Materials Engineering, Degradation Mechanisms, and the Role of Artificial Intelligence for Aluminium Alloy AA7075: A Technical Review
Year: 2026
Type: article
Abstract: Materials engineering plays a vibrant role in the selection, processing, performance, and durability of engineering materials. This technical review presents the evolution stages of materials science, the structural classification of engineering materials, and the industrial importance of light alloys, with a explicit focus on Aluminum alloy AA7075 under varying heat-treatment profiles. It systematically documents raw Aluminum extraction via the Bayer and Hall-Héroult processes, metallurgical precipitation-hardening frameworks, structural aerospace applications, and core architectural limits such as poor fusion weldability and mechanical anisotropy. Moreover, the report maps the localized electrochemical degradation timeline of AA7075 including pitting initiation, intergranular propagation, exfoliation delamination, and stress corrosion cracking in conjunction with critical commercial countermeasures such as over-aging thermal tempers (T73), chemical anodizing, and protective cladding configurations. To conclude, this work sightsees the integrated role of artificial intelligence, machine learning algorithms, and deep neural networks in streamlining non-destructive testing, automated defect classification, corrosion prediction, and predictive structural health monitoring.
Author: Ali
Institution: Guangdong Ocean University
Language: English
Subfield: Metals and Alloys
Field: Materials Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7225647358
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