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Modeling of rapidly solidified aging process of Cu–Cr–Sn–Zn alloy by an artificial neural network

✍ Scribed by Juan-hua Su; He-jun Li; Qi-ming Dong; Ping Liu; Bao-hong Tian


Book ID
116374417
Publisher
Elsevier Science
Year
2005
Tongue
English
Weight
202 KB
Volume
34
Category
Article
ISSN
0927-0256

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✍ Juan-hua Su; Ping Liu; Qi-ming Dong; He-jun Li; Feng-zhang Ren 📂 Article 📅 2008 🏛 Elsevier Science 🌐 English ⚖ 589 KB

The effects of different solution methods on aging microstructure and properties of Cu-Cr-Sn-Zn alloy have been studied. The grain size of rapid solidification is much smaller than solid-solution grain size. Strengthening of smaller grain size is obvious. There are much more fine precipitates in the