The Spallation Neutron Source (SNS) at ORNL is a unique research facility capable of producing the most intense neutron beams currently available anywhere in the world. With this beam technology, SNS offers unprecedented research and data collection opportunities through neutron scattering. Unfortunately, that data does not emerge in a readily useful format. Maik Lang, assistant professor of nuclear engineering and Pietro F. Pasqua Fellow, is working to change that.
Lang’s JDRD project focuses on understanding the effects of extreme conditions on glass. His team has already gathered initial neutron scattering data that will be used by his ORNL partners to set up a new integrated environment for translating raw data into a usable format.
“This platform will help to process your raw data collected at the spallation source and better understand that data and tie it together to other measurements you did at different beam lines, or even at different facilities,” said Lang.
This platform, the Integrated Computational Environment–Modeling and Analysis for Neutrons, or ICE-MAN, will work as a translator, taking the information logged by the SNS and converting it into the format needed for modeling and analysis.
“It’s kind of like a black box. The data enters in one format and then the black box changes it into the right format for your software or models,” said Lang. By integrating his “black box” with the measuring device, Lang hopes to streamline the process from data collection to useful information for researchers studying a variety of materials.
This technology will allow Lang to use his data to model the effects of radiation on glass, a popular storage substance for nuclear waste. Researchers need to know exactly how and when glass and other storage materials begin to break down from exposure to plasma in order to determine possible uses and future complications.
According to Lang, the disordered nature of glass makes it especially difficult to study, as the effects of radiation are very subtle.
“When you have glass, it’s a noncrystalline material so you have no order. When you measure you get a lot of peaks but don’t know what it means,” said Lang. “You have data but you can’t interpret it. For this you need modeling, and for the modeling we need this platform.”
Lang’s team will assist a team at ORNL led by Anibal Ramirez-Cuesto in setting up ICE-MAN using the JDRD project data and in creating a manual for the system. Lang believes this collaboration will not only create opportunities for future efforts and funding but also open the door for discovery in materials science as a whole.