Interdisciplinary Research Topics

Imaging Sciences

Imaging-based characterization methods form an essential pillar of atomic-structure determination. Whether using electrons or photons, new advances in these techniques are capturing more atomic-level details than ever before. In particular, experiments have moved beyond the two-dimensions that we usually consider for imaging. Rather, multidimensional– spatial, temporal, and spectral– atomically resolved datasets can now be collected and approach hundreds of gigabytes per experiment. With high dimensionality and data rates, the interpretation is constrained by traditional quantification methods due to the shear amount of information that can potentially be extracted. With this in mind, this research thrust will address core challenges of this data-rich field to provide new opportunities to revolutionize structural imaging through the integration of high-dimensional analyses and statistics. The experimental techniques within the Imaging IRG are varied, and include electron microscopy and x-ray microscopy conducted at the NCSU Analytical Instrumentation Facility and at several national user facilities including Brookhaven National Laboratory and Oak Ridge National Laboratory.

Participating Faculty

  • James LeBeau – IRG Lead (MSE, NCSU),
  • Brian Reich IRG co-Lead (Statistics, NCSU),
  • Harald Ade (Physics, NCSU),
  • Elizabeth Dickey (MSE, NCSU),
  • Montse Fuentes (Statistics, NCSU),
  • Dean Hesterberg (Soil Science, NCSU),
  • Douglas Irving (MSE, NCSU).

Scattering Sciences

For decades, experimentalists have used scattering of photons, electrons, and neutrons from solids to extract information about material structure and composition – e.g., diffraction of X-rays from crystals, neutron diffuse scattering from liquids, and optical reflectivity from materials surfaces. However, the central challenge in using scattering data to determine or refine material structure is the indirect relationship between the measured data and the information sought; since critical phase information is lost during data acquisition most scattering measurements require inference to determine structure. Experimentalists routinely use inference-based approaches today; for example, a diffraction scientist will believe (based on prior evidence) that a material exhibits a particular space group, and then adopt that space group as truth, then choose somewhat arbitrary starting values for atomic structural parameters (e.g., atomic positions, occupancies), and then refine those parameters against the measured diffracted intensities. This process yields one solution in cases where there can be many. The solution is biased by the initial biases and assumptions, and lacks rigorous uncertainty quantification.

Participating Faculty

  • Jacob Jones – IRG Lead (MSE, NCSU),
  • Kimberly Weems – IRG co-Lead (Mathematics, NCCU),
  • Harald Ade (Physics, NCSU),
  • Jon-Paul Maria (MSE, NCSU),
  • Alyson Wilson (Statistics, NCSU),
  • Brian Reich (Statistics, NCSU),
  • Ralph Smith (Mathematics, NCSU)

Computational Materials Science

This IRG addresses significant research and training opportunities to advance the ability of computational materials science to address structure-related problems. Integrating traditional training in modeling with advanced statistical tools will enable a new generation of computational scientists to attack increasingly complex problems in atomic structure analysis that are beyond current capabilities.

Participating Faculty

  • Don Brenner- IRG Lead (MSE, NCSU),
  • Ralph Smith IRG co- Lead,
  • Igor Bondarev (Physics, NCCU),
  • Doug Irving (MSE, NCSU),
  • Melissa Pasquinelli (Textile Engineering, Chemistry, and Science, NCSU),
  • Srikanth Patala (MSE, NCSU),
  • Brian Reich (Statistics, NCSU),
  • Alyson Wilson (Statistics, NCSU),
  • Yara Yingling (MSE, NCSU).