The aim of the course is to introduce students to the interaction of X-ray and matter, with application into structural characterization. Students will learn to interpret complex scattering/diffraction patterns, the nuts and bolts of X-ray instrumentation, and the science behind (and practical aspects of) data collection, correction and analysis. The course is aimed at (primarily, but not exclusively) students who are likely to become expert users of the X-ray facilities at ISTA, or who need deeper understanding of structural characterization.
Lectures:
1. Interaction of X-rays with matter. Elastic scattering, atomic form factors.
2. Scattering at phase boundaries. Form factor of nanoparticles, pores and biomolecules.
3. Scattering in crystals. Structure factor, most common crystal lattices. Miller indices.
4. Non-idealities in diffraction/scattering data: domain size, strain, occupation, disorder, symmetry breaking, absorption/fluorescence.
5. Instrumentation: sources, optics, detectors.
6. Data collection on XRD and SAXS (samples provided by students).
7. Dealing with data: range, resolution, corrections, information content.
8. Dealing with data: fitting to models (SAXS).
9. Dealing with data: Rietveld-refinement (XRD).
10. Inelastic scattering/anomalous diffraction, X-ray absorption fine structure.
11. Instrumentation: synchrotrons.
12. Extra time, discussions.
Practicals:
1. Refractive index and form factor calculations in Matlab/Python/etc.
2. Structure factor calculations manually and in Vesta or similar software.
3. Data collection: XRD.
4. Data collection: SAXS.
5. Working on the collected data.
6. Working on the collected data.
Target group: current or future users of the X-ray facilities who need deeper understanding of the science, technology and data processing
Prerequisites: fundamental understanding crystals, waves and electronics (e.g. BSc-level courses on Solid State or Condensed Matter Physics, Structure of Matter, Inorganic Chemistry, Electromagnetism, Spectroscopy, Scientific Instrumentation, or anything similar)
Evaluation: participation, report on data analysis
Teaching format: Lectures (2x a week), Practicals (1x a week), report on data analysis
ECTS: 3 Year: 2022
Track segment(s):
Elective
Teacher(s):
Daniel Balazs
Teaching assistant(s):
If you want to enroll to this course, please click: REGISTER
- Teacher: Daniel Balazs