REPLAY - SSE9 - Olivier Martin

On The March 2, 2023

Olivier Martin, Nanophotonics and Metrology Lab at EPFL, during the SSE9 - UJM
Olivier Martin, Nanophotonics and Metrology Lab at EPFL, during the SSE9 - UJM

Missed a lecture during the 9th SLEIGHT Science Event ? Here is the replay

Olivier Martin, Professor at EPFL and researcher at the Nanophotonics and Metrology Lab in Lausanne, Switzerland, gave a lecture on plasmonics nanostructures.

Plasmonics studies the optical response of metallic nanostructures made from coinage metals (Au, Ag, Al, and a few others) which have an especially strong interaction with light in the visible part of the spectrum. For a given metal this interaction is also governed by the shape of the nanostructures and it is important to control their fabrication with un accuracy in the order of 20 nm. Nanotechnology is therefore at the heart of this field of research and, after a brief introduction to plasmonics, he described different approaches for the fabrication of plasmonic nanostructures. They can be divided into either top-down techniques like electron-beam lithography with lift-off or etching; or bottom-up approaches, such as chemical synthesis. For the latter, he showed that even human cells can produce plasmonic nanostructures by reducing a gold salt. Among the numerous applications of plasmonic nanostructures, he focused on near-field enhancement with its application to surface enhanced Raman spectroscopy and on the generation of strong optical forces with plasmonic nanostructures.

Besides, a collection of plasmonic nanostructures deposited on a surface can build a so-called metasurface – the modern equivalent of planar optics – with applications in holography and biosensing. Numerical simulations are also essential to guide these experiments at the nanoscale and the presentation will include some of our research efforts on the development of suitable numerical techniques that can match well the effectively fabricated nanostructures. Finally, he reported some on-going work on the design of plasmonic nano-motors using a machine learning approach and illustrate its suitability to discover plasmonic nanostructures with an especially strong torque under linear-polarized light illumination.