| dc.identifier.uri | http://hdl.handle.net/11401/77641 | |
| dc.description.sponsorship | This work is sponsored by the Stony Brook University Graduate School in compliance with the requirements for completion of degree. | en_US |
| dc.format | Monograph | |
| dc.format.medium | Electronic Resource | en_US |
| dc.language.iso | en_US | |
| dc.publisher | The Graduate School, Stony Brook University: Stony Brook, NY. | |
| dc.type | Thesis | |
| dcterms.abstract | Obtaining correct intensities and their uncertainties are imperative for acquiring meaningful structural parameters for high-pressure X-ray powder diffraction data that typically have intrinsically low peak-to-background ratios of measured intensities. This is important for full structural determination techniques. Commonly used software packages like Fit2D and pyFAI are useful for reducing 2D X-ray powder diffraction (XPD) images into 1D diffraction plots. However, the default weighting scheme that programs use for fitting diffraction data normally causes unreasonable goodness of fit values, which causes statistical uncertainties to seldom be determined. Hence, we created an integrated open source data analysis software that builds on pyFAI, which was possible because it uses the relatively easy to use open source Python programming language. Our program can covert 2D X-ray powder diffraction images taken from 2D detectors into 1D diffraction data using azimuthal integration with a routine that performs a statistical bin analysis of the collected diffraction intensities. The statistical analysis will be used to provide reliable intensities with calculated intensity errors and any contributions to the diffraction pattern not coming from the sample will be automatically filtered out utilizing this analysis. Due to this, the program can provide meaningful intensity error estimates for high-pressure synchrotron XPD data, which can then be utilized for performing an in-depth structural analysis using Rietveld refinement. This will allow for more precise structure determination and give way for the development of robust structure-property relationships in materials at extreme conditions. | |
| dcterms.available | 2017-09-20T16:53:09Z | |
| dcterms.contributor | Parise, John | en_US |
| dcterms.contributor | Ehm, Lars | en_US |
| dcterms.contributor | Ghose, Sanjit. | en_US |
| dcterms.creator | Rhymer, Brandon | |
| dcterms.dateAccepted | 2017-09-20T16:53:09Z | |
| dcterms.dateSubmitted | 2017-09-20T16:53:09Z | |
| dcterms.description | Department of Geosciences | en_US |
| dcterms.extent | 84 pg. | en_US |
| dcterms.format | Application/PDF | en_US |
| dcterms.format | Monograph | |
| dcterms.identifier | http://hdl.handle.net/11401/77641 | |
| dcterms.issued | 2016-12-01 | |
| dcterms.language | en_US | |
| dcterms.provenance | Made available in DSpace on 2017-09-20T16:53:09Z (GMT). No. of bitstreams: 1
Rhymer_grad.sunysb_0771M_12805.pdf: 5051076 bytes, checksum: 3f8386e8a8c62935e356c66a8dda1e5a (MD5)
Previous issue date: 1 | en |
| dcterms.publisher | The Graduate School, Stony Brook University: Stony Brook, NY. | |
| dcterms.subject | Geology -- Mineralogy | |
| dcterms.subject | analysis, diffraction, intensity, powder, Synchrotron, X-ray | |
| dcterms.title | py321DIAS: Data Intensity Analysis Software for 2D Powder Diffraction Data | |
| dcterms.type | Thesis | |
