Revisiting the Copson Curve Using Data Science

Autor:	Abraham Rojas Zuniga, Sam Bakhtiari, Ke Wang, Victor Calo, Mariano Iannuzzi
Rok vydání:	2023
Předmět:	Renewable Energy Sustainability and the Environment Materials Chemistry Electrochemistry Condensed Matter Physics Surfaces Coatings and Films Electronic Optical and Magnetic Materials
Zdroj:	Journal of The Electrochemical Society.
ISSN:	1945-7111 0013-4651
DOI:	10.1149/1945-7111/acd7ab
Popis:	This work applies machine learning to holistically interrogate the influence of metallurgical factors, such as chemical composition, heat treatment, and mechanical properties, on the stress corrosion cracking resistance of corrosion-resistant alloys. In particular, we explored the effect of nickel in reducing the stress corrosion cracking susceptibility in boiling magnesium chloride, arguably a controversial topic since Copson’s 1959 seminal publication. This paper offers insights into the synergies of nickel with other alloying elements that ultimately impact the resistance to stress corrosion cracking. Furthermore, a more detailed description of statistical patterns in the so-called Copson curve is provided.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::ed5de5c986eb7cc8ee506f6fedf532bb https://doi.org/10.1149/1945-7111/acd7ab Zobrazit plný text záznamu