X-Ray Tomography Group
Prof. Stampanoni heads a group of over 20 people, including three staff scientists, two technicians, one controls engineer, and many postdocs and PhD students. The team focuses on the development of tools, both instrumentation and algorithms, for tomographic X-ray imaging, exploiting synchrotron and laboratory sources. The group is engaged in the design and construction of ultra-fast data acquisition systems (stroboscopic coherent X-ray radiology and tomography) to provide dynamic investigation of rapidly evolving systems. The group also intensively develops optimized applications for fast, concurrent post-processing of tomographic data starting from simple normalization corrections to ad-hoc reconstruction and artifact reductions algorithms. Finally, the group investigates, creates and optimizes novel imaging modalities based on the coherent properties of synchrotron radiation and works on the transition of such work to conventional x-ray sources.
Scientific Highlights
Hierarchical imaging and computational analysis of three-dimensional vascular network architecture in mouse brain
An international team involving researchers from the University and University Hospital Zürich, the Krembil Research Institute and the University and University Hospital in Toronto (Canada), the Department of Physics of Jyväskylä (Finland), the University of Leuven (Belgium), the Johannes Kepler University in Linz (Austria), the Novartis Institutes for Biomedical Research in Emeryville (USA), the ETH Zürich and the Paul Scherrer Institute has developed a protocol that enables hierarchical imaging and computational analysis of vascular networks in entire postnatal- and adult mouse brains, enabling direct and quantitative comparisons of the morphological brain vascular network architecture between different postnatal and / or adult developmental stages. The results have been published on Nature Protocols on September 3rd, 2021.
Understanding Why Solid-State Batteries Fail
Researchers from the University of Oxford, the Diamond Light Source and the Paul Scherrer Institut have generated strong evidence supporting one of two competing theories regarding the mechanism by which lithium metal dendrites grow through ceramic electrolytes. A process leading to short circuit at high rates of charge. The X-ray phase-contrast imaging capabilities of the TOMCAT beamline of the Swiss light source allowed researchers to visualize and characterize the growth of cracks and dendrites deep within an operating solid-state battery. The results were published in Nature Materials on April 22, 2021.
Deep evolutionary origins of the human smile
Detailed characterization of the tooth and jaw structure and development among shark ancestors by synchrotron based X-ray tomographic microscopy at TOMCAT led an international team of researchers from the Naturalis Biodiversity Center in Leiden and the University of Bristol to the discovery that while teeth evolved once, complex dentitions have been gained and lost many times in evolutionary history.
3D printing silica aerogels at the micrometer scale
A group of EMPA and ETH Zürich researchers have developed a new method to directly write ink made of silica aerogels in 3D. Thanks to X-ray phase contrast tomography at the TOMCAT beamline they characterized the resulting printed material with different compositions. Their results were published in Nature on August 18, 2020.
Women in Engineering Materials highlights Dr. Lucia Romano's work
The paper "High aspect ratio grating microfabrication by Pt assisted chemical etching and Au electroplating” by Dr. Lucia Romano & coauthors has been highlighted in the "Women in Engineering Materials" Virtual Issue published on Advanced Engineering Materials. This Virtual Issue draws attention to outstanding works within Materials Science created under the lead of women as principal investigators.
Congratulations to Lucia and the x-ray optics design and fabrication team!
SLS 2.0 approved - TOMCAT 2.0 cleared for takeoff!
In December 2020 the Swiss parliament approved the Swiss Dispatch on Promotion of Education, Research and Innovation (ERI) for 2021 to 2024 which includes funding for the planned SLS 2.0 upgrade. The new machine will lead to significantly increased brightness, thus providing a firm basis for keeping the SLS and its beamlines state-of-the-art for the decades to come. The TOMCAT crew is very excited that the TOMCAT 2.0 plans (deployment of the S- and I-TOMCAT branches, see SLS 2.0 CDR, p. 353ff) have been included in the Phase-I beamline upgrade portfolio. These beamlines will receive first light right after the commissioning of the SLS 2.0 machine around mid 2025. A first milestone towards this goal has just been achieved, with the successful installation of the S-TOMCAT optics hutch during W1 of 2021. The TOMCAT scientific and technical staff would like to thank Mr. Nolte and his Innospec crew for delivering perfectly on schedule.
BEATS beamline scientist from SESAME synchrotron trains at TOMCAT
TOMCAT welcomes Gianluca Iori, beamline scientist from BEATS - the new beamline for tomography at the SESAME synchrotron in Jordan, to a 3-month training on beamline operations. Gianluca’s visit is part of the Staff Training (BEATS Work Package 2) organized for BEATS scientific staff and SESAME control engineers. BEATS is a European project, funded under the EU’s Horizon 2020 research and innovation programme and coordinated by the ESRF.
3 Post Docs and 1 PhD student join TOMCAT
The X-ray Tomography group welcomes Stefan Gstöhl (Post-Doc), Maxim Polikarpov (Post-Doc), Margaux Schmeltz (Post-Doc) and Aleksandra Ivanovic (PhD Student) as new members. The group also thank everybody who helped making it possible for our Post-Docs and PhD student to join PSI amidst the challenges brought by the COVID-19 pandemic.
Automatic extraction of dynamic features from sub-second tomographic microscopy data
A fully automatized iterative reconstruction pipeline designed to reconstruct and segment dynamic processes within a static matrix has been developed at TOMCAT. The algorithm performance is demonstrated on dynamic fuel cell data where it enabled automatic extraction of liquid water dynamics from sub-second tomographic microscopy data. The work is published in Scientific Reports on 2 October 2020.
4 times compression factor for tomographic data feasible
In a recent study, TOMCAT has shown that lossy compression by a factor of at least 3 to 4 of raw acquisitions generally does not affect the reconstruction quality and that higher factors (six to eight times) can be achieved for tomographic volumes with a high signal-to-noise ratio as it is the case for phase-retrieved datasets. This finding is relevant to current challenges on large tomography data management and storage especially at synchrotron facilities. The results of this study was published in Journal of Synchrotron Radiation.