Workshop on Measurement Needs for Local-Structure Determination in Inorganic Materials

The functional responses (e.g., dielectric, magnetic, catalytic, etc.) of many industrially-relevant materials are controlled by their local structure—a term that refers to the atomic arrangements on a scale ranging from atomic (sub-nanometer) to several nanometers. Thus, accurate knowledge of local structure is central to understanding the properties of nanostructured materials, thereby placing the problem of determining atomic positions on the nanoscale—the so-called “nanostructure problem”—at the center of modern materials development. Today, multiple experimental techniques exist for probing local atomic arrangements; nonetheless, finding accurate comprehensive, and robust structural solutions for the nanostructured materials still remains a formidable challenge because any one of these methods yields only a partial view of the local structure. The primary goal of this 2-day NIST-sponsored workshop was to bring together experts in the key experimental and theoretical areas relevant to local-structure determination to devise a strategy for the collaborative effort required to develop a comprehensive measurement solution on the local scale. The participants unanimously agreed that solving the nanostructure problem—an ultimate frontier in materials characterization—necessitates a coordinated interdisciplinary effort that transcends the existing capabilities of any single institution, including national laboratories, centers, and user facilities. The discussions converged on an institute dedicated to local structure determination as the most viable organizational platform for successfully addressing the nanostructure problem. The proposed “institute” would provide an intellectual infrastructure for local structure determination by (1) developing and maintaining relevant computer software integrated in an open-source global optimization framework (Fig. 2), (2) connecting industrial and academic users with experts in measurement techniques, (3) developing and maintaining pertinent databases, and (4) providing necessary education and training.Open in a separate windowFig. 2A schematic representation of the complex modeling idea: integration of combined inputs from multiple experimental techniques and theory into the global optimization framework Billinge and Levin, unpublished]. In this concept, the structural model evolves toward the correct solution as more data is provided for the fit.