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Materials Research Letters Volume 12, 2024 - Issue 8
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Original Reports

Breaking hardness and electrical conductivity trade-off in Cu-Ti alloys through machine learning and Pareto front

Hang Fua State Key Laboratory of Powder Metallurgy, Central South University, Changsha, People’s Republic of ChinaView further author information
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Tianchuang Gaoa State Key Laboratory of Powder Metallurgy, Central South University, Changsha, People’s Republic of ChinaView further author information
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Jianbao Gaoa State Key Laboratory of Powder Metallurgy, Central South University, Changsha, People’s Republic of China;b State Key Laboratory of Materials Processing and Die & Mould Technology, School of Materials Science and Engineering, Huazhong University of Science and Technology, Wuhan, People’s Republic of ChinaCorrespondence[email protected]
View further author information
,
Qin Lia State Key Laboratory of Powder Metallurgy, Central South University, Changsha, People’s Republic of ChinaView further author information
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Xiangpeng Mengc Ningbo Boway Alloy Material Co., Ltd, Ningbo, People’s Republic of ChinaView further author information
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Min Zhanga State Key Laboratory of Powder Metallurgy, Central South University, Changsha, People’s Republic of China;c Ningbo Boway Alloy Material Co., Ltd, Ningbo, People’s Republic of ChinaView further author information
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Haoyue Linga State Key Laboratory of Powder Metallurgy, Central South University, Changsha, People’s Republic of ChinaView further author information
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Jing Zhonga State Key Laboratory of Powder Metallurgy, Central South University, Changsha, People’s Republic of ChinaView further author information
&
Lijun Zhanga State Key Laboratory of Powder Metallurgy, Central South University, Changsha, People’s Republic of ChinaCorrespondence[email protected]
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Pages 580-589 | Received 26 Feb 2024, Published online: 15 Jun 2024

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