Paper | Title | Page |
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MOPAB139 | High Resolution Imaging Design Using Permanent Magnet Quadrupoles at BNL UEM | 485 |
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Ultrafast electron microscopy techniques have demonstrated the potential to reach very high combined spatio-temporal resolution. In order to achieve high resolution, strong focusing magnets must be used as the objective and projector lenses. In this paper, we discuss the design and development of a high-resolution objective lens for use in the BNL UEM. The objective lens is a quintuplet array of permanent magnet quadrupoles, which in sum, provide symmetric focusing, high magnification, and control of higher order aberration terms. The application and design for a proof-of-concept experiment using a calibrated slit for imaging are presented. The image resolution is monitored as a function of beam parameters (energy, energy spread, charge, bunch length, spot size), and quintuplet lens parameters (drifts between lenses). | ||
DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-MOPAB139 | |
About • | paper received ※ 26 May 2021 paper accepted ※ 28 May 2021 issue date ※ 18 August 2021 | |
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MOPAB286 | Towards a Data Science Enabled MeV Ultrafast Electron Diffraction System | 906 |
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Funding: US DOE, SC, BES, MSE, award DE-SC0021365 and DOE NNSA award 89233218CNA000001 through DOE’s EPSCoR program in Office of BES with resources of DOE SC User Facilities BNL’s ATF and ALCF. A MeV ultrafast electron diffraction (MUED) instrument is a unique characterization technique to study ultrafast processes in materials by a pump-probe technique. This relatively young technology can be advanced further into a turn-key instrument by using data science and artificial intelligence (AI) mechanisms in conjunctions with high-performance computing. This can facilitate automated operation, data acquisition and real time or near- real time processing. AI based system controls can provide real time feedback on the electron beam which is currently not possible due to the use of destructive diagnostics. Deep learning can be applied to the MUED diffraction patterns to recover valuable information on subtle lattice variations that can lead to a greater understanding of a wide range of material systems. A data science enabled MUED facility will also facilitate the application of this technique, expand its user base, and provide a fully automated state-of-the-art instrument. We will discuss the progress made on the MUED instrument in the Accelerator Test Facility of Brookhaven National Laboratory. |
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DOI • | reference for this paper ※ https://doi.org/10.18429/JACoW-IPAC2021-MOPAB286 | |
About • | paper received ※ 20 May 2021 paper accepted ※ 09 June 2021 issue date ※ 25 August 2021 | |
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