학술논문
Structure Prediction from Neutron Scattering Profiles: A Data Sciences Approach
Document Type
Conference
Author
Source
2020 IEEE International Conference on Big Data (Big Data) Big Data (Big Data), 2020 IEEE International Conference on. :1147-1155 Dec, 2020
Subject
Language
Abstract
One of the main goals of neutron data analysis is to determine the internal structure of materials from their neutron scattering profiles. These structures are defined by a crystallographic class label and a set of real-valued parameters specific to that class. Existing structure analysis approaches use computationally expensive loop refinements methods that routinely take days, and even weeks, to complete. Additionally, the outcomes often rely on the fidelity of physical models that are computed during the refinement process.