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001     1042605
005     20250521202232.0
024 7 _ |a 10.1051/bioconf/202412910022
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024 7 _ |a 2117-4458
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024 7 _ |a 2273-1709
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024 7 _ |a 10.34734/FZJ-2025-02591
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037 _ _ |a FZJ-2025-02591
082 _ _ |a 570
100 1 _ |a Ruzaeva, Karina
|0 P:(DE-Juel1)180323
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|u fzj
111 2 _ |a The 17th European Microscopy Congress 2024
|c Copenhagen
|d 2024-08-25 - 2024-08-30
|w Denmark
245 _ _ |a Unsupervised Machine Learning-based STEM diffraction pattern denoising for enhanced grain visualization in phase change materials
260 _ _ |a Les Ulis
|c 2024
|b EDP Sciences
300 _ _ |a 202412910022
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336 7 _ |a Contribution to a book
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490 0 _ |a BIO Web of Conferences
520 _ _ |a Phase change materials (PCM) are an emerging class of materials in whichdifferent phases of the same material may have different optical, electric, ormagnetic properties and can be used as a phase change memory [1]. Phase-change memory materials, exemplified by (Ag, In)-doped Sb2Te (AIST) in thisresearch, have several advantages, including high-speed read and writeoperations, non-volatility, and a long lifespan [2]. PCMs are able to switchbetween amorphous and crystalline phases when subjected to heat orelectrical current. However, the full understanding of PCMs depends heavilyon accurate characterization, often through techniques such as scanningtransmission electron microscopy (STEM).
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700 1 _ |a Weber, Dieter
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700 1 _ |a Werner, Jonas
|0 P:(DE-Juel1)162457
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700 1 _ |a Sandfeld, Stefan
|0 P:(DE-Juel1)186075
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|e Corresponding author
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773 _ _ |a 10.1051/bioconf/202412910022
|g Vol. 129, p. 10022 -
|0 PERI:(DE-600)2673408-4
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856 4 _ |u https://juser.fz-juelich.de/record/1042605/files/bioconf_emc2024_10022.pdf
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