Preparation and the properties of PMR‐type polyimide composites with aluminum nitride

Wang, Jiajun; Yi, Xiaosu

doi:10.1002/app.12618

Cited by 57 publications

(46 citation statements)

References 29 publications

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“…The measurement data of AlN/PI composite were from ref. Wang and Yi (2003). It can be observed from Fig.…”

Section: Resultsmentioning

confidence: 50%

“…As for these structures, the corresponding filler volume percentage is a fixed value at each case, among which the FCC structure possesses the highest one, i.e., 0.7405 (Agari et al 1990). On the other hand, experimental data showed that the volume percentages of fillers can be fairly high, e.g., *65% (Wang and Yi 2003). In order to reflect the close-packed distribution of filler particles, the FCC structure was chosen as the elementary cell in the filler arrangement in the present model, as shown in Fig.1a.…”

Section: Modelingmentioning

confidence: 99%

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Modeling of the effective thermal conductivity of composite materials with FEM based on resistor networks approach

Zhang

et al. 2010

Microsyst Technol

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In the present paper, a novel and efficient model was developed for predicting the effective thermal conductivity of the composite materials at different filler percentages. By introducing the relative radius as a parameter, the effective thermal conductivity can be predicted precisely when the thermal properties of filler and matrix are prescribed. The model employed the resistor network strategy to achieve a highly efficient prediction during the overall conductivity calculation. To verify this model, a wide range of two-phase composites, including Cu/PP, AlN/PI and a self-developed thermal conductive adhesive, were analyzed. The model-based simulation values showed good agreement with the experimental results. Moreover, a discussion on the effects of the newlyintroduced parameter was given. Finally, the relationship between the filler radius variation and the thermal conductivity of the composite was studied.

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“…The measurement data of AlN/PI composite were from ref. Wang and Yi (2003). It can be observed from Fig.…”

Section: Resultsmentioning

confidence: 50%

Section: Modelingmentioning

confidence: 99%

Modeling of the effective thermal conductivity of composite materials with FEM based on resistor networks approach

Zhang

et al. 2010

Microsyst Technol

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“…There are also other models to obtain the thermal conductivity, such as the Maxwell-Eucken equation (EMT) (Nielsen 1974), the Nelsen model (Davis and Artz 1995), the effective unit cell model (EUCM) (Ganapathy et al 2005), and the percolation model (Devpura and Phelan 2000). Numerical studies and experimental measurement on the thermal conductivities of the composite materials of different matrix and filler materials (Falat et al 2007a, b;Wang and Yi 2003;Bounenne et al 2005) as well as the filler volume fractions (Agari et al 1990) have also been conducted.…”

Section: Introductionmentioning

confidence: 98%

Study on the bimodal filler influence on the effective thermal conductivity of thermal conductive adhesive

Zhang

Fan

et al. 2010

Microsyst Technol

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The thermal management for electronics systems becomes more crucial to the overall system performance as the packaging density becomes much higher and the IC power increases at the same time. Thermal conductive adhesives (TCAs) have been widely adopted in electronics systems. As an epoxy matrix with conductive fillers, it is essential to figure out the effective thermal conductivity of this composite material. In the present paper, a parameterized cubic cell model (CCM) is developed and then implemented by the finite element method to investigate the effects of the bimodal fillers on the effective thermal conductivity. In addition, a series of bimodal TCA samples are prepared and the thermal conductivities in the in-plane and vertical directions are measured experimentally. An obvious anisotropy with respect to the thermal conductivities has been observed for the bimodal filler loading under consideration. A good agreement between the numerical results and the experimental data is obtained.

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“…Aluminum nitride exhibits excellent thermal conductivity, good electrical insulation characteristics and a coefficient of thermal expansion closely matching that of silicon in the temperature range of 20-200°C, which make it become a promising substrate and package material [1][2][3]. However, the use of AlN in the micro-electronics industry has been severely constrained because of several inherent impediments.…”

Section: Introductionmentioning

confidence: 99%

Effects of rare earth oxide additives on the thermal behaviors of aluminum nitride ceramics

et al. 2009

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The effects of Y 2 O 3 and Er 2 O 3 on the sintering behaviors, thermal properties and microstructure of AlN ceramics were investigated. The experimental results show that the sintering temperature can be decreased; the relative density and thermal behavior can be improved by adding rare earth oxide in AlN ceramics. For AlN ceramics with 3 wt.% Er 2 O 3 additive, the relative density is 98.8%, and the thermal conductivity reaches 106 W·m −1 ·K −1 . The microstructure research found that no obvious aluminum erbium oxide was found in AlN ceramics doped with 3 wt.% Er 2 O 3 , which favored the improvement of the thermal conductivity of AlN ceramics.

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Preparation and the properties of PMR‐type polyimide composites with aluminum nitride

Cited by 57 publications

References 29 publications

Modeling of the effective thermal conductivity of composite materials with FEM based on resistor networks approach

Modeling of the effective thermal conductivity of composite materials with FEM based on resistor networks approach

Study on the bimodal filler influence on the effective thermal conductivity of thermal conductive adhesive

Effects of rare earth oxide additives on the thermal behaviors of aluminum nitride ceramics

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