Publication

We hope that your P05 beamtime was as enjoyable as it was fruitful. When your research is ready for pulication and is based on / contains experiments performed at P05 we would kindly ask to add your local contact to the coauthor list. Running and keeping a syncrotron beamline up to its potential is a demanding task and involves a lot of research and development which unfortunately goes often unseen by external users. Since most of our beamtime is dedicated to external users, we are relying on visibilty through user publications. Your publications enables us to justify and maintain this work. Thank you for your cooperation!

In addition to adding the local contact to the coauthor list, we would kindly ask you to add the following references to your publication:

TXM setup with Zernike phase contrast:

1. S. Flenner, M. Storm, A. Kubec, E. Longo, F. Doring, D. M. Pelt, C. David, M. Muller, and I. Greving, "Pushing the temporal resolution in absorption and Zernike phase contrast nanotomography: Enabling fast in situ experiments," J. Synchrotron Radiat. 27, 1339–1346 (2020). 

Zernike phase contrast with large field of view (ROI scans):

E. Longo, L. Sancey, S. Flenner, A. Kubec, A. Bonnin, C. David, M. Müller, and I. Greving, "X-ray Zernike phase contrast tomography: 3D ROI visualization of mm-sized mice organ tissues down to sub-cellular components," Biomed. Opt. Express 11(10), 5506 (2020).

Holotomography setup:

 S. Flenner, A. Kubec, C. David, M. Storm, C. F. Schaber, F. Vollrath, M. Müller, I. Greving, and J. Hagemann, "Hard X-ray nano-holotomography with a Fresnel zone plate," Opt. Express 28(25), 37514 (2020). https://doi.org/10.1364/OE.406074

Machine learning denoising:

Flenner, S., Bruns, S., Longo, E., Parnell, A. J., Stockhausen, K. E., Müller, M., & Greving, I. (2022). Machine learning denoising of high-resolution X-ray nanotomography data. Journal of Synchrotron Radiation, 29(1), 230–238. https://doi.org/10.1107/s1600577521011139

Holotomography reconstruction:

Dora, J., Möddel, M., Flenner, S., Schroer, C. G., Knopp, T., & Hagemann, J. (2024). Artifact-suppressing reconstruction of strongly interacting objects in X-ray near-field holography without a spatial support constraint. Optics Express, 32(7), 10801. https://doi.org/10.1364/OE.514641

Dora, J., Flenner, S., Lopes Marinho, A., Grün, J. & Hagemann, J. HoloWizard: A Python framework for processing X-ray near-field holography data version v2.0.0. July 2025. https://doi.org/10.5281/zenodo.16275928