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A new approach to crunching massive volumes of data uses neural networks, an architecture of multiple elements that is figuratively taught to pool imbedded information into results, like an artificial brain.
Researchers at ORNL's Center for Nanophase Materials Sciences developed and trained a neural net to recognize significant patterns in data from analytical experiments using methods such as atomic force microscopy.
The work was recently published in Physical Review Letters. The neural-network approach provides a bridge between theoretical and experimental research by quickly extracting physical parameters from voluminous and complex data.
The work is funded by ORNL's Laboratory Directed Research and Development program.
About Oak Ridge National Laboratory
ORNL is a multiprogram science and technology laboratory managed for the U.S. Department of Energy by UT-Battelle, LLC. Scientists and engineers at ORNL conduct basic and applied research and development to create scientific knowledge and technological solutions that strengthen the nation's leadership in key areas of science; increase the availability of clean, abundant energy; restore and protect the environment; and contribute to national security.
ORNL also performs other work for the Department of Energy, including isotope production, information management, and technical program management, and provides research and technical assistance to other organizations. The laboratory is a program of DOE's Oak Ridge Field Office.
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