This work is a collaboration with the muon-spin relaxation community from the ISIS experimental facility. The muon-spin relaxation technique uses spin-polarized positive muons, which are generated at ISIS and then implanted in a chosen sample. This technique is a sensitive probe of magnetism, and can be used to probe the local static and dynamic magnetic properties of a sample and determine its microscopic magnetic structure. However, one of the limitations of the muon-spin relaxation technique is not knowing the site of implantation of the muon.
At the SCD, we are using a combination of computational tools, ranging from ab initio calculations to machine learning techniques, to model the behavior of muons in different materials and try to predict where these muons would be implanted during a muon-spin relaxation experiment.