2022
DOI: 10.1007/s40042-022-00471-5
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Direct visualization and control of SrOx segregation on semiconducting Nb doped SrTiO3 (100) surface

Abstract: We investigated howSrOx segregates on a Nb doped SrTiO3 (100) surface by in air annealing. Using atomic force and photoemission electron microscopes, we can directly visualize the morphology and the electronic phase changes with SrOx segregation. SrOx islands less than 2 𝜇m in size and 1-5 unit cells thick nucleate first and grow in a labyrinth domain pattern. After prolonged annealing, SrOx forms a ~10 nm thick film. We show that the domain pattern can be controlled by introducing a surface miscut angle of S… Show more

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Cited by 5 publications
(2 citation statements)
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References 37 publications
(49 reference statements)
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“…Lastly, XPS Sr 3d spectra in Figure D show that the primary contributions to the degraded layer (blue curve) are Sr 3d peaks at 0.9 eV higher binding energy than for pristine STO (black curve). Assigned previously and especially for Sr defects within SrTiO 3 , , this shift conclusively identifies the formation of local SrO separate from TiO 2 . The XPS data for Ti 2p and Sr 3d shown in Figure B and D were also utilized to corroborate the Ti and Sr dissolution seen by EDS.…”
Section: Elemental Composition Of the Degraded Layersupporting
confidence: 66%
“…Lastly, XPS Sr 3d spectra in Figure D show that the primary contributions to the degraded layer (blue curve) are Sr 3d peaks at 0.9 eV higher binding energy than for pristine STO (black curve). Assigned previously and especially for Sr defects within SrTiO 3 , , this shift conclusively identifies the formation of local SrO separate from TiO 2 . The XPS data for Ti 2p and Sr 3d shown in Figure B and D were also utilized to corroborate the Ti and Sr dissolution seen by EDS.…”
Section: Elemental Composition Of the Degraded Layersupporting
confidence: 66%
“…This ML analysis is beneficial for analyzing the growth dynamics and layer thicknesses for ultrathin van der Waals thin films, and the corresponding results are consistent with those of the K-means clustering method. Our results suggest that the ML-assisted RHEED analysis could be developed into an automatic validation method for investigating ultrathin 2D materials films, and it is complementary to other surface analysis tools [ 7 , 38 , 39 ]. Furthermore, this method can be applied to analyze the thin-film growth of other 2D materials, such as 2D chalcogenides, 2D MXenes, 2D oxides, and hexagonal boron nitrides [ 40 – 43 ].…”
Section: Discussionmentioning
confidence: 95%