Chemistrynpj Computational Materials
Quantifying defects in thin films using machine vision
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Discover how a pioneering convolutional neural network, DeepThin, is set to revolutionize thin-film material research by efficiently analyzing optical images and identifying defects across various materials. This groundbreaking work, conducted by Nina Taherimakhsousis, Benjamin P. MacLeod, Fraser G. L. Parlane, Thomas D. Morrissey, Edward P. Booker, Kevan E. Dettelbach, and Curtis P. Berlinguette, opens the door to faster advancements in film morphology optimization.
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