Coupled analysis of hydrogen diffusion, deformation, and fracture: a review

International Journal of Hydrogen Energy, Journal Year: 2024, Volume and Issue: 82, P. 281 - 310

Published: Aug. 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.

Language: Английский

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Effect of Alkyl Chain Length of Quaternary Ammonium Surfactant Corrosion Inhibitor on Fe (110) in Acetic Acid Media via Computer Simulation

ChemEngineering, Journal Year: 2025, Volume and Issue: 9(1), P. 7 - 7

Published: Jan. 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.

Language: Английский

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Chemically functionalized polymers as corrosion inhibitors: Effect of solubility, adsorption and coordination bonding

Coordination Chemistry Reviews, Journal Year: 2025, Volume and Issue: 535, P. 216637 - 216637

Published: March 27, 2025

Language: Английский

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Corrosion Inhibition of API 5L X60 Steel in Acid Medium: Theoretical and Experimental Approaches

ACS Omega, Journal Year: 2025, Volume and Issue: unknown

Published: April 28, 2025

Language: Английский

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Insight into the synergetic effect of alanine-derived copolymer and KI on the corrosion inhibition of SLM manufactured 17-4 PH steel in acidified NaCl solution

Published: April 28, 2025

The 17 − 4 precipitation hardening (PH) stainless steel, produced by additive manufacturing (AM), provides an exceptional balance of strength, toughness, and corrosion resistance, making it a versatile engineering alloy, especially in the aerospace sector. Nonetheless, microstructural defects that occur during adversely affect its application structural contexts, particularly concerning issues. In current study, novel Alanine-derived water-soluble copolymer referred to as L-1 was synthesized, characterized ability suppress SLM printed PH steel acidified NaCl solution is examined. Electrochemical surface characterizations computational methods were systematically utilized explore individual inhibitors' inhibitory efficacy synergistic effects their blends with potassium iodide (KI). Based on electrochemical outcomes, mixture L-1/KI (hybrid inhibitor) gave impressive rate inhibition efficiency than blank ones. An index synergism greater one showcases more significant potential for passivation mitigating progression. adsorption or chelation inhibitive co-polymer film metal examined utilizing X-ray photoelectron spectroscopy (XPS), FT-IR, UV vis analyses. examination morphology using SEM AFM revealed smooth surface, devoid conspicuous features presence co-polymer, prominent blend. Quantum chemical (QC) calculations Mulliken charge analysis indicate active centers heightened are predominantly located benzene rings alanine pendant groups. combined experimental-theoretical approach highlights effectiveness hybrid inhibitors efficient within realm sustainable chemistry.

Language: Английский

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Prolonged corrosion protection via application of 4-ferrocenylbutyl saturated carboxylate ester derivatives with superior inhibition performance for mild steel

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: June 15, 2024

A series of 4-ferrcenylbutyl carboxylate esters with different alkyl chain length (C

Language: Английский

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Machine Learning Augmentation of the Failure Assessment Diagram Methodology for Enhanced Tubular Structures Integrity Evaluation

Engineering Fracture Mechanics, Journal Year: 2024, Volume and Issue: 307, P. 110318 - 110318

Published: July 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.

Language: Английский

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Enhancing corrosion resistance of mild steel in acid pickling bath: An investigation of new quinazoline derivatives by synthesis, electrochemical analysis EFM, surface analysis, AFM, DFT and molecular dynamics simulation

Inorganic Chemistry Communications, Journal Year: 2024, Volume and Issue: unknown, P. 113640 - 113640

Published: Nov. 1, 2024

Language: Английский

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INVESTIGATING THE POTENTIAL OF 1,2,4-TRIAZOLES AS CORROSION INHIBITORS FOR COPPER AND STEEL: A COMPREHENSIVE REVIEW

Next research., Journal Year: 2024, Volume and Issue: 1(2), P. 100033 - 100033

Published: Oct. 4, 2024

Language: Английский

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