1 citations · 1 across the 2 of their papers we have counts for
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Microstructure sensitive recurrent neural network surrogate model of crystal plasticity
Michael D. Atkinson, Michael D. White, Adam J. Plowman +1
The development of next-generation structural materials for harsh environments requires rapid assessment of mechanical performance and its dependence on microstructure. While full-…
3D variational autoencoder for fingerprinting microstructure volume elements
Michael D. White, Michael D. Atkinson, Adam J. Plowman +1
Microstructure quantification is an important step towards establishing structure-property relationships in materials. Machine learning-based image processing methods have been sho…
Exploring descriptors for titanium microstructure via digital fingerprints from variational autoencoders
Michael D. White, Gowtham Nimmal Haribabu, Jeyapriya Thimukonda Jegadeesan +3
Microstructure is key to controlling and understanding the properties of metallic materials, but traditional approaches to describing microstructure capture only a small number of…