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## Enhanced Kinetic Modeling of Heterogeneous Catalysis Using Bayesian Hyperparameter Optimization and Deep Neural Networks for Langmuir-Hinshelwood Mechanisms
**Abstract:** This paper introduces a novel approach to modeling heterogeneous catalytic reactions governed by Langmuir-Hinshelwood (LH) mechanisms. We leverage Bayesian hyperparameter optimization (BHPO) coupled with deep neural networks (DNNs) to dynamically adjust reaction rate constants and adsorption energies, significantly improving model accuracy and predictive capabilities compared to traditional fitting methods. The system analyzes experimental data alongside first-principles calculations to fine-tune the model parameters, enabling its application in optimizing catalyst design and reaction conditions across various industrial applications.