X-Ray Diffraction as a Characterisation Method

Learning Outcomes

Learning Outcomes

Having successfully completed this module you will be able to:

• Understand and apply the various types of powder diffraction experiment and appreciate the importance of sample preparation.
• Evaluate the differences and synergies of powder and single crystal diffraction.
• Apply the concepts of unit cells and lattices to describe observed diffraction patterns in reciprocal space.
• Be aware off advanced techniques such as X-ray reflectivity, texture analyse and high-resolution measurements.
• Have an understanding of the advantages of synchrotron and neutron diffraction and the additional information they can provide.
• Interpret data using line positions and profiles.
• Setup data collection strategies and collect data on both a single crystal and powder samples.
• Understand the basics of X-ray diffraction theory in terms of X-rays, diffraction and Bragg’s Law.
• Be aware of and use various crystallographic databases.
• Process data, solve/refine and interpret a single crystal structure.
• Understand point and translational symmetry elements and derive symmetry from measured data.
• Complete a Rietveld refinement and extract crystallographic and sample information.
• Understand solid-state matter in terms of crystallinity and bonding.
• Perform basic calculations relating to crystal planes, lattice parameters and sample characteristics.

PART 1 Basics of Diffraction & Materials

Types of bonding and materials, X-rays and Bragg’s Law, unit cells and lattices, reciprocal space, symmetry, space-groups and systematic absences.

PART 2 Single crystal diffraction

Collecting and processing data, structure solution and refinement, structure validation.

PART 3 Powder diffraction

Diffraction geometry, indexing, line profile analysis and residual stress, Rietveld, reflectivity and high-resolution diffraction, texture and non-crystalline diffraction.

PART 4 Combined Topics

Synchrotron diffraction, neutron diffraction, databases.

Lectures, demonstrations, data analysis workshops, practical sessions, self-study problems

Summative

This is how we’ll formally assess what you have learned in this module.