TY  - CONF
AU  - Ruzaeva, Karina
AU  - Weber, Dieter
AU  - Werner, Jonas
AU  - Sandfeld, Stefan
TI  - Unsupervised Machine Learning-based STEM diffraction pattern denoising for enhanced grain visualization in phase change materials
VL  - 129
SN  - 2117-4458
CY  - Les Ulis
PB  - EDP Sciences
M1  - FZJ-2025-02591
T2  - BIO Web of Conferences
SP  - 10022 -
PY  - 2024
AB  - 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).
T2  - The 17th European Microscopy Congress 2024
CY  - 25 Aug 2024 - 30 Aug 2024, Copenhagen (Denmark)
Y2  - 25 Aug 2024 - 30 Aug 2024
M2  - Copenhagen, Denmark
LB  - PUB:(DE-HGF)8 ; PUB:(DE-HGF)7
DO  - DOI:10.1051/bioconf/202412910022
UR  - https://juser.fz-juelich.de/record/1042605
ER  -