Multi-Scale Modeling of Doped Magnesium Hydride Nanomaterials for Hydrogen Storage Applications

TL;DR

This paper introduces a multi-scale model to study how doping magnesium hydride nanomaterials improves hydrogen storage performance.

Contribution

A novel multi-scale modeling framework combining DFT and system-level modeling for hydrogen storage material design.

Findings

Ti-, Zr-, and V-doping reduces hydrogenation time by 21-42% compared to pristine MgH2.

V-doping decreases thermal energy consumption during hydrogenation by ~17%.

Doping modifies thermodynamic properties, leading to improved hydrogen storage performance.

Abstract

This work presents the development of a novel multi-scale modeling framework for investigating the beneficial impact of Ti-, Zr-, and V-doped magnesium hydride nanomaterials on hydrogen storage performance. The proposed model integrates atomistic-scale simulations based on density functional theory (DFT) with system-level dynamic heat and mass transfer modeling. At the nanoscale, DFT analysis provides key thermodynamic and kinetic parameters, including reaction enthalpy, entropy, and activation energy, which are incorporated into the macroscopic model to predict the hydrogenation behavior of MgH2 nanostructures under realistic thermal boundary conditions. Model validation is performed through comparison with experimental data from the literature, showing excellent agreement. The DFT analysis reveals that doping MgH2 nanomaterials with Ti, V, and Zr modifies their thermodynamic properties, including enthalpy of formation and desorption temperature. At the reactor scale, these modifications lead to enhanced hydrogenation kinetics and improved thermal management. Compared to pristine MgH2, hydrogenation time is reduced by 21%, 40%, and 42% for Ti-, Zr-, and V-doped nanomaterials, respectively, while thermal energy consumption during hydrogenation decreases by ~17% for V doping. These results highlight the strong correlation between nanoscale modifications and macroscopic system performance. The proposed multi-scale model provides a powerful tool for guiding the design and optimization of advanced nanostructured hydrogen storage materials for sustainable energy applications.

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