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An optimized TEM specimen preparation method of quantum nanostructures.
Wang, Hongguang; Srot, Vesna; Fenk, Bernhard; Laskin, Gennadii; Mannhart, Jochen; van Aken, Peter A.
Affiliation
  • Wang H; Max Planck Institute for Solid State Research, 70569 Stuttgart, Germany. Electronic address: hgwang@fkf.mpg.de.
  • Srot V; Max Planck Institute for Solid State Research, 70569 Stuttgart, Germany.
  • Fenk B; Max Planck Institute for Solid State Research, 70569 Stuttgart, Germany.
  • Laskin G; Max Planck Institute for Solid State Research, 70569 Stuttgart, Germany.
  • Mannhart J; Max Planck Institute for Solid State Research, 70569 Stuttgart, Germany.
  • van Aken PA; Max Planck Institute for Solid State Research, 70569 Stuttgart, Germany.
Micron ; 140: 102979, 2021 Jan.
Article in En | MEDLINE | ID: mdl-33197749
ABSTRACT
Electron transparent TEM lamella with unaltered microstructure and chemistry is the prerequisite for successful TEM explorations. Currently, TEM specimen preparation of quantum nanostructures, such as quantum dots (QDs), remains a challenge. In this work, we optimize the sample-preparation routine for achieving high-quality TEM specimens consisting of SrRuO3 (SRO) QDs grown on SrTiO3 (STO) substrates. We demonstrate that a combination of ion-beam-milling techniques can produce higher-quality specimens of quantum nanostructures compared to TEM specimens prepared by a combination of tripod polishing followed by Ar+ ion milling. In the proposed method, simultaneous imaging in a focused ion-beam device enables accurate positioning of the QD regions and assures the presence of dots in the thin lamella by cutting the sample inclined by 5° relative to the dots array. Furthermore, the preparation of TEM lamellae with several large electron-transparent regions that are separated by thicker walls effectively reduces the bending of the specimen and offers broad thin areas. The final use of a NanoMill efficiently removes the amorphous layer without introducing any additional damage.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Micron Journal subject: DIAGNOSTICO POR IMAGEM Year: 2021 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Micron Journal subject: DIAGNOSTICO POR IMAGEM Year: 2021 Document type: Article