We developed a novel uncertainty-aware framework MatPhase to predict material phases of electrodes from low contrast SEM images.
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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.
Oak Ridge National Laboratory researchers developed an invertible neural network (INN) to effectively and efficiently solve earth-system model calibration and simulation problems.
Achievement: Designed a polymer for selective and reversible carbon dioxide (CO2) capture.
Significance and Impact: The new polymer that is based on amidines can provide a more efficient alternative to conventional polyethyleneimine (PEI) based solid-sorb