Saved in:
| Main Authors: | , |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2309.12255 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866916354419851264 |
|---|---|
| author | Ober, Derick E. Van der Ven, Anton |
| author_facet | Ober, Derick E. Van der Ven, Anton |
| contents | This work demonstrates how first-principles thermodynamic research within a Bayesian framework can quantify and propagate uncertainties to downstream thermodynamic calculations. To address the issue of Bayesian prior selection, knowledge of zero Kelvin ground states in the material system of interest is incorporated into the prior. The effectiveness of this framework is shown by creating a phase diagram for the FCC Zirconium Nitride system, including confidence intervals on phase boundary regions of interest. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2309_12255 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Thermodynamically Informed Priors for Uncertainty Propagation in First-Principles Statistical Mechanics Ober, Derick E. Van der Ven, Anton Materials Science Statistical Mechanics This work demonstrates how first-principles thermodynamic research within a Bayesian framework can quantify and propagate uncertainties to downstream thermodynamic calculations. To address the issue of Bayesian prior selection, knowledge of zero Kelvin ground states in the material system of interest is incorporated into the prior. The effectiveness of this framework is shown by creating a phase diagram for the FCC Zirconium Nitride system, including confidence intervals on phase boundary regions of interest. |
| title | Thermodynamically Informed Priors for Uncertainty Propagation in First-Principles Statistical Mechanics |
| topic | Materials Science Statistical Mechanics |
| url | https://arxiv.org/abs/2309.12255 |