Hauptseite > Publikationsdatenbank > Inverse Multislice Ptychography by Layer-wise Optimisation and Sparse Matrix Decomposition > print |
001 | 911182 | ||
005 | 20230123110730.0 | ||
024 | 7 | _ | |a 10.1109/TCI.2022.3218993 |2 doi |
024 | 7 | _ | |a 2128/32764 |2 Handle |
024 | 7 | _ | |a WOS:000888957200001 |2 WOS |
037 | _ | _ | |a FZJ-2022-04494 |
041 | _ | _ | |a English |
082 | _ | _ | |a 004 |
100 | 1 | _ | |a Bangun, Arya |0 P:(DE-Juel1)184644 |b 0 |e Corresponding author |u fzj |
245 | _ | _ | |a Inverse Multislice Ptychography by Layer-wise Optimisation and Sparse Matrix Decomposition |
260 | _ | _ | |a [New York, NY] |c 2022 |b IEEE |
336 | 7 | _ | |a article |2 DRIVER |
336 | 7 | _ | |a Output Types/Journal article |2 DataCite |
336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1669206904_30325 |2 PUB:(DE-HGF) |
336 | 7 | _ | |a ARTICLE |2 BibTeX |
336 | 7 | _ | |a JOURNAL_ARTICLE |2 ORCID |
336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
520 | _ | _ | |a We propose algorithms based on an optimisation method for inverse multislice ptychography in, e.g. electron microscopy. The multislice method is widely used to model the interaction between relativistic electrons and thick specimens. Since only the intensity of diffraction patterns can be recorded, the challenge in applying inverse multislice ptychography is to uniquely reconstruct the electrostatic potential in each slice up to some ambiguities. In this conceptual study, we show that a unique separation of atomic layers for simulated data is possible when considering a low acceleration voltage. We also introduce an adaptation for estimating the illuminating probe. For the sake of practical application, we finally present slice reconstructions using experimental 4D scanning transmission electron microscopy (STEM) data. |
536 | _ | _ | |a 5351 - Platform for Correlative, In Situ and Operando Characterization (POF4-535) |0 G:(DE-HGF)POF4-5351 |c POF4-535 |f POF IV |x 0 |
536 | _ | _ | |a moreSTEM - Momentum-resolved Scanning Transmission Electron Microscopy (VH-NG-1317) |0 G:(DE-HGF)VH-NG-1317 |c VH-NG-1317 |x 1 |
536 | _ | _ | |a Ptychography 4.0 - Proposal for a pilot project "Information & Data Science" (ZT-I-0025) |0 G:(DE-HGF)ZT-I-0025 |c ZT-I-0025 |x 2 |
536 | _ | _ | |a EDARTI - Electron Diffraction Inversion by Artificial Intelligence Approaches (ZT-I-PF-Z5-28) |0 G:(DE-HGF)ZT-I-PF-Z5-28 |c ZT-I-PF-Z5-28 |x 3 |
588 | _ | _ | |a Dataset connected to CrossRef, Journals: juser.fz-juelich.de |
700 | 1 | _ | |a Melnykyz, Oleh |0 P:(DE-HGF)0 |b 1 |
700 | 1 | _ | |a März, Benjamin |0 P:(DE-Juel1)180986 |b 2 |
700 | 1 | _ | |a Diederichs, Benedikt |0 P:(DE-Juel1)185768 |b 3 |u fzj |
700 | 1 | _ | |a Clausen, Alexander |0 P:(DE-Juel1)174151 |b 4 |u fzj |
700 | 1 | _ | |a Weber, Dieter |0 P:(DE-Juel1)171370 |b 5 |u fzj |
700 | 1 | _ | |a Filbir, Frank |0 P:(DE-HGF)0 |b 6 |
700 | 1 | _ | |a Muller-Caspary, Knut |0 P:(DE-Juel1)165314 |b 7 |u fzj |
773 | _ | _ | |a 10.1109/TCI.2022.3218993 |g p. 1 - 16 |0 PERI:(DE-600)2806107-X |p 996 - 1011 |t IEEE transactions on computational imaging |v 8 |y 2022 |x 2333-9403 |
856 | 4 | _ | |u https://juser.fz-juelich.de/record/911182/files/Invoice_APC600364395.pdf |
856 | 4 | _ | |u https://juser.fz-juelich.de/record/911182/files/Invoice_APC600368218.pdf |
856 | 4 | _ | |y OpenAccess |u https://juser.fz-juelich.de/record/911182/files/Inverse_Multislice_Ptychography_by_Layer-Wise_Optimisation_and_Sparse_Matrix_Decomposition.pdf |
909 | C | O | |o oai:juser.fz-juelich.de:911182 |p openaire |p open_access |p OpenAPC |p driver |p VDB |p openCost |p dnbdelivery |
910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 0 |6 P:(DE-Juel1)184644 |
910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 3 |6 P:(DE-Juel1)185768 |
910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 4 |6 P:(DE-Juel1)174151 |
910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 5 |6 P:(DE-Juel1)171370 |
910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 7 |6 P:(DE-Juel1)165314 |
913 | 1 | _ | |a DE-HGF |b Key Technologies |l Materials Systems Engineering |1 G:(DE-HGF)POF4-530 |0 G:(DE-HGF)POF4-535 |3 G:(DE-HGF)POF4 |2 G:(DE-HGF)POF4-500 |4 G:(DE-HGF)POF |v Materials Information Discovery |9 G:(DE-HGF)POF4-5351 |x 0 |
914 | 1 | _ | |y 2022 |
915 | p | c | |a Local Funding |0 PC:(DE-HGF)0001 |2 APC |
915 | _ | _ | |a Creative Commons Attribution CC BY 4.0 |0 LIC:(DE-HGF)CCBY4 |2 HGFVOC |
915 | _ | _ | |a WoS |0 StatID:(DE-HGF)0113 |2 StatID |b Science Citation Index Expanded |d 2021-02-03 |
915 | _ | _ | |a OpenAccess |0 StatID:(DE-HGF)0510 |2 StatID |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0160 |2 StatID |b Essential Science Indicators |d 2021-02-03 |
915 | _ | _ | |a JCR |0 StatID:(DE-HGF)0100 |2 StatID |b IEEE T COMPUT IMAG : 2021 |d 2022-11-11 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0200 |2 StatID |b SCOPUS |d 2022-11-11 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0300 |2 StatID |b Medline |d 2022-11-11 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0199 |2 StatID |b Clarivate Analytics Master Journal List |d 2022-11-11 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1160 |2 StatID |b Current Contents - Engineering, Computing and Technology |d 2022-11-11 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0150 |2 StatID |b Web of Science Core Collection |d 2022-11-11 |
915 | _ | _ | |a IF < 5 |0 StatID:(DE-HGF)9900 |2 StatID |d 2022-11-11 |
920 | _ | _ | |l yes |
920 | 1 | _ | |0 I:(DE-Juel1)ER-C-1-20170209 |k ER-C-1 |l Physik Nanoskaliger Systeme |x 0 |
980 | _ | _ | |a journal |
980 | _ | _ | |a VDB |
980 | _ | _ | |a UNRESTRICTED |
980 | _ | _ | |a I:(DE-Juel1)ER-C-1-20170209 |
980 | _ | _ | |a APC |
980 | 1 | _ | |a APC |
980 | 1 | _ | |a FullTexts |
Library | Collection | CLSMajor | CLSMinor | Language | Author |
---|