The momentum does not stop when the hackathon ends. The University of Tennessee, Knoxville—together with several of our co-organizers—hosts automated STEM and SPM instruments that can be fully controlled through Python-based workflows. Beyond the hackathon, if you would like to continue developing your ideas, explore autonomous experimentation, or run your codes on real microscopes, please reach out. We are delighted to collaborate on joint research projects and help you deploy your workflows on physical instruments.

Our partners in automation include Rama Vasudevan and Yongtao Liu at ORNL, Steven R. Spurgeon at the University of Colorado Boulder, and Marcos Penedo GarcĂ­a and his group at EPFL.

Representative Automated Workflows

  • Exploring combinatorial libraries using automated SPM
  • Optimizing AFM parameters using Bayesian Optimization
  • Topography-based discovery on combinatorial libraries
  • Theory–experiment co-navigation on automated AFM
  • Real-time structure–property relationship mapping
  • Deep Kernel Learning based optimization workflows in real time automated SPM and STEM
  • Atomic fabrication and control in STEM
  • Automated EDS acquisition and analysis in STEM

UTK Automated SPM

Examples of autonomous Scanning Probe Microscopy (SPM) workflows developed at UT Knoxville.

Example SPM Videos

Domain Switching Optimization with MOBO-DKL

MOBO-DKL explores how nanoscale domain structure and local neighborhood control ferroelectric switching dynamics under applied bias.

Combinatorial Library Optimization

Multi-objective Bayesian Optimization searches a combi library for compositions with large grains and low surface roughness.

Cross-Platform Automated SPM on OpenSPM

Automated tapping-mode optimization is deployed on the open-source OpenSPM controller, demonstrating portable, standards-based SPM workflows.

Automated STEM & Spectroscopy

Examples of automated STEM and spectroscopy workflows developed with Utkarsh and collaborators.

Example STEM / Spectra Videos

Reward-Driven STEM Segmentation

Reward-based optimization enables robust, unsupervised atom finding and segmentation for real-time STEM image analysis.

Automated EDS Acquisition

An autonomous workflow controls EDS acquisition to efficiently explore device structure and uncover structure–property relationships.

More Examples

For more videos and demonstrations of automated SPM and STEM workflows, visit https://ae-spm.utk.edu/about/.