Machine Learning in Scanning Probe Microscopy

INVITED · M36 · ID: 788567

Presentations

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

    ORAL · Invited

    –

    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

    –

    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

    –

    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

    View abstract →

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

    ORAL · Invited

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    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

    View abstract →

  • Universal image segmentation for optical identification of 2D materials

    ORAL · Invited

    –

    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 →