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Updated: May 31, 2026

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Fully Autonomous Characterization and Data Collection from Crystals of Biological Macromolecules
Published on: March 22, 2019
Automatic loop centring with a high-precision goniometer head at the SLS macromolecular crystallography beamlines.
Anuschka Pauluhn1, Claude Pradervand, Daniel Rossetti
1Paul Scherrer Institut, Villigen, Switzerland. anuschka.pauluhn@psi.ch
Journal of Synchrotron Radiation
|June 21, 2011
Summary
Automated loop centering for crystallographic data collection is now faster and more accurate. This new system at the Swiss Light Source improves sample alignment and robotic mounting capabilities.
Area of Science:
- Crystallography
- Structural Biology
- Automation in Scientific Instrumentation
Background:
- Automated sample handling is crucial for high-throughput crystallographic data collection.
- Accurate centering of crystal loops is a key step in preparing samples for X-ray diffraction.
- Existing manual methods can be time-consuming and prone to user error.
Purpose of the Study:
- To develop and implement an automated loop centering system for crystallographic data collection.
- To improve the speed and accuracy of sample centering compared to manual methods.
- To integrate robotic sample mounting capabilities.
Main Methods:
- Algorithm development utilizing boundary and center-of-mass detection across two microscope magnifications.
- Implementation of a novel flexural-hinge-based compact goniometer head for precise sample alignment.
- Integration of an electromagnet for robotic wet sample mounting.
Main Results:
- Automated loop centering achieved in 15-26 seconds, comparable to manual speed.
- High precision alignment with a circle of confusion smaller than 1 µm (r.m.s.).
- Bidirectional backlash of the goniometer head measured below 2 µm.
Conclusions:
- The developed automatic loop centering system significantly enhances the automation of crystallographic data collection.
- The system offers high speed, accuracy, and integrates advanced robotic sample handling.
- This advancement is expected to improve efficiency and data quality in structural biology research.

