Predicting microstructure evolution can be a formidable challenge, yet it is essential to building microstructure-processing-property relationships. Yang et al. offer a new solution to traditional partial differential equation-based simulations: a data-driven machine learning approach motivated by the practical needs to accelerate the materials design process and deal with incomplete information in the real world of microstructure simulation.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8276005 | PMC |
| http://dx.doi.org/10.1016/j.patter.2021.100285 | DOI Listing |
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