Effects of lattice strain on hydrogen diffusion, trapping and escape in bcc iron from ab-initio calculations

Luo, Fengping; Li, Qingyuan; Huang, Jia; Xiao, Hao; Gao, Zhiying; Ge, Wei; Gao, Fei; Wang, Yugang; Wang, Chenxu

doi:10.1016/j.ijhydene.2022.11.206

Cited by 9 publications

(5 citation statements)

References 102 publications

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“…In contrast, H trapping at dislocations has been demonstrated to depend highly on shear stresses. 256 Moreover, atomistic results showed a weak hydrostatic stress effect, 257,258 which conflicted with the large enhancement factor predicted by those equations at high stress triaxialities, e.g., at a crack tip.…”

Section: Krom Et Al (1999) 222mentioning

confidence: 88%

Hydrogen Embrittlement as a Conspicuous Material Challenge─Comprehensive Review and Future Directions

Yu,

Díaz,

et al. 2024

Chem. Rev.

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Hydrogen is considered a clean and efficient energy carrier crucial for shaping the net-zero future. Large-scale production, transportation, storage, and use of green hydrogen are expected to be undertaken in the coming decades. As the smallest element in the universe, however, hydrogen can adsorb on, diffuse into, and interact with many metallic materials, degrading their mechanical properties. This multifaceted phenomenon is generically categorized as hydrogen embrittlement (HE). HE is one of the most complex material problems that arises as an outcome of the intricate interplay across specific spatial and temporal scales between the mechanical driving force and the material resistance fingerprinted by the microstructures and subsequently weakened by the presence of hydrogen. Based on recent developments in the field as well as our collective understanding, this Review is devoted to treating HE as a whole and providing a constructive and systematic discussion on hydrogen entry, diffusion, trapping, hydrogen–microstructure interaction mechanisms, and consequences of HE in steels, nickel alloys, and aluminum alloys used for energy transport and storage. HE in emerging material systems, such as high entropy alloys and additively manufactured materials, is also discussed. Priority has been particularly given to these less understood aspects. Combining perspectives of materials chemistry, materials science, mechanics, and artificial intelligence, this Review aspires to present a comprehensive and impartial viewpoint on the existing knowledge and conclude with our forecasts of various paths forward meant to fuel the exploration of future research regarding hydrogen-induced material challenges.

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Section: Krom Et Al (1999) 222mentioning

confidence: 88%

Hydrogen Embrittlement as a Conspicuous Material Challenge─Comprehensive Review and Future Directions

Yu,

Díaz,

et al. 2024

Chem. Rev.

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show abstract

“…where P LOAD (t) and H LOAD (t) are the electrical and thermal loads of the system at time t, respectively; P WTQ (t) is the abandoned air volume of the system at time t. Among them, the scenario considering the thermal inertia of the building does not need to consider the thermal power balance constraint, and eqn (3)(4)(5)(6)(7)(8)(9)(10)(11) applies to the scenario not considering the thermal inertia of the building.…”

Section: Constraintsmentioning

confidence: 99%

“…HSS MIN # HSS(t) # HSS MAX (3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15) where TSS MIN and TSS MAX are the minimum heat storage state and maximum heat storage state of the HST, respectively; HSS MIN and HSS MAX are the minimum and maximum hydrogen storage states of the HT, respectively.…”

Section: Constraintsmentioning

confidence: 99%

“…where w is the inertia weight; c 1 and c 2 are the acceleration coefficients, respectively. The individual positions are updated by eqn (3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20)(21).…”

Section: Bpso-cs Algorithmmentioning

confidence: 99%

“…Wu et al 9 proposed an optimal energy reserve dispatch model for wind-photovoltaic-hydrogen IESs, with multiple types of energy storage devices (including electric, thermal and hydrogen) to reduce the overall operating cost. Liu et al 10 proposed an aging economic model for wind-hydrogen IESs, which was solved by using an improved multi-objective Gray Wolf optimization algorithm to strive for maximum production capacity at minimum cost and enhance the overall system efficiency. Wang et al 11 constructed a synergistic planning method for hydrogen storage IESs considering coupled electric and thermal utilization, which reduced the system carbon emissions and improved the overall energy efficiency level.…”

Section: Introductionmentioning

confidence: 99%

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