【新文速递】2026年1月2日复合材料SCI期刊最新文章

今日更新：Composite Structures 2 篇，Composites Part B: Engineering 2 篇，Composites Science and Technology 1 篇Composite StructuresAn inf-sup stable phase-field formulation for fracture of thermo-responsive hydrogels: Isotropic and transversely isotropic material modelsA. Valverde-González, P. Olivares-Rodríguez, J. Reinoso, B. Dortdivanliogludoi:10.1016/j.compstruct.2025.119785热响应性水凝胶断裂的一种稳定相场公式：各向同性和横向各向同性材料模型This investigation presents a comprehensive phase-field formulation for fracture an alysis of thermo-responsive hydrogels, encompassing both isotropic and transversely isotropic material models within an integrated thermo-chemo-mechanical framework. The proposed numerical approach addresses computational challenges through a mixed variational formulation that ensures inf-sup stability while maintaining robust fracture simulation capabilities. The finite element implementation employs quadratic interpolation functions for the displacement field and linear shape functions for the chemical potential (fluid pressure), temperature, and fracture fields. This formulation is implemented as a user-element subroutine UEL in ABAQUS, utilizing a Q2Q1Q1Q1 finite element formulation. The validation strategy comprises two key investigations. First, a comparative an alysis against the foundational work of Böger et al. (2017), pinpoints the capacity of the current formulation to achieve numerical stability while accurately capturing fracture limit states across varying temperature conditions. Second, the methodology is applied to simulate complex material behavior through the a nalysis of pre-notched specimens under combined swelling and mechanical loading conditions. This thorough assess ment provides valuable insights into the coupled chemical and mechanical responses of thermo-responsive hydrogels, demonstrating the ability of the proposed formulation in simulating these advanced materials.本研究提出了一个用于热响应性水凝胶断裂分析的综合相场公式，包括各向同性和横向各向同性材料模型，在一个集成的热化学力学框架内。所提出的数值方法通过混合变分公式解决了计算难题，确保了压裂稳定性，同时保持了强大的压裂模拟能力。有限元实现对位移场采用二次插值函数，对化学势（流体压力）、温度和裂缝场采用线性形状函数。该公式在ABAQUS中作为用户元素子程序UEL实现，利用Q2Q1Q1Q1有限元公式。验证策略包括两个关键的调查。首先，与Böger等人（2017）的基础工作进行对比分析，确定了当前公式在实现数值稳定性的同时，在不同温度条件下准确捕获断裂极限状态的能力。其次，通过分析预缺口试件在膨胀和机械载荷联合作用下的复杂材料行为，将该方法应用于模拟材料行为。这项全面的评估为热响应水凝胶的耦合化学和机械响应提供了有价值的见解，证明了所提出的配方在模拟这些先进材料方面的能力。Advances in 4D printing of polymeric composite s mart materialsSandeep Olhan, Bindu Antil, P. Maimí, B.K. Beheradoi:10.1016/j.compstruct.2025.119859高分子复合智能材料的4D打印研究进展4D printing, an advanced evolution of 3D printing, has revolutionized the fabrication of s mart materials that can dynamically change shape and adapt their functionality over time when exposed to external stimuli. These materials hold significant promise for use in aerospace, biomedical engineering, soft robotics, and s mart textiles, where responsiveness and adaptability are crucial. This review provides an in-depth ana lysis of latest advancements in 4D printing of polymeric composite s mart materials (4D-PCS M), focusing on key aspects such as material selection, fibre functionalities, structural design, printing techniques, and activation stimuli. Additionally, the study examines critical printing parameters, computational design-strategies, and both current and emerging applications. The review further addresses major challenges such as precise shape-morphing, enhanced mechanical robustness, and sustainable development of 4D-PCS M. Emerging trends, including AI-driven design optimization, bio-based polymer advancement, and high-resolution printing techniques, are also discussed as key drivers of future innovations. This document serves as a guiding framework for researchers and industry professionals, bridging the gap between material science and additive manufacturing. Although 4D printing is still in its embryonic developmental stages, the field holds significant promise to drive next-generation s mart materials with dynamic, adaptive, and multifunctional properties, paving the way for groundbreaking applications across various industries.4D打印是3D打印的先进发展，它彻底改变了智能材料的制造，当暴露于外部刺 激时，智能材料可以随着时间的推移动态改变形状并适应其功能。这些材料在航空航天、生物医学工程、软机器人和智能纺织品等领域具有重要的应用前景，在这些领域，响应能力和适应性至关重要。本文综述了聚合物复合智能材料（4D- pcs m） 4D打印的最新进展，重点介绍了材料选择、纤维功能、结构设计、打印技术和激活刺 激等关键方面。此外，该研究还考察了关键的打印参数、计算设计策略以及当前和新兴的应用。本文进一步讨论了3d - pcs m的主要挑战，如精确的形状变形、增强的机械稳健性和可持续发展。新兴趋势，包括人工智能驱动的设计优化、生物基聚合物的进步和高分辨率打印技术，也被认为是未来创新的关键驱动因素。该文件为研究人员和行业专业人士提供了指导框架，弥合了材料科学和增材制造之间的差距。尽管4D打印仍处于萌芽发展阶段，但该领域有望推动具有动态、自适应和多功能特性的下一代智能材料，为各行各业的突破性应用铺平道路。Composites Part B: EngineeringSynergistic Augmentation of Mechanical and Tribological Properties in Bionic Mortise-Tenon Carbon Fiber/Epoxy CompositesYameng Wan, Longlong Zhang, Bingli Pan, Hongyu Liu, Liming Zhu, Yingying Lv, Menghan Li, Huaying Lu, Yibin Zhang, Zhengke Li, Honggang Wangdoi:10.1016/j.composites b.2025.113202仿生榫卯碳纤维/环氧复合材料力学和摩擦学性能的协同增强This study proposed a novel interface enhancement and synergistic lubrication strategy to improve the mechanical and tribological properties of carbon fiber epoxy composites (CFRPs) and expanded their application in wear-resistant and trans mission components. Three-dimensional (3D) CF/PDA/GO/PW reinforced structures were constructed by modifying the surface of carbon fiber (CF) with polydopamine (PDA) and grappling graphene oxide (GO) as “tenon”. At the same time, the epoxy resin (EP) matrix serves as “mortise,” resulting in an EP/CF/PDA/GO/PW composite material with a biomimetic tenon slot structure. This structure significantly improved the interface bonding strength and mechanical properties across the thickness of the composite material. In addition, phase-change lubricant paraffin wax (PW) was incorporated into the reinforcement to improve tribological performance. The experimental results showed that the interfacial shear strength of the modified CF was significantly improved by 19.26% compared with the pure CF. The tensile strength and tensile modulus of the composite materials were increased by 29.81% and 14.77% compared to pure EP material when the mass ratio of GO to PW was 1:3, respectively, owing to the robust mortise-tenon connection structure. Also, it showed outstanding tribological properties, which reduced the coefficient of friction (COF) and wear rate by 87.95% and 20.93%, respectively, compared to pure EP. The results of the experiments consistent with molecular dynamics (MD) simulations indicated that the synergistic lubrication effect between CF, GO, and PW was the key mechanis m contributing to the significant improvement in the tribological properties of the composite materials.本研究提出了一种新的界面增强和协同润滑策略，以提高碳纤维环氧复合材料（CFRPs）的力学和摩擦学性能，并扩大其在耐磨和传动部件中的应用。以聚多巴胺（PDA）和氧化石墨烯（GO）作为“榫”，对碳纤维（CF）表面进行修饰，构建了三维（3D） CF/PDA/GO/PW增强结构。同时，环氧树脂（EP）基体作为“榫卯”，形成具有仿生榫槽结构的EP/CF/PDA/GO/PW复合材料。这种结构显著提高了复合材料的界面结合强度和机械性能。此外，在增强材料中加入了相变润滑剂石蜡（PW），提高了增强材料的摩擦学性能。实验结果表明，当氧化石墨烯与PW的质量比为1:3时，改性后的CF界面抗剪强度比纯CF提高了19.26%，复合材料的抗拉强度和抗拉模量分别比纯EP材料提高了29.81%和14.77%，这主要是由于其坚固的榫头连接结构。与纯EP相比，其摩擦系数（COF）和磨损率分别降低了87.95%和20.93%。与分子动力学（MD）模拟结果一致的实验结果表明，CF、GO和PW之间的协同润滑作用是复合材料摩擦学性能显著改善的关键机制。VCT-Based Buckling Load Prediction in Unstiffened CFRP Cylinders: Assess ment of Predictive Robustness Under Varied Imperfection Maps and Modifications to the Arbelo Characteristic ChartA. Gliszczynski, F. Franzoni, R. Degenhardt, T.D. Baciudoi:10.1016/j.composites b.2025.113201基于vct的非加筋CFRP钢瓶屈曲载荷预测：不同缺陷图下的预测鲁棒性评估及对Arbelo特征图的修正This study presents a comprehensive evaluation of the predictive accuracy and robustness of the Vibration Correlation Technique (VCT) for estimating the buckling load of unstiffened cylindrical CFRP shells under axial compression. The an alysis combines experimental and numerical data for ten cylinders (Z15–Z26), incorporating measured maps of mid-surface imperfections and thickness variations. The numerical investigation was extended to include modified imperfection scenarios through scaling and inversion of the original maps. Buckling load predictions were obtained using the standard Arbelo-type approach (as originally proposed) and several alternative formulations, differing in the definitions of the unloaded natural frequency and reference critical buckling load. Results show that both the standard Arbelo-type approach and its modified variant—based on a redefinition of the reference critical buckling load—provide accurate and consistently conservative predictions. VCT estimations remained stable across a wide range of imperfection amplitudes, confirming the method’s robustness. Gradient-based a nalysis enabled anomaly detection within large datasets, often linked to cases where local buckling preceded global instability. These anomalies can be mitigated by incorporating higher-order vibration modes. The influence of imperfection direction was found to be moderate, with original and inverted maps producing comparable prediction deviation distributions. Although the modified formulation yields more conservative results, statistical an alysis does not support its overall superiority over the standard Arbelo-type chart. The findings confirm that VCT offers a reliable, nondestructive framework for buckling load prediction across diverse imperfection scenarios. The proposed modifications may be beneficial in selected cases, but the standard Arbelo-based approach remains a robust and practical baseline.本文综合评价了振动相关技术（VCT）在预估未加筋CFRP圆柱壳轴压下屈曲载荷时的预测精度和鲁棒性。分析结合了10个圆柱体（Z15-Z26）的实验和数值数据，结合了中间表面缺陷和厚度变化的测量图。通过对原始地图的缩放和反演，将数值研究扩展到包括修正的缺陷场景。屈曲载荷预测使用标准arbelo型方法（如最初提出的）和几种替代公式，在卸载固有频率和参考临界屈曲载荷的定义上有所不同。结果表明，标准arbelo型方法及其基于参考临界屈曲载荷重新定义的修正变体都提供了准确且一致的保守预测。VCT估计在很大的不完美幅度范围内保持稳定，证实了该方法的鲁棒性。基于梯度的分析可以在大型数据集中进行异常检测，通常与局部屈曲先于全局不稳定的情况有关。这些异常可以通过结合高阶振动模式来缓解。发现缺陷方向的影响是温和的，原始和倒立的地图产生可比的预测偏差分布。虽然修改后的公式得到了更保守的结果，但统计分析并不支持其优于标准arbelo型图表。研究结果证实，VCT为各种缺陷情况下的屈曲载荷预测提供了可靠、无损的框架。建议的修改在某些情况下可能是有益的，但是基于arbelo的标准方法仍然是一个健壮和实用的基线。Composites Science and TechnologyMultilayer design and multi-objective optimization of neutron shielding composites by means of MCNP simulation and machine learningBenben Liu, Yizhuo Gu, Ruiqi Guo, Shaokai Wang, Min Lidoi:10.1016/j.compscitech.2025.111451 基于MCNP仿真和机器学习的中子屏蔽复合材料多层设计与多目标优化To meet neutron shielding and lightweight requirements, fiber-reinforced polymer matrix composites offer significant advantages as multifunctional materials with both structural and shielding capabilities. Owing to their inherent multicomponent and multilayered configurations, selecting suitable reinforcements and optimizing multilayer structure remains challenging. This study addresses the design and multi-objective optimization of multilayer composite shielding structures for neutron radiation protection. Monte Carlo N-Particle (MCNP) simulation method is adopted to predict radiation shielding property of various composites. A homogeneous model is first employed to examine the effects of typical shielding fillers (B4C and WO3) on the effective neutron dose in an epoxy resin matrix across the full neutron energy spectrum. Subsequently, an idealized layered structure model is used to clarify material composition strategies and multi-layer design principles for epoxy resin matrix composite. The results show that for fast neutron protection, a bilayer configuration with a high-Z material as the front layer and a hydrogen-rich matrix as the rear layer is optimal. For slow neutron protection, multilayer configurations demonstrate significant advantages: a 128-layer structure can reduce the effective dose of slow neutrons by up to 30 % compared with a bilayer structure. Furthermore, a multi-objective optimization strategy is proposed for multilayer structures by integrating MCNP simulations with machine learning, which can optimize shielding efficiency, structural thickness, and overall mass. Among six regression algorithms, a three-layer neural network model is chosen, which achieves high prediction precision. This approach optimizes both the minimum-dose configuration at fixed thickness and the minimum-weight configuration at fixed dose, providing efficient design guidelines for multilayer composite shielding.为了满足中子屏蔽和轻量化的要求，纤维增强聚合物基复合材料作为兼具结构和屏蔽能力的多功能材料具有显著的优势。由于其固有的多组分和多层结构，选择合适的增强材料和优化多层结构仍然是一个挑战。研究了用于中子辐射防护的多层复合屏蔽结构的设计与多目标优化。采用蒙特卡罗n粒子（MCNP）模拟方法对各种复合材料的辐射屏蔽性能进行了预测。本文首先采用均匀模型研究了典型屏蔽填料（B4C和WO3）在全中子能谱范围内对环氧树脂基体中有效中子剂量的影响。随后，利用理想分层结构模型阐明了环氧树脂基复合材料的材料组成策略和多层设计原则。结果表明，对于快中子防护，以高z材料为前层，富氢基质为后层的双层结构是最优的。对于慢中子防护，多层结构显示出显著的优势：与双层结构相比，128层结构可以减少多达30%的慢中子有效剂量。此外，将MCNP仿真与机器学习相结合，提出了多层结构的多目标优化策略，可以优化屏蔽效率、结构厚度和总质量。在六种回归算法中，选择了三层神经网络模型，实现了较高的预测精度。该方法优化了固定厚度下的最小剂量配置和固定剂量下的最小重量配置，为多层复合屏蔽提供了有效的设计指导。来源：复合材料力学仿真Composites FEM