Optimization of Effective Thermal Conductivity of Thermal Interface Materials Based on the Genetic Algorithm-Driven Random Thermal Network Model

Functionalization of Graphene by Interfacial Engineering in Thermally Conductive Nanofibrillated Cellulose Films

Flexible nanocomposites incorporating nanofibrillated cellulose (NFC) hold significant promise for thermal management applications. However, their heat dissipation performance is primarily constrained by the interfacial thermal resistance (Rbd). In this work, 1-pyrenemethylamine hydrochloride (PyNH2) noncovalent functionalized graphene subsequently self-assembled with NFC through a vacuum-assisted filtration technique. PyNH2 could not only stabilize graphene with π-π conjugation but also interact with NFC via hydrogen bonding. The prepared layered-structure nanocomposites achieve a thermal conductivity of 11.32 W·m-1·K-1 with a low filler content of just 5 wt %. Utilizing the effective medium approximation (EMA) method and two-dimensional X-ray scattering techniques, we know that this satisfactory thermal conductivity is mainly attributed to pyrene functionalization of graphene by interfacial engineering-induced low Rbd and high orientation degree of graphene. Undoubtedly, this study provides experimental and theoretical guide for fabrication of thermal conductive nanocomposites in the near future.

Inverse Identification and Design of Thermal Parameters of Woven Composites through a Particle Swarm Optimization Method

Designing thermal conductivity efficiently is one of the most important study fields for taking the advantages of woven composites. This paper presents an inverse method for the thermal conductivity design of woven composite materials. Based on the multi-scale structure characteristics of woven composites, a multi-scale model of inversing heat conduction coefficient of fibers is established, including a macroscale composite model, mesoscale fiber yarn model, microscale fiber and matrix model. In order to improve computational efficiency, the particle swarm optimization (PSO) algorithm and locally exact homogenization theory (LEHT) are utilized. LEHT is an efficient analytical method for heat conduction analysis. It does not require meshing and preprocessing but obtains analytical expressions of internal temperature and heat flow of materials by solving heat differential equations and combined with Fourier's formula, relevant thermal conductivity parameters can be obtained. The proposed method is based on the idea of optimum design ideology of material parameters from top to bottom. The optimized parameters of components need to be designed hierarchically, including: (1) combing theoretical model with the particle swarm optimization algorithm at the macroscale to inverse parameters of yarn; (2) combining LEHT with the particle swarm optimization algorithm at the mesoscale to inverse original fiber parameters. To identify the validation of the proposed method, the present results are compared with given definite value, which can be seen that they have a good agreement with errors less than 1%. The proposed optimization method could effectively design thermal conductivity parameters and volume fraction for all components of woven composites.

Synchronously improved thermal conductivity and dielectric constant for epoxy composites by introducing functionalized silicon carbide nanoparticles and boron nitride microspheres

Polymer-based dielectrics with high thermal conductivity and superb dielectric properties hold great promising for advanced electronic packaging and thermal management application. However, integrating these properties into a single material remains challenging due to their mutually exclusive physical connotations. Here, an ideal dielectric thermally conductive epoxy composite is successfully prepared by incorporating multiscale hybrid fillers of boron nitride microsphere (BNMS) and silicon dioxide coated silicon carbide nanoparticles (SiC@SiO₂). In the resultant composites, the microscale BNMS serve as the principal building blocks to establish the thermally conductive network, while the nanoscale SiC@SiO₂ as bridges to optimize the heat transfer and suppress the interfacial phonon scattering. In addition, the special core-shell nanoarchitecture of SiC@SiO₂ can significantly impede the leakage current and generate a great deal of minicapacitors in the composites. Consequently, favorable thermal conductivity (0.76 W/mK) and dielectric constant (∼8.19) are simultaneously achieved in the BNMS/SiC@SiO₂/Epoxy composites without compromising the dielectric loss (∼0.022). The strategy described in this study provides important insights into the design of high-performance dielectric composites by capitalizing on the merits of different particles.

A Novel Branched Al2O3/Silicon Rubber Composite with Improved Thermal Conductivity and Excellent Electrical Insulation Performance

In this paper, we report a thermal conductive polymer composite that consists of silicone rubber (SR) and branched Al₂O₃ (B-Al₂O₃). Owing to the unique two-dimensional branched structure, B-Al₂O₃ particles form a continuous three-dimensional network structure by overlapping each other in the matrix, serving as a continuous heat conductive pathway. As a result, the polymer composite with a 70 wt% filler achieves a maximum thermal conductivity of 1.242 Wm⁻¹ K⁻¹, which is equivalent to a significant enhancement of 521% compared to that of a pure matrix. In addition, the composite maintains a high volume resistivity of 7.94 × 10¹⁴ Ω·cm with the loading of 70 wt%, indicating that it meets the requirements in the field of electrical insulation. Moreover, B-Al₂O₃ fillers are well dispersed (no large agglomerates) and form a strong interfacial adhesion with the matrix. Therefore, the thermal decomposition temperature, residual mass, tensile strength, modulus and modulus of toughness of composites are significantly improved simultaneously. This strategy provides new insights for the design of high-performance polymer composites with potential application in advanced thermal management in modern electronics.