Corrosion Evaluation for Absorption - Based CO2 Capture Process Using Single and Blended Amines
Notice bibliographique
Résumé
One of the major problems associated with the amine-based carbon dioxide (CO2) capture process is corrosion of process components, which results in unexpected downtime, production loss, and even major fatalities. Most of the published corrosion literature is on conventional monoethanolamine (MEA) solvent, and there have been very few corrosion studies conducted on other single amines like methyldiethanolamine (MDEA), diethanolamine (DEA), 2-amino-2-methyl-1-propanol (AMP), and some blended amines. Although there has been extensive research conducted on the kinetics of concentrated piperazine (PZ) as an attractive solvent for the CO2 absorption process, no corrosion studies have been conducted for this solvent. This work investigated the corrosion of construction materials including carbon steel (CS1018) and stainless steels (SS304 and SS316) in the CO2 capture process, using various types of CO2 absorption solvents. The tested solvents included MEA, DEA, MDEA, AMP, PZ, and their blends. A series of laboratory corrosion tests was carried out using electrochemical techniques (DC-cyclic potentiodynamic polarization and ACimpedance measurement) and weight loss technique to establish an engineering corrosion database for the CO2 capture process. Experimental conditions were chosen to be CO2 saturation and 80°C for most experiments. The electrochemical results show that the corrosivity order of CS1018 for the single amine systems was MEA > AMP > DEA > PZ > MDEA. The corrosion rates in MEA and AMP systems were almost double those of the PZ and MDEA systems. The passivation of carbon steel in the DEA system was more compact and less porous than those in the MDEA, PZ, MEA, and AMP systems. The corrosive effects of process contaminants, i.e., thiosulfate, oxalate, sulfite, and chloride, on corrosion rate were observed in all amine systems. The presence of thiosulfate reduced the corrosion rate of carbon steel in the MEA system, whereas the presence of oxalate increased the corrosion rate in all tested single amines. Two corrosivity behaviours were found in the presence of sulfite and chloride. In the presence of sulfite, the corrosion rate of carbon steel was increased in the MEA, DEA, MDEA, and PZ systems, but decreased in the AMP system. In the presence of chloride, the corrosion rate increased only in the MDEA system, but decreased in the MEA, DEA, AMP, and PZ systems. In addition to single amines, five different blended amines were also tested for their corrosiveness. The results show that the corrosivity trend of CS1018 in blended amine systems was MEA-PZ ≥ MEA-AMP ≥ MEA-MDEA > MDEA-PZ > AMP-PZ. The stainless steel materials (SS316 and/or SS304) offered great resistance to corrosion in all amine systems. For example, the corrosion rates were very low, in the range of 0.006 - 0.036 mmpy, which is well below the standard acceptable corrosion rate (0.07 mmpy). Conductivity of the solution was found to correlate well with corrosion rate in both single and blended amine systems. The weight loss results show that after 28 days, the corrosivity order of CS1018 in single amine systems was MEA > DEA > PZ > AMP ≈ MDEA. The corrosion products deposited over carbon steel were found to be iron carbonate (FeCO3) and iron oxide (Fe3O4).
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 | 0,000 | 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 | 0,001 | 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 ».