Abstract
This study introduces the integration of dynamic computer vision–enabled imaging with electron energy loss spectroscopy (EELS) in scanning transmission electron microscopy (STEM). This approach involves real-time discovery and analysis of atomic structures as they form, allowing us to observe the evolution of material properties at the atomic level, capturing transient states traditional techniques often miss. Rapid object detection and action system enhances the efficiency and accuracy of STEM-EELS by autonomously identifying and targeting only areas of interest. This machine learning (ML)–based approach differs from classical ML in that it must be executed on the fly, not using static data. We apply this technology to V-doped MoS2, uncovering insights into defect formation and evolution under electron beam exposure. This approach opens uncharted avenues for exploring and characterizing materials in dynamic states, offering a pathway to increase our understanding of dynamic phenomena in materials under thermal, chemical, and beam stimuli.
| Original language | English |
|---|---|
| Article number | eadn5899 |
| Journal | Science Advances |
| Volume | 10 |
| Issue number | 29 |
| DOIs | |
| State | Published - Jul 19 2024 |
Funding
This research is sponsored by the INTERSECT Initiative as part of the Laboratory Directed Research and Development Program of Oak Ridge National Laboratory, managed by UT-Battelle, LLC, for the U.S. Department of Energy under contract DE-AC05-00OR22725. The STEM experiments were supported by the U.S. Department of Energy, Office of Science, Basic Energy Sciences, Materials Sciences and Engineering Division and Oak Ridge National Laboratory’s Center for Nanophase Materials Sciences (CNMS), a U.S. Department of Energy, Office of Science User Facility. This work was supported (S.K.) by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, as part of the Energy Frontier Research Centers program: CSSAS (The Center for the Science of Synthesis Across Scales) under award number DE-SC0019288. R.T. and J.R. acknowledge funding from NEWLIMITS, a center in nCORE as part of the Semiconductor Research Corporation (SRC) program sponsored by NIST through award number 70NANB17H041 and the Department of Energy (DOE) through award number DESC0010697. Acknowledgments Funding: this research is sponsored by the inteRSect initiative as part of the laboratory directed Research and development Program of Oak Ridge national laboratory, managed by Ut-Battelle, llc, for the U.S. department of energy under contract de-Ac05-00OR22725. the SteM experiments were supported by the U.S. department of energy, Office of Science, Basic energy Sciences, Materials Sciences and engineering division and Oak Ridge national laboratory’s center for nanophase Materials Sciences (cnMS), a U.S. department of energy, Office of Science User Facility. this work was supported (S.K.) by the U.S. department of energy, Office of Science, Office of Basic energy Sciences, as part of the energy Frontier Research centers program: cSSAS (the center for the Science of Synthesis Across Scales) under award number de-Sc0019288. R.t. and J.R. acknowledge funding from neWliMitS, a center in ncORe as part of the Semiconductor Research corporation (SRc) program sponsored by niSt through award number 70nAnB17h041 and the department of energy (dOe) through award number deSc0010697. Author contributions: K.M.R. developed and implemented algorithms on the scanning transmission electron microscopes, conducted the experiments, performed analysis, and wrote the manuscript. R.t. synthesized specimens and contributed to writing the manuscript. J.R. helped synthesize specimens and contributed to writing the manuscript. S.K. contributed to writing the manuscript and supervised the project. M.Z. developed the algorithms, contributed to writing the manuscript, and supervised the project. Competing interests: the authors declare that they have no competing interests. Data and materials availability: All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials. the as-acquired live experimental data may be accessed via: https://doi.org/10.5281/ zenodo.10798656.