Projects per year
Abstract
The emergence of nematic electronic states which break the symmetry of the underlying lattice is a recurring theme in many correlated electron materials, among them the high temperature copper-oxide and iron-based superconductors. Here we provide evidence for the existence of nematic electronic states in the iron chalcogenide superconductor FeSe0.4Te0.6. The symmetry breaking states persist above TC into the normal state. We find an anisotropic coherence length, which is suppressed in a direction perpendicular to the nematic modulations. We interpret the scattering patterns by comparison with quasiparticle interference patterns obtained within a tight-binding model, accounting for orbital ordering.
Original language | English |
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Article number | e1500206 |
Journal | Science Advances |
Volume | 1 |
Issue number | 9 |
DOIs | |
Publication status | Published - 16 Oct 2015 |
Keywords
- Iron-based superconductors
- Scanning tunneling microscopy and spectroscopy
- Nematicity
- Symmetry breaking
- Superconductivity
- Quasi-particle interference
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Dive into the research topics of 'Evidence for orbital order and its relation to superconductivity in FeSe0.4Te0.6'. Together they form a unique fingerprint.Projects
- 1 Finished
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Topological Protection and NonEquilibriu: Topological Protection and NonEquilibrium States in Strongly Correlated Electron Systems
Wahl, P. (PI), Baumberger, F. (CoI), Davis, J. C. (CoI), Green, A. (CoI), Hooley, C. (CoI), Keeling, J. M. J. (CoI) & Mackenzie, A. (CoI)
1/09/11 → 31/08/17
Project: Standard
Profiles
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Peter Wahl
- School of Physics and Astronomy - Professor, Director of Research
- Centre for Designer Quantum Materials
- Condensed Matter Physics
Person: Academic
Datasets
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Underpinning Data: Evidence for orbital order and its relation to superconductivity in FeSe0.4Te0.6
Singh, U. R. (Creator), White, S. C. (Creator), Schmaus, S. (Creator), Tsurkan, V. (Creator), Loidl, A. (Creator), Deisenhofer, J. (Creator) & Wahl, P. (Creator), University of St Andrews, 2016
DOI: 10.17630/1def59e5-4f2d-4c10-87d3-44220167402b
Dataset
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