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Description
Phase problem has been long-standing in x-ray diffractive imaging. It is originated from the fact that only the amplitude of the scattered wave can be recorded by the detector, losing the phase information. The measurement of amplitude alone is insufficient to solve the structure. Therefore, phase retrieval is essential to structure determination with X-ray diffractive imaging. So far, many experimental as well as algorithmic approaches have been developed to address the phase problem. The experimental phasing methods, such as MAD, SAD etc, exploit the phase relation in vector space. They usually demand a lot of efforts to prepare the samples and require much more data. On the other hand, iterative phasing algorithms make use of the prior knowledge and various constraints in real and reciprocal space. In this thesis, new approaches to the problem of direct digital phasing of X-ray diffraction patterns from two-dimensional organic crystals were presented. The phase problem for Bragg diffraction from two-dimensional (2D) crystalline monolayer in transmission may be solved by imposing a compact support that sets the density to zero outside the monolayer. By iterating between the measured stucture factor magnitudes along reciprocal space rods (starting with random phases) and a density of the correct sign, the complex scattered amplitudes may be found (J. Struct Biol 144, 209 (2003)). However this one-dimensional support function fails to link the rod phases correctly unless a low-resolution real-space map is also available. Minimum prior information required for successful three-dimensional (3D) structure retrieval from a 2D crystal XFEL diffraction dataset were investigated, when using the HIO algorithm. This method provides an alternative way to phase 2D crystal dataset, with less dependence on the high quality model used in the molecular replacement method.
ContributorsZhao, Yun (Author) / Spence, John C.H. (Thesis advisor) / Schmidt, Kevin (Committee member) / Weierstall, Uwe (Committee member) / Kirian, Richard (Committee member) / Zatsepin, Nadia (Committee member) / Arizona State University (Publisher)
Created2016
Description
In disordered soft matter system, amorphous and crystalline components might be coexisted. The interaction between the two distinct structures and the correlation within the crystalline components are crucial to the macroscopic property of the such material. The spider dragline silk biopolymer, is one of such soft matter material that exhibits exceptional mechanical strength though its mass density is considerably small compare to structural metal. Through wide-angle X-ray scattering (WAXS), the research community learned that the silk fiber is mainly composed of amorphous backbone and $\beta$-sheet nano-crystals. However, the morphology of the crystalline system within the fiber is still not clear. Therefore, a combination of small-angle X-ray scattering experiments and stochastic simulation is designed here to reveal the nano-crystalline ordering in spider silk biopolymer. In addition, several density functional theory (DFT) calculations were performed to help understanding the interaction between amorphous backbone and the crystalline $\beta$-sheets.
By taking advantage of the prior information obtained from WAXS, a rather crude nano-crystalline model was initialized for further numerical reconstruction. Using Markov-Chain stochastic method, a hundreds of nanometer size $\beta$-sheet distribution model was reconstructed from experimental SAXS data, including silk fiber sampled from \textit{Latrodectus hesperus}, \textit{Nephila clavipes}, \textit{Argiope aurantia} and \textit{Araneus gemmoides}. The reconstruction method was implemented using MATLAB and C++ programming language and can be extended to study a broad range of disordered material systems.
By taking advantage of the prior information obtained from WAXS, a rather crude nano-crystalline model was initialized for further numerical reconstruction. Using Markov-Chain stochastic method, a hundreds of nanometer size $\beta$-sheet distribution model was reconstructed from experimental SAXS data, including silk fiber sampled from \textit{Latrodectus hesperus}, \textit{Nephila clavipes}, \textit{Argiope aurantia} and \textit{Araneus gemmoides}. The reconstruction method was implemented using MATLAB and C++ programming language and can be extended to study a broad range of disordered material systems.
ContributorsMou, Qiushi (Author) / Yarger, Jeffery (Thesis advisor) / Benmore, Chris (Committee member) / Holland, Gregory (Committee member) / Ros, Robert (Committee member) / Arizona State University (Publisher)
Created2015