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  • SNSF-funded project enhances THG microscopy for materials imaging

    18.01.23 - A cross-disciplinary project involving three EPFL units – the Hub for Advanced Image Reconstruction, the Galatea Lab and the AudioVisual Communications Laboratory (LCAV) – has received a grant from the Swiss National Science Foundation (SNSF) to study methods for speeding image capture in non-linear optical microscopy. Their work will be used to examine nanostructures in transparent materials. Non-linear optical microscopy is a method for generating 3D images of living samples with micrometer resolution, and it has become increasingly widespread in the past two decades. “Scientists around the world have done a lot of research into using this method in biology applications, but relatively little has been done for applications in materials science,” says Matthieu Simeoni, the head of EPFL’s Hub for Advanced Image Reconstruction. The Hub, along with the Galatea Lab (in EPFL’s School of Engineering), LCAV (in EPFL’s School of Computer and Communication Sciences) and the Colorado School of Mines in the US, has recently been awarded a three-year, CHF 1.2 million SNSF Sinergia grant to develop a microscopy system for observing complex structures at greater speed. The project will draw on skills in optics, laser-matter interaction, signal processing and image processing, and fits in perfectly with the cross-disciplinary, collaborative approach promoted by the Sinergia funding scheme. A spatial light modulator to take the whole sample at once More specifically, Simeoni and his colleagues will design a third harmonic generation (THG) microscope that can take rapid images of submicroscopic laser-engraved structures in transparent materials. The Galatea Lab specializes in this area and is carrying out pioneering research on new properties for materials that would enable them to be used as waveguides or improve their thermal conductivity and thermomechanical performance. For now, a major obstacle in conducting more sophisticated experiments and bringing technology to industry is the time needed to generate control images. To obtain high-resolution images from a THG microscope, scientists have to shine intense beams of light on a sample while being careful not to damage the sample. The Galatea Lab currently has a prototype microscope where a single laser focused by a lens scans an entire sample, while a highly sensitive CMOS sensor – developed at EPFL specifically for this application – delivers high resolution. The prototype takes images from several angles and then combines them to generate 3D computer models and compare the results of experiments. But under this research project, scientists will develop a more advanced optical system (a spatial light modulator) to replace the focusing lens and allow the microscope to capture an entire sample more quickly with a single image. The new system will work by adapting the impulse response, or the way in which the signal from the CMOS sensor is modified. LCAV will lead the development work on the optical system. Simeoni explains: “Our goal is to improve the microscope’s optical properties, but that also means the image will be blurry and hard to read with the naked eye.” The research team will also work with EPFL’s Center for Imaging to program the right computational imaging methods. This project, called Digilight, will bring together recent advances in digital signal processing, computational imaging, structured light scanning, direct microscopy, image processing and CMOS technology in order to develop a rapid 3D microscopy system and enable the collection of an unparalleled amount of data. Three positions are open in the frame of this project: PhD in Computational Imaging for Third-Harmonic Generation Microscopy (EPFL Imaging Center/LCAV) Postdoctoral Fellowship in Computerized Third-Harmonic Generation Microscopy for Advanced Manufacturing (EPFL Imaging Center/LCAV) PhD in laser-based manufacturing methods for integrated Fabry-Perot resonators for quantum sensing applications (Galatea Lab) Cécilia Carron

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