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Machine learning-guided accelerated discovery of structure-property correlations in lean magnesium alloys for biomedical applications

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Journal of Magnesium and Alloys 2024年第6期12卷 2267-2283页

作者： Sreenivas Raguraman maitreyee sharma priyadarshini Tram Nguyen Ryan McGovern Andrew Kim Adam J.Griebel Paulette Clancy Timothy P.Weihs Department of Materials Science and Engineering Johns Hopkins University3400 N Charles StBaltimore21218MDU.S.A Hopkins Extreme Materials Institute Johns Hopkins University3400 N Charles StBaltimore21218MDU.S.A Department of Chemical and Biomolecular Engineering Johns Hopkins University3400 N Charles StBaltimore21218MDU.S.A Translational Tissue Engineering Center Johns Hopkins School of Medicine400 N BroadwayBaltimore21231MDU.S.A Department of Biomedical Engineering Johns Hopkins University3400 N Charles StBaltimore21218MDU.S.A Research and Development Fort Wayne Metals Research ProductsLLC9609 Ardmore AveFort Wayne46809INU.S.A Department of Mechanical Engineering Johns Hopkins University3400 N Charles StBaltimore21218MDU.S.A

Magnesium alloys are emerging as promising alternatives to traditional orthopedic implant materials thanks to their biodegradability,biocompatibility,and impressive mechanical ***,their rapid in-vivo degradation presents challenges,notably in upholding mechanical integrity over *** study investigates the impact of high-temperature thermal processing on the mechanical and degradation attributes of a lean Mg-Zn-Ca-Mn alloy,*** rapid,cost-efficient characterization methods like X-ray diffraction and optical microscopy,we swiftly examine microstructural changes post-thermal *** Pearson correlation coefficient analysis,we unveil the relationship between microstructural properties and critical targets(properties):hardness and corrosion ***,leveraging the least absolute shrinkage and selection operator(LASSO),we pinpoint the dominant microstructural factors among closely correlated *** findings underscore the significant role of grain size refinement in strengthening and the predominance of the ternary Ca_(2)Mg_(6)Zn_(3)phase in corrosion *** suggests that achieving an optimal blend of strength and corrosion resistance is attainable through fine grains and reduced concentration of ternary *** thorough investigation furnishes valuable insights into the intricate interplay of processing,structure,and properties in magnesium alloys,thereby advancing the development of superior biodegradable implant materials.

关键词： Magnesium alloys Machine learning Corrosion Mechanical properties Rapid characterization

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