6 papers
Material Prediction for Design Automation Using Graph Representation Learning
Shijie Bian, Daniele Grandi, Kaveh Hassani +8
Successful material selection is critical in designing and manufacturing products for design automation. Designers leverage their knowledge and experience to create high-quality de…
Thermodynamic modeling with uncertainty quantification using the modified quasichemical model in quadruplet approximation: Implementation into PyCalphad and ESPEI
Jorge Paz Soldan Palma, Rushi Gong, Brandon J. Bocklund +9
The modified quasichemical model in the quadruplet approximation (MQMQA) considers the first- and the second-nearest-neighbor coordination and interactions, particularly useful in…
Sensitivity estimation for calculated phase equilibria
Richard Otis, Brandon Bocklund, Zi-Kui Liu
The development of a consistent framework for Calphad model sensitivity is necessary for the rational reduction of uncertainty via new models and experiments. In the present work,…
Scheil-Gulliver simulations for the design of functionally graded alloys by additive manufacturing using pycalphad
Brandon Bocklund, Lourdes D. Bobbio, Richard A. Otis +2
Additive manufacturing (AM), through directed energy deposition, supports planned composition changes between locations within a single component, allowing for functionally graded…
ESPEI for efficient thermodynamic database development, modification, and uncertainty quantification: application to Cu-Mg
Brandon Bocklund, Richard Otis, Aleksei Egorov +3
The software package ESPEI has been developed for efficient evaluation of thermodynamic model parameters within the CALPHAD method. ESPEI uses a linear fitting strategy to paramete…
Quantified Uncertainty in Thermodynamic Modeling for Materials Design
Noah H Paulson, Brandon J Bocklund, Richard A Otis +2
Phase fractions, compositions and energies of the stable phases as a function of macroscopic composition, temperature, and pressure (X-T-P) are the principle correlations needed fo…