Prospects for kinematical least-squares refinement in polymer electron crystallography.

Area of Science:

• Crystallography
• Polymer Science
• Materials Science

Background:

• Electron crystallography presents challenges for least-squares refinement due to sparse intensity data and dynamical scattering errors.
• Accurate structural models are crucial for understanding polymer properties and behavior.

Purpose of the Study:

• To evaluate conditions for improving structural models in electron crystallography using least-squares refinement.
• To refine the structure of polymorphic form III of isotactic poly(1-butene) using limited diffraction data.

Main Methods:

• Collected 120 unique hkl electron diffraction intensities from poly(1-butene) polymorphic form III.
• Employed constrained least-squares refinement cycles on an existing structural model derived from direct methods.
• Analyzed crystallographic residuals (R-factor) and weighted residuals (based on |F|²) to assess refinement quality.

Main Results:

• Least-squares refinement improved bonding parameters and lowered the conventional crystallographic residual from R = 0.26 to R = 0.185 (58 reflections) and R = 0.216 (120 reflections).
• Weighted residuals based on |F|² decreased from 0.50 to 0.41 for the complete dataset.
• Attempts to incorporate weak intensity data did not improve refinement; dynamical scattering effects were observed in thermal parameters.

Conclusions:

• Constrained least-squares refinement is effective for improving poly(1-butene) structural models in electron crystallography.
• The study highlights the importance of careful data handling and acknowledges limitations due to dynamical scattering.