橡塑复合材料力学和摩擦学及耐腐蚀性能的研究进展

陈之举1, 李云龙1*, 钱程1, 王世杰1, 聂瑞2

化工新型材料 ›› 2025, Vol. 53 ›› Issue (3) : 72 -77.

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化工新型材料 ›› 2025, Vol. 53 ›› Issue (3) : 72-77. DOI: 10.19817/j.cnki.issn1006-3536.2025.03.043
综述与专论

橡塑复合材料力学和摩擦学及耐腐蚀性能的研究进展

    陈之举1, 李云龙1*, 钱程1, 王世杰1, 聂瑞2
作者信息 +

Research progress in mechanical,tribological,and corrosion resistance properties of rubber-plastic composites

  • Chen Zhiju1, Li Yunlong1, Qian Cheng1, Wang Shijie1, Nie Rui2
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文章历史 +
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摘要

橡塑复合材料因其良好的耐磨、耐高温和耐腐蚀性,被广泛应用于石油化工、航空和汽车等领域。因此综述了以橡胶和酚醛树脂为基体的橡塑复合材料。总结了对其增强改性的纳米材料和耐腐剂,例如石墨烯(GO)、碳纳米管(CNTs)和防老剂4010NA等。同时分析了橡塑复合材料的拉伸、压缩、耐磨特性和耐腐蚀等性能。明确了表面涂层法能有效延缓橡塑复合材料的腐蚀。最后归纳了橡塑复合材料宏观试验的研究方法。同时总结了分子动力学模拟和机器学习两种研究方法。发现两种研究方法均可模拟原子和分子的行为并快速准确地预测材料性能。

Abstract

Rubber-plastic composites are widely used in petrochemical,aerospace,and automotive applications due to their good wear resistance,high-temperature tolerance,and corrosion resistance.Therefore,rubber-plastic composites with rubber and phenolic resins as matrix were reviewed.Nanomaterials and corrosion-resistant agents for their enhancement and modification were summarized,such as graphene (GO),carbon nanotubes (CNTs) and antioxidant 4010NA.The properties of rubber-plastic composites such as tensile,compression,abrasion characteristics,and corrosion resistance were also analyzed.The surface coating method could effectively retard the corrosion of rubber-plastic composites.Finally,the research methods for macro test of rubber-plastic composite materials were summarized.Two research methods,molecular dynamics simulation and machine learning,were also summarized.It was found that both research methods could simulate the behavior of atoms and molecules and predict material properties quickly and accurately.

关键词

橡塑复合材料 / 耐磨特性 / 耐腐蚀性能 / 分子动力学模拟 / 机器学习

Key words

rubber-plastic composites material / wear resistance / corrosion resistance / molecular dynamics simulation / machine learning

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引用格式 ▾
橡塑复合材料力学和摩擦学及耐腐蚀性能的研究进展[J]. 化工新型材料, 2025, 53(3): 72-77 DOI:10.19817/j.cnki.issn1006-3536.2025.03.043

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基金资助

2023年辽宁省应用基础研究计划项目(2023JH2/101600065);国家自然科学基金(52105062);宁波市自然科学基金项目(2021J013)

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