Analyzing the Mechanical Behavior of Magnesium Metal Matrix Composites Fabricated Through Friction Stir Processing.
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| Title: | Analyzing the Mechanical Behavior of Magnesium Metal Matrix Composites Fabricated Through Friction Stir Processing. |
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| Authors: | Adetunla, Adedotun1 (AUTHOR) aadedotun@uj.ac.za, Jen, Tien-Chien1 (AUTHOR), Habib, Mohammad Rezwan1 (AUTHOR) mohabib@wiley.com |
| Source: | Advances in Materials Science & Engineering. 11/17/2025, Vol. 2025, p1-12. 12p. |
| Subjects: | Magnesium alloys, Bioabsorbable implants, Friction stir processing, Tensile strength, Mechanical wear, Durability, Orthopedics, Machine learning |
| Abstract: | Magnesium alloys show promise for orthopedic implants due to biodegradability and biocompatibility, but rapid degradation limits their use. This study fabricates AZ31 magnesium composites reinforced with CaCO3 powder via friction stir processing (FSP). Three conditions were tested: one‐pass reinforced (Sample A), three‐pass reinforced (Sample B), and three‐pass unreinforced (Sample C). Mechanical characterization included tensile, hardness, impact, and wear tests, while degradation was assessed in blood and plasma media. Sample B exhibited superior tensile strength (306.13 MPa) and the highest impact strength (0.1352 J/mm2), though hardness decreased relative to Sample C. Degradation rates were 0.033 g/day (blood) and 0.031 g/day (plasma), with Sample B showing slower plasma degradation. Machine learning models—Linear Regression and Lasso Regression—were applied to predict long‐term degradability. Linear Regression achieved lower prediction error (7.69 days vs. 13.75 days for Lasso), forecasting full degradation of a 71.5 g implant in ∼2190 days (6 years). The integrated experimental–ML framework supports optimized design of biodegradable implants with predictable lifespans. This predictive model could help plan maintenance and ensure implant safety, potentially reducing the need for second surgeries. [ABSTRACT FROM AUTHOR] |
| Copyright of Advances in Materials Science & Engineering is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 189364819 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Analyzing the Mechanical Behavior of Magnesium Metal Matrix Composites Fabricated Through Friction Stir Processing. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Adetunla%2C+Adedotun%22">Adetunla, Adedotun</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> aadedotun@uj.ac.za</i><br /><searchLink fieldCode="AR" term="%22Jen%2C+Tien-Chien%22">Jen, Tien-Chien</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Habib%2C+Mohammad+Rezwan%22">Habib, Mohammad Rezwan</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> mohabib@wiley.com</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Advances+in+Materials+Science+%26+Engineering%22">Advances in Materials Science & Engineering</searchLink>. 11/17/2025, Vol. 2025, p1-12. 12p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Magnesium+alloys%22">Magnesium alloys</searchLink><br /><searchLink fieldCode="DE" term="%22Bioabsorbable+implants%22">Bioabsorbable implants</searchLink><br /><searchLink fieldCode="DE" term="%22Friction+stir+processing%22">Friction stir processing</searchLink><br /><searchLink fieldCode="DE" term="%22Tensile+strength%22">Tensile strength</searchLink><br /><searchLink fieldCode="DE" term="%22Mechanical+wear%22">Mechanical wear</searchLink><br /><searchLink fieldCode="DE" term="%22Durability%22">Durability</searchLink><br /><searchLink fieldCode="DE" term="%22Orthopedics%22">Orthopedics</searchLink><br /><searchLink fieldCode="DE" term="%22Machine+learning%22">Machine learning</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Magnesium alloys show promise for orthopedic implants due to biodegradability and biocompatibility, but rapid degradation limits their use. This study fabricates AZ31 magnesium composites reinforced with CaCO3 powder via friction stir processing (FSP). Three conditions were tested: one‐pass reinforced (Sample A), three‐pass reinforced (Sample B), and three‐pass unreinforced (Sample C). Mechanical characterization included tensile, hardness, impact, and wear tests, while degradation was assessed in blood and plasma media. Sample B exhibited superior tensile strength (306.13 MPa) and the highest impact strength (0.1352 J/mm2), though hardness decreased relative to Sample C. Degradation rates were 0.033 g/day (blood) and 0.031 g/day (plasma), with Sample B showing slower plasma degradation. Machine learning models—Linear Regression and Lasso Regression—were applied to predict long‐term degradability. Linear Regression achieved lower prediction error (7.69 days vs. 13.75 days for Lasso), forecasting full degradation of a 71.5 g implant in ∼2190 days (6 years). The integrated experimental–ML framework supports optimized design of biodegradable implants with predictable lifespans. This predictive model could help plan maintenance and ensure implant safety, potentially reducing the need for second surgeries. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Advances in Materials Science & Engineering is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1155/amse/2253654 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 12 StartPage: 1 Subjects: – SubjectFull: Magnesium alloys Type: general – SubjectFull: Bioabsorbable implants Type: general – SubjectFull: Friction stir processing Type: general – SubjectFull: Tensile strength Type: general – SubjectFull: Mechanical wear Type: general – SubjectFull: Durability Type: general – SubjectFull: Orthopedics Type: general – SubjectFull: Machine learning Type: general Titles: – TitleFull: Analyzing the Mechanical Behavior of Magnesium Metal Matrix Composites Fabricated Through Friction Stir Processing. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Adetunla, Adedotun – PersonEntity: Name: NameFull: Jen, Tien-Chien – PersonEntity: Name: NameFull: Habib, Mohammad Rezwan IsPartOfRelationships: – BibEntity: Dates: – D: 17 M: 11 Text: 11/17/2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 16878434 Numbering: – Type: volume Value: 2025 Titles: – TitleFull: Advances in Materials Science & Engineering Type: main |
| ResultId | 1 |
