| About this Abstract |
| Meeting |
MS&T22: Materials Science & Technology
|
| Symposium
|
Thermodynamics of Materials in Extreme Environments
|
| Presentation Title |
Predictive Modeling of Complex Liquids with Uncertainty Quantification by Open-Source Tools: Illustrated with Thermodynamic Properties of Molten Salts |
| Author(s) |
Shun-Li Shang, Rushi Gong, Jorge Paz Soldan Palma, Brandon Bocklund, Nathan Smith, Yi Wang, Hojong Kim, Zi-Kui Liu |
| On-Site Speaker (Planned) |
Shun-Li Shang |
| Abstract Scope |
Design and development of molten salts depend on understanding and predictive modeling of critical salt properties such as melting points, heat capacities, and solubility of fission products, hence appealing for accurate models and especially modeling tools. Using a model system of NiF2-FLiNaK, the present work demonstrates the recent development of our open-source tools PyCalphad (https://pycalphad.org) and ESPEI (https://espei.org) to perform CALPHAD modeling using the modified quasichemical model in quadruplet approximation (MQMQA), which were recently implemented in the PyCalphad/ESPEI framework. The modelled results are compared with experimental results in the literature, the present measurements using electromotive force and differential scanning calorimetry, and the present ab initio molecular dynamics (AIMD) simulations; demonstrating a new approach to perform CALPHAD modeling with uncertainty quantification for complex liquids using the MQMQA. |