Paper 14110-19
Tilt angle estimation for conical diffraction correction in lensless imaging of nanostructures
16 April 2026 • 09:50 - 10:10 CEST | Madrid 1/Salon 3 (Niveau/Level 0)
Abstract
Coherent Diffractive Imaging (CDI) is a promising method for the metrology of EUV masks and wafers because of its contained costs and ease of implementation. The imaging step in CDI is performed computationally by iterating back and forth among the real and the Fourier space to reconstruct the missing phase. This usually implies the use of Fast Fourier Transforms to model light propagation between the sample and diffraction plane. When the data is collected with a detector which is tilted with respect to the sample (or viceversa), the diffraction patterns are distorted at the detector plane. The distorted data cannot be directly processed with the aforementioned propagation method, however it can be re–mapped (diffraction correction) onto a suitable grid for such a purpose. This mapping is performed with an interpolation step, which is computationally expensive and prone to errors due to the uncertainty of the exact illumination angle in a typical experimental setup. Here, we present an approach for diffraction correction for CDI which is based on an efficient routine that estimates the tilt angle with high accuracy from a diffraction pattern alone and performs the mapping of the diffraction data efficiently.
Presenter
Paolo Ansuinelli
Paul Scherrer Institute (Switzerland)
Paolo Ansuinelli received the MsC in nanotechnology engineering from La Sapienza, the University of Rome and the PhD in optics from TU Delft, with a thesis focused on inverse problems in semiconductor metrology, especially scatterometry and coherent diffractive imaging. Afterwards, he joined ASML (the Netherlands), as a member of the projection optics group, where he was primarily involved with the thermal and optical modeling of the NXE:3800 lens. Following this appointment, he joined the Paul Scherrer Institute (PSI) in Switzerland, as a member of the advanced lithography and metrology group. His current research work lies at the intersection of coherent diffractive imaging and deep learning for applications in semiconductor metrology.