Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature

Abstract

High-entropy alloys (HEAs) have received considerable attention for hydrogen storage because of their compositional flexibility; however, designing HEAs with optimal thermodynamics is critical. This study employs machine learning via artificial neural networks (ANN) and density functional theory (DFT) to design a novel AB-type TixNb2-xVCrMnFe (x = 0.5-2.0) high-entropy system for hydrogen storage at ambient temperature (A: Ti, V and Nb, and B: Cr, Mn and Fe). Both ANN and DFT predict that the hydride formation enthalpy decreases to negative values with increasing the titanium content. Two alloys with x > 1.5 are predicted to achieve enthalpies within the -25 to -39 kJ/mol range, making them appropriate for room-temperature hydrogen storage. Experiments demonstrate good agreement with the enthalpy predictions, with the Ti-rich alloys showing reversible hydrogen storage with fast kinetics at room temperature. These results provide a framework for reliable use of data analysis and ab initio calculations to explore high-entropy hydrides as hydrogen storage materials.

References in corpus (12)

• Materials for hydrogen-based energy storage: Past, recent progress and future outlook
• icet - A Python library for constructing and sampling alloy cluster expansions
• High-Entropy Hydrides for Fast and Reversible Hydrogen Storage at Room Temperature: Binding-Energy Engineering via First-Principles Calculations and Experiments
• Impact of Severe Plastic Deformation on Kinetics and Thermodynamics of Hydrogen Storage in Magnesium and Its Alloys
• High-entropy alloy TiV2ZrCrMnFeNi for hydrogen storage at room temperature with full reversibility and good activation
• Machine learning to explore high-entropy alloys with desired enthalpy for room-temperature hydrogen storage: Prediction of density functional theory and experimental data
• Significance of interphase boundaries on activation of high-entropy alloys for room-temperature hydrogen storage
• Developing a single-phase and nanograined refractory high-entropy alloy ZrHfNbTaW with ultrahigh hardness by phase transformation via high-pressure torsion
• High-entropy perovskites as new photocatalysts for cocatalyst-free water splitting
• Influence of interphase boundary coherency in high-entropy alloys on their hydrogen storage performance
• AB-Type Dual-Phase High-Entropy Alloys as Negative Electrode of Ni-MH Batteries: Impact of Interphases on Electrochemical Performance
• Machine Learning Potentials for Hydrogen Absorption in TiCr${}_2$ Laves Phases