The Role of Lithium Salt Concentration in the Active Corrosion Protection of Aluminium Alloys
Notice bibliographique
Résumé
It has been demonstrated previously that lithium salts containing organic coatings offer effective active corrosion protection on AA2024-T3 alloys when exposed to neutral salt spray test for 168 hours [1, 2]. In the presence of a coating defect the lithium salts leach from the organic coating to the exposed metal substrate increasing the local pH to moderate alkaline conditions followed by the formation of a protective layer within the defect site [2, 3]. The lithium accumulation at the defect site and hence the formation of the protective layer is influenced by the inhibitor loading and solubility in the coating as well as the coating defect size. Three different surface compositions of the lithium protective layer have been recently identified as lithium-based layered double hydroxide (Li-LDH), lithium mixed pseudo-boehmite (Li-PB) and pseudo-boehmite (PB) each depending on the lithium leaching rate and the coating defect size [4]. For small defect sizes a high lithium concentration is hypothesized to result in the generation of Li-LDH. Furthermore, Li-PB is identified within moderate defect sizes and moderate inhibitor concentration and PB is generated within large defect sizes where low lithium concentrations are expected. On this basis, this paper describes the lithium active corrosion protection on aerospace aluminium alloys as a function of the inhibitor concentration. In doing so, commercial AA2198-T8 and AA2024-T3 aluminium alloys are immersed for 24 hours in lithium salt containing aqueous solutions at systematically varied lithium salts concentration from 10 -6 M to 10 -1 M. The alloys are then transferred to 10 -1 M aqueous NaCl solution at near neutral pH conditions and either LPR measurements are performed as a function of time over 100 hours or anodic polarization is performed. The surface composition of the alloys after 24 hours immersion in lithium containing aqueous solution is also characterized. The surface composition and the electrochemical characteristics of each lithium passive layer generated is determined as a function of the lithium concentration. The surface composition of the passive layer ranges from PB to Li-PB and Li-LDH with increasing inhibitor concentration. The polarization resistance obtained as a function of time is correlated to the corrosion rate of each generated passive layer thus demonstrating the corrosion protection performance of Li-LDH, Li-PB and PB. The generation and corrosion protection performance of each passive layer is also demonstrated under relatively thin electrolyte layers mimicking the exposure of a coating defect and the leaching of lithium salt from the coating matrix under atmospheric conditions. Visser, P., et al., Study of the formation of a protective layer in a defect from lithium-leaching organic coatings. Progress in Organic Coatings, 2016. 99 : p. 80-90. Visser, P., et al., Electrochemical Evaluation of Corrosion Inhibiting Layers Formed in a Defect from Lithium-Leaching Organic Coatings. Journal of The Electrochemical Society, 2017. 164 (7): p. C396-C406. Visser, P., et al., Mechanism of Passive Layer Formation on AA2024-T3 from Alkaline Lithium Carbonate Solutions in the Presence of Sodium Chloride. Journal of The Electrochemical Society, 2018. 165 (2): p. C60-C70. Visser, P., et al., The chemical throwing power of lithium-based inhibitors from organic coatings on AA2024-T3. Corrosion Science, 2019. 150 : p. 194-206.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».