Fatigue Behavior of Polymer Nanocomposites under Low-Strain Cyclic Loading: Insights from Molecular Dynamics Simulation.

IF 3.7 2区 化学 Q2 CHEMISTRY, MULTIDISCIPLINARY Langmuir Pub Date : 2024-11-12 Epub Date: 2024-11-04 DOI:10.1021/acs.langmuir.4c02769
Tongkui Yue, Hengheng Zhao, Jiajun Qu, Liqun Zhang, Jun Liu
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Abstract

Understanding the structural evolution and bond-breaking behavior under cyclic loading is crucial for designing polymer nanocomposites (PNCs) with superior fatigue resistance. Coarse-grained models of PNCs filled with spherical carbon black nanoparticles (NPs) at varying filling fractions of φ were successfully constructed using molecular dynamics simulations. Structural and dynamic simulation results reveal that higher φ leads to increased aggregation of NPs and markedly restricts the relaxation behavior of the polymer matrix. Subsequently, fatigue testing of PNCs was conducted under low-strain cyclic tensile deformation, and the real-time bond-breaking behavior was tracked. The decay behavior of the bond number autocorrelation function was found to be accurately described by the KWW equation, enabling precise determination of the characteristic lifetime τf. With increasing φ, the dominant factor influencing bond-breaking behavior gradually shifts from the polymer network, including entanglements and cross-linking networks, to the filler network. This suggests the presence of a critical filling fraction φc where τf is maximized. For low-strain failure mechanisms, temperature field observations at varying cycles reveal that localized temperature rise emerges as the predominant factor. Furthermore, the mobility of both polymers and NPs increases with cycles. Specifically, the diffusion coefficient of polymer monomers shows a clear power-law relationship with the bond-breaking rate, characterized by Dfbroken1.5. Finally, the stiffness of polymer chains significantly influences the fatigue behavior, evidenced by an initial increase followed by a decrease in the τf with increasing bending energy k. This behavior is attributed to the competitive relationship between high entanglement density at low k and enhanced preorientation at high k. In summary, this study provides a general paradigm for describing failure behavior under cyclic deformation and offers insights into fatigue mechanisms at the molecular level, thereby guiding the development of improved fatigue-resistant PNCs.

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低应变循环加载下聚合物纳米复合材料的疲劳行为:分子动力学模拟的启示。
了解循环加载下的结构演变和断键行为对于设计具有优异抗疲劳性能的聚合物纳米复合材料(PNC)至关重要。利用分子动力学模拟成功构建了填充不同填充分数φ的球形炭黑纳米颗粒(NPs)的 PNC 粗粒度模型。结构和动态模拟结果表明,φ 越大,NPs 的聚集越多,并明显限制了聚合物基体的松弛行为。随后,在低应变循环拉伸变形条件下对 PNCs 进行了疲劳测试,并跟踪了实时断键行为。研究发现,键数自相关函数的衰减行为可以用 KWW 方程准确描述,从而可以精确测定特征寿命 τf。随着 φ 的增大,影响断键行为的主导因素逐渐从聚合物网络(包括缠结和交联网络)转移到填料网络。这表明存在临界填充分数φc,在此τf达到最大值。对于低应变失效机制,不同循环下的温度场观测结果表明,局部温升是主要因素。此外,聚合物和 NPs 的流动性都会随着循环次数的增加而增加。具体来说,聚合物单体的扩散系数与断键速率呈明显的幂律关系,即 D∼fbroken1.5。最后,聚合物链的刚度对疲劳行为有显著影响,表现为随着弯曲能 k 的增加,τf 初始增加,随后减小。这种行为归因于低 k 时的高纠缠密度与高 k 时的增强预取向之间的竞争关系。总之,本研究为描述循环变形下的失效行为提供了一个通用范例,并提供了对分子水平疲劳机制的见解,从而指导了耐疲劳 PNCs 的开发。
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Langmuir
Langmuir 化学-材料科学:综合
CiteScore
6.50
自引率
10.30%
发文量
1464
审稿时长
2.1 months
期刊介绍: Langmuir is an interdisciplinary journal publishing articles in the following subject categories: Colloids: surfactants and self-assembly, dispersions, emulsions, foams Interfaces: adsorption, reactions, films, forces Biological Interfaces: biocolloids, biomolecular and biomimetic materials Materials: nano- and mesostructured materials, polymers, gels, liquid crystals Electrochemistry: interfacial charge transfer, charge transport, electrocatalysis, electrokinetic phenomena, bioelectrochemistry Devices and Applications: sensors, fluidics, patterning, catalysis, photonic crystals However, when high-impact, original work is submitted that does not fit within the above categories, decisions to accept or decline such papers will be based on one criteria: What Would Irving Do? Langmuir ranks #2 in citations out of 136 journals in the category of Physical Chemistry with 113,157 total citations. The journal received an Impact Factor of 4.384*. This journal is also indexed in the categories of Materials Science (ranked #1) and Multidisciplinary Chemistry (ranked #5).
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