In JoVE (1)
Other Publications (1)
Articles by Lucian Roiban in JoVE
Obtaining 3D Chemical Maps by Energy Filtered Transmission Electron Microscopy Tomography Lucian Roiban1, Loïc Sorbier2, Charles Hirlimann3, Ovidiu Ersen3 1Univ Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, 2IFP Energies nouvelles, 3Institut de Physique et Chimie des Matériaux de Strasbourg (IPCMS) This paper describes a protocol to achieve 3D chemical maps combining energy filtered imaging and electron tomography. The chemical distribution of two catalyst supports formed by elements that are difficult to distinguish by other imaging techniques was studied. Each application consists of mapping overlapped chemical elements - respectively spaced-ionization edges.
Other articles by Lucian Roiban on PubMed
Evaluation of Noise and Blur Effects with SIRT-FISTA-TV Reconstruction Algorithm: Application to Fast Environmental Transmission Electron Tomography Ultramicroscopy. Jun, 2018 | Pubmed ID: 29655113 Fast tomography in Environmental Transmission Electron Microscopy (ETEM) is of a great interest for in situ experiments where it allows to observe 3D real-time evolution of nanomaterials under operating conditions. In this context, we are working on speeding up the acquisition step to a few seconds mainly with applications on nanocatalysts. In order to accomplish such rapid acquisitions of the required tilt series of projections, a modern 4K high-speed camera is used, that can capture up to 100 images per second in a 2K binning mode. However, due to the fast rotation of the sample during the tilt procedure, noise and blur effects may occur in many projections which in turn would lead to poor quality reconstructions. Blurred projections make classical reconstruction algorithms inappropriate and require the use of prior information. In this work, a regularized algebraic reconstruction algorithm named SIRT-FISTA-TV is proposed. The performance of this algorithm using blurred data is studied by means of a numerical blur introduced into simulated images series to mimic possible mechanical instabilities/drifts during fast acquisitions. We also present reconstruction results from noisy data to show the robustness of the algorithm to noise. Finally, we show reconstructions with experimental datasets and we demonstrate the interest of fast tomography with an ultra-fast acquisition performed under environmental conditions, i.e. gas and temperature, in the ETEM. Compared to classically used SIRT and SART approaches, our proposed SIRT-FISTA-TV reconstruction algorithm provides higher quality tomograms allowing easier segmentation of the reconstructed volume for a better final processing and analysis.