| Autor: |
Hanicinec, Martin, Mohr, Sebastian, Tennyson, Jonathan |
| Předmět: |
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| Zdroj: |
Journal of Physics D: Applied Physics; 9/14/2023, Vol. 56 Issue 37, p1-24, 24p |
| Abstrakt: |
Machine learning (ML) is used to provide reactions rates appropriate for models of low temperature plasmas with a focus on A + B → C + D binary chemical reactions. The regression model is trained on data extracted from the QBD, KIDA, NFRI and UfDA databases. The regression model used a variety of data on the reactant and product species, some of which also had to be estimated using ML. The final model is a voting regressor comprising three distinct optimized regression models: a support vector regressor, random forest regressor and a gradient-boosted trees regressor model; this model is made freely available via a GitHub repository. As a sample use case, the ML results are used to augment the chemistry of a BCl3/H2 gas mixture. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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