ISIS Neutron and Muon Source Data Journal

This is a page describing data taken during an experiment at the ISIS Neutron and Muon Source. Information about the ISIS Neutron and Muon Source can be found at https://www.isis.stfc.ac.uk.


Developing QLCR spectroscopy as a muSR tool

Abstract: Quadrupolar level crossing resonance (QLCR) in muSR of solid state systems with diamagnetic muon states in proximity to quadrupolar nuclei was discovered many years ago, however its application has been held back by the lack of a computational framework for predicting, analyzing and interpreting such resonance spectra. QLCR is unique among muSR methods in being sensitive to charge as well as spin and thus has great potential for new application areas of muon spectroscopy. Recent progress in the computation of muon states in materials using density functional theory (DFT+mu) can also be applied to QLCR. Solid nitrogen provides an excellent benchmark system to test calculations against experiment. A comprehensive QLCR data set will be collected for solid nitrogen in its fully ordered alpha-phase and DFT-based spectral calculation methods for QLCR will be refined against the data obtained

Principal Investigator: Dr Francis Pratt
Experimenter: Dr Benjamin Huddart
Experimenter: Dr Adam Berlie
Experimenter: Dr Stephen Cottrell
Experimenter: Professor Tom Lancaster
Experimenter: Dr Leandro Liborio
Experimenter: Professor Matja? Gomil?ek

DOI: 10.5286/ISIS.E.RB1900029

ISIS Experiment Number: RB1900029

Part DOI Instrument Public release date Download Link
10.5286/ISIS.E.98028070 EMU 15 October 2021 Download

Publisher: STFC ISIS Neutron and Muon Source

Data format: RAW/Nexus
Select the data format above to find out more about it.

Data Citation

The recommended format for citing this dataset in a research publication is as:
[author], [date], [title], [publisher], [doi]

For Example:
Dr Francis Pratt et al; (2018): Developing QLCR spectroscopy as a muSR tool, STFC ISIS Neutron and Muon Source, https://doi.org/10.5286/ISIS.E.RB1900029

Data is released under the CC-BY-4.0 license.



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