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Title: Improving signal strength in serial crystallography with DIALS geometry refinement

Abstract

The DIALS diffraction-modeling software package has been applied to serial crystallography data. Diffraction modeling is an exercise in determining the experimental parameters, such as incident beam wavelength, crystal unit cell and orientation, and detector geometry, that are most consistent with the observed positions of Bragg spots. These parameters can be refined by nonlinear least-squares fitting. In previous work, it has been challenging to refine both the positions of the sensors (metrology) on multipanel imaging detectors such as the CSPAD and the orientations of all of the crystals studied. Since the optimal models for metrology and crystal orientation are interdependent, alternate cycles of panel refinement and crystal refinement have been required. To simplify the process, a sparse linear algebra technique for solving the normal equations was implemented, allowing the detector panels to be refined simultaneously against the diffraction from thousands of crystals with excellent computational performance. Separately, it is shown how to refine the metrology of a second CSPAD detector, positioned at a distance of 2.5 m from the crystal, used for recording low-angle reflections. With the ability to jointly refine the detector position against the ensemble of all crystals used for structure determination, it is shown that ensemble refinement greatly reducesmore » the apparent nonisomorphism that is often observed in the unit-cell distributions from still-shot serial crystallography. In addition, it is shown that batching the images by timestamp and re-refining the detector position can realistically model small, time-dependent variations in detector position relative to the sample, and thereby improve the integrated structure-factor intensity signal and heavy-atom anomalous peak heights.« less

Authors:
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Publication Date:
Research Org.:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1468376
Alternate Identifier(s):
OSTI ID: 1477374
Grant/Contract Number:  
AC02-05CH11231
Resource Type:
Journal Article: Published Article
Journal Name:
Acta Crystallographica. Section D. Structural Biology
Additional Journal Information:
Journal Name: Acta Crystallographica. Section D. Structural Biology Journal Volume: 74 Journal Issue: 9; Journal ID: ISSN 2059-7983
Publisher:
International Union of Crystallography (IUCr)
Country of Publication:
United Kingdom
Language:
English
Subject:
36 MATERIALS SCIENCE

Citation Formats

Brewster, Aaron S., Waterman, David G., Parkhurst, James M., Gildea, Richard J., Young, Iris D., O'Riordan, Lee J., Yano, Junko, Winter, Graeme, Evans, Gwyndaf, and Sauter, Nicholas K. Improving signal strength in serial crystallography with DIALS geometry refinement. United Kingdom: N. p., 2018. Web. doi:10.1107/S2059798318009191.
Brewster, Aaron S., Waterman, David G., Parkhurst, James M., Gildea, Richard J., Young, Iris D., O'Riordan, Lee J., Yano, Junko, Winter, Graeme, Evans, Gwyndaf, & Sauter, Nicholas K. Improving signal strength in serial crystallography with DIALS geometry refinement. United Kingdom. https://doi.org/10.1107/S2059798318009191
Brewster, Aaron S., Waterman, David G., Parkhurst, James M., Gildea, Richard J., Young, Iris D., O'Riordan, Lee J., Yano, Junko, Winter, Graeme, Evans, Gwyndaf, and Sauter, Nicholas K. 2018. "Improving signal strength in serial crystallography with DIALS geometry refinement". United Kingdom. https://doi.org/10.1107/S2059798318009191.
@article{osti_1468376,
title = {Improving signal strength in serial crystallography with DIALS geometry refinement},
author = {Brewster, Aaron S. and Waterman, David G. and Parkhurst, James M. and Gildea, Richard J. and Young, Iris D. and O'Riordan, Lee J. and Yano, Junko and Winter, Graeme and Evans, Gwyndaf and Sauter, Nicholas K.},
abstractNote = {The DIALS diffraction-modeling software package has been applied to serial crystallography data. Diffraction modeling is an exercise in determining the experimental parameters, such as incident beam wavelength, crystal unit cell and orientation, and detector geometry, that are most consistent with the observed positions of Bragg spots. These parameters can be refined by nonlinear least-squares fitting. In previous work, it has been challenging to refine both the positions of the sensors (metrology) on multipanel imaging detectors such as the CSPAD and the orientations of all of the crystals studied. Since the optimal models for metrology and crystal orientation are interdependent, alternate cycles of panel refinement and crystal refinement have been required. To simplify the process, a sparse linear algebra technique for solving the normal equations was implemented, allowing the detector panels to be refined simultaneously against the diffraction from thousands of crystals with excellent computational performance. Separately, it is shown how to refine the metrology of a second CSPAD detector, positioned at a distance of 2.5 m from the crystal, used for recording low-angle reflections. With the ability to jointly refine the detector position against the ensemble of all crystals used for structure determination, it is shown that ensemble refinement greatly reduces the apparent nonisomorphism that is often observed in the unit-cell distributions from still-shot serial crystallography. In addition, it is shown that batching the images by timestamp and re-refining the detector position can realistically model small, time-dependent variations in detector position relative to the sample, and thereby improve the integrated structure-factor intensity signal and heavy-atom anomalous peak heights.},
doi = {10.1107/S2059798318009191},
url = {https://www.osti.gov/biblio/1468376}, journal = {Acta Crystallographica. Section D. Structural Biology},
issn = {2059-7983},
number = 9,
volume = 74,
place = {United Kingdom},
year = {Mon Sep 03 00:00:00 EDT 2018},
month = {Mon Sep 03 00:00:00 EDT 2018}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record at https://doi.org/10.1107/S2059798318009191

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Cited by: 42 works
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Works referenced in this record:

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