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Product Number:
51322-17831-SG
Author:
Natalie Hana Frank, Iain Stuart Hall, Paolo Brunello
Publication Date:
2022
$20.00
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Product Number:
51323-19423-SG
Author:
Sherman Kung, Nolan Miller, Feras EI Yaakobi, Jeremy Moloney
Publication Date:
2023
$20.00
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Product Number:
51321-16742-SG
Author:
Takahiro Tsuda; Nozomi Satake; Manabu Itoki
Publication Date:
2021
$20.00
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Product Number:
MECC23-20008-SG
Author:
Faisal Al-Refai; Abdulaziz Al-Beajan; Fahad Al-Qanaee; Anas Abdelmotelb; Vinoraj Selvaraj
Publication Date:
2023
$20.00
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Product Number:
51321-16995-SG
Author:
Zhiwei (David) Yue; Megan Westerman; Ping Chen; Chunli Li; John Hazlewood
Publication Date:
2021
$20.00
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Product Number:
51322-17588-SG
Author:
Jian Hou, Tao Chen, Ming Han, Mohammed Bataweel
Publication Date:
2022
$20.00
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Product Number:
MECC23-20036-SG
Author:
Talal Al-Zahrani; Abdullatif Al-Abdulhadi; Haitham Al-Jahani; Nayef Al-Anazi; Balasubramani Bakthavatchalu; Abdulrahman Al-Huwaiji
Publication Date:
2023
$20.00
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Product Number:
51324-20704-SG
Author:
Naim Dakwar; Sankara Papavinasam; Abdullah Hammoud
Publication Date:
2024
$40.00
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Product Number:
51324-20731-SG
Author:
Deepti Ballal; Andre Anderko
Publication Date:
2024
$40.00
Corrosion in acidic solutions frequently leads to equipment failure in industry. The ability to model corrosion in acidic solutions is thus necessary to increase asset integrity. A prerequisite for any corrosion model is the accurate knowledge of solution thermodynamics. In this study, a previously developed electrochemical module has been integrated with the Mixed-Solvent Electrolyte (MSE) thermodynamic model. MSE has been previously proven to accurately represent the behavior of solutions, including solubility limits, pH, and transport properties. Here, the accuracy of MSE in predicting speciation in acidic systems is demonstrated. The electrochemical module, which incorporates partial anodic and cathodic reactions, can model active corrosion, active-passive transition, as well as dissolution in the passive state. The model is shown to quantitatively predict the corrosion rates of two duplex stainless steels, i.e., 2507 (UNS S32750) and 255 (UNS S32550) in acid mixtures containing both oxidizing and non-oxidizing acids. The effects of aggressive (fluoride and chloride) and inhibitive (nitrate) species are also accurately predicted. Simulated polarization curves are presented for the mixed acid systems to illustrate the effect of different species on the anodic and cathodic processes.
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Product Number:
ED22-17160-SG
Author:
Benjamin S Anglin, Thomas W Web
Publication Date:
2022
$20.00
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Product Number:
51323-19068-SG
Author:
M. Gagné
Publication Date:
2023
$20.00
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Product Number:
51322-17520-SG
Author:
Andy C. Gysbers, J. Tim Korstanje, Michael S. Cayard, Peiming Wang, Ezequiel Vincent
Publication Date:
2022
$20.00
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