Because the impacts of climate change proceed to grow, so does interest in fusion’s potential as a clean energy source. While fusion reactions have been studied in laboratories for the reason that Nineteen Thirties, there are still many critical questions scientists must answer to make fusion power a reality, and time is of the essence. As a part of their technique to speed up fusion energy’s arrival and reach carbon neutrality by 2050, the U.S. Department of Energy (DoE) has announced latest funding for a project led by researchers at MIT’s Plasma Science and Fusion Center (PSFC) and 4 collaborating institutions.

Cristina Rea, a research scientist and group leader on the PSFC, will function the first investigator for the newly funded three-year collaboration to pilot the combination of fusion data right into a system that might be read by AI-powered tools. The PSFC, along with scientists from the College of William and Mary, the University of Wisconsin at Madison, Auburn University, and the nonprofit HDF Group, plan to create a holistic fusion data platform, the weather of which could offer unprecedented access for researchers, especially underrepresented students. The project goals to encourage diverse participation in fusion and data science, each in academia and the workforce, through outreach programs led by the group’s co-investigators, of whom 4 out of 5 are women. 

The DoE’s award, a part of a $29 million funding package for seven projects across 19 institutions, will support the group’s efforts to distribute data produced by fusion devices just like the PSFC’s Alcator C-Mod, a donut-shaped “tokamak” that utilized powerful magnets to manage and confine fusion reactions. Alcator C-Mod operated from 1991 to 2016 and its data are still being studied, thanks partly to the PSFC’s commitment to the free exchange of information.

Currently, there are nearly 50 public experimental magnetic confinement-type fusion devices; nevertheless, each historical and current data from these devices might be difficult to access. Some fusion databases require signing user agreements, and never all data are catalogued and arranged the identical way. Furthermore, it could be difficult to leverage machine learning, a category of AI tools, for data evaluation and to enable scientific discovery without time-consuming data reorganization. The result’s fewer scientists working on fusion, greater barriers to discovery, and a bottleneck in harnessing AI to speed up progress.

The project’s proposed data platform addresses technical barriers by being FAIR — Findable, Interoperable, Accessible, Reusable — and by adhering to UNESCO’s Open Science (OS) recommendations to enhance the transparency and inclusivity of science; all the researchers’ deliverables will adhere to FAIR and OS principles, as required by the DoE. The platform’s databases will probably be built using MDSplusML, an upgraded version of the MDSplus open-source software developed by PSFC researchers within the Nineteen Eighties to catalogue the outcomes of Alcator C-Mod’s experiments. Today, nearly 40 fusion research institutes use MDSplus to store and supply external access to their fusion data. The discharge of MDSplusML goals to proceed that legacy of open collaboration.

The researchers intend to deal with barriers to participation for ladies and disadvantaged groups not only by improving general access to fusion data, but in addition through a subsidized summer school that may give attention to topics on the intersection of fusion and machine learning, which will probably be held at William and Mary for the subsequent three years.

Of the importance of their research, Rea says, “This project is about responding to the fusion community’s needs and setting ourselves up for fulfillment. Scientific advancements in fusion are enabled via multidisciplinary collaboration and cross-pollination, so accessibility is totally essential. I feel all of us understand now that diverse communities have more diverse ideas, they usually allow faster problem-solving.”

The collaboration’s work also aligns with vital areas of research identified within the International Atomic Energy Agency’s “AI for Fusion” Coordinated Research Project (CRP). Rea was chosen because the technical coordinator for the IAEA’s CRP emphasizing community engagement and knowledge access to speed up fusion research and development. In a letter of support written for the group’s proposed project, the IAEA stated that, “the work [the researchers] will perform […] will probably be useful not only to our CRP but in addition to the international fusion community in large.”

PSFC Director and Hitachi America Professor of Engineering Dennis Whyte adds, “I’m thrilled to see PSFC and our collaborators be on the forefront of applying latest AI tools while concurrently encouraging and enabling extraction of critical data from our experiments.”

“Having the chance to guide such a vital project is incredibly meaningful, and I feel a responsibility to point out that ladies are leaders in STEM,” says Rea. “We’ve an incredible team, strongly motivated to enhance our fusion ecosystem and to contribute to creating fusion energy a reality.”