Neutronmapping

Neutronmapping is a computational imaging technique used in neutron science to reconstruct the spatial distribution of neutron flux or neutron interactions within a sample or device from detector data. It combines measurements from arrays of neutron detectors with geometric models of the illumination and detector arrangement to produce two- or three-dimensional maps of where neutrons originate or interact.

Data for neutronmapping are typically acquired in neutron imaging experiments, such as tomography or differential phase-contrast imaging, and may employ time-of-flight or energy-resolved detection to discriminate neutron energies. Each detected event is related to a possible line of response through the object; the mapping problem is formulated as an inverse problem solved by reconstruction algorithms.

Common algorithms include filtered back projection, algebraic reconstruction techniques, iterative methods with regularization, and Bayesian or maximum-entropy approaches. Prior information about the sample, such as smoothness or known material boundaries, is often incorporated to stabilize the solution and improve resolution.

Applications span materials science, energy research, and cultural heritage. Neutronmapping supports visualization of internal features in metals, ceramics, and hydrogen-rich materials, enabling studies of porosity, phase distribution, moisture content, and diffusion pathways. It is particularly valuable for locating light elements like hydrogen, which interact weakly with X-rays but strongly with neutrons.

Limitations include dependence on neutron source flux, detector efficiency, and geometry, which constrain spatial resolution and acquisition time. Radiation safety, background scattering, and sample activation also affect quality and practicality. Ongoing advances in detector technology, data processing, and source facilities continue to enhance the capabilities of neutronmapping.