Effect of interfacial bridging atoms on the strength of Al/CNT composites: machine-learning-based prediction and experimental validation
Weak interfacial adhesion is one of key obstacles to develop aluminum matrix composites containing carbon nanotubes (CNTs). This study suggests the concept of bridging atoms to enhance the interfacial wetting between aluminum and CNTs. Machine learning and sensitivity analyses were employed to deter...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-03-01
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| Series: | Journal of Materials Research and Technology |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2238785422000928 |
| _version_ | 1818312609219215360 |
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| author | KeunWon Lee HanSol Son KiSub Cho HyunJoo Choi |
| author_facet | KeunWon Lee HanSol Son KiSub Cho HyunJoo Choi |
| author_sort | KeunWon Lee |
| collection | DOAJ |
| description | Weak interfacial adhesion is one of key obstacles to develop aluminum matrix composites containing carbon nanotubes (CNTs). This study suggests the concept of bridging atoms to enhance the interfacial wetting between aluminum and CNTs. Machine learning and sensitivity analyses were employed to determine the most favorable element as a bridging atom. Copper was identified as the most effective bridging atom, and its bridging efficiency (enhancement of strengthening efficiency of CNTs) was experimentally validated by comparison with those in the monolithic Al and Al–Si matrix. As a result, the strengthening efficiencies of the CNTs were measured to be ∼43, 27, and 73 MPa/vol% for the Al, Al–Si, and Al–Cu matrices, respectively, which is comparable with the prediction by the machine learning model. |
| first_indexed | 2024-12-13T08:20:34Z |
| format | Article |
| id | doaj.art-b62122891a434ddcb2c6f4dd0c06c510 |
| institution | Directory Open Access Journal |
| issn | 2238-7854 |
| language | English |
| last_indexed | 2024-12-13T08:20:34Z |
| publishDate | 2022-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of Materials Research and Technology |
| spelling | doaj.art-b62122891a434ddcb2c6f4dd0c06c5102022-12-21T23:54:01ZengElsevierJournal of Materials Research and Technology2238-78542022-03-011717701776Effect of interfacial bridging atoms on the strength of Al/CNT composites: machine-learning-based prediction and experimental validationKeunWon Lee0HanSol Son1KiSub Cho2HyunJoo Choi3Department of Materials Science and Engineering, Kookmin University, Seoul, 02707, Republic of KoreaDepartment of Materials Science and Engineering, Kookmin University, Seoul, 02707, Republic of KoreaDepartment of Materials Science and Engineering, Kookmin University, Seoul, 02707, Republic of KoreaCorresponding author.; Department of Materials Science and Engineering, Kookmin University, Seoul, 02707, Republic of KoreaWeak interfacial adhesion is one of key obstacles to develop aluminum matrix composites containing carbon nanotubes (CNTs). This study suggests the concept of bridging atoms to enhance the interfacial wetting between aluminum and CNTs. Machine learning and sensitivity analyses were employed to determine the most favorable element as a bridging atom. Copper was identified as the most effective bridging atom, and its bridging efficiency (enhancement of strengthening efficiency of CNTs) was experimentally validated by comparison with those in the monolithic Al and Al–Si matrix. As a result, the strengthening efficiencies of the CNTs were measured to be ∼43, 27, and 73 MPa/vol% for the Al, Al–Si, and Al–Cu matrices, respectively, which is comparable with the prediction by the machine learning model.http://www.sciencedirect.com/science/article/pii/S2238785422000928Metal matrix compositesMechanical propertiesMechanical alloyingCarbon nanotubesMachine learningInterface |
| spellingShingle | KeunWon Lee HanSol Son KiSub Cho HyunJoo Choi Effect of interfacial bridging atoms on the strength of Al/CNT composites: machine-learning-based prediction and experimental validation Journal of Materials Research and Technology Metal matrix composites Mechanical properties Mechanical alloying Carbon nanotubes Machine learning Interface |
| title | Effect of interfacial bridging atoms on the strength of Al/CNT composites: machine-learning-based prediction and experimental validation |
| title_full | Effect of interfacial bridging atoms on the strength of Al/CNT composites: machine-learning-based prediction and experimental validation |
| title_fullStr | Effect of interfacial bridging atoms on the strength of Al/CNT composites: machine-learning-based prediction and experimental validation |
| title_full_unstemmed | Effect of interfacial bridging atoms on the strength of Al/CNT composites: machine-learning-based prediction and experimental validation |
| title_short | Effect of interfacial bridging atoms on the strength of Al/CNT composites: machine-learning-based prediction and experimental validation |
| title_sort | effect of interfacial bridging atoms on the strength of al cnt composites machine learning based prediction and experimental validation |
| topic | Metal matrix composites Mechanical properties Mechanical alloying Carbon nanotubes Machine learning Interface |
| url | http://www.sciencedirect.com/science/article/pii/S2238785422000928 |
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