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Machine Learning-Based Prediction of Micromechanical Properties of GAP-BPS Binders Using Molecular Simulation Data.

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Title: Machine Learning-Based Prediction of Micromechanical Properties of GAP-BPS Binders Using Molecular Simulation Data.
Authors: Zheng, Haitao1, Zhou, Wei2, zhouwei23@nudt.edu.cn, Cao, Peng3, Tang, Xianqiong1,4, boyuanyin@hnust.edu.cn, Zhou, Xing1,2, Yin, Boyuan2,4
Source: Coatings (2079-6412); Apr2026, Vol. 16 Issue 4, p495, 24p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 193439976
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  Data: Machine Learning-Based Prediction of Micromechanical Properties of GAP-BPS Binders Using Molecular Simulation Data.
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      – Type: doi
        Value: 10.3390/coatings16040495
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      – Code: eng
        Text: English
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        PageCount: 24
        StartPage: 495
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      – TitleFull: Machine Learning-Based Prediction of Micromechanical Properties of GAP-BPS Binders Using Molecular Simulation Data.
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            NameFull: Zheng, Haitao
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            NameFull: Zhou, Wei
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            NameFull: Tang, Xianqiong
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            NameFull: Zhou, Xing
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            – D: 01
              M: 04
              Text: Apr2026
              Type: published
              Y: 2026
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              Value: 16
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