Composites Science and Technology最新文献_第3页

Improving the high-voltage insulation properties of polypropylene by introducing trace addition of polyvinylidene fluoride: An experimental and simulation study 通过微量添加聚偏二氟乙烯改善聚丙烯的高压绝缘性能：实验和模拟研究

IF 8.3 1区材料科学 Q1 MATERIALS SCIENCE, COMPOSITES

Composites Science and Technology

Pub Date : 2024-10-30 DOI: 10.1016/j.compscitech.2024.110939

Ohuk Lee , Do-Kyun Kim , Hana Kim , Seong Hwan Lee , Taehoon Kwon , Ik-Su Kwon , Keisuke Shinozaki , Masayuki Hikita , Jin Hong Lee , Dae Ho Lee , Min Hee Kim , Masahiro Kozako , Seunggun Yu

Various additives ranging from inorganic nanoparticles to organic additives have been suggested to improve the insulation performance of polymeric materials for high-voltage engineering applications. Herein, a simple method for doping fluorine into a polypropylene (PP) matrix was presented by melt-blending of isotactic PP (iPP) with a small amount of polyvinylidene fluoride (PVDF) as a thermoplastic voltage stabilizer (TVS). During melt-mixing, the PVDF TVS, which is immiscible with PP, is gradually split into smaller domains within the iPP matrix and finely distributed, especially at a low PVDF content. The direct current (DC) breakdown strength (BDS) values of the PVDF-doped iPP increased by 110 % and 149 % at 25 and 110 °C, respectively, compared to those of the pristine PP, while its dielectric permittivity and loss tangent values remained nearly similar to those of iPP at wide temperature between 25 and 140 °C and frequency range between 1 Hz and 10 MHz. Quantum chemical simulation results reveal that a small amount of PVDF with high dipole moment introduces deep trap sites within the polymer matrix, which contribute for increasing BDS of iPP. Also, the PP with a small amount of PVDF dopants below 1.0 phr exhibited no any decrease in the tensile strength and elongation at break values. Therefore, the PVDF-doped iPP is anticipated as a potential candidate as high-performance high-voltage insulation materials for next-generation insulation applications.

为了改善高压工程应用中聚合物材料的绝缘性能，人们提出了从无机纳米粒子到有机添加剂等各种添加剂。本文介绍了一种在聚丙烯（PP）基体中掺入氟的简单方法，即在异方性聚丙烯（iPP）中熔融混合少量聚偏二氟乙烯（PVDF）作为热塑性电压稳定剂（TVS）。在熔融混合过程中，与聚丙烯不相溶的 PVDF TVS 在 iPP 基体中逐渐分裂成更小的畴，并精细分布，尤其是在 PVDF 含量较低时。与原始聚丙烯相比，掺杂 PVDF 的 iPP 在 25 ℃ 和 110 ℃ 时的直流击穿强度（BDS）值分别增加了 110 % 和 149 %，而其介电常数和损耗正切值在 25 ℃ 至 140 ℃ 的宽温度和 1 Hz 至 10 MHz 的频率范围内几乎与 iPP 保持相似。量子化学模拟结果表明，少量具有高偶极矩的 PVDF 会在聚合物基体中引入深阱点，从而增加 iPP 的 BDS。此外，掺入少量 PVDF（低于 1.0 phr）的聚丙烯在拉伸强度和断裂伸长率值方面没有任何下降。因此，掺杂 PVDF 的 iPP 有可能成为下一代绝缘应用中高性能高压绝缘材料的候选材料。

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引用次数: 0

Fully automated measurement of the spatial distribution of both fibre length and orientation from micro-CT images of short fibre reinforced polymers 从短纤维增强聚合物的显微 CT 图像中全自动测量纤维长度和取向的空间分布

IF 8.3 1区材料科学 Q1 MATERIALS SCIENCE, COMPOSITES

Composites Science and Technology

Pub Date : 2024-10-29 DOI: 10.1016/j.compscitech.2024.110943

L.M. Martulli, M. Sordi, A. Dinosio, A. Bernasconi

The morphology of Short Fibre Reinforced Polymers (SFRPs) plays a fundamental role in determining their stiffness, strength and fracture behaviour. Measurements tools for the analysis of their microstructure are therefore of paramount importance. To this end, a fully automated algorithm able to segment single fibres from X-ray micro-computed tomography images was developed. This method was tailored to reconstruct the microstructure of large volumes of material; in particular, to acquire fibre length, position and orientation, even dealing with low-resolution images. The algorithm was tested on different specimens of short glass fibre-reinforced polyamide and it was validated comparing the fibre orientation with the one obtained with commercial software analysis and the fibre length with the experimentally determined one. Therefore, the proposed algorithm allows to easily identify microstructural trends without requiring the usual complex evaluating procedures.

短纤维增强聚合物（SFRP）的形态在决定其刚度、强度和断裂行为方面起着至关重要的作用。因此，分析其微观结构的测量工具至关重要。为此，我们开发了一种能够从 X 射线微型计算机断层扫描图像中分割单根纤维的全自动算法。该方法专门用于重建大量材料的微观结构，特别是获取纤维长度、位置和方向，甚至可以处理低分辨率图像。该算法在不同的短玻璃纤维增强聚酰胺试样上进行了测试，并将纤维取向与商业软件分析获得的取向进行了比较，将纤维长度与实验确定的纤维长度进行了比较。因此，所提出的算法可以轻松识别微观结构趋势，而无需通常复杂的评估程序。

引用次数: 0

Electromagnetic wave absorption and enhanced mechanical properties of magnetic self-healing metal shell microcapsules filled polymer 填充聚合物的磁性自修复金属壳微胶囊的电磁波吸收和增强机械性能

IF 8.3 1区材料科学 Q1 MATERIALS SCIENCE, COMPOSITES

Composites Science and Technology

Pub Date : 2024-10-29 DOI: 10.1016/j.compscitech.2024.110944

Qian Ren , Xiaoyu Zhang , Yiran Wu , Dawei Sun , Xin Zhang

In this work, PUF/PU@IPDI (PPI) polymer shell microcapsules were synthesized through interfacial polymerization and in situ polymerization. Subsequently, a layer of metal Ni was plated on the surface of microcapsules to fabricate Ni/PUF/PU@IPDI (NPPI) composites. The results revealed that NPPI microcapsules exhibited superior thermal stability and mechanical properties, and NPPI-60 obtained the greatest strength (102.8 MPa). The minimum reflection loss (RL) value of the NPPI-20 composite was up to −32.8 dB at 5.5 mm and the corresponding effective absorption bandwidth (EAB) was 2.4 GHz. Additionally, the NPPI-10 composite displayed the highest healing efficiency (78.6 % and 86.6 % for the scratch depth and width, respectively), and the mechanical strength and fracture toughness of epoxy resin were enhanced by the addition of metal microcapsules. The core-shell structure established by electroless plating can endow self-healing microcapsules with outstanding mechanical characteristics as well as good wave absorption capability, indicating that NPPI composites have promising applications in the field of electromagnetic wave absorption and function and structure integration design of composites.

本研究通过界面聚合和原位聚合合成了 PUF/PU@IPDI (PPI) 聚合物外壳微胶囊。随后，在微胶囊表面镀上一层金属镍，制成了镍/PUF/PU@IPDI（NPPI）复合材料。结果表明，NPPI 微胶囊具有优异的热稳定性和机械性能，其中 NPPI-60 的强度最大（102.8 兆帕）。NPPI-20 复合材料在 5.5 mm 时的最小反射损耗 (RL) 值高达 -32.8 dB，相应的有效吸收带宽 (EAB) 为 2.4 GHz。此外，NPPI-10 复合材料的愈合效率最高（划痕深度和宽度分别为 78.6 % 和 86.6 %），环氧树脂的机械强度和断裂韧性也因添加了金属微胶囊而得到增强。通过无电解电镀建立的核壳结构可使自愈合微胶囊具有出色的力学特性和良好的吸波能力，这表明 NPPI 复合材料在电磁波吸收和复合材料功能与结构一体化设计领域具有广阔的应用前景。

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引用次数: 0

Anti-ballistic properties of hybrid UHMWPE fiber-reinforced composite armour 混合超高分子量聚乙烯纤维增强复合装甲的防弹性能

IF 8.3 1区材料科学 Q1 MATERIALS SCIENCE, COMPOSITES

Composites Science and Technology

Pub Date : 2024-10-28 DOI: 10.1016/j.compscitech.2024.110941

Jun Lin , Yongqiang Li , sheng Liu , Hualin Fan

The ballistic performance of three hybrid composite plates, including ultra-high molecular weight polyethylene (UHMWPE), UHMWPE/Aramid, and UHMWPE/CFRP with similar surface density, was studied in the paper. These plates were tested under the impact of 7.62×25 mm full metal jacket (FMJ) bullets, with the dynamic back deformation (BFD) captured using Digital Image Correlation (DIC) technology. The effects of material combinations and striking faces on the dynamic response were discussed. The deformation and penetration mechanisms were analyzed using optical microscopy and micro-CT tomography. The results indicated that the UHMWPE/CFRP plate exhibited the lowest BFD, followed by UHMWPE and the UHMWPE/Aramid plate. When UHMWPE severed as the striking face, the fibers underwent through-thickness compression, which transitioned to in-plane tension and led to an elongated fracture of yarns. Similarly, Aramid fibers also experienced tensile fractures under similar conditions. In contrast, carbon fibers had brittle shear fractures when CFRP was the striking face. Additionally, the “V-shaped” cone traveling hinge velocity was calculated using DIC results, and the effects of the plate bending stiffness and wave impedance on protective performance were discussed. The findings emphasize the importance of an optimal material configuration to mitigate the propagation of compressive waves in the thickness direction and enhance bending stiffness, which is crucial for improving protection within ballistic limits.

本文研究了三种混合复合材料板的弹道性能，包括具有相似表面密度的超高分子量聚乙烯（UHMWPE）、UHMWPE/芳纶和 UHMWPE/CFRP。这些板材在 7.62×25 毫米全金属护套（FMJ）子弹的冲击下进行了测试，并使用数字图像相关（DIC）技术捕捉了动态背面变形（BFD）。讨论了材料组合和撞击面对动态响应的影响。使用光学显微镜和显微 CT 断层扫描分析了变形和穿透机制。结果表明，超高分子量聚乙烯/CFRP 板的 BFD 最低，其次是超高分子量聚乙烯和超高分子量聚乙烯/芳纶板。当超高分子量聚乙烯作为撞击面断裂时，纤维经历了厚度压缩，然后过渡到平面内拉伸，导致纱线拉长断裂。同样，芳纶纤维也在类似条件下发生拉伸断裂。与此相反，当 CFRP 作为打击面时，碳纤维会出现脆性剪切断裂。此外，还利用 DIC 结果计算了 "V 形 "锥体行进铰链速度，并讨论了板弯曲刚度和波阻抗对保护性能的影响。研究结果强调了最佳材料配置对减轻压缩波在厚度方向传播和增强弯曲刚度的重要性，这对于在弹道限制范围内提高防护性能至关重要。

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引用次数: 0

Array infrared thermography for visualization of defects in bonded fiber reinforced polymer joints 阵列红外热成像技术用于观察粘接纤维增强聚合物接头中的缺陷

IF 8.3 1区材料科学 Q1 MATERIALS SCIENCE, COMPOSITES

Composites Science and Technology

Pub Date : 2024-10-28 DOI: 10.1016/j.compscitech.2024.110930

Xingxing Zou , Mengyao Li , Hao Xu , Xiaofeng Lu

Fiber reinforced polymer (FRP) is widely used in new and existing structures, however, interfacial defects in the bonded joints pose a significant threat to structural integrity. Therefore, detection of interfacial defects is imperative for ensuring structural safety. This study proposes array infrared thermography (IRT) as a novel non-destructive evaluation method to visualize interfacial defects. Array IRT provides uniform heat excitation within the spatial domain, which overcomes the problem of heat concentration by conventional IRT. Forty-five bonded FRP plate specimens were tested using array IRT, results of which show that interfacial defects can be accurately detected within (8h + 8) s (where h is the thickness of the upper layer of FRP in mm). Array IRT achieves high accuracy in detecting shapes, particularly sharp corners of defects. A pre-processing method was proposed to eliminate the twisted angles of thermal camera and to more clearly show the defects in the thermograms. A database containing tested thermograms and the corresponding predefined defects was established. Intelligent algorithms - UNet, Deeplabv3, and YOLOv8 - were used to segment the defected regions for array IRT analysis, results of which show a precision of 95.8 %, 94.4 %, and 94.1 %, respectively.

纤维增强聚合物（FRP）被广泛应用于新建和现有结构中，然而，粘合接头中的界面缺陷对结构完整性构成了重大威胁。因此，检测界面缺陷对于确保结构安全至关重要。本研究提出阵列红外热成像技术（IRT）作为一种新型的非破坏性评估方法来观察界面缺陷。阵列 IRT 在空间域内提供均匀的热激励，克服了传统 IRT 的热集中问题。使用阵列 IRT 测试了 45 块粘接的玻璃钢板试样，结果表明可在 (8h + 8) 秒内（h 为玻璃钢上层的厚度，单位为毫米）准确检测出界面缺陷。阵列 IRT 对形状，尤其是尖角缺陷的检测精度很高。我们提出了一种预处理方法，以消除热像仪的扭曲角度，并更清晰地显示热图中的缺陷。建立了一个数据库，其中包含测试过的热图和相应的预定义缺陷。使用 UNet、Deeplabv3 和 YOLOv8 等智能算法分割缺陷区域，进行阵列 IRT 分析，结果显示精确度分别为 95.8%、94.4% 和 94.1%。

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引用次数: 0

Efficient property-oriented design of composite layups via controllable latent features using generative VAE 利用生成式 VAE，通过可控潜特征高效设计以属性为导向的复合材料铺层

IF 8.3 1区材料科学 Q1 MATERIALS SCIENCE, COMPOSITES

Composites Science and Technology

Pub Date : 2024-10-28 DOI: 10.1016/j.compscitech.2024.110936

Huaixiang Sun , Xiaodong Wang , Jiaxue Li, Zengshan Li, Zhidong Guan

Fiber-reinforced composites provide substantial tailoring potential, while the extensive parameters and complex coupling mechanisms pose formidable challenges to layup designs. This paper presents an efficient inverse design framework for composite layups utilizing a variational autoencoder (VAE), which is applicable to non-conventional laminates. By leveraging the VAE's exceptional feature extraction and generative capabilities, the decoder rapidly produces layups with desired properties through controllable feature vectors. Based on the stacking characteristics of layups, multi-scale one-dimensional convolutions precisely extract sequence features relevant to mechanical properties and specific manufacturing constraints. A customized loss function is formulated to constrain the latent features, while addressing the non-uniqueness problem for layups with certain mechanical properties. The developed property-oriented VAE can generate 100,000 layups in seconds, achieving an average success rate of 66.9 % under comprehensive in-plane and bending stiffness design, and remains effective for 100-ply thick laminate. For comparison, the VAE model outperforms the genetic algorithm and the logic-based method in reinforced panel designs, reducing the retrieval error by 46.4 % and 38.1 %, respectively. The proposed approach demonstrates flexible and efficient design advantages using generative machine learning models, and is easily extendable to other inverse design scenarios.

纤维增强复合材料具有巨大的定制潜力，但其广泛的参数和复杂的耦合机制给铺层设计带来了严峻的挑战。本文介绍了一种利用变异自动编码器（VAE）进行复合材料层叠的高效反设计框架，该框架适用于非常规层压板。利用 VAE 卓越的特征提取和生成能力，解码器可通过可控特征向量快速生成具有所需特性的层叠结构。根据层叠的堆叠特性，多尺度一维卷积可精确提取与机械特性和特定制造约束相关的序列特征。制定了一个定制的损失函数来约束潜在特征，同时解决了具有特定机械性能的叠层的非唯一性问题。所开发的面向特性的 VAE 可在数秒内生成 100,000 个层叠，在全面的面内和弯曲刚度设计下，平均成功率达到 66.9%，并且对 100 层厚的层压板仍然有效。相比之下，VAE 模型在增强板设计中的表现优于遗传算法和基于逻辑的方法，检索误差分别减少了 46.4% 和 38.1%。所提出的方法利用生成式机器学习模型展示了灵活高效的设计优势，并可轻松扩展到其他逆向设计场景。

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引用次数: 0

Covalently engineering novel sandwich-like rGO@POSS nanofillers for high-performance dielectric energy storage of PVDF film capacitor 共价工程化新型夹层状 rGO@POSS 纳米填料，用于 PVDF 薄膜电容器的高性能电介质储能

IF 8.3 1区材料科学 Q1 MATERIALS SCIENCE, COMPOSITES

Composites Science and Technology

Pub Date : 2024-10-26 DOI: 10.1016/j.compscitech.2024.110938

Hui Liu , Mingming Ding , Xuecheng Chen , Zhaotian Ba , Zhewen Ma , Lili Ma , Xin Wen , Pingan Song , Qingquan Lei

With the development of modern electronic and electrical industry, it is still a great challenge to develop poly(vinylidene fluoride) (PVDF) based dielectric capacitors with high energy storage capability. Herein, a novel sandwich-like nanofiller was constructed via covalently grafting polyhedral oligomeric silsesquioxane onto graphene oxide nanosheets (GO@POSS), further PVDF/rGO@POSS film were fabricated via solvent-casting and in-situ thermal reduction processes. The results indicated that the grafting of POSS promoted the uniform dispersion of nanofillers to realize strong interfacial interaction with PVDF matrix. The optimal PVDF film containing 0.75 wt% rGO@POSS (0.75PGP-60) exhibited larger dielectric constant (ε_r = 13.32) and higher breakdown strength (E_b = 339.1 MV m⁻¹), thus resulting in synchronous improvements on energy density (U_e = 5.42 J·cm⁻³) and charge-discharge efficiency (η = 73.1 %), which increased by 95.0 % and 19.4 % compared to pure PVDF, respectively. Meanwhile, it presented excellent cycling stability with 97.6 % energy density retention after 10000^th cycles. The improved energy storage capability was attributed to reasonably-designed sandwich-like nanofiller: the formation of rGO micro-capacitors raised the dielectric constant of PVDF nanocomposites, while the insulative POSS layer helped to improve its breakdown strength and decrease its dielectric loss. The current work provides a novel and efficient paradigm to design PVDF nanocomposites with promising dielectric properties and energy storage capacity, and further contributes to broadening the practical applications of advanced dielectric capacitors.

随着现代电子电气工业的发展，开发基于聚偏二氟乙烯（PVDF）的高储能电介质电容器仍是一项巨大挑战。本文通过在氧化石墨烯纳米片（GO@POSS）上共价接枝多面体低聚硅倍半氧烷，构建了一种新型的三明治状纳米填料，并进一步通过溶剂浇铸和原位热还原工艺制备了 PVDF/rGO@POSS 薄膜。结果表明，POSS 的接枝促进了纳米填料的均匀分散，实现了与 PVDF 基体的强界面相互作用。含有 0.75 wt% rGO@POSS 的最佳 PVDF 薄膜（0.75PGP-60）表现出更大的介电常数（εr = 13.32）和更高的击穿强度（Eb = 339.1 MV m-1），从而使能量密度（Ue = 5.42 J-cm-3）和充放电效率（η = 73.1 %）同步提高，与纯 PVDF 相比分别提高了 95.0 % 和 19.4 %。同时，它还具有出色的循环稳定性，在循环 10000 次后，能量密度保持率为 97.6%。储能能力的提高归功于合理设计的三明治状纳米填料：rGO 微电容器的形成提高了 PVDF 纳米复合材料的介电常数，而绝缘的 POSS 层则有助于提高其击穿强度并降低介电损耗。目前的研究工作为设计具有良好介电性能和储能能力的 PVDF 纳米复合材料提供了一种新颖、高效的范例，有助于进一步拓宽先进介质电容器的实际应用。

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引用次数: 0

A superhydrophobic Fe3O4@MSN-PDMS based composite coating with icephobicity, long-term durability and self-healing property for anti-/de-icing 一种基于 Fe3O4@MSN-PDMS 的超疏水性复合涂层，具有疏冰性、长期耐久性和自愈性，可用于防/除冰

IF 8.3 1区材料科学 Q1 MATERIALS SCIENCE, COMPOSITES

Composites Science and Technology

Pub Date : 2024-10-26 DOI: 10.1016/j.compscitech.2024.110937

Lechun Deng , Zongwen Wang , Junzhi Wu , Xingshi Gu , Hao Yu , Yang Li , Yaru Cao , Fa Luo , Xianhu Liu , Qiang Chen

Ice formation is a ubiquitous phenomenon in various fields and often leads to catastrophic consequences. Despite numerous anti-icing coating strategies have been exploited, there are still multiple roadblocks in the way of developing anti-icing coatings with durable and effective anti-/de-icing properties. In this work, Fe₃O₄ was coated in-situ with mesoporous silica nanoparticle (MSN), in which a high dosage of polydimethylsiloxane (PDMS) was then loaded. As-obtained core-shelled Fe₃O₄@MSN-PDMS aggregates were incorporated into silicone resin to construct an NIR responsive anti-/de-icing coating via spraying method. The as-prepared coating exhibited superhydrophobicity (156.7° of water contact angle) and delayed icing time to 412 s under −20 °C. Besides, the prepared coating could heat and release PDMS to constitute a PDMS/water double-layer lubricant under NIR irradiation, significantly reducing ice adhesion strength from 90.60 kPa to 12.04 kPa. Furthermore, the prepared coating demonstrates self-healing properties and high durability, releasing PDMS stored in the coating sustainably to heal the damaged coating surface and keeping superhydrophobicity after chemical etching and mechanical erosion. Finally, the de-icing applicability of the coating was validated using a homemade rotor wing model. Such core-shelled anti-/de-icing materials would provide a theoretical basis and a brand-new design strategy for development and application of anti-/de-icing materials.

结冰是各行各业普遍存在的现象，往往会导致灾难性后果。尽管人们已经探索出了许多防冰涂层策略，但在开发具有持久、有效的防冰/除冰性能的防冰涂层的道路上仍有许多障碍。在这项工作中，Fe3O4 与介孔二氧化硅纳米粒子（MSN）进行了原位涂层，然后在其中负载了高剂量的聚二甲基硅氧烷（PDMS）。将获得的核壳 Fe3O4@MSN-PDMS 聚集体加入硅树脂中，通过喷涂方法构建了一种近红外响应型防冰/除冰涂层。所制备的涂层具有超疏水性能（水接触角为 156.7°），在-20 °C条件下可将结冰时间延迟至 412 秒。此外，制备的涂层还能在近红外照射下加热并释放 PDMS，形成 PDMS/ 水双层润滑剂，将冰粘附强度从 90.60 kPa 显著降低到 12.04 kPa。此外，制备的涂层还具有自修复特性和高耐久性，可持续释放涂层中储存的 PDMS 以修复受损涂层表面，并在化学蚀刻和机械侵蚀后保持超疏水性。最后，利用自制的旋翼模型对涂层的除冰适用性进行了验证。这种核壳防除冰材料将为防除冰材料的开发和应用提供理论依据和全新的设计策略。

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引用次数: 0

An improved automatic image labeling and classification algorithm for multi-mode damage quantification of 2.5D woven composites based on deep learning strategy 基于深度学习策略的用于 2.5D 编织复合材料多模式损伤量化的改进型自动图像标记和分类算法

IF 8.3 1区材料科学 Q1 MATERIALS SCIENCE, COMPOSITES

Composites Science and Technology

Pub Date : 2024-10-24 DOI: 10.1016/j.compscitech.2024.110932

Jianhua Zheng , Kun Qian , Xiaodong Liu , Zengyuan Pang , Zhengyan Yang , Jin Sun , Diantang Zhang

Accurately identifying and quantifying the complex multi-mode damages in woven composites is of vital importance to evaluate the service life and improve reliability of the components. However, the current advanced methods based on the deep learning framework remain mainly the manual labeling, resulting in unclear fiber/resin interfaces, easily-overlooked microcracks, and lower efficiency. To overcome the problem, this paper proposes an improved automatic image labeling and classification algorithm based on deep learning strategy to quantify the uncertainty damages of 2.5D woven composites. In detail, the original micro-computed tomography (CT) images are automatically labeled by an image algorithm that utilizes grayscale values and image boundaries to produce image datasets. Subsequently, the DCNN model is trained using the image datasets. Then, the trained deep convolutional neural networks (DCNN) model is used to identify unseen CT images and separate the damage and different sub-phases of 2.5D woven composites. Finally, the connected component analysis is introduced to classify the global cracks at the meso-scale. The results show that the proposed automatic image labeling and classification algorithm can achieve a damage identification precision of 85.87 %, surpassing that of other models. Moreover, the multi-mode damages of 2.5D woven composites are accurately captured. In the warp direction, the bending damage accumulation predominantly manifests as interface debonding, representing 51.93 % of the damage percentage. In the weft direction, it is primarily characterized by matrix cracking, representing 60.98 % of the damage percentage. It is expected that the study can provide data support for the application of large-scale and complex structural components.

准确识别和量化编织复合材料中复杂的多模损伤对于评估组件的使用寿命和提高可靠性至关重要。然而，目前基于深度学习框架的先进方法仍以人工标注为主，导致纤维/树脂界面不清晰、微裂纹易被忽略、效率较低。为了克服这一问题，本文提出了一种基于深度学习策略的改进型自动图像标注和分类算法，用于量化 2.5D 编织复合材料的不确定性损伤。具体来说，利用灰度值和图像边界生成图像数据集的图像算法对原始微型计算机断层扫描（CT）图像进行自动标注。随后，利用图像数据集训练 DCNN 模型。然后，使用训练好的深度卷积神经网络（DCNN）模型来识别未见过的 CT 图像，并分离 2.5D 编织复合材料的损伤和不同子阶段。最后，引入连通成分分析法对中观尺度的全局裂纹进行分类。结果表明，所提出的自动图像标注和分类算法的损伤识别精度可达 85.87%，超过了其他模型。此外，还准确捕捉到了 2.5D 编织复合材料的多模式损伤。在经向，弯曲损伤累积主要表现为界面脱粘，占损伤百分比的 51.93%。在纬向，主要表现为基体开裂，占损伤百分比的 60.98%。该研究有望为大型复杂结构部件的应用提供数据支持。

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引用次数: 0

Layer-by-layer assembling boron nitride/polyethyleneimine/MXene hierarchical sandwich structure onto basalt fibers for high-performance epoxy composites 在玄武岩纤维上逐层装配氮化硼/聚乙烯亚胺/二甲苯分层夹层结构，以制造高性能环氧树脂复合材料

IF 8.3 1区材料科学 Q1 MATERIALS SCIENCE, COMPOSITES

Composites Science and Technology

Pub Date : 2024-10-24 DOI: 10.1016/j.compscitech.2024.110931

Ying Yu , Shaolong Han , Haoyu Wang , Gang Wei , Zheng Gu , Ping Han

Interfacial adhesion directly affects the mechanical properties of basalt fiber (BF)-reinforced polymer composites. To construct a more superior interphase between BFs and epoxy resin (EP) than a weak interphase of the unmodified BF/EP, we propose a hierarchical sandwich structure consisting of sodium hydroxide–activated boron nitride (BN_OH), polyethyleneimine (PEI), and MXene (MX, Ti₃C₂T_x) through facile layer-by-layer self-assembly. The fabricated BN_OH/P/MX sandwich structure (P denoting “PEI”) can synergistically improve the interface adhesion by enhancing the mechanical interlocking and chemical bonding of the composites. When the composites reinforced by BF–BN_OH/P/MX subject to the external loading, flexible PEI molecules allow two-dimensional (2D) rigid BN_OH and MX nanosheets to slip at the interface by uncurling the molecular chains, dissipating a great amount of energy during the fracture progress. Meanwhile, the hierarchical BN_OH/P/MX sandwich structure acts as an excellent interface and possesses multistage gradient modulus and wider thickness, uniformly and efficiently transferring the stress from the EP matrix to BFs. The interfacial shear strength, impact strength, and fracture toughness of BF–BN_OH/P/MX-reinforced EP composite are substantially improved by 45.9 %, 60.6 %, and 148.9 %, respectively, compared with bare BF–based composites. This study can provide valuable references and inspirations for designing and constructing high-quality interfaces for high-strength and high-toughness BF structural materials, taking advantage of 2D materials.

界面粘附力直接影响玄武岩纤维（BF）增强聚合物复合材料的机械性能。为了在玄武岩纤维和环氧树脂（EP）之间构建比未经改性的玄武岩纤维/EP弱界面更优越的界面，我们提出了一种分层夹层结构，该结构由氢氧化钠活化的氮化硼（BNOH）、聚乙烯亚胺（PEI）和MXene（MX，Ti3C2Tx）通过简单的逐层自组装组成。制成的 BNOH/P/MX 夹层结构（P 表示 "PEI"）可通过增强复合材料的机械互锁和化学键合来协同改善界面粘附性。当 BF-BNOH/P/MX 增强复合材料受到外部载荷作用时，柔性 PEI 分子允许二维（2D）刚性 BNOH 和 MX 纳米片通过松开分子链在界面上滑动，从而在断裂过程中耗散大量能量。同时，分层 BNOH/P/MX 夹层结构作为一种优异的界面，具有多级梯度模量和更宽的厚度，能均匀有效地将应力从 EP 基体传递到 BFs。与裸 BF 基复合材料相比，BF-BNOH/P/MX 增强 EP 复合材料的界面剪切强度、冲击强度和断裂韧性分别大幅提高了 45.9%、60.6% 和 148.9%。该研究可为利用二维材料优势设计和构建高强度、高韧性 BF 结构材料的高质量界面提供有价值的参考和启示。

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