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The highly thermally conductive yet electrically insulating polymeric materials are exhibiting tremendous potential for thermal management materials. However, the practical application of these materials is restrained by the limited thermal conductivity (TC) and deterioration of mechanical properties. In this work, an ultraflexible polyamide-imide (PAI) film with a sandwich-like structure composed with assembled well-oriented functionalized boron nitride nanosheets (FBN) by facile layer-by-layer solution-coating strategy is constructed. The design of the layered structure and highly oriented arrangement of interconnected FBN (Herman's orientation parameter ƒ up to 0.847) endows the obtained PAI composite film with super-flexibility, ultrahigh in-plane thermal conductivity (λ //), superior thermal transfer capability (ΔT max = 24.4 °C) and excellent electrical insulation performance. The PBP composite film reaches an ultrahigh λ // of 45.7 W m−1 K−1 with only 23 wt% FBN loading and exhibits a remarkable TC enhancement factor over 23 because of the more continuous phonon transfer networks that constructed by interconnected well-oriented FBN which could effectively suppress the phonon scattering. Furthermore, the mechanical properties of the layered composite film (PB4P) exhibit noteworthy enhancement compared with uniform PBN composite film, in which the tensile strength is increased by 110% and toughness enhancement is 329%. Meaningfully, our fabrication strategy has the advantage of simplicity and adaptability for commercial amplification. The composite film developed in this work provides a promising prospect for the thermal management system of modern power electronic devices. [Display omitted] [ABSTRACT FROM AUTHOR]

Carbon-based polymer composites with excellent thermal conductivity are highly desired in thermal management materials. However, the thermal conductivity enhancement of carbon-based polymer composites is limited, which are mostly caused by defects of fillers, unsatisfactory distribution and inferior interface between carbon fillers and matrix. Herein, we prepared polyamide composites with three-dimensional (3D) vertically aligned carbon network. The vertically aligned structure demonstrates a through-plane thermal conductivity up to 1.45 W m−1 K−1 at 5.2 wt% carbon fillers content, which is 644% higher than that of matrix. Moreover, through the regulated surface modification of carbon fillers, the carbon fiber with lower defect density and improved interfacial compatibility were obtained. The vertically aligned structure could take advantage of the intrinsic properties of carbon fillers and effectively reduce thermal contact resistance. The fabricated polyamide composites could be employed to dissipate excessive heat in thermal management system, and effectively reduce the working temperature of CPU. The design principles and preparation techniques in this work could also be applied to other carbon-based composites to surmount difficulties in effective thermal management of modern electronics. [ABSTRACT FROM AUTHOR]

Chemical functionalization of boron nitride (BN) is necessary to improve the dispersion of the BN as well as interface compatibility within polymer matrix to enhance the properties of their composites. However, the degree of BN functionalization needs to be considered comprehensively to fully highlight the advantages. In the present work, a polyamide-imide (PAI) film with a parallel arrangement structure and designed functionalization of BN nanosheets by self-assembly technique is constructed. The design of optimum functionalization and defect control of the functionalized BN nanosheets (f-BNNSs) provides this flexible PAI/f-BNNSs composite film exhibits highly in-plane thermal conductivity, superior electrically insulating and improved mechanical properties. The thermal conductivity of the PAI/f-BNNSs film had an impressive improvement of 167%, from 5.06 W m−1 K−1 of PAI/BN film to 13.5 W m−1 K−1 of PAI/f-BNNSs film (PP1W3) at a low filler content of only 9 wt%. More importantly, systematic research was carried out in terms of the degree of functionalization, the quantities of defect of f-BNNSs and the performance of the composite films, which further revealed the mechanism of the thermal conductivity improvement of PAI/f-BNNSs composite films. This research provides significant guidance for the design of composite materials with excellent thermal conductivity based on the functionalization of low dimensional fillers, ensuring its application in the thermal management of high-power density electronic devices. [Display omitted] [ABSTRACT FROM AUTHOR]

Thermal conductive and electrical insulating polymer composites are showing tremendous potential for modern electrical systems and electronic devices. Melt blending has been utilized as an effective technique to prepare thermal interface materials. However, during the process of melt-blending, strong π-π stacking and particle aggregation may be caused by thermal heating and local mechanical stress. Herein, ISP-PA6/BNNSs-OH (ISP-PN) composite has been fabricated by a masterbatch obtained via in-situ polymerization (ISP) and melt blending with polyamide-6 (PA6), with the incorporation of hydroxylated boron nitride nanosheets (BNNSs-OH). At the filler loading of 10 wt%, the through-plane thermal conductivity (TC) and Young's modulus of ISP-PN composites are respectively increased by 163% and 118%, compared to that of the neat PA6 resin. Prevailing over the matrix, the ISP-PN composites own volume electrical resistivity of ~5.11 × 1019 Ω cm. Meanwhile, the TC and mechanical properties of ISP-PN composites are 21.4% and 28.0% higher than the composites obtained by direct melt blending. The improved properties are attributed to the pre-disperse of filler through the masterbatch method. The PA6 chains were immobilized onto the BNNSs-OH by the condensation reaction, resulting in a sort of "chain-extender" and preventing the filler from re-aggregating during the process of melt-blending. This study pioneers a simple and versatile path to melt blending of thermally conductive polymer composites with good mechanical and electrical insulation properties in high-performance thermal management systems. [ABSTRACT FROM AUTHOR]

Thermal conductive polymer matrix composites are becoming more widely used in modern electronic devices. However, the dispersion of the filler in the composite material limits the improvement of its heat dissipation performance. In order to solve the problem, we prepared polyamide-imide composites with three-dimensional (3D) carbon fiber-graphene network. The network is built by braided frame of carbon fiber felt and the hydrogen bonding between carbon fiber and graphene oxide. When the amount of filler is 4.25 wt%, the vertical thermal conductivity (TC) of composites reaches 0.53 W m−1 K−1, which is 165% higher than that of pure PAI. The improvement of TC is mainly attributed to the following factors, for example, 1) the 3D carbon fiber-graphene network structure was established to construct the heat conduction path in the composite material; 2) the interaction between fillers reduced contact thermal resistance; 3) the introduction of oxygen-containing functional groups adversely affected the TC of the composite. Meanwhile, the tensile strength of the composites reaches 34.1 MPa and the Young's modulus is 1.2 GPa. The composites can be used as a heat sink for next-generation electronic devices. Polyamide-imide composites are fabricated using three-dimensional (3D) carbon fiber-graphene network. The network is built by braided frame of carbon fiber felt and the hydrogen bonding between carbon fiber and graphene oxide. When the amount of filler is 4.25 wt%, the vertical thermal conductivity (TC) of composites reaches 0.53 W m−1 K−1, which is 165% higher than that of pure PAI. Image 1 [ABSTRACT FROM AUTHOR]

Emerging structural materials for aerospace deformable structures, soft robotics, and advanced smart electronic devices necessitate reversible, lockable, and reprogrammable shape transformation capabilities. A challenge in this realm is heat accumulation in high-power density devices, which limited impedes broader applications of these materials. This study introduces magneto-thermal coupling response and efficient heat dissipation to structural composite, facilitating reversible and reprogrammable material deformation. Our composites prepared using bi-directional freeze casting strategy demonstrated excellent thermal management capabilities. When the composites were applied to the chip heat dissipation, the chip temperature was significantly reduced by 36.3 °C from 112.2 °C. Furthermore, the integration of a flexible boron nitride nanosheets (BNNS)/carbon fibers (CFs) network with magnetic Fe 3 O 4 particles and phase-change material enables effective magneto-thermal response. This magnetically controlled thermal deformation behavior of composites provides a promising avenue for the development of multimodal morphing structures for soft robotics and aerospace applications. [ABSTRACT FROM AUTHOR]

Polymeric composites with excellent thermal conductivity are in high demand in modern electronics because of their need for efficient heat dissipation. Whereas, the thermally conductive polymeric composites usually be limited by the insufficient effectiveness of the thermally conductive pathway, at the cost of high filler content and deterioration of mechanical strength. At the same time, they lack multi-functionality. Here, we reported advanced thermoresponsive polymeric composites containing a three-dimensional interconnected boron nitride (BN) network, which simultaneously displayed high thermal conductivity enhancement, thermal transfer performance, improved shape memory, and mechanical properties. Manufactured composites on the basis of commercial polyurethane sponges which were modified by polydopamine and coated with BN through dip-coating assemble method and the subsequent vacuum infiltration. The composites exhibit 2.4 W•m−1•K−1 with 17.5 wt% BN loading, and the through-plane thermal conductivity enhancement reaches 1100%. Furthermore, the mechanical properties of the composites have improved four times compared with pure polyethylene glycol. The obtained composites demonstrate the strong application in thermal management and were simulated in the CPU of the computer. Our fabrication provides a promising strategy to achieve multi-functional polymeric composites through constructing a three-dimensional thermally conductive pathway. [Display omitted] • The composites with 17.5 wt% BN exhibits excellent TC enhancement of 1100%. • The mechanical properties of the composites have improved 4 times. • The composites show application in thermal management which could comparable to Cu. • The composites show combined enhanced TC, mechanical and shape memory properties. [ABSTRACT FROM AUTHOR]

• The PFRB structure is constructed to enhance feature learning by adaptively selecting the number of PFRBs according to the data characteristics. • An attention mechanism is introduced to focus on the fault features extracted by PFRBs. Different attention values are assigned to the identified fault features and noise. Due to the difficulty of fault feature extraction and low accuracy of pattern recognition in fault diagnosis of gearboxes, a differential continuous wavelet transform-parallel multi-block fusion residual network fault diagnosis method is proposed. The signal is subjected to continuous wavelet transform after the first-order difference, which can effectively improve the resolution of the time–frequency feature images. The parallel fusion residual block (PFRB) is constructed, and the number of PFRBs can be selected adaptively based on the data features, thus enhancing the learning capability of the features. An attentional feature fusion layer is designed. This layer locates the fault features extracted by the previous layer through the attention mechanism. Through the feature fusion mechanism, the effective fault information is fused to achieve feature augmentation inside the network. The experimental results show that the proposed method has superior diagnostic performance compared with other methods in bearing and gearbox gear faults. [ABSTRACT FROM AUTHOR]

• Generative adversarial networks has strong ability of generation, diagnosis and classification for small sample fault data of wind turbine. • A weak learner is built to optimize the generator gradient by Gradient Boosting. • K-Nearest Neighbor algorithm makes the decision of fault boundary more complete and the measurement of Mahalanobis distance more accurate. • The fault scoring mechanism of Two-stream convolutional networks architecture is implemented to determine the fault type through fusion scoring. Fault diagnosis of gearbox in engineering can effectively improve operational efficiency and reduce maintenance costs. In this paper, a small sample diagnosis method based on improved generative adversarial networks is proposed. Firstly, the Gradient Boosting is used to optimize the iteration strategy of the generator, the deep learning efficiency is optimized by establishing the weak learner. Then, the decision boundary of fault samples is established by the K-Nearest Neighbor algorithm, the distribution of probability space is measured by Mahalanobis distance continuity. Finally, fault classification and diagnosis are achieved by scoring and fusing fault data with two-stream convolutional networks. The effectiveness of the proposed method is verified by comparison and analysis of experiments. The results showed that the proposed method has higher diagnosis accuracy and classification accuracy in the small sample set fault diagnosis of wind turbine gearbox, and also has better performance in fault generation and strengthening. [ABSTRACT FROM AUTHOR]

The side chains of a molecule affect the molecular packing and crystallinity which are crucial factors determining the photovoltaic properties in organic solar cells (OSCs). In this work, two small molecule donors, BDT(X1) and BDT(X2), with identical backbone and slightly different side chains on the end groups have been designed and synthesized. Compared with BDT(X1) with linear alkyl chain, BDT(X2) featuring a branched alkyl chain in the terminal groups has larger steric hindrance and exhibits weaker crystallinity and less compact molecule stacking. Application of the two small molecule donors in OSCs shows that BDT(X1) is more suitable for IDIC, a non-fullerene acceptor, while BDT(X2) demonstrates higher OSC performance when blended with fullerene acceptor PC 71 BM. Morphology and grazing-incidence wide-angle X-ray scattering (GIWAXS) studies reveal that crystallinity plays a key role in determining the molecular packing and phase separation with fullerene/non-fullerene acceptors which in turn influence the charge transport and photovoltaic properties. Our results provide some guidance on selection of acceptors for a given donor and demonstrate the importance of fine tuning of the crystallinity in small molecule OSCs. Image 1 • To enhance or to decrease the crystallinity of a donor is acceptor dependent. • Subtle side chain modification generates obvious crystallinity difference. • Matched donor and acceptor crystallinity provides higher OSC performance. [ABSTRACT FROM AUTHOR]