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Meeting MS&T25: Materials Science & Technology
Symposium Autonomous Platforms for Designing and Understanding Materials
Presentation Title From deposition to degradation of thin films and devices through autonomous experimentation
Author(s) Davi Febba, Stephen Schaefer, Brooks Tellekamp, William Callahan, Andriy Zakutayev
On-Site Speaker (Planned) Davi Febba
Abstract Scope Autonomous experimentation is transforming materials science. By automating repetitive tasks and using artificial-intelligence-driven experiment planners, we can accelerate the materials-discovery pipeline while minimizing human intervention, freeing researchers to focus on higher-level questions. In this presentation, we will summarize recent progress at NREL on (i) autonomous sputtering and molecular beam epitaxy growth of thin films and (ii) long-term degradation studies of electronic devices under extreme environmental condition. These platforms employ genetic algorithms, computer-vision feedback, and multidimensional Bayesian optimization to identify the most informative experiments in real time, maximizing information gain per unit time. Finally, we will discuss the practical challenges of retrofitting existing laboratories for autonomy—including instrument-level automation, workflow orchestration, data-management infrastructure, and subnetworks that link remote servers to command-and-control computers—and outline solutions that have enabled seamless, closed-loop operation of scientific instruments in the context of autonomous experimentation at NREL.

OTHER PAPERS PLANNED FOR THIS SYMPOSIUM

Digital laboratory with modular measurement system and standardized data format
Ferroics Reimagined with Causal Machine Learning
From deposition to degradation of thin films and devices through autonomous experimentation
Knowledge Graphs for Chemical Synthesis: Using Historical Data for Querying and Semantic Reasoning
Materials discovery using deep microscopic optics
Operating autonomous laboratories with AI agents
Robust reflection set matching for online phase identification from X-ray diffraction data
Self Driving Labs and and Digital Twins
Sparse Sampling and Inpainting for High-Throughput Scanning Transmission Electron Microscopy
Towards Autonomous Imaging and Analysis of Magnetic Domains

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