Supercomputer Simulations Help Researchers Predict Solar Wind Storms

Researchers at the University of New Hampshire used SDSC’s Comet supercomputer to validate a model using a machine learning technique called Dynamic Time Lag Regression (DTLR) to help predict the solar wind arrival near the Earth’s orbit from physical parameters of the Sun.

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Six Argonne researchers receive DOE Early Career Research Program awards

Argonne scientists Michael Bishof, Maria Chan, Marco Govini, Alessandro Lovato, Bogdan Nicolae and Stefan Wild have received funding for their research as part of DOE’s Early Career Research Program.

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RENEWABLE ENERGY ADVANCE

In order to identify materials that can improve storage technologies for fuel cells and batteries, you need to be able to visualize the actual three-dimensional structure of a particular material up close and in context. Researchers from the University of Delaware’s Catalysis Center for Energy Innovation (CCEI) have done just that, developing new techniques for characterizing complex materials.

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Researchers use drones, machine learning to detect dangerous ‘butterfly’ landmines

Using advanced machine learning, drones could be used to detect dangerous “butterfly” landmines in remote regions of post-conflict countries, according to research from Binghamton University, State University at New York.

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