EPFL news on enhanced chemical analysis at the nanoscale
In a front-page news article, EPFL profiles the latest publication from LSME, part of the lab’s ongoing work on innovating novel machine learning approaches for the improved analysis of analytical TEM data: AI enhances chemical analysis at the nanoscale
Improving X-ray analytics: new publication in Nano Letters!
Just out in Nano Letters is our 100% lab-driven work on: Leveraging Machine Learning for Advanced Nanoscale X-ray Analysis: Unmixing Multicomponent Signals and Enhancing Chemical Quantification In this letter, LSME introduces a new method for processing STEM-EDX spectroscopy data sets, that we term non-negative matrix factorization based pan-sharpening (PSNMF). Leveraging the Poisson nature of EDX (…)
Welcoming two new collaborators!
This November, we were pleased to have two new collaborators join the LSME team. During his studies of applied physics and renewable energy studies, Sebastian Cozma discovered a deep interest in microstructure characterization and analytical techniques. To pursue this interest, Sebastian is beginning a Ph.D. with Prof. Cécile Hébert on segmentation and quantification of STEM (…)
New in ACS Nano: EELS mapping of dielectric photonic nanocavities
In a new article published in ACS Nano, working with Dr Valentin Flauraud and Dr Frank Demming-Janssen, LSME scientist Dr Duncan Alexander uses advanced electron spectroscopy and finite element simulations to analyse the spatial and spectral signatures of different optical excitations supported in patterned silicon photonic nanocavities. By sampling nanocavities of different shapes and sizes, (…)
New in Acta Materialia: growth of grain triplets in ZnO thin films
Just published in Acta Materialia, using the detailed analysis of transmission electron microscopy (TEM) data, researchers from the LSME identify a novel growth mechanism of grain triplets in polycrystalline thin films of ZnO. The study primarily depends on the mining of data acquired using automated crystal orientation mapping with scanning nanobeam electron diffraction, which is (…)
Welcome to Adrien Teurtrie!
We are pleased to announce the arrival of Dr Adrien Teurtrie, who joins the LSME as a post-doctoral researcher on projects of Opening Up Hyperspectral TEM Data, as supported by the EPFL Open Science Fund, and new approaches to hyperspectral data decomposition using machine learning methods. Adrien recently completed a PhD in the STEM Group (…)
EPFL feature on Cécile Hébert
LSME director Prof. Cécile Hébert is interviewed in this profile that currently features on EPFL’s homepage. Cécile, who was recently awarded the prize for best physics teacher at EPFL, discusses her career and research, and her novel approaches to teaching physics to EPFL’s bachelors and masters students.
Special guest at LSME
We are very pleased to welcome Dr Juan Carlos Idrobo from the Center for Nanophase Materials Science at the Oak Ridge National Laboratory for a two day visit. Dr Idrobo has been invited to present a seminar in the Quantum Science and Condensed Matter series, where he gives “A Glimpse into Electron Microscopy in the (…)
Teaching award for LSME director!
Congratulations to LSME director Prof. Cécile Hébert for being awarded the 2019 prize of best teacher in the Physics Section at the recent “Magistrale” Graduation Day!
Poster prize at Microscopy Conference 2019!
Congratulations to LSME PhD student Hui Chen, who received a Best Poster Award for Materials Science at the recent Microscopy Conference 2019 in Berlin. At the conference, Chen presented a poster on her ongoing research into improved STEM hyperspectral data segmentation and quantification entitled “STEM EDS/(EELS) for Deep-Mantle Rock Assemblages Analyses Assisted by Machine Learning”.