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A novel machine-learning method can detect internal structures, voids and cracks inside a material by utilizing data about the material’s surface.

Boston MA (SPX) May 01, 2023 - Maybe you can't tell a book from its cover, but according to researchers at MIT you may now be able to do the equivalent for materials of all sorts, from an airplane part to a medical implant. Their

An MIT machine-learning method detects internal structures, voids, and cracks inside a material, based on data about the material’s surface.

 E-Mail IMAGE: This visualization shows the deep-learning approach in predicting physical fields given different input geometries. The left figure shows a varying geometry of the composite in which the soft material is... view more  Credit: Courtesy of Zhenze Yang, Markus Buehler, et al Isaac Newton may have met his match. For centuries, engineers have relied on physical laws -- developed by Newton and others -- to understand the stresses and strains on the materials they work with. But solving those equations can be a computational slog, especially for complex materials. MIT rese...

Credits: Courtesy of the researchers Previous image Isaac Newton may have met his match. For centuries, engineers have relied on physical laws — developed by Newton and others — to understand the stresses and strains on the materials they work with. But solving those equations can be a computational slog, especially for complex materials. MIT researchers have developed a technique to quickly determine certain properties of a material, like stress and strain, based on an image of the material showing its internal structure. The approach could one day elimi...