Valley-Free Silicon Fins Caused by Shear Strain

Journal Article (2024)
Author(s)

Christoph Adelsberger (University of Basel)

S. Bosco (TU Delft - QCD/Bosco Group, Kavli institute of nanoscience Delft, TU Delft - QuTech Advanced Research Centre, University of Basel)

Jelena Klinovaja (University of Basel)

Daniel Loss (University of Basel)

Research Group
QCD/Bosco Group
DOI related publication
https://doi.org/10.1103/PhysRevLett.133.037001
More Info
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Publication Year
2024
Language
English
Research Group
QCD/Bosco Group
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.@en
Issue number
3
Volume number
133
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Abstract

Electron spins confined in silicon quantum dots are promising candidates for large-scale quantum computers. However, the degeneracy of the conduction band of bulk silicon introduces additional levels dangerously close to the window of computational energies, where the quantum information can leak. The energy of the valley states—typically 0.1 meV—depends on hardly controllable atomistic disorder and still constitutes a fundamental limit to the scalability of these architectures. In this work, we introduce designs of complementary metal-oxide-semiconductor (CMOS)-compatible silicon fin field-effect transistors that enhance the energy gap to noncomputational states by more than one order of magnitude. Our devices comprise realistic silicon-germanium nanostructures with a large shear strain, where troublesome valley degrees of freedom are completely removed. The energy of noncomputational states is therefore not affected by unavoidable atomistic disorder and can further be tuned in situ by applied electric fields. Our design ideas are directly applicable to a variety of setups and will offer a blueprint toward silicon-based large-scale quantum processors.

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