ryan Chard, Joseph A. Libera, Kyle Chard, Aarthi Koripelly, Jakob R. Elias, Marcus Schwarting, Ben Blaiszik, Marius Stan, Santanu Chaudhuri, Ian Foster

Flame Spray Pyrolysis (FSP) is a manufacturing technique to mass produce engineered nanoparticles for applications in catalysis, energy materials, composites, and more.