Data‐driven designing on mechanical properties of biodegradable wrought zinc alloys

Data‐driven designing on mechanical properties of biodegradable wrought zinc alloys

Abstract A small dataset of ∼300 datapoints of zinc (Zn) alloys were collected and 125 entries containing alloying elements, extrusion parameters (temperature (ET), speed (ES) and ratio (ER)), and mechanical properties (yield strength (YS), ultimate tensile strength (UTS), and final elongation (EL))...

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Bibliographic Details
Main Authors: Zongqing Hu, Shaojie Li, Jianfeng Jin, Yuping Ren, Rui Hou, Lei Yang, Gaowu Qin
Format: Article
Language:English
Published: Wiley-VCH 2025-06-01
Series:Materials Genome Engineering Advances
Subjects:
composition design
machine learning
mechanical properties
process optimization
zinc alloy
Online Access:https://doi.org/10.1002/mgea.70009
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https://doi.org/10.1002/mgea.70009

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