layout published title wiki true Workshop IX Presentations Group Photo of Attendees Agenda <iframe src="{{ site.baseurl }}/docs/PhaseFieldIX.pdf" width="595" height="485" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" style="border:1px solid #CCC; border-width:1px; margin-bottom:5px; max-width: 100%;" allowfullscreen></iframe> Implementing a neural network potential for exascale molecular dynamics <iframe src="//www.slideshare.net/slideshow/embed_code/key/eQr88W0tSGF7U6" width="595" height="485" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" style="border:1px solid #CCC; border-width:1px; margin-bottom:5px; max-width: 100%;" allowfullscreen> </iframe> Implementing a neural network potential for exascale molecular dynamics from Jim Belak Uncertainty quantification of phase equilibria and thermodynamics <iframe src="//www.slideshare.net/slideshow/embed_code/key/j8xof2Lw69lr2l" width="595" height="485" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" style="border:1px solid #CCC; border-width:1px; margin-bottom:5px; max-width: 100%;" allowfullscreen> </iframe> Uncertainty quantification of phase equilibria and thermodynamics from from Noah Paulson Uncertainty Propagation in CALPHAD-reinforced Elastochemical Phase-field Modeling <iframe src="//www.slideshare.net/slideshow/embed_code/key/cKKbYO2ZOoFTbQ" width="595" height="485" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" style="border:1px solid #CCC; border-width:1px; margin-bottom:5px; max-width: 100%;" allowfullscreen> </iframe> Uncertainty Propagation in CALPHAD-reinforced Elastochemical Phase-field Modeling from Vahid Attari Using phase field simulations to assist with experiments and experimental data <iframe src="//www.slideshare.net/slideshow/embed_code/key/1WGLKzj209fng7" width="595" height="485" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" style="border:1px solid #CCC; border-width:1px; margin-bottom:5px; max-width: 100%;" allowfullscreen> </iframe> Using phase field simulations to assist with experiments and experimental data from Michael Tonks Microstructural Analysis and Machine Learning <iframe src="//www.slideshare.net/slideshow/embed_code/key/1SJWcOAaBZWaK1" width="595" height="485" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" style="border:1px solid #CCC; border-width:1px; margin-bottom:5px; max-width: 100%;" allowfullscreen> </iframe> Microstructural Analysis and Machine Learning from Tiberiu Stan Cobalt-based Superalloys Development in CHiMaD <iframe src="//www.slideshare.net/slideshow/embed_code/key/jtI3VasU2FR322" width="595" height="485" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" style="border:1px solid #CCC; border-width:1px; margin-bottom:5px; max-width: 100%;" allowfullscreen> </iframe> Cobalt-based Superalloys Development in CHiMaD from Ding-Wen Chung AI for Science Grand Challenges <iframe src="//www.slideshare.net/slideshow/embed_code/key/1ZxPRN6i2BcFkA" width="595" height="485" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" style="border:1px solid #CCC; border-width:1px; margin-bottom:5px; max-width: 100%;" allowfullscreen> </iframe> AI for Science Grand Challenges from Jim Belak PFHub Overview - November 2019 <iframe src="//slides.com/danielwheeler-1/pfhub-6-11/embed" width="576" height="420" scrolling="no" frameborder="0" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe> PFHub Overview - November 2019 from Daniel Wheeler