journal article·2021-02Open access

Band Structure Extraction at Hybrid Narrow‐Gap Semiconductor–Metal Interfaces

Sergej Schuwalow, Niels B. M. Schröter, Jan Gukelberger, Candice Thomas, Vladimir Strocov, John Gamble, Alla Chikina, Marco Caputo, Jonas Krieger, Geoffrey C. Gardner, Matthias Troyer, Gabriel Aeppli, Michael J. Manfra, Peter Krogstrup

Advanced Science· Volume 8· Issue 4

Abstract

Abstract The design of epitaxial semiconductor–superconductor and semiconductor–metal quantum devices requires a detailed understanding of the interfacial electronic band structure. However, the band alignment of buried interfaces is difficult to predict theoretically and to measure experimentally. This work presents a procedure that allows to reliably determine critical parameters for engineering quantum devices; band offset, band bending profile, and number of occupied quantum well subbands of interfacial accumulation layers at semiconductor‐metal interfaces. Soft X‐ray angle‐resolved photoemission is used to directly measure the quantum well states as well as valence bands and core levels for the InAs(100)/Al interface, an important platform for Majorana‐zero‐mode based topological qubits, and demonstrate that the fabrication process strongly influences the band offset, which in turn controls the topological phase diagrams. Since the method is transferable to other narrow gap semiconductors, it can be used more generally for engineering semiconductor–metal and semiconductor–superconductor interfaces in gate‐tunable superconducting devices.
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Research context

OpenAlex topics: Topological Materials and Phenomena · Electronic and Structural Properties of Oxides · Graphene research and applications

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Center for Quantum Devices Niels Bohr Institute University of Copenhagen and Microsoft Quantum Materials Lab Copenhagen Lyngby Denmark

Paul Scherrer Institut Swiss Light Source PSI Villigen CH‐5232 Switzerland

Microsoft Quantum One Microsoft Way Redmond WA 98052 USA

Microsoft Station Q Purdue Birck Nanotechnology Center Purdue University West Lafayette IN 47907 USA

Department of Physics and Astronomy Purdue University West Lafayette IN 47907 USA

Physics Department ETH Zurich CH‐8093 Switzerland

Institut de Physique EPFL Lausanne CH‐1015 Switzerland

School of Electrical and Computer Engineering and School of Materials Engineering Purdue University West Lafayette IN 47907 USA

Funding

Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung · European Research Council

References (42)

Show source-provided references
1. 10.1103/PhysRevLett.52.46510.1103/PhysRevLett.52.465 ↗
2. 10.1103/PhysRev.138.A168910.1103/PhysRev.138.A1689 ↗
3. 10.1016/0039-6028(86)90867-810.1016/0039-6028(86)90867-8 ↗
4. 10.1063/1.9286310.1063/1.92863 ↗
5. 10.1103/RevModPhys.80.108310.1103/RevModPhys.80.1083 ↗
6. 10.1126/science.aaf396110.1126/science.aaf3961 ↗
7. 10.1038/s41578-018-0003-110.1038/s41578-018-0003-1 ↗
8. 10.1038/npjqi.2015.110.1038/npjqi.2015.1 ↗
9. 10.1103/PhysRevLett.119.13680310.1103/PhysRevLett.119.136803 ↗
10. 10.1103/PhysRevB.99.24540810.1103/PhysRevB.99.245408 ↗
11. Antipov A. E. · Phys. Rev. X · 2018 · 8 · 031041
12. 10.1103/PhysRevB.75.11531210.1103/PhysRevB.75.115312 ↗
13. 10.1103/PhysRevLett.104.25680310.1103/PhysRevLett.104.256803 ↗
14. 10.1116/1.58353710.1116/1.583537 ↗
15. 10.1007/978-3-662-06945-510.1007/978-3-662-06945-5 ↗
16. 10.1116/1.57021510.1116/1.570215 ↗
17. 10.1103/PhysRevLett.76.362610.1103/PhysRevLett.76.3626 ↗
18. 10.1103/PhysRevB.73.19532110.1103/PhysRevB.73.195321 ↗
19. 10.1002/pssb.222088011510.1002/pssb.2220880115 ↗
20. 10.1116/1.58289910.1116/1.582899 ↗
21. 10.1103/PhysRevB.28.701410.1103/PhysRevB.28.7014 ↗
22. 10.1116/1.176852510.1116/1.1768525 ↗
23. 10.1063/1.303337310.1063/1.3033373 ↗
24. 10.1063/1.302146110.1063/1.3021461 ↗
25. 10.1103/PhysRevB.88.19512810.1103/PhysRevB.88.195128 ↗
26. 10.1063/1.357145410.1063/1.3571454 ↗
27. 10.1021/acsami.6b0466610.1021/acsami.6b04666 ↗
28. 10.1103/PhysRevB.85.16510810.1103/PhysRevB.85.165108 ↗
29. 10.1103/PhysRevMaterials.2.09460210.1103/PhysRevMaterials.2.094602 ↗
30. 10.1103/PhysRev.110.77610.1103/PhysRev.110.776 ↗
31. M.Newville T.Stensitzki D. B.Allen A.Ingargiola Lmfit: Non‐linear least‐square minimization and curve‐fitting for python https://doi.org/10.5281/zenodo.11813. Accessed July 15 2020.
32. 10.1063/1.36539610.1063/1.365396 ↗
33. 10.1016/S0038-1101(01)00271-410.1016/S0038-1101(01)00271-4 ↗
34. 10.1038/ncomms113110.1038/ncomms1131 ↗
35. 10.1103/PhysRevB.53.473410.1103/PhysRevB.53.4734 ↗
36. 10.1016/0039-6028(88)90322-610.1016/0039-6028(88)90322-6 ↗
37. 10.1103/PhysRevB.35.958010.1103/PhysRevB.35.9580 ↗
38. 10.1038/nmat417610.1038/nmat4176 ↗
39. 10.1103/PhysRevB.61.1380510.1103/PhysRevB.61.13805 ↗
40. 10.1103/PhysRevB.63.20530510.1103/PhysRevB.63.205305 ↗
41. 10.1103/PhysRevB.65.15532510.1103/PhysRevB.65.155325 ↗
42. 10.1103/PhysRevB.53.1360510.1103/PhysRevB.53.13605 ↗