Artificial intelligence in the modeling of chemical reactions kinetics
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Maciej Staszak
Abstract
The work presents a selection of recent papers in the field of modeling chemical kinetics by the use of artificial intelligence methods. Due to the fact that kinetics of the chemical reaction is the key element of industrial reactor design and analysis, the work is focused on the presentation of the quality of modeling, the assembly of neural network systems and methods of training required to achieve acceptable results. The work covers a wide range of classes of chemical processes and modeling approaches presented by several authors. Because of the fact that the methods of neural networks training require huge amounts of data, many approaches proposed are intrinsically based on classical kinetics modeling like Monte Carlo methods, quantum ab initio models or classical Arrhenius-like approaches using mass balance rate equations. The work does not fully exhaust the area of artificial intelligence because of its very broad scope and very fast evolution, which has been greatly accelerated recently. However, it is a contribution to describing the current state of science in this field.
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Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
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Research funding: None declared.
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Conflict of interest statement: The authors declare no conflicts of interest regarding this article.
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© 2020 Walter de Gruyter GmbH, Berlin/Boston
Artikel in diesem Heft
- Frontmatter
- Reviews
- Multiscale modeling and simulation of magneto-active elastomers based on experimental data
- Theoretical examination of efficiency of anthocyanidins as sensitizers in dye-sensitized solar cells
- Artificial intelligence in the modeling of chemical reactions kinetics
- Computational studies of biologically active alkaloids of plant origin: an overview
- Certainty through uncertainty: stochastic optimization of grid-integrated large-scale energy storage in Germany
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Artikel in diesem Heft
- Frontmatter
- Reviews
- Multiscale modeling and simulation of magneto-active elastomers based on experimental data
- Theoretical examination of efficiency of anthocyanidins as sensitizers in dye-sensitized solar cells
- Artificial intelligence in the modeling of chemical reactions kinetics
- Computational studies of biologically active alkaloids of plant origin: an overview
- Certainty through uncertainty: stochastic optimization of grid-integrated large-scale energy storage in Germany
- Shaping the future energy markets with hybrid multimicrogrids by sequential least squares programming
