Predicting hydrogen storage capacity of V–Ti–Cr–Fe alloy via ensemble machine learning

Lu, Ziliang; Wang, Jianwei; Wu, Yuanfang; Guo, Xiping; Xiao, Wei

doi:10.1016/j.ijhydene.2022.08.050

Cited by 24 publications

(10 citation statements)

References 19 publications

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“…It has been demonstrated, particularly in [71], that doping elements with high electronegativity can reduce dehydrogenation energy by nearly 25%. For instance, the hydrogen storage capacity of V-Ti-Cr-Fe alloys can be predicted by utilizing electronegativity as one of the inputs [72].…”

Section: Design Of Heas For Hydrogen Storage: Theory and Calculationsmentioning

confidence: 99%

“…Suwarno et al trained models to investigate the effect of alloying elements on the properties of AB 2 alloys, showing that Ni controls the enthalpy of hydride formation, Cr determines the phase fraction of the Laves phase C14, and Mn influences the hydrogen weight percentage (wt.% H 2 ) [86]. Additionally, a compositionspecific ensemble learning method was developed to predict the wt.% H 2 of V-Ti-Cr-Fe alloys with high accuracy [87]. The model, trained on 19 features, was able to predict wt% H 2 with a mean absolute error of 0.187 wt.%.…”

Section: Design Of Heas For Hydrogen Storage: Theory and Calculationsmentioning

confidence: 99%

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Application of High-Entropy Alloys in Hydrogen Storage Technology

Karpov

2024

Problems of Atomic Science and Technology

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High-entropy alloys (HEAs), a new class of materials with promising structural and functional properties, have recently garnered significant attention in various fields, including hydrogen storage. Their unique design concept and vast compositional diversity offer unprecedented opportunities for the development of advanced hydrogen storage materials. This review aims to systematically analyze the current research status of high-entropy alloys for hydrogen storage, with a focus on compositional designs, synthesis processes, and hydrogen storage characteristics. The review also examines correlations between hydrogen storage performance and composition-related properties, particularly for hydrogen storage alloys crystallizing as BCC solid solutions and Laves phase structures. Various aspects of hydrogen interaction with HEAs, including reversibility of hydrogen storage, cycling stability, and activation behavior have been considered in detail. The potential of HEAs in the development of novel hydrogen storage materials with superior performance is highlighted, emphasizing the importance of effective compositional design and synthesis methods.

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Section: Design Of Heas For Hydrogen Storage: Theory and Calculationsmentioning

confidence: 99%

Section: Design Of Heas For Hydrogen Storage: Theory and Calculationsmentioning

confidence: 99%

Application of High-Entropy Alloys in Hydrogen Storage Technology

Karpov

2024

Problems of Atomic Science and Technology

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“…12 An alternative approach proposed in this work is based on the identication of physically motivated descriptors (arising from the electronic, atomic, or dynamic traits of the material) that strongly correlate with the target properties. [55][56][57][58] For instance, previous studies have demonstrated the successful utilization of physics-based descriptors to predict the adsorption energy of small molecules (H 2 , CO, CH 4 etc. ), [59][60][61][62] while absorption of hydrogen has not received much attention.…”

Section: Introductionmentioning

confidence: 99%

“…Based on the literature review, we explore several classes of physics-based descriptors that can be used to map the local atomic and electronic environment of interstitial absorption sites to hydrogen absorption energies. Successful examples of previously identied descriptors include electronic structure features (d-band features, 63 valence electron concentration, 32,33,57 etc.) that govern reactivity on catalytically active metallic surfaces 25 and determine binding energies of hydrogen atoms.…”

Section: Introductionmentioning

confidence: 99%

Simple local environment descriptors for accurate prediction of hydrogen absorption and migration in metal alloys

Korostelev,

Wagner,

Klyukin

2023

J. Mater. Chem. A

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“…12 An alternative approach proposed in this work is based on the identification of physically motivated descriptors (arising from the electronic, atomic, or dynamic traits of the material) that strongly correlate with the target properties. [54][55][56] For instance, previous studies have demonstrated the successful utilization of physics-based descriptors to predict the adsorption energy of small molecules (H2, CO, CH4 etc.) [57][58][59][60] , while absorption of hydrogen has not received much attention.…”

Section: Introductionmentioning

confidence: 99%

Simple local environment descriptors for accurate prediction of hydrogen absorption and migration in metal alloys

Korostelev

Wagner

Klyukin

2023

Preprint

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The control of hydrogen concentration and diffusion in metal alloys is critical for advancing clean energy technologies. A quantitative understanding of the composition-property relationship can accelerate the design of hydrogen storage materials, structural hydrogen-resistant alloys, and materials for energy-efficient nanoelectronics. In this work, we employed Density Functional Theory simulations to investigate the energy landscape of hydrogen absorption and mobility for a wide spectrum of high-entropy alloys and intermetallic compounds. Our study sheds light on the origin of hydrogen stability also providing quantitative guidance for compositional considerations and the design of technologically useful materials. The developed analytical model uses physically intuitive metrics characterizing the local environment, such as electronic structure features, volume of interstitial voids, and lattice vibrational modes, to predict the energy landscape of hydrogen in metal alloys based on simple calculations of bulk properties. The developed model exhibits remarkable accuracy in predicting hydrogen binding energy, achieving a low mean absolute error of less than 0.1 eV. Utilizing this model, we successfully predicted hydrogen absorption energies and migration barriers demonstrating that these quantities are linearly correlated, akin to the Brønsted−Evans−Polanyi principle. In addition, our study revealed that a similar list of material features can be employed to predict zero-point energy contribution associated with hydrogen vibrational motion.

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Predicting hydrogen storage capacity of V–Ti–Cr–Fe alloy via ensemble machine learning

Cited by 24 publications

References 19 publications

Application of High-Entropy Alloys in Hydrogen Storage Technology

Application of High-Entropy Alloys in Hydrogen Storage Technology

Simple local environment descriptors for accurate prediction of hydrogen absorption and migration in metal alloys

Simple local environment descriptors for accurate prediction of hydrogen absorption and migration in metal alloys

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