Extreme gradient boosting machine for modeling hydrogen gas storage in carbon slit pores from molecular simulation data
Document Type
Article
Publication Date
12-1-2022
Abstract
To accelerate the computation of hydrogen storage capacity in uniform slit-shaped porous carbon determined by molecular simulation, the traditional Gradient Boosting and XGBoost algorithms are introduced to create the predictive models, and evaluate their prediction effectiveness and accuracy. The resultant models are tuned their hyperparameters by the random grid search method. From the comparison among the obtained models, it is found that the XGBoost model with optimized hyperparameters shows superior performance in predicting the hydrogen storage capacity in simulated carbon pores. According to the comparison of the results, the XGBoost model with optimized hyperparameters outperforms the other models in forecasting hydrogen storage capacity in simulated carbon pores as a function of pressure and pore sizes. Furthermore, the predicted results are in the best agreement with the pristine target dataset as measured by various evaluation metrics. Note that other models yield reasonable performance metrics, but they are unable to forecast high-pressure storage capacity in the ultramicropore region (less than 1 nm). The developed model could be applied for precisely and rapidly searching and comprehending the temperature-dependent optimal pore size for high-capacity hydrogen-storage systems in vehicular applications. (C) 2022 The Author(s). Published by Elsevier Ltd.
Keywords
Hydrogen storage, Data prediction, Gradient Boosting, XGBoost, Molecular simulation
Divisions
InstituteofBiologicalSciences
Funders
Mahidol University, Thailand,SATU Joint Research Scheme Program 2021, Thailand
Publication Title
Energy Reports
Volume
8
Issue
16
Publisher
Elsevier
Publisher Location
RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
Additional Information
7th International Conference on Advances on Clean Energy Research (ICACER), Barcelona, SPAIN, APR 20-22, 2022