Novel Approach To Determine How Atoms Are Arranged Could Help Development Of New Resources For Vehicles, Electronics, Nanotechnologies
Scientists from the National Institute of Standards and Technology (NST), North Carolina State University and Oak Ridge National Laboratory (ORNL) discovered a new approach to materials characterization using the Bayesian statistical methods. This could lead to the development of new materials for use in various applications such as electronics, vehicles and nanotechnologies.
The study was printed in the journal Nature Scientific reports. It is entitled "Use of Bayesian Inference in Crystallographic Structure Refinement via Full Profile Diffraction Analysis." The research was led by Chris Fancher, a postdoctoral researcher at NC State and Zhen Han, a former Ph.D. student at NC State. Among the co-authors are Katharine Page of ORNL, Igor Levin of NIST, Ralph Smith, a distinguished professor of mathematics at NC State and Brian Reich, an associate professor of statistics at NC State.
Jacob Jones, co-author of the study and a professor of materials science and engineering at NC State stated that they want to understand the crystallographic structure of materials. This includes where the atoms are located in the matrix of a material so that they have a basis for understanding how that structure affects a material's performance. "This is a fundamentally new advance that will help us develop new materials that can be used in everything from manufacturing to electronic and vehicles and nanotechnologies," said Prof. Jones.
The crystallographic structure is a depiction of the ordered arrangement of atoms, ions or molecules in a crystalline material. The ordered structures take place from the intrinsic nature of the integral particles to form symmetric patterns that repeat along the main directions of three-dimensional space in a matter. This structure and symmetry determine many physical properties that include electronic band structure, cleavage and optical transparency.
To understand the material's crystallographic structure, the researchers must examine a sample of the material with photons, electrons or other subatomic particles. They have to use the technology known as the Spallation Neutron Source at ORNL or the Advanced Photon Source at Argonne National Laboratory. They can then gauge the angle and energy of these particles as they are scattered by the material.
The researchers also used the Bayesian statistics to allow them to characterize materials in a new and richer way. Prof. Jones said that this approach will allow them to analyze data from a wide variety of materials characterization techniques. These include all forms of mass spectrometry spectroscopy and all kinds of matter.