Wilson plots

Definition

Wilson plots are a graphical representation used in crystallography to assess the quality of data collected during the refinement process. These plots illustrate the relationship between the observed structure factors and their corresponding calculated structure factors, allowing researchers to evaluate the goodness of fit and identify potential issues such as disorder or twinning in the crystal structure.

5 Must Know Facts For Your Next Test

1. Wilson plots help identify systematic errors in data collection by comparing observed versus calculated structure factors, making it easier to detect problems like disorder.
2. A linear relationship in a Wilson plot suggests that the model adequately represents the data, while deviations can indicate refinement issues such as incomplete or incorrect model parameters.
3. These plots can also be useful in determining overall B-factors, which reflect atomic displacement and are important for understanding thermal motion in the crystal structure.
4. Wilson plots can highlight regions of a crystal that may exhibit twinning, providing insights into how this affects data collection and refinement processes.
5. The application of Wilson plots is not limited to just identifying errors; they can also assist in improving model accuracy by guiding adjustments during refinement.

Review Questions

• How do Wilson plots help identify problems in data collection during crystallographic studies?
  • Wilson plots provide a visual representation of the relationship between observed and calculated structure factors. By analyzing the linearity of this plot, researchers can detect discrepancies that may indicate systematic errors in data collection. Such discrepancies could point to issues like disorder within the crystal or problems arising from twinning, allowing for targeted refinements to address these concerns.
• Discuss how deviations from linearity in Wilson plots can inform the refinement process in crystallography.
  • Deviations from linearity in Wilson plots signal that the current model does not adequately represent the data. This may result from incomplete structural information or inaccuracies in model parameters. By identifying specific regions where these deviations occur, researchers can make informed adjustments to improve the fit between observed and calculated values, ultimately enhancing the overall reliability of the structural model.
• Evaluate the role of Wilson plots in assessing the impact of twinning on crystal structure analysis and refinement.
  • Wilson plots play a crucial role in evaluating how twinning affects crystallographic analysis. When twinning occurs, it complicates diffraction patterns, leading to potential discrepancies in observed versus calculated data. By analyzing Wilson plots, researchers can identify specific anomalies that may arise due to twinning, allowing them to implement corrective measures during refinement. This evaluation is essential for ensuring accurate interpretations of crystal structures and minimizing errors introduced by twinned domains.

Related terms

Structure Factors:

Complex numbers that describe the amplitude and phase of scattered waves from a crystal lattice, essential for determining electron density.

Refinement: The process of adjusting model parameters to improve the agreement between observed and calculated data in crystallographic studies.

Twinning: A phenomenon where two or more crystal domains share some symmetry elements, complicating the interpretation of diffraction data.