On the instrumental and data processing side, we focus on improving the precision of structural information derived using transmission electron microscopy (TEM). Aberration-corrected scanning TEM enables direct imaging of atomic columns but the precision of column positions extracted from the images remains limited by sample drift. Likewise, while recent advances in electron tomography have enabled the qualitative determination of structures at the atomic scale, the technique currently lacks the required quantitative precision. The research under this project is aimed at drastically improving the precision of both techniques by developing and applying compressive sampling and related computational algorithms and software for the removal of sample drift and other artifacts, thus revealing the true intrinsic material signature with picometer precision, as needed for effective computational studies.
On the data analysis side, this project targets problems related to data fusion, which is necessary to elucidate comprehensive structural models of complex materials. Combining inputs from different experimental measurements as well as theoretical calculations requires a computational framework for simultaneous fitting of multiple datasets. A basic example of data fusion in structure determination involves the joint fitting of neutron and X-ray powder diffraction data. Currently, the use of this technique is hindered by the inability to appropriately treat systematic errors associated with each dataset. We are developing a Bayesian-statistics approach that accounts for the presence of unknown systematic errors in structural refinements, thus providing significantly more accurate structural models compared to standard fits. Data fusion becomes particularly critical for determination of local and nanoscale atomic arrangements which control the properties and resulting functionality of many advanced materials. As a part of this project, we are developing a computational framework and relevant computer software for simultaneous fitting of various diffraction and spectroscopic data to determine local and nanoscale atomic arrangements in bulk materials and nanoparticles with high fidelity.