Objective
Nuclear magnetic resonance (NMR) and magnetic resonance imaging (MRI) are supremely important techniques with widespread applications in chemistry, physics and medicine. NMR methodology has until recently been limited by the time constant T1 for the decay of nuclear spin magnetization back to thermal equilibrium. Long-lived nuclear singlet states (LLS) have been shown to overcome this limit with a decay constant TLLS that may be two orders of magnitude longer than T1. However, so far mostly ideal systems have been studied in the LLS context, involving simple solvents and oxygen and other paramagnetic molecules removed. This is far from the conditions in many potential applications of MRI and/or materials research, and it is not clear how LLS performs in environments such as complex fluids or biological matter. To overcome this limitation, the proposed project is to develop state-of-the-art quantum-statistical simulation methodology toolbox to model TLLS in complex fluids (lipid/water phases). The project builds on the experience of the research fellow in LLS and computational engineering combined with quantum-chemical, molecular simulation, and experimental expertise of the host institution. Methodology for the essential but challenging quadrupole and paramagnetic spin relaxation enhancement will be developed for LLS. Machine learning techniques will overcome the excessive computational burden of very many quantum-chemical calculations needed in conventional computational relaxation studies.The simulated TLLS will provide a general understanding of the applicability of LLS at the microscopic level, for colloidal systems. The theoretical understanding will guide the development of LLS in materials research and MRI. Machine learning development will feed into the quantum chemistry studies of NMR and other molecular properties in complex systems, as well as computational engineering.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- natural sciences physical sciences condensed matter physics soft matter physics
- natural sciences chemical sciences physical chemistry quantum chemistry
- natural sciences biological sciences biochemistry biomolecules lipids
- engineering and technology medical engineering diagnostic imaging magnetic resonance imaging
- natural sciences computer and information sciences artificial intelligence machine learning
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Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions
MAIN PROGRAMME
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H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
MSCA-IF-EF-ST - Standard EF
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) H2020-MSCA-IF-2015
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
90014 Oulu
Finland
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.