Representational Analysis of Magnetic Structures
Ended May 1, 2022
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Full course description
Please visit our site, go.umd.edu/magnetic , for more information.
Neutron diffraction: One of the most powerful techniques for exploring the magnetic materials and compounds is neutron scattering. When a material develops long-range magnetic ordering, neutron diffraction is the perfect technique to determine the struture of such ordering. In this school, you will be working with neutron data from both single crystal and powder neutron diffraction and learning the basic concepts of representational analysis to interpret the data.
Representational analysis: Modern science has given rise to exotic materials with interesting bulk properties, which can only be understood in light of their magnetic structures. However, these magnetic structures are increasingly complex and characterized by a large number of parameters. In order to reduce this complexity one must apply representational analysis to take advantage of the inherent symmetries in the crystallographic systems studied.
Target audience: The school is intended for advanced graduate students, post-doctoral fellows, and young scientists working in condensed matter physics, materials science, and related fields. The main goal is to provide an overview of this rapidly growing field so that young scientists will have the opportunity to work at the frontiers of this new exciting field.
Topics will include
- Representational analysis and magnetic space group symmetry
- Magnetic structure determination from powder and single crystal data
- Developments in refinement techniques and examples
- Commensurate and incommensurate magnetic ordering
- Software tools for modeling magnetic structures include:
(1) ISOTROPY Software Suite
(2) Bilbao Crystallographic Server
(4) JANA 2020