Machine Learning in Scanning Probe Microscopy

Presentations

• TopoStats, a tool to discover the hidden structures and states of biomolecule

  ORAL · Invited

  March 8, 2023, 8:00 AM – March 8, 2023, 8:36 AM

  Publication: Pyne, A. L. B. et al. Base-pair resolution analysis of the effect of supercoiling on DNA flexibility and major groove recognition by triplex-forming oligonucleotides. Nature Communications 12, 1053 (2021)
  Beton, J. G. et al. TopoStats – A program for automated tracing of biomolecules from AFM images. Methods 193, 68–79 (2021)
  dos Santos, Á. et al. Autophagy receptor NDP52 alters DNA conformation to modulate RNA Polymerase II transcription. bioRxiv 2022.02.01.478690 (2022)

  Presenters

  • Alice Pyne

    • University of Sheffield
    • University of Sheffield, UK

  Authors

  • Alice Pyne

    • University of Sheffield
    • University of Sheffield, UK

  View abstract →

• Machine Learning to classify, predict structure-property relationships, and detect artifacts in AFM images

  ORAL · Invited

  March 8, 2023, 8:36 AM – March 8, 2023, 9:12 AM

  Publication: Yablon et al., MRS Communications, Volume 11, Issue 6, p.962-968 DOI
  10.1557/s43579-021-00103-2
  
  Yablon et al., Machine Learning in Materials Informatics: Methods and Applications
  Chapter 3pp 51-64 10.1021/bk-2022-1416.ch003

  Presenters

  • Dalia Yablon

    • SurfaceChar

  Authors

  • Dalia Yablon

    • SurfaceChar

  • Ishita Chakraborty

    • Cognite

  • John Thornton

    • bruker

  • Bede Pittenger

    • bruker

  View abstract →

• AI-driven atomic manipulation and characterization in the STEM

  ORAL · Invited

  March 8, 2023, 9:12 AM – March 8, 2023, 9:48 AM

  Publication: 1. Roccapriore K.M.., Boebinger M.G., Dyck O., Ghosh A., Unocic R.R., Kalinin, S.V., Ziatdinov M. "Probing Electron Beam Induced Transformations on a Single Defect Level via Automated Scanning Transmission Electron Microscopy." ACS Nano 2022 10.1021/acsnano.2c07451
  2. Roccapriore K.M., Dyck O., Oxley M.P., Ziatdinov M., Kalinin S.V. "Automated Experiment in 4D-STEM: Exploring Emergent Physics and Structural Behaviors." ACS Nano 2022, 16, 5, 7605–7614. 10.1021/acsnano.1c11118
  3. Kalinin S.V., Vasudevan R.K., Liu Y., Ghosh A., Roccapriore K.M., Ziatdinov M. "Microscopy is All You Need." arXiv:2210.06526
  4. Mukherjee D., Roccapriore K.M., Al-Najjar A., Ghosh A., Hinkle J.D., Lupini A.R., Vasudevan R.K., Kalinin S.V., Ovchinnikova O.S., Ziatdinov M., Rao N.S. "A roadmap for edge computing enabled automated multidimensional transmission electron microscopy." arXiv:2210.02538
  5. Roccapriore K.M., Ziatdinov M., Lupini A.R., Singh A.P., Philipose U., Kalinin S.V. "Discovering Invariant Spatial Features in Electron Energy Loss Spectroscopy Images on the Mesoscopic and Atomic Levels." arXiv:2202.00657
  6. Roccapriore K.M., Cho S.-H., Lupini A.R., Milliron D.J., Kalinin S.V., Sculpting the plasmonic responses of nanoparticles by directed electron beam irradiation. Small 10.1002/smll.202105099
  7. Roccapriore K.M., Kalinin S.V., Ziatdinov M., Physics discovery in nanoplasmonic systems via autonomous experiments in Scanning Transmission Electron Microscopy. Adv Sci 2022. 10.1002/advs.202203422
  8. Roccapriore K.M., Ziatdinov M., Cho S.-H., Hachtel J.A., Kalinin S.V., Predictability of localized plasmonic responses in nanoparticle assemblies. Small, 17, 2100181

  Presenters

  • Kevin M Roccapriore

    • Oak Ridge National Lab
    • Oak Ridge National Laboratory

  Authors

  • Kevin M Roccapriore

    • Oak Ridge National Lab
    • Oak Ridge National Laboratory

  • Maxim Ziatdinov

    • Oak Ridge National Lab

  • Matthew Boebinger

    • Oak Ridge National Laboratory

  • Ondrej Dyck

    • Oak Ridge National Laboratory

  • Ayana Ghosh

    • Oak Ridge National Lab

  • Raymond Unocic

    • Oak Ridge National Laboratory

  • Sergei V Kalinin

    • University of Tennessee
    • University of Tennessee, Knoxville

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• Identification of geometrical features of cell surface responsible for cancer aggressiveness: Machine learning analysis of atomic force microscopy images.

  ORAL · Invited

  March 8, 2023, 9:48 AM – March 8, 2023, 10:24 AM

  Publication: Previous work.
  Prasad, S., Rankine, A., Prasad, T., Song, P., Dokukin, M.E., Makarova, N., Backman, V. and Sokolov, I. (2021), Atomic Force Microscopy Detects the Difference in Cancer Cells of Different Neoplastic Aggressiveness via Machine Learning. Adv. NanoBiomed Res., 1: 2000116. https://doi.org/10.1002/anbr.202000116

  Presenters

  • Mikhail Petrov

    • Tufts University

  Authors

  • Mikhail Petrov

    • Tufts University

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• Universal image segmentation for optical identification of 2D materials

  ORAL · Invited

  March 8, 2023, 10:24 AM – March 8, 2023, 11:00 AM

  Publication: Sterbentz, R.M., Haley, K.L. & Island, J.O. Universal image segmentation for optical identification of 2D materials. Sci Rep 11, 5808 (2021). https://doi.org/10.1038/s41598-021-85159-9

  Presenters

  • Randy M Sterbentz

    • University of Nevada, Las Vegas

  Authors

  • Randy M Sterbentz

    • University of Nevada, Las Vegas

  • Joshua Island

    • University of Nevada, Las Vegas

  • Kristine Haley

    • University of Nevada - Las Vegas

  View abstract →