IPVF Internship: Compressed Sensing for Photovoltaic Material Luminescence Imaging

Contract type: Internship

Starting date: ASAP (2021)

Duration: 3 months

Working Place: Palaiseau

Education: M1 ; M2 ; Engineer

Salary: Salary grid

IPVF in brief

Become an actor of the Energy Transition by joining a team driven by innovation and impact to address today’s most decisive challenges.

IPVF – Institut Photovoltaïque d’Île-de-France, is a global Research, Innovation and Education center, which mission is to accelerate energy transition through science & technology.

Gathering industrial PV leaders (EDF, Total, Air Liquide, Horiba and Riber) and world-renowned academic research teams (CNRS, Ecole Polytechnique), multi-disciplinary and international IPVF teams conduct research for clean energy technologies.

Supported by the French State, IPVF is labelled Institute for Energy Transition (ITE).

IPVF at a glance:

  • An ambitious Scientific and Technological Program: from tandem solar cell technologies to economy & market assessment, state-of-the art characterization, photocatalysis and concepts breakthrough.
  • A state-of-the-art technological platform: more than 100 tools, located in cleanrooms (advanced characterization, materials deposition, prototypes for fabrication, modelling…).
  • A high-standard Education program (M.S. and PhD students).

Job context

The IPVF characterization team aims at developping new characterization techniques based on luminescence imaging to extract key properties of the photovoltaic materials. In that frame, we are building the first 4D photoluminescence-imaging set-up, which provides the local spectral and temporal information of the light emitted by semiconductors. It employs Single Pixel Imaging as an alternative to raster scanning to reconstruct the spatial information from a series of measurements performed by a non-imaging detector. A matrix of micro mirrors decomposes the light spatially and select a different area to be analyzed at each measure. Many different approaches can be used to decompose and reconstruct the image. Implementing a compressed sensing algorithm would allow acquisitions with less measurements yet the same spatial resolution. This is crucial in order to reduce the acquisition time of our novel set-up without reducing its spatial resolution and signal-to-noise ratio.

References:

Duarte, M. F. et al. Single-pixel imaging via compressive sampling. IEEE Signal Process. Mag. 25, 83–91 (2008).

Rousset, F. Single-pixel Imaging: development and applications of adaptive methods. (2017).

Bian, L., Suo, J., Dai, Q. & Chen, F. Experimental comparison of single-pixel imaging algorithms. J. Opt. Soc. Am. A 35, 78 (2018).Rousset, F. et al. Adaptive Basis Scan by Wavelet Prediction for Single-Pixel Imaging. IEEE Trans. Comput. Imaging 3, 36–46 (2017).

Yao, R., Ochoa, M., Yan, P. & Intes, X. Net-FLICS: fast quantitative wide-field fluorescence lifetime imaging with compressed sensing – a deep learning approach. Light Sci Appl 8, 26 (2019).

Yu, W.-K. Super sub-Nyquist single-pixel imaging by means of cake-cutting Hadamard basis sort. Sensors 19, 4122 (2019).

IPVF Research Program involving this internship position: https://ipvf.fr/jean-paul-kleider-philip-schulz-and-daniel-ory-introducing-programme-4-characterization-modeling-reliability/

Main missions

  • Simulation of different compressed sensing approaches,
  • Choice of an algorithm relevant to our set-up and implementation,
  • Assessment of its performance and estimation of its uncertainty.

Expected profile

Knowledge

  • Statistics
  • Data processing

Knowhow

  • MATLAB and Python programming
  • English B1

Self-management skills

  • Curious and challenge-driven
  • Autonomous

Contact

Cover letter and CV to be sent to : marie.legrand@edf.fr
Specify the title of the offer in the subject line of the email

Need a direct line?

Feel free to contact us for more information about our offers.

  • +33(0)1 69 86 58 60
  • contact@ipvf.fr