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Density Functional Theory-Based Indicators to Estimate the Corrosion Potentials of Zinc Alloys in Chlorine-, Oxidizing-, and Sulfur-Harsh Environments.
Mukhametov, Azamat; Samikov, Insaf; Korznikova, Elena A; Kistanov, Andrey A.
Afiliación
  • Mukhametov A; The Laboratory of Metals and Alloys Under Extreme Impacts, Ufa University of Science and Technology, 450076 Ufa, Russia.
  • Samikov I; The Laboratory of Metals and Alloys Under Extreme Impacts, Ufa University of Science and Technology, 450076 Ufa, Russia.
  • Korznikova EA; The Laboratory of Metals and Alloys Under Extreme Impacts, Ufa University of Science and Technology, 450076 Ufa, Russia.
  • Kistanov AA; Polytechnic Institute (Branch) in Mirny, North-Eastern Federal University, 678170 Mirny, Russia.
Molecules ; 29(16)2024 Aug 10.
Article en En | MEDLINE | ID: mdl-39202869
ABSTRACT
Nowadays, biodegradable metals and alloys, as well as their corrosion behavior, are of particular interest. The corrosion process of metals and alloys under various harsh conditions can be studied via the investigation of corrosion atom adsorption on metal surfaces. This can be performed using density functional theory-based simulations. Importantly, comprehensive analytical data obtained in simulations including parameters such as adsorption energy, the amount of charge transferred, atomic coordinates, etc., can be utilized in machine learning models to predict corrosion behavior, adsorption ability, catalytic activity, etc., of metals and alloys. In this work, data on the corrosion indicators of Zn surfaces in Cl-, S-, and O-rich harsh environments are collected. A dataset containing adsorption height, adsorption energy, partial density of states, work function values, and electronic charges of individual atoms is presented. In addition, based on these corrosion descriptors, it is found that a Cl-rich environment is less harmful for different Zn surfaces compared to an O-rich environment, and more harmful compared to a S-rich environment.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Molecules Asunto de la revista: BIOLOGIA Año: 2024 Tipo del documento: Article País de afiliación: Rusia Pais de publicación: Suiza

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Molecules Asunto de la revista: BIOLOGIA Año: 2024 Tipo del documento: Article País de afiliación: Rusia Pais de publicación: Suiza