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7 results in Authors: Martin Votsmeier

Chemical Engineering and Industrial Chemistry

Working Paper

A neural network with embedded stoichiometry and thermodynamics for learning kinetics from reactor data

Tim Kircher, Felix Döppel, Martin Votsmeier

Version 1 posted 14 September 2023

668

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Chemical Engineering and Industrial Chemistry

Working Paper

Robust Mechanism Discovery with Atom Conserving Chemical Reaction Neural Networks

Felix Döppel, Martin Votsmeier

Version 1 posted 06 December 2023

246

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Citations

Catalysis

Working Paper

Efficient machine learning based surrogate models for surface kinetics by approximating the rates of the rate-determining steps

Felix Döppel, Martin Votsmeier

Version 1 posted 29 March 2022

581

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Chemical Engineering and Industrial Chemistry

Working Paper

Embedding Physics into Neural ODEs to learn Kinetics from Integral Reactors

Tim Kircher, Felix Döppel, Martin Votsmeier

Version 2 posted 07 March 2024

348

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Chemical Engineering and Industrial Chemistry

Working Paper

N2O selectivity in industrial NH3 oxidation on Pt-gauze is determined by interaction of local flow and surface chemistry: A simulation study using mechanistic kinetics

Michael Haas, Teng-Wang Nien, Anton Fadic, Joe P. Mmbaga, Markus Klingenberger, Dirk Born, Bastian J. M. Etzold, Robert Hayes, Martin Votsmeier

Version 2 posted 27 June 2022

443

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Theoretical and Computational Chemistry

Working Paper

Efficient Neural Network Models of Chemical Kinetics Using a Latent asinh Rate Transformation

Felix Döppel, Martin Votsmeier

Version 1 posted 10 April 2023

367

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Chemical Engineering and Industrial Chemistry

Working Paper

Learning kinetics from non-ideal reactors by implicitly solved finite volumes and global reaction neural networks

Tim Kircher, Martin Votsmeier

Version 1 posted 22 November 2024

167

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7 results in Martin Votsmeier in Authors: Martin Votsmeier

A neural network with embedded stoichiometry and thermodynamics for learning kinetics from reactor data

Robust Mechanism Discovery with Atom Conserving Chemical Reaction Neural Networks

Efficient machine learning based surrogate models for surface kinetics by approximating the rates of the rate-determining steps

Embedding Physics into Neural ODEs to learn Kinetics from Integral Reactors

N2O selectivity in industrial NH3 oxidation on Pt-gauze is determined by interaction of local flow and surface chemistry: A simulation study using mechanistic kinetics

Efficient Neural Network Models of Chemical Kinetics Using a Latent asinh Rate Transformation

Learning kinetics from non-ideal reactors by implicitly solved finite volumes and global reaction neural networks

7 results in Authors: Martin Votsmeier