High-resolution imaging with coherent X-rays - V. Favre Nicolin

QUICK INFORMATION
Type
Webinar
Start Date
23-10-2020 14:00
End Date
23-10-2020 15:00
Location
Zoom
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Coordinator contact(s)
Anne-Françoise Maydew

Scientific contact(s)
Patrick Bruno


  
Capture d’écran 2020-06-12 à 21.29.21.png
 

INVITATION

#ESRFscience Live Online Seminars

"High-resolution imaging with coherent X-rays "
Friday, October 23rd, 2:00 p.m.

 

Presented by Vincent Favre Nicolin, ESRF scientist
 
 The use of coherent X-rays for imaging has been steadily increasing for the past 25 years, from phase contrast imaging to coherent diffraction and ptychography experiments, resulting in two and three-dimensional material inspection with a spatial resolution down to about 10 nanometers. This progress is now enhanced by the ESRF-EBS upgrade, with an improved spatial and temporal resolution.
    I will present the various techniques which can be used for standard small-angle imaging, yielding the sample's electronic density, with applications from brain imaging to fuel cells, as well as those in the Bragg geometry, giving access to strain information, e.g. for semi-conductor nano-structures or catalysts.
    Most importantly I will show how algorithms and data processing have improved during the last few years with the PyNX package [1], providing a more robust data analysis which can be performed with limited supervision or hand-tuning. Additionally, efforts on a more efficient use of modern computing resources allows much faster two or three-dimensional reconstructions, both during and after the experimental time. These new analysis tools enable a wider community to take advantage of the increased coherent photon flux, and focus on working on an extended range of applications and samples.
 
[1] J. Appl. Cryst. (2020). 53, 1404-1413
 

Please click here to attend the webinar on Zoom:
https://esrf.zoom.us/j/94070404766?pwd=YUYyY0p2dlJXSU5QOSsxM0Q1Y3ovdz09
Passcode: py$2L3
Webinar ID: 940 7040 4766
 

Funding: The organisation of this online seminar series is supported by STREAMLINE, a European project funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement No 870313.