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![Scientists will use ORNL’s computing resources such as the Titan supercomputer to develop deep learning solutions for data analysis. Credit: Jason Richards/Oak Ridge National Laboratory, U.S. Dept. of Energy. Scientists will use ORNL’s computing resources such as the Titan supercomputer to develop deep learning solutions for data analysis. Credit: Jason Richards/Oak Ridge National Laboratory, U.S. Dept. of Energy.](/sites/default/files/styles/list_page_thumbnail/public/news/images/2012-P03136%281%29.jpg?itok=i0w1NZWs)
A team of researchers from Oak Ridge National Laboratory has been awarded nearly $2 million over three years from the Department of Energy to explore the potential of machine learning in revolutionizing scientific data analysis. The Advances in Machine Learning to Improve Scient...
![ORNL’s Xiahan Sang unambiguously resolved the atomic structure of MXene, a 2D material promising for energy storage, catalysis and electronic conductivity. Image credit: Oak Ridge National Laboratory, U.S. Dept. of Energy; photographer Carlos Jones ORNL’s Xiahan Sang unambiguously resolved the atomic structure of MXene, a 2D material promising for energy storage, catalysis and electronic conductivity. Image credit: Oak Ridge National Laboratory, U.S. Dept. of Energy; photographer Carlos Jones](/sites/default/files/styles/list_page_thumbnail/public/Sang_2016-P07680_0.jpg?itok=w0e5eR_U)
Researchers have long sought electrically conductive materials for economical energy-storage devices. Two-dimensional (2D) ceramics called MXenes are contenders. Unlike most 2D ceramics, MXenes have inherently good conductivity because they are molecular sheets made from the carbides ...