Next research., Год журнала: 2024, Номер 1(2), С. 100033 - 100033
Опубликована: Окт. 4, 2024
Язык: Английский
Next research., Год журнала: 2024, Номер 1(2), С. 100033 - 100033
Опубликована: Окт. 4, 2024
Язык: Английский
International Journal of Hydrogen Energy, Год журнала: 2024, Номер 82, С. 281 - 310
Опубликована: Авг. 1, 2024
Hydrogen (H), emerging as a sustainable and promising clean energy source, holds significant potential for transitioning towards H-based economy, offering cleaner alternative to traditional fossil fuels. However, hydrogen embrittlement (HE) poses substantial obstacle this transition, impacting critical sectors such transportation, defense, production, construction. Computational modeling, driven by the continuous development of new algorithms high-performance computing platforms, emerges an attractive avenue unravel address complexities associated with HE. In particular, multidisciplinary modeling approach shows in investigating intricate interactions between H materials across different temporal spatial scales. Over last few decades, there have already been many developments computational investigations based on coupled study diffusion, deformation, fracture processes multifaceted aspects HE problem. This comprehensive review sheds light these advancements, providing insights into methodologies adopted their results. The begins concise overview commonly mechanisms explain Thereafter, discussion shifts various advancements diffusion from early works most recent developments, encompassing diverse aspects, uptake through lattice structure role microstructural traps material microstructure. section focuses several theoretical numerical studies that simulate how affects characteristics mechanical properties metals alloys. includes applications state-of-the-art models predict H-assisted crack growth, well range models, continuum-based finite element simulations, micro-meso scale studies.
Язык: Английский
Процитировано
5ChemEngineering, Год журнала: 2025, Номер 9(1), С. 7 - 7
Опубликована: Янв. 8, 2025
Density functional theory (DFT) and molecular dynamics (MD) simulations were employed to investigate the inhibition mechanism of cationic quaternary ammonium surfactant corrosion inhibitors (CIs) with varying chain lengths in 1.0 M HCl 500 ppm acetic acid on Fe (110) surfaces. DFT calculations demonstrated that all CI molecules possess favorable properties, groups (N+) alpha carbon serving as electron-donating reactive centers, characterized by a low band-gap energy 1.26 eV. MD highlighted C12, 12-alkyl length, most promising molecule, exhibiting high adsorption binding energies, diffusion coefficient, random distribution at concentrations, thereby facilitating optimal onto metal surface. The insights gained from computational modeling regarding influence alkyl length efficiency, coupled comprehensive theoretical understanding acidic systems, can serve foundation for future development innovative incorporating ammonium-based groups.
Язык: Английский
Процитировано
0Coordination Chemistry Reviews, Год журнала: 2025, Номер 535, С. 216637 - 216637
Опубликована: Март 27, 2025
Язык: Английский
Процитировано
0ACS Omega, Год журнала: 2025, Номер unknown
Опубликована: Апрель 28, 2025
Язык: Английский
Процитировано
0Опубликована: Апрель 28, 2025
Язык: Английский
Процитировано
0Scientific Reports, Год журнала: 2024, Номер 14(1)
Опубликована: Июнь 15, 2024
A series of 4-ferrcenylbutyl carboxylate esters with different alkyl chain length (C
Язык: Английский
Процитировано
3Engineering Fracture Mechanics, Год журнала: 2024, Номер 307, С. 110318 - 110318
Опубликована: Июль 23, 2024
Failure assessment diagrams (FADs) are essential engineering tools for evaluating the structural integrity of components. However, their widespread application can be limited by complexity and computational expense. This study presents a novel machine learning-based approach to streamline FAD analysis, offering accuracy efficiency while overcoming these limitations. The integrates numerical contour integral-based FADs with artificial neural networks (ANNs). To ensure reliable material modeling Finite Element Analysis (FEA) used generate J-integral based that train ANNs, careful experimental procedures were employed. involved uniaxial tensile tests, an iterative method obtaining precise true stress–strain curves, Ramberg–Osgood model accurate behavior representation. ANNs themselves not only analyze large datasets envelopes but also predict limit loads Φ parameter, incorporating effect residual stress on methodology. verify test proposed method, hypothetical fitness-for-service cases conducted, measurements from split-ring tests P110 L80 pipes. These assessments compared both traditional methods computationally intensive FEA-based FADs. Results demonstrate closer agreement calculations than provided in standards. Ultimately, this work provides rather innovative adaptable evaluations critical through proposal ANN enhanced approach, simplifying maintaining high fidelity.
Язык: Английский
Процитировано
3Inorganic Chemistry Communications, Год журнала: 2024, Номер unknown, С. 113640 - 113640
Опубликована: Ноя. 1, 2024
Язык: Английский
Процитировано
1Next research., Год журнала: 2024, Номер 1(2), С. 100033 - 100033
Опубликована: Окт. 4, 2024
Язык: Английский
Процитировано
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