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Multi-scale fibre-based optical frequency combs: science, technology and applications

Project description

Training network on optical frequency combs

An optical frequency comb is a very precise tool for measuring different frequencies of light. The technology, made possible by recent advances in ultrafast lasers, can accurately measure much higher frequencies than any other tool. Funded by the Marie Skłodowska Curie programme, the MEFISTA project will train six young researchers in the field. Researchers will conduct research on novel techniques for generating specialised laser waveforms, mid-infrared tuneable dual-comb sources, and manufacturing of mode-locked fibre lasers. Special focus will be placed on the use of frequency combs in laser radar/LIDAR in autonomous cars. The initiative will foster collaboration between academic and industrial partners, enriching EU research and innovation in optical frequency comb technologies.

Objective

The key photonic technology that enables a cluster of applications and so is a driving force for an expanding photonic market in the context of addressing the global challenges is an optical frequency comb (OFC) technology based on mode locked femtosecond lasers (MLFLs). To respond to the huge demand for qualified experts on OFC technologies, we envisaged and are proposing European Training Network (ETN) “Multi-scale fibre-based optical frequency combs: science, technology and applications” (MEFISTA). MEFISTA will provide a world class advanced training programme (TP) to 6 early stage researchers (ESRs) to the level of the next generation of leaders in the fields MLFLs-based OFCs technologies, by exploiting challenging interaction between academy (Aston, UPC, ULille, EPFL and DTU) and industry (NKT and RDM). MEFISTA aims research and training collaborations that will help ESRs to acquire unique knowledge and research skills on OFC technology from the theory to implementation: development of novel mode- locking techniques and speciality fibres and waveguides for MLFLs, mid-infrared (mid-IR) tuneable dual combs sources for molecular fingerprinting, design and characterisation of dual comb MLFLs, and MLFLs manufacturing. A special focus will be the industrial applications related to development and trial tests of MLFLs in the context of autonomous driving (car-object distance ranging, object recognition, moving objects speed tracing: Doppler LIDAR). The TP will be implemented through the unique combination of the “hands-on” research training, non-academic placements and advanced inter/multidisciplinary/inter-sectoral training on nonlinear science, laser physics, fibre optics, and autonomous driving technologies and transferable skills including Research Integrity, Gender Dimension in Research, and Open Science. The TP will be also supported by synergistic merging the expertise of 4 academic, two non-academic beneficiaries and 1 academic partners from 5 countries.

Fields of science (EuroSciVoc)

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Keywords

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Programme(s)

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Topic(s)

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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.

MSCA-ITN - Marie Skłodowska-Curie Innovative Training Networks (ITN)

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Call for proposal

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(opens in new window) H2020-MSCA-ITN-2019

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Coordinator

ASTON UNIVERSITY
Net EU contribution

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.

€ 606 345,12
Address
ASTON TRIANGLE
B4 7ET Birmingham
United Kingdom

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Activity type
Higher or Secondary Education Establishments
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Total cost

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.

€ 606 345,12

Participants (5)

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