Materials scientists can learn a lot about a sample material by shooting lasers at it. With nonlinear optical microscopy — a specialized imaging technique that looks for a change in the color of intense laser light — researchers can collect data on how the light interacts with the sample and, through time-consuming and sometimes expensive analyses, characterize the material’s structure and other properties. Now, researchers at Penn State have developed a computational framework that can interpret the nonlinear optical microscopy images to characterize the material in microscopic detail.
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Researchers developed a computational framework to evaluate nonlinear optical microscopy analyses, determine atomic structure of materials
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