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Description
The superior brightness and ultra short pulse duration of X-ray free electron laser
(XFEL) allows it to outrun radiation damage in coherent diffractive imaging since elastic scattering terminates before photoelectron cascades commences. This “diffract-before-destroy” feature of XFEL opened up new opportunities for biological macromolecule imaging and structure studies by breaking the limit to spatial resolution imposed by the maximum dose that is allowed before radiation damage. However, data collection in serial femto-second crystallography (SFX) using XFEL is affected by a bunch of stochastic factors, which pose great challenges to the data analysis in SFX. These stochastic factors include crystal size, shape, random orientation, X-ray photon flux, position and energy spectrum. Monte-Carlo integration proves effective and successful in extracting the structure factors by merging all diffraction patterns given that the data set is sufficiently large to average out all stochastic factors. However, this approach typically requires hundreds of thousands of patterns collected from experiments. This dissertation explores both experimental and algorithmic methods to eliminate or reduce the effect of stochastic factors in data acquisition and analysis. Coherent convergent X-ray beam diffraction (CCB) is discussed for possibilities of obtaining single-shot angular-integrated rocking curves. It is also shown the interference between Bragg disks helps ab-initio phasing. Two-color diffraction scheme is proposed for time-resolved studies and general data collection strategies are discussed based on error metrics. A new auto-indexing algorithm for sparse patterns is developed and demonstrated for both simulated and experimental data. Statistics show that indexing rate is increased by 3 times for I3C data set collected from beam time LJ69 at Linac coherent light source (LCLS). Finally, dynamical inversion from electron diffraction is explored as an alternative approach for structure determination.
(XFEL) allows it to outrun radiation damage in coherent diffractive imaging since elastic scattering terminates before photoelectron cascades commences. This “diffract-before-destroy” feature of XFEL opened up new opportunities for biological macromolecule imaging and structure studies by breaking the limit to spatial resolution imposed by the maximum dose that is allowed before radiation damage. However, data collection in serial femto-second crystallography (SFX) using XFEL is affected by a bunch of stochastic factors, which pose great challenges to the data analysis in SFX. These stochastic factors include crystal size, shape, random orientation, X-ray photon flux, position and energy spectrum. Monte-Carlo integration proves effective and successful in extracting the structure factors by merging all diffraction patterns given that the data set is sufficiently large to average out all stochastic factors. However, this approach typically requires hundreds of thousands of patterns collected from experiments. This dissertation explores both experimental and algorithmic methods to eliminate or reduce the effect of stochastic factors in data acquisition and analysis. Coherent convergent X-ray beam diffraction (CCB) is discussed for possibilities of obtaining single-shot angular-integrated rocking curves. It is also shown the interference between Bragg disks helps ab-initio phasing. Two-color diffraction scheme is proposed for time-resolved studies and general data collection strategies are discussed based on error metrics. A new auto-indexing algorithm for sparse patterns is developed and demonstrated for both simulated and experimental data. Statistics show that indexing rate is increased by 3 times for I3C data set collected from beam time LJ69 at Linac coherent light source (LCLS). Finally, dynamical inversion from electron diffraction is explored as an alternative approach for structure determination.
ContributorsLi, Chufeng (Author) / Spence, John CH (Thesis advisor) / Spence, John (Committee member) / Kirian, Richard (Committee member) / Weierstall, Uwe (Committee member) / Schmidt, Kevin (Committee member) / Arizona State University (Publisher)
Created2016
Description
Serial femtosecond crystallography (SFX) uses diffraction patterns from crystals delivered in a serial fashion to an X-Ray Free Electron Laser (XFEL) for structure determination. Typically, each diffraction pattern is a snapshot from a different crystal. SFX limits the effect of radiation damage and enables the use of nano/micro crystals for structure determination. However, analysis of SFX data is challenging since each snapshot is processed individually.
Many photosystem II (PSII) dataset have been collected at XFELs, several of which are time-resolved (containing both dark and laser illuminated frames). Comparison of light and dark datasets requires understanding systematic errors that can be introduced during data analysis. This dissertation describes data analysis of PSII datasets with a focus on the effect of parameters on later results. The influence of the subset of data used in the analysis is also examined and several criteria are screened for their utility in creating better subsets of data. Subsets are compared with Bragg data analysis and continuous diffuse scattering data analysis.
A new tool, DatView aids in the creation of subsets and visualization of statistics. DatView was developed to improve the loading speed to visualize statistics of large SFX datasets and simplify the creation of subsets based on the statistics. It combines the functionality of several existing visualization tools into a single interface, improving the exploratory power of the tool. In addition, it has comparison features that allow a pattern-by-pattern analysis of the effect of processing parameters. \emph{DatView} improves the efficiency of SFX data analysis by reducing loading time and providing novel visualization tools.
Many photosystem II (PSII) dataset have been collected at XFELs, several of which are time-resolved (containing both dark and laser illuminated frames). Comparison of light and dark datasets requires understanding systematic errors that can be introduced during data analysis. This dissertation describes data analysis of PSII datasets with a focus on the effect of parameters on later results. The influence of the subset of data used in the analysis is also examined and several criteria are screened for their utility in creating better subsets of data. Subsets are compared with Bragg data analysis and continuous diffuse scattering data analysis.
A new tool, DatView aids in the creation of subsets and visualization of statistics. DatView was developed to improve the loading speed to visualize statistics of large SFX datasets and simplify the creation of subsets based on the statistics. It combines the functionality of several existing visualization tools into a single interface, improving the exploratory power of the tool. In addition, it has comparison features that allow a pattern-by-pattern analysis of the effect of processing parameters. \emph{DatView} improves the efficiency of SFX data analysis by reducing loading time and providing novel visualization tools.
ContributorsStander, Natasha (Author) / Fromme, Petra (Thesis advisor) / Zatsepin, Nadia (Thesis advisor) / Kirian, Richard (Committee member) / Liu, Wei (Committee member) / Arizona State University (Publisher)
Created2019