K. Weigandt
National Institute of Standards and Technology,
United States
Keywords: Neutron Imaging, Far-Field Interferometry
Summary:
A colleague of mine likes to say that superman should have had “neutron vision” instead of “x-ray vision”. The reason lies in the nature of the interaction of these very different particles with the materials they are probing. X-rays are sensitive to electron density and are effectively blocked by high-z elements. The most obvious example of this is medical x-rays, where x-rays are very useful for imaging bones. Neutrons interact with the nuclei of the atom and this interaction can seem almost random with respect to atomic number and even isotopes. Neutron imaging has been used to locate water in a fully operational fuel cell and measure in situ water distribution and root growth in soil. These examples are excellent illustrations of how neutron imaging can be used to characterize the distribution of hydrogen and hydrogen containing molecules contained within or in the presence of other high-z materials. Even more powerful, is the combination of the neutron and x-ray imaging, which has been used to fully characterize rock core composition including mineral and kerogen distribution.[1] Over the last two decades, neutron imaging has rapidly evolved with improvements in resolution driven by ever improving digital camera technology and development of specialized optics. More recently, efforts have begun to seamlessly measure length scales from nanometers to centimeters with dark field imaging using grating interferometers.[2]. Far field interferometry will enable “tomographic SANS” measurements in heterogeneous materials. In addition to attenuation tomography, each 100 µm3 voxel will also contain microstructural information from 1 nm – 10 µm and provide unprecedented insight into the hierarchical structures of many natural and manmade materials. 1. J. M. LaManna et al, Review of Scientific Instruments 88, 113702 (2017); doi: 10.1063/1.4989642 2. A.J. Brooks et al, Materials and Design 140, 420–430 (2018); doi: 10.1016/j.matdes.2017.12.001