2018/08/22 by B. Heacock, Dusan Sarenac, D. Sarenac +9 · 15 citations
Earth and Planetary Sciences · Materials Science · Physics and Astronomy · #Artificial intelligence #Computer science #Diffraction #High-pressure geophysics and materials #Image resolution #Materials science #Neutron #Neutron diffraction #Neutron imaging #Neutron scattering #Nuclear Physics and Applications #Nuclear physics #Optics #Physics #Resolution (logic) #Scattering #Small-angle neutron scattering #Tomographic reconstruction #Tomography #X-ray Diffraction in Crystallography #nucl-ex #physics.ins-det
paper · pdf · doi:10.1107/s2052252520010295
published in IUCrJ 7(5), 893-900 (International Union of Crystallography)
arxiv created 2018/08/22 · openalex publication_date 2020/08/19 · arxiv updated 2020/11/13 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01
Neutrons are valuable probes for various material samples across many areas of research. Neutron imaging typically has a spatial resolution of larger than 20 µm, whereas neutron scattering is sensitive to smaller features but does not provide a real-space image of the sample. A computed-tomography technique is demonstrated that uses neutron-scattering data to generate an image of a periodic sample with a spatial resolution of ∼300 nm. The achieved resolution is over an order of magnitude smaller than the resolution of other forms of neutron tomography. This method consists of measuring neutron diffraction using a double-crystal diffractometer as a function of sample rotation and then using a phase-retrieval algorithm followed by tomographic reconstruction to generate a map of the sample's scattering-length density. Topological features found in the reconstructions are confirmed with scanning electron micrographs. This technique should be applicable to any sample that generates clear neutron-diffraction patterns, including nanofabricated samples, biological membranes and magnetic materials, such as skyrmion lattices.