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Dataset for the Thesis "Generalized Methodology for Control of Long-lived Nuclear Spin Order in Magnetic Resonance"

Dataset for the Thesis "Generalized Methodology for Control of Long-lived Nuclear Spin Order in Magnetic Resonance"
Dataset for the Thesis "Generalized Methodology for Control of Long-lived Nuclear Spin Order in Magnetic Resonance"
Contains the relevant diagrams and simulations that appear in my thesis "Generalized Methodology for Control of Long-lived Nuclear Spin Order in Magnetic Resonance". All of the figures can be accessed with open graphical processing software (I recommend paint.net), while the simulations rely on the openly available SpinDynamica and SPINACH packages. However, the proprietary softwares Mathematica, MatLab, and MestreNova are needed to access the spectra/simulations.
University of Southampton
Sabba, Mohamed
86002c7a-3fb8-4629-a13b-fbd6737b3c46
Levitt, Malcolm
bcc5a80a-e5c5-4e0e-9a9a-249d036747c3
Sabba, Mohamed
86002c7a-3fb8-4629-a13b-fbd6737b3c46
Levitt, Malcolm
bcc5a80a-e5c5-4e0e-9a9a-249d036747c3

Sabba, Mohamed (2021) Dataset for the Thesis "Generalized Methodology for Control of Long-lived Nuclear Spin Order in Magnetic Resonance". University of Southampton doi:10.5258/SOTON/D2006 [Dataset]

Record type: Dataset

Abstract

Contains the relevant diagrams and simulations that appear in my thesis "Generalized Methodology for Control of Long-lived Nuclear Spin Order in Magnetic Resonance". All of the figures can be accessed with open graphical processing software (I recommend paint.net), while the simulations rely on the openly available SpinDynamica and SPINACH packages. However, the proprietary softwares Mathematica, MatLab, and MestreNova are needed to access the spectra/simulations.

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Published date: 2021
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Identifiers

Local EPrints ID: 451631
URI: http://eprints.soton.ac.uk/id/eprint/451631
DOI: doi:10.5258/SOTON/D2006
PURE UUID: 790f90bd-575a-432f-bba6-4855945e63d7
ORCID for Malcolm Levitt: ORCID iD orcid.org/0000-0001-9878-1180

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Date deposited: 15 Oct 2021 16:32
Last modified: 06 May 2023 01:38

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Contributors

Creator: Mohamed Sabba
Research team head: Malcolm Levitt ORCID iD

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