1
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Peters JJP, Reed BW, Jimbo Y, Noguchi K, Müller KH, Porter A, Masiel DJ, Jones L. Event-responsive scanning transmission electron microscopy. Science 2024; 385:549-553. [PMID: 39088619 DOI: 10.1126/science.ado8579] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2024] [Accepted: 06/17/2024] [Indexed: 08/03/2024]
Abstract
An ever-present limitation of transmission electron microscopy is the damage caused by high-energy electrons interacting with any sample. By reconsidering the fundamentals of imaging, we demonstrate an event-responsive approach to electron microscopy that delivers more information about the sample for a given beam current. Measuring the time to achieve an electron count threshold rather than waiting a predefined constant time improves the information obtained per electron. The microscope was made to respond to these events by blanking the beam, thus reducing the overall dose required. This approach automatically apportions dose to achieve a given signal-to-noise ratio in each pixel, eliminating excess dose that is associated with diminishing returns of information. We demonstrate the wide applicability of our approach to beam-sensitive materials by imaging biological tissue and zeolite.
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Affiliation(s)
- Jonathan J P Peters
- Advanced Microscopy Laboratory, CRANN, Trinity College Dublin, The University of Dublin, Dublin, Ireland
- School of Physics, Trinity College Dublin, The University of Dublin, Dublin, Ireland
- turboTEM Ltd., Dublin, Ireland
| | | | - Yu Jimbo
- JEOL Ltd. Akishima, Tokyo, Japan
| | | | - Karin H Müller
- Faculty of Engineering, Department of Materials, Imperial College London, London, UK
| | - Alexandra Porter
- Faculty of Engineering, Department of Materials, Imperial College London, London, UK
| | | | - Lewys Jones
- Advanced Microscopy Laboratory, CRANN, Trinity College Dublin, The University of Dublin, Dublin, Ireland
- School of Physics, Trinity College Dublin, The University of Dublin, Dublin, Ireland
- turboTEM Ltd., Dublin, Ireland
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2
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Boebinger MG, Yilmaz DE, Ghosh A, Misra S, Mathis TS, Kalinin SV, Jesse S, Gogotsi Y, van Duin ACT, Unocic RR. Direct Fabrication of Atomically Defined Pores in MXenes Using Feedback-Driven STEM. SMALL METHODS 2024:e2400203. [PMID: 38803318 DOI: 10.1002/smtd.202400203] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/07/2024] [Revised: 05/05/2024] [Indexed: 05/29/2024]
Abstract
Controlled fabrication of nanopores in 2D materials offer the means to create robust membranes needed for ion transport and nanofiltration. Techniques for creating nanopores have relied upon either plasma etching or direct irradiation; however, aberration-corrected scanning transmission electron microscopy (STEM) offers the advantage of combining a sub-Å sized electron beam for atomic manipulation along with atomic resolution imaging. Here, a method for automated nanopore fabrication is utilized with real-time atomic visualization to enhance the mechanistic understanding of beam-induced transformations. Additionally, an electron beam simulation technique, Electron-Beam Simulator (E-BeamSim) is developed to observe the atomic movements and interactions resulting from electron beam irradiation. Using the MXene Ti3C2Tx, the influence of temperature on nanopore fabrication is explored by tracking atomic transformations and find that at room temperature the electron beam irradiation induces random displacement and results in titanium pileups at the nanopore edge, which is confirmed by E-BeamSim. At elevated temperatures, after removal of the surface functional groups and with the increased mobility of atoms results in atomic transformations that lead to the selective removal of atoms layer by layer. This work can lead to the development of defect engineering techniques within functionalized MXene layers and other 2D materials.
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Affiliation(s)
- Matthew G Boebinger
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA
| | - Dundar E Yilmaz
- Department of Mechanical Engineering, The Pennsylvania State University, University Park, PA, 16802, USA
| | - Ayana Ghosh
- Computational Sciences and Engineering Division, Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA
| | - Sudhajit Misra
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA
| | - Tyler S Mathis
- A.J. Drexel Nanomaterials Institute and Department of Materials Science and Engineering, Drexel University, Philadelphia, PA, 19104, USA
| | - Sergei V Kalinin
- Department of Materials Science and Engineering, University of Tennessee, Knoxville, TN, 37996, USA
| | - Stephen Jesse
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA
| | - Yury Gogotsi
- A.J. Drexel Nanomaterials Institute and Department of Materials Science and Engineering, Drexel University, Philadelphia, PA, 19104, USA
| | - Adri C T van Duin
- Department of Mechanical Engineering, The Pennsylvania State University, University Park, PA, 16802, USA
| | - Raymond R Unocic
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA
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3
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Liu Y, Roccapriore K, Checa M, Valleti SM, Yang JC, Jesse S, Vasudevan RK. AEcroscopy: A Software-Hardware Framework Empowering Microscopy Toward Automated and Autonomous Experimentation. SMALL METHODS 2024:e2301740. [PMID: 38639016 DOI: 10.1002/smtd.202301740] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Revised: 03/31/2024] [Indexed: 04/20/2024]
Abstract
Microscopy has been pivotal in improving the understanding of structure-function relationships at the nanoscale and is by now ubiquitous in most characterization labs. However, traditional microscopy operations are still limited largely by a human-centric click-and-go paradigm utilizing vendor-provided software, which limits the scope, utility, efficiency, effectiveness, and at times reproducibility of microscopy experiments. Here, a coupled software-hardware platform is developed that consists of a software package termed AEcroscopy (short for Automated Experiments in Microscopy), along with a field-programmable-gate-array device with LabView-built customized acquisition scripts, which overcome these limitations and provide the necessary abstractions toward full automation of microscopy platforms. The platform works across multiple vendor devices on scanning probe microscopes and electron microscopes. It enables customized scan trajectories, processing functions that can be triggered locally or remotely on processing servers, user-defined excitation waveforms, standardization of data models, and completely seamless operation through simple Python commands to enable a plethora of microscopy experiments to be performed in a reproducible, automated manner. This platform can be readily coupled with existing machine-learning libraries and simulations, to provide automated decision-making and active theory-experiment optimization to turn microscopes from characterization tools to instruments capable of autonomous model refinement and physics discovery.
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Affiliation(s)
- Yongtao Liu
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA
| | - Kevin Roccapriore
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA
| | - Marti Checa
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA
| | - Sai Mani Valleti
- Bredesen Center for Interdisciplinary Research, University of Tennessee, Knoxville, TN, 37996, USA
| | - Jan-Chi Yang
- Department of Physics, National Cheng Kung University, Tainan, 70101, Taiwan
| | - Stephen Jesse
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA
| | - Rama K Vasudevan
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA
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4
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Dyck O, Lupini AR, Jesse S. A Platform for Atomic Fabrication and In Situ Synthesis in a Scanning Transmission Electron Microscope. SMALL METHODS 2023; 7:e2300401. [PMID: 37415539 DOI: 10.1002/smtd.202300401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Revised: 05/30/2023] [Indexed: 07/08/2023]
Abstract
The engineering of quantum materials requires the development of tools able to address various synthesis and characterization challenges. These include the establishment and refinement of growth methods, material manipulation, and defect engineering. Atomic-scale modification will be a key enabling factor for engineering quantum materials where desired phenomena are critically determined by atomic structures. Successful use of scanning transmission electron microscopes (STEMs) for atomic scale material manipulation has opened the door for a transformed view of what can be accomplished using electron-beam-based strategies. However, serious obstacles exist on the pathway from possibility to practical reality. One such obstacle is the in situ delivery of atomized material in the STEM to the region of interest for further fabrication processes. Here, progress on this front is presented with a view toward performing synthesis (deposition and growth) processes in a scanning transmission electron microscope in combination with top-down control over the reaction region. An in situ thermal deposition platform is presented, tested, and deposition and growth processes are demonstrated. In particular, it is shown that isolated Sn atoms can be evaporated from a filament and caught on the nearby sample, demonstrating atomized material delivery. This platform is envisioned to facilitate real-time atomic resolution imaging of growth processes and open new pathways toward atomic fabrication.
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Affiliation(s)
- Ondrej Dyck
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, 1 Bethel Valley Rd., Oak Ridge, TN, 37830, USA
| | - Andrew R Lupini
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, 1 Bethel Valley Rd., Oak Ridge, TN, 37830, USA
| | - Stephen Jesse
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, 1 Bethel Valley Rd., Oak Ridge, TN, 37830, USA
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5
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Peters JJP, Mullarkey T, Hedley E, Müller KH, Porter A, Mostaed A, Jones L. Electron counting detectors in scanning transmission electron microscopy via hardware signal processing. Nat Commun 2023; 14:5184. [PMID: 37626044 PMCID: PMC10457289 DOI: 10.1038/s41467-023-40875-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Accepted: 08/10/2023] [Indexed: 08/27/2023] Open
Abstract
Transmission electron microscopy is a pivotal instrument in materials and biological sciences due to its ability to provide local structural and spectroscopic information on a wide range of materials. However, the electron detectors used in scanning transmission electron microscopy are often unable to provide quantified information, that is the number of electrons impacting the detector, without exhaustive calibration and processing. This results in arbitrary signal values with slow response times that cannot be used for quantification or comparison to simulations. Here we demonstrate and optimise a hardware signal processing approach to augment electron detectors to perform single electron counting.
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Affiliation(s)
- Jonathan J P Peters
- Advanced Microscopy Laboratory (AML), Trinity College Dublin, the University of Dublin, Dublin, Ireland.
- School of Physics, Trinity College Dublin, the University of Dublin, Dublin, Ireland.
| | - Tiarnan Mullarkey
- Advanced Microscopy Laboratory (AML), Trinity College Dublin, the University of Dublin, Dublin, Ireland
- Centre for Doctoral Training in the Advanced Characterisation of Materials, AMBER Centre, Dublin, Ireland
| | - Emma Hedley
- Department of Materials, University of Oxford, Oxford, UK
| | - Karin H Müller
- Faculty of Engineering, Department of Materials, Imperial College London, London, UK
| | - Alexandra Porter
- Faculty of Engineering, Department of Materials, Imperial College London, London, UK
| | - Ali Mostaed
- Department of Materials, University of Oxford, Oxford, UK
| | - Lewys Jones
- Advanced Microscopy Laboratory (AML), Trinity College Dublin, the University of Dublin, Dublin, Ireland
- School of Physics, Trinity College Dublin, the University of Dublin, Dublin, Ireland
- Centre for Doctoral Training in the Advanced Characterisation of Materials, AMBER Centre, Dublin, Ireland
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6
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Dyck O, Yeom S, Lupini AR, Swett JL, Hensley D, Yoon M, Jesse S. Top-Down Fabrication of Atomic Patterns in Twisted Bilayer Graphene. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2023; 35:e2302906. [PMID: 37309684 DOI: 10.1002/adma.202302906] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Revised: 05/23/2023] [Indexed: 06/14/2023]
Abstract
Atomic-scale engineering typically involves bottom-up approaches, leveraging parameters such as temperature, partial pressures, and chemical affinity to promote spontaneous arrangement of atoms. These parameters are applied globally, resulting in atomic-scale features scattered probabilistically throughout the material. In a top-down approach, different regions of the material are exposed to different parameters, resulting in structural changes varying on the scale of the resolution. In this work, the application of global and local parameters is combined in an aberration-corrected scanning transmission electron microscope (STEM) to demonstrate atomic-scale precision patterning of atoms in twisted bilayer graphene. The focused electron beam is used to define attachment points for foreign atoms through the controlled ejection of carbon atoms from the graphene lattice. The sample environment is staged with nearby source materials such that the sample temperature can induce migration of the source atoms across the sample surface. Under these conditions, the electron-beam (top-down) enables carbon atoms in the graphene to be replaced spontaneously by diffusing adatoms (bottom-up). Using image-based feedback control, arbitrary patterns of atoms and atom clusters are attached to the twisted bilayer graphene with limited human interaction. The role of substrate temperature on adatom and vacancy diffusion is explored by first-principles simulations.
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Affiliation(s)
- Ondrej Dyck
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, TN, 37830, USA
| | - Sinchul Yeom
- Materials Science and Technology Division, Oak Ridge National Laboratory, Oak Ridge, TN, 37830, USA
| | - Andrew R Lupini
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, TN, 37830, USA
| | - Jacob L Swett
- Biodesign Institute, Arizona State University, Tempe, AZ, 87287, USA
| | - Dale Hensley
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, TN, 37830, USA
| | - Mina Yoon
- Materials Science and Technology Division, Oak Ridge National Laboratory, Oak Ridge, TN, 37830, USA
| | - Stephen Jesse
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, TN, 37830, USA
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7
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Dyck O, Lupini AR, Yoon M, Jesse S. E-beam Patterning of Atoms in Graphene. MICROSCOPY AND MICROANALYSIS : THE OFFICIAL JOURNAL OF MICROSCOPY SOCIETY OF AMERICA, MICROBEAM ANALYSIS SOCIETY, MICROSCOPICAL SOCIETY OF CANADA 2023; 29:1368-1369. [PMID: 37613717 DOI: 10.1093/micmic/ozad067.703] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/25/2023]
Affiliation(s)
- Ondrej Dyck
- Center for Nanophase Materials Science, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Andrew R Lupini
- Center for Nanophase Materials Science, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Mina Yoon
- Materials Science and Technology Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Stephen Jesse
- Center for Nanophase Materials Science, Oak Ridge National Laboratory, Oak Ridge, TN, USA
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8
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Boebinger MG, Brea C, Ding LP, Misra S, Olunloyo O, Yu Y, Xiao K, Lupini AR, Ding F, Hu G, Ganesh P, Jesse S, Unocic RR. The Atomic Drill Bit: Precision Controlled Atomic Fabrication of 2D Materials. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2023; 35:e2210116. [PMID: 36635517 DOI: 10.1002/adma.202210116] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 01/02/2023] [Indexed: 06/17/2023]
Abstract
The ability to deterministically fabricate nanoscale architectures with atomic precision is the central goal of nanotechnology, whereby highly localized changes in the atomic structure can be exploited to control device properties at their fundamental physical limit. Here, an automated, feedback-controlled atomic fabrication method is reported and the formation of 1D-2D heterostructures in MoS2 is demonstrated through selective transformations along specific crystallographic orientations. The atomic-scale probe of an aberration-corrected scanning transmission electron microscope (STEM) is used, and the shape and symmetry of the scan pathway relative to the sample orientation are controlled. The focused and shaped electron beam is used to reliably create Mo6 S6 nanowire (MoS-NW) terminated metallic-semiconductor 1D-2D edge structures within a pristine MoS2 monolayer with atomic precision. From these results, it is found that a triangular beam path aligned along the zig-zag sulfur terminated (ZZS) direction forms stable MoS-NW edge structures with the highest degree of fidelity without resulting in disordering of the surrounding MoS2 monolayer. Density functional theory (DFT) calculations and ab initio molecular dynamic simulations (AIMD) are used to calculate the energetic barriers for the most stable atomic edge structures and atomic transformation pathways. These discoveries provide an automated method to improve understanding of atomic-scale transformations while opening a pathway toward more precise atomic-scale engineering of materials.
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Affiliation(s)
- Matthew G Boebinger
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, 1 Bethel Valley Road, Oak Ridge, TN, 37830, USA
| | - Courtney Brea
- Department of Chemistry and Biochemistry, Queens College, City University of New York, 65-30 Kissena Blvd, Flushing, NY, 11367, USA
| | - Li-Ping Ding
- Department of Physics, Shaanxi University of Science and Technology, Xi'an Weiyang University Park, Xi'an, Shaanxi Province, China
| | - Sudhajit Misra
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, 1 Bethel Valley Road, Oak Ridge, TN, 37830, USA
| | - Olugbenga Olunloyo
- Department of Physics and Astronomy, University of Tennessee, 1408 Circle Dr, Knoxville, TN, 37996, USA
| | - Yiling Yu
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, 1 Bethel Valley Road, Oak Ridge, TN, 37830, USA
- School of Physics and Technology, Wuhan University, Wuchang District, Wuhan, Hubei, 430072, China
| | - Kai Xiao
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, 1 Bethel Valley Road, Oak Ridge, TN, 37830, USA
| | - Andrew R Lupini
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, 1 Bethel Valley Road, Oak Ridge, TN, 37830, USA
| | - Feng Ding
- Centre for Multidimensional Carbon Materials, Institute for Basic Science, 50 UNIST-gil, Ulsan, 44919, South Korea
- School of Materials Science and Engineering, Ulsan Institute of Science and Technology, 50 UNIST-gil, Ulsan, 44919, South Korea
| | - Guoxiang Hu
- Department of Chemistry and Biochemistry, Queens College, City University of New York, 65-30 Kissena Blvd, Flushing, NY, 11367, USA
| | - Panchapakesan Ganesh
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, 1 Bethel Valley Road, Oak Ridge, TN, 37830, USA
| | - Stephen Jesse
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, 1 Bethel Valley Road, Oak Ridge, TN, 37830, USA
| | - Raymond R Unocic
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, 1 Bethel Valley Road, Oak Ridge, TN, 37830, USA
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9
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Dyck O, Swett JL, Evangeli C, Lupini AR, Mol J, Jesse S. Contrast Mechanisms in Secondary Electron e-Beam-Induced Current (SEEBIC) Imaging. MICROSCOPY AND MICROANALYSIS : THE OFFICIAL JOURNAL OF MICROSCOPY SOCIETY OF AMERICA, MICROBEAM ANALYSIS SOCIETY, MICROSCOPICAL SOCIETY OF CANADA 2022; 28:1-17. [PMID: 35644675 DOI: 10.1017/s1431927622000824] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Over the last few years, a new mode for imaging in the scanning transmission electron microscope (STEM) has gained attention as it permits the direct visualization of sample conductivity and electrical connectivity. When the electron beam (e-beam) is focused on the sample in the STEM, secondary electrons (SEs) are generated. If the sample is conductive and electrically connected to an amplifier, the SE current can be measured as a function of the e-beam position. This scenario is similar to the better-known scanning electron microscopy-based technique, electron beam-induced current imaging, except that the signal in the STEM is generated by the emission of SEs, hence the name secondary electron e-beam-induced current (SEEBIC), and in this case, the current flows in the opposite direction. Here, we provide a brief review of recent work in this area, examine the various contrast generation mechanisms associated with SEEBIC, and illustrate its use for the characterization of graphene nanoribbon devices.
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Affiliation(s)
- Ondrej Dyck
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Jacob L Swett
- Biodesign Institute, Arizona State University, Tempe, AZ 87287, USA
- Department of Materials, University of Oxford, Oxford OX1 3PH, UK
| | | | - Andrew R Lupini
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Jan Mol
- School of Physics and Astronomy, Queen Mary University of London, London E1 4NS, UK
| | - Stephen Jesse
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, TN, USA
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10
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Ede JM. Adaptive partial scanning transmission electron microscopy with reinforcement learning. MACHINE LEARNING: SCIENCE AND TECHNOLOGY 2021. [DOI: 10.1088/2632-2153/abf5b6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022] Open
Abstract
Abstract
Compressed sensing can decrease scanning transmission electron microscopy electron dose and scan time with minimal information loss. Traditionally, sparse scans used in compressed sensing sample a static set of probing locations. However, dynamic scans that adapt to specimens are expected to be able to match or surpass the performance of static scans as static scans are a subset of possible dynamic scans. Thus, we present a prototype for a contiguous sparse scan system that piecewise adapts scan paths to specimens as they are scanned. Sampling directions for scan segments are chosen by a recurrent neural network (RNN) based on previously observed scan segments. The RNN is trained by reinforcement learning to cooperate with a feedforward convolutional neural network that completes the sparse scans. This paper presents our learning policy, experiments, and example partial scans, and discusses future research directions. Source code, pretrained models, and training data is openly accessible at https://github.com/Jeffrey-Ede/adaptive-scans.
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11
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Ortega E, Nicholls D, Browning ND, de Jonge N. High temporal-resolution scanning transmission electron microscopy using sparse-serpentine scan pathways. Sci Rep 2021; 11:22722. [PMID: 34811427 PMCID: PMC8608981 DOI: 10.1038/s41598-021-02052-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Accepted: 11/01/2021] [Indexed: 11/25/2022] Open
Abstract
Scanning transmission electron microscopy (STEM) provides structural analysis with sub-angstrom resolution. But the pixel-by-pixel scanning process is a limiting factor in acquiring high-speed data. Different strategies have been implemented to increase scanning speeds while at the same time minimizing beam damage via optimizing the scanning strategy. Here, we achieve the highest possible scanning speed by eliminating the image acquisition dead time induced by the beam flyback time combined with reducing the amount of scanning pixels via sparse imaging. A calibration procedure was developed to compensate for the hysteresis of the magnetic scan coils. A combination of sparse and serpentine scanning routines was tested for a crystalline thin film, gold nanoparticles, and in an in-situ liquid phase STEM experiment. Frame rates of 92, 23 and 5.8 s-1 were achieved for images of a width of 128, 256, and 512 pixels, respectively. The methods described here can be applied to single-particle tracking and analysis of radiation sensitive materials.
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Affiliation(s)
- Eduardo Ortega
- INM - Leibniz Institute for New Materials, 66123, Saarbrucken, Germany
| | - Daniel Nicholls
- School of Engineering & School of Physical Sciences, University of Liverpool, Liverpool, L69 3GQ, UK
| | - Nigel D Browning
- School of Engineering & School of Physical Sciences, University of Liverpool, Liverpool, L69 3GQ, UK.,Sivananthan Laboratories, 590 Territorial Drive, Bolingbrook, IL, 60440, USA
| | - Niels de Jonge
- INM - Leibniz Institute for New Materials, 66123, Saarbrucken, Germany. .,Department of Physics, Saarland University, 66123, Saarbrucken, Germany.
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12
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Phal Y, Yeh K, Bhargava R. Design Considerations for Discrete Frequency Infrared Microscopy Systems. APPLIED SPECTROSCOPY 2021; 75:1067-1092. [PMID: 33876990 PMCID: PMC9993325 DOI: 10.1177/00037028211013372] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Discrete frequency infrared chemical imaging is transforming the practice of microspectroscopy by enabling a diversity of instrumentation and new measurement capabilities. While a variety of hardware implementations have been realized, design considerations that are unique to infrared (IR) microscopes have not yet been compiled in literature. Here, we describe the evolution of IR microscopes, provide rationales for design choices, and catalog some major considerations for each of the optical components in an imaging system. We analyze design choices that use these components to optimize performance, under their particular constraints, while providing illustrative examples. We then summarize a framework to assess the factors that determine an instrument's performance mathematically. Finally, we provide a validation approach by enumerating performance metrics that can be used to evaluate the capabilities of imaging systems or suitability for specific intended applications. Together, the presented concepts and examples should aid in understanding available instrument configurations, while guiding innovations in design of the next generation of IR chemical imaging spectrometers.
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Affiliation(s)
- Yamuna Phal
- Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, USA
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, USA
| | - Kevin Yeh
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, USA
| | - Rohit Bhargava
- Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, USA
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, USA
- Departments of Bioengineering, Mechanical Science and Engineering, Chemical and Biomolecular Engineering, and Chemistry, University of Illinois at Urbana-Champaign, Urbana, USA
- Cancer Center at Illinois, University of Illinois at Urbana-Champaign, Urbana, USA
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13
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Kalinin SV, Ziatdinov M, Hinkle J, Jesse S, Ghosh A, Kelley KP, Lupini AR, Sumpter BG, Vasudevan RK. Automated and Autonomous Experiments in Electron and Scanning Probe Microscopy. ACS NANO 2021; 15:12604-12627. [PMID: 34269558 DOI: 10.1021/acsnano.1c02104] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Machine learning and artificial intelligence (ML/AI) are rapidly becoming an indispensable part of physics research, with domain applications ranging from theory and materials prediction to high-throughput data analysis. In parallel, the recent successes in applying ML/AI methods for autonomous systems from robotics to self-driving cars to organic and inorganic synthesis are generating enthusiasm for the potential of these techniques to enable automated and autonomous experiments (AE) in imaging. Here, we aim to analyze the major pathways toward AE in imaging methods with sequential image formation mechanisms, focusing on scanning probe microscopy (SPM) and (scanning) transmission electron microscopy ((S)TEM). We argue that automated experiments should necessarily be discussed in a broader context of the general domain knowledge that both informs the experiment and is increased as the result of the experiment. As such, this analysis should explore the human and ML/AI roles prior to and during the experiment and consider the latencies, biases, and prior knowledge of the decision-making process. Similarly, such discussion should include the limitations of the existing imaging systems, including intrinsic latencies, non-idealities, and drifts comprising both correctable and stochastic components. We further pose that the role of the AE in microscopy is not the exclusion of human operators (as is the case for autonomous driving), but rather automation of routine operations such as microscope tuning, etc., prior to the experiment, and conversion of low latency decision making processes on the time scale spanning from image acquisition to human-level high-order experiment planning. Overall, we argue that ML/AI can dramatically alter the (S)TEM and SPM fields; however, this process is likely to be highly nontrivial and initiated by combined human-ML workflows and will bring challenges both from the microscope and ML/AI sides. At the same time, these methods will enable opportunities and paradigms for scientific discovery and nanostructure fabrication.
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Liu JJ. Advances and Applications of Atomic-Resolution Scanning Transmission Electron Microscopy. MICROSCOPY AND MICROANALYSIS : THE OFFICIAL JOURNAL OF MICROSCOPY SOCIETY OF AMERICA, MICROBEAM ANALYSIS SOCIETY, MICROSCOPICAL SOCIETY OF CANADA 2021; 27:1-53. [PMID: 34414878 DOI: 10.1017/s1431927621012125] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Although scanning transmission electron microscopy (STEM) images of individual heavy atoms were reported 50 years ago, the applications of atomic-resolution STEM imaging became wide spread only after the practical realization of aberration correctors on field-emission STEM/TEM instruments to form sub-Ångstrom electron probes. The innovative designs and advances of electron optical systems, the fundamental understanding of electron–specimen interaction processes, and the advances in detector technology all played a major role in achieving the goal of atomic-resolution STEM imaging of practical materials. It is clear that tremendous advances in computer technology and electronics, image acquisition and processing algorithms, image simulations, and precision machining synergistically made atomic-resolution STEM imaging routinely accessible. It is anticipated that further hardware/software development is needed to achieve three-dimensional atomic-resolution STEM imaging with single-atom chemical sensitivity, even for electron-beam-sensitive materials. Artificial intelligence, machine learning, and big-data science are expected to significantly enhance the impact of STEM and associated techniques on many research fields such as materials science and engineering, quantum and nanoscale science, physics and chemistry, and biology and medicine. This review focuses on advances of STEM imaging from the invention of the field-emission electron gun to the realization of aberration-corrected and monochromated atomic-resolution STEM and its broad applications.
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Affiliation(s)
- Jingyue Jimmy Liu
- Department of Physics, Arizona State University, Tempe, AZ85287, USA
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15
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Dyck O, Swett JL, Lupini AR, Mol JA, Jesse S. Imaging Secondary Electron Emission from a Single Atomic Layer. SMALL METHODS 2021; 5:e2000950. [PMID: 34927845 DOI: 10.1002/smtd.202000950] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/07/2020] [Revised: 12/17/2020] [Indexed: 06/14/2023]
Abstract
Graphene-based devices hold promise for a wide range of technological applications. Yet characterizing the structure and the electrical properties of a material that is only one atomic layer thick still poses technical challenges. Recent investigations indicate that secondary-electron electron-beam-induced current (SE-EBIC) imaging can reveal subtle details regarding electrical conductivity and electron transport with high spatial resolution. Here, it is shown that the SEEBIC imaging mode can be used to detect suspended single layers of graphene and distinguish between different numbers of layers. Pristine and contaminated areas of graphene are also compared to show that pristine graphene exhibits a substantially lower SE yield than contaminated regions. This SEEBIC imaging mode may provide valuable information for the engineering of surface coatings where SE yield is a priority.
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Affiliation(s)
- Ondrej Dyck
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, TN, 37830, USA
| | - Jacob L Swett
- Department of Materials, University of Oxford, Oxford, OX1 3PH, UK
| | - Andrew R Lupini
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, TN, 37830, USA
| | - Jan A Mol
- Department of Materials, University of Oxford, Oxford, OX1 3PH, UK
- School of Physics and Astronomy, Queen Mary University of London, London, E1 4NS, UK
| | - Stephen Jesse
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, TN, 37830, USA
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Abstract
Abstract
Deep learning is transforming most areas of science and technology, including electron microscopy. This review paper offers a practical perspective aimed at developers with limited familiarity. For context, we review popular applications of deep learning in electron microscopy. Following, we discuss hardware and software needed to get started with deep learning and interface with electron microscopes. We then review neural network components, popular architectures, and their optimization. Finally, we discuss future directions of deep learning in electron microscopy.
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17
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Bárcena-González G, Guerrero-Lebrero MDLP, Guerrero E, Yañez A, Nuñez-Moraleda B, Fernández-Reyes D, Real P, González D, Galindo PL. CDrift: An Algorithm to Correct Linear Drift From A Single High-Resolution STEM Image. MICROSCOPY AND MICROANALYSIS : THE OFFICIAL JOURNAL OF MICROSCOPY SOCIETY OF AMERICA, MICROBEAM ANALYSIS SOCIETY, MICROSCOPICAL SOCIETY OF CANADA 2020; 26:913-920. [PMID: 32703333 DOI: 10.1017/s1431927620001774] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
In this work, a new method to determine and correct the linear drift for any crystalline orientation in a single-column-resolved high-resolution scanning transmission electron microscopy (HR-STEM) image, which is based on angle measurements in the Fourier space, is presented. This proposal supposes a generalization and the improvement of a previous work that needs the presence of two symmetrical planes in the crystalline orientation to be applicable. Now, a mathematical derivation of the drift effect on two families of asymmetric planes in the reciprocal space is inferred. However, though it was not possible to find an analytical solution for all conditions, a simple formula was derived to calculate the drift effect that is exact for three specific rotation angles. Taking this into account, an iterative algorithm based on successive rotation/drift correction steps is devised to remove drift distortions in HR-STEM images. The procedure has been evaluated using a simulated micrograph of a monoclinic material in an orientation where all the reciprocal lattice vectors are different. The algorithm only needs four iterations to resolve a 15° drift angle in the image.
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Affiliation(s)
| | | | - Elisa Guerrero
- Department of Computer Science and Engineering, University of Cádiz, Puerto Real, Cádiz, Spain
| | - Andres Yañez
- Department of Computer Science and Engineering, University of Cádiz, Puerto Real, Cádiz, Spain
| | - Bernardo Nuñez-Moraleda
- Department of Computer Science and Engineering, University of Cádiz, Puerto Real, Cádiz, Spain
| | - Daniel Fernández-Reyes
- Department of Material Science and Metallurgy Engineering and Inorganic Chemistry, University of Cádiz, Puerto Real, Cádiz, Spain
| | - Pedro Real
- Department of Applied Mathematics I, University of Seville, Seville, Spain
| | - David González
- Department of Material Science and Metallurgy Engineering and Inorganic Chemistry, University of Cádiz, Puerto Real, Cádiz, Spain
| | - Pedro L Galindo
- Department of Computer Science and Engineering, University of Cádiz, Puerto Real, Cádiz, Spain
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18
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Ede JM, Beanland R. Partial Scanning Transmission Electron Microscopy with Deep Learning. Sci Rep 2020; 10:8332. [PMID: 32433582 PMCID: PMC7239858 DOI: 10.1038/s41598-020-65261-0] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2020] [Accepted: 04/28/2020] [Indexed: 11/09/2022] Open
Abstract
Compressed sensing algorithms are used to decrease electron microscope scan time and electron beam exposure with minimal information loss. Following successful applications of deep learning to compressed sensing, we have developed a two-stage multiscale generative adversarial neural network to complete realistic 512 × 512 scanning transmission electron micrographs from spiral, jittered gridlike, and other partial scans. For spiral scans and mean squared error based pre-training, this enables electron beam coverage to be decreased by 17.9× with a 3.8% test set root mean squared intensity error, and by 87.0× with a 6.2% error. Our generator networks are trained on partial scans created from a new dataset of 16227 scanning transmission electron micrographs. High performance is achieved with adaptive learning rate clipping of loss spikes and an auxiliary trainer network. Our source code, new dataset, and pre-trained models are publicly available.
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Affiliation(s)
- Jeffrey M Ede
- University of Warwick, Department of Physics, Coventry, CV4 7AL, UK.
| | - Richard Beanland
- University of Warwick, Department of Physics, Coventry, CV4 7AL, UK
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Zobelli A, Woo SY, Tararan A, Tizei LH, Brun N, Li X, Stéphan O, Kociak M, Tencé M. Spatial and spectral dynamics in STEM hyperspectral imaging using random scan patterns. Ultramicroscopy 2020; 212:112912. [DOI: 10.1016/j.ultramic.2019.112912] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2019] [Revised: 11/12/2019] [Accepted: 11/22/2019] [Indexed: 12/19/2022]
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20
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Wang Y, Suyolcu YE, Salzberger U, Hahn K, Srot V, Sigle W, van Aken PA. Correcting the linear and nonlinear distortions for atomically resolved STEM spectrum and diffraction imaging. Microscopy (Oxf) 2018; 67:i114-i122. [PMID: 29385502 PMCID: PMC6025237 DOI: 10.1093/jmicro/dfy002] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2017] [Accepted: 01/10/2018] [Indexed: 11/12/2022] Open
Abstract
Specimen and stage drift as well as scan distortions can lead to a mismatch between true and desired electron probe positions in scanning transmission electron microscopy (STEM) which can result in both linear and nonlinear distortions in the subsequent experimental images. This problem is intensified in STEM spectrum and diffraction imaging techniques owing to the extended dwell times (pixel exposure time) as compared to conventional STEM imaging. As a consequence, these image distortions become more severe in STEM spectrum/diffraction imaging. This becomes visible as expansion, compression and/or shearing of the crystal lattice, and can even prohibit atomic resolution and thus limits the interpretability of the results. Here, we report a software tool for post-correcting the linear and nonlinear image distortions of atomically resolved 3D spectrum imaging as well as 4D diffraction imaging. This tool improves the interpretability of distorted STEM spectrum/diffraction imaging data.
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Affiliation(s)
- Yi Wang
- Stuttgart Center for Electron Microscopy, Max Planck Institute for Solid State Research, Stuttgart, Germany
| | - Y Eren Suyolcu
- Stuttgart Center for Electron Microscopy, Max Planck Institute for Solid State Research, Stuttgart, Germany
| | - Ute Salzberger
- Stuttgart Center for Electron Microscopy, Max Planck Institute for Solid State Research, Stuttgart, Germany
| | - Kersten Hahn
- Stuttgart Center for Electron Microscopy, Max Planck Institute for Solid State Research, Stuttgart, Germany
| | - Vesna Srot
- Stuttgart Center for Electron Microscopy, Max Planck Institute for Solid State Research, Stuttgart, Germany
| | - Wilfried Sigle
- Stuttgart Center for Electron Microscopy, Max Planck Institute for Solid State Research, Stuttgart, Germany
| | - Peter A van Aken
- Stuttgart Center for Electron Microscopy, Max Planck Institute for Solid State Research, Stuttgart, Germany
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