A multi-university team first reported a unique lead-free ferroelectric compound - (Ca,Sr)3Mn2O7, which belongs to a class of materials described as hybrid improper ferroelectrics.
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A multidisciplinary team of researchers has developed an adaptive physics refinement (APR) technique to effectively model cancer cell transport.
We present an intercomparison of a suite of high-resolution downscaled climate projections based on a six-member General Climate Models (GCM) ensemble from the 6th Phase of Coupled Models Intercomparison Project (CMIP6).
A web-based GUI for INTERSECT has been created which allows a user to configure an experiment on an electron microscope, setting such parameters as maximum number of steps for the machine learning algorithm to perform.
Researchers at Oak Ridge National Laboratory developed a new parallel performance portable algorithm for solving the Euclidean minimum spanning tree problem (EMST), capable of processing tens of millions of data points a second.
A team of Oak Ridge National Laboratory (ORNL) scientists involved in research topics of cybersecurity, statistical approaches, control systems, and dynamical models, reported a basic approach to security of physical systems that are interfaced with IT
Researchers associated with the ExaAM project, a part of the Exascale Computing Project, developed ExaCA, a cellular automata (CA)-based model for grain-scale alloy solidification capable of simulation on both CPU and GPU architectures.
Researchers associated with the ExaAM project, a part of the Exascale Computing Project, developed ExaCA, a cellular automata (CA)-based model for grain-scale alloy solidification capable of simulation on both CPU and GPU a
Machine learning is rapidly becoming an integral part of experimental physical discovery via automated and high-throughput synthesis, and active experiments in scattering and electron/probe microscopy.