scholarly journals Thermal Transport in Polymers: A Review

2021 ◽  
Author(s):  
Xingfei Wei ◽  
Zhi Wang ◽  
Zhiting Tian ◽  
Tengfei Luo
Keyword(s):  
Thermal Conductivity ◽  
Structural Property ◽  
Thermal Transport ◽  
Large Scale ◽  
Applied Research ◽  
Amorphous Polymers ◽  
High Thermal Conductivity ◽  
Molecular Alignments ◽  
Amorphous States ◽  
Engineering Polymers

Abstract In this article, we review thermal transport in polymers with different morphologies from aligned fibers to bulk amorphous states. We survey early and recent efforts in engineering polymers with high thermal conductivity by fabricating polymers with large-scale molecular alignments. The experimentally realized extremely high thermal conductivity of polymer nanofibers are highlighted, and understanding of thermal transport physics from molecular simulations are discussed. We then transition to the discussion of bulk amorphous polymers with an emphasize on the physics of thermal transport and its relation with the conformation of molecular chains in polymers. We also discuss the current understanding of how the chemistry of polymers would influence thermal transport in amorphous polymers and some limited, but important chemistry-structural-property relationships. Lastly, challenges, perspectives and outlook of this field are presented. We hope this review will inspire more fundamental and applied research in the polymer thermal transport field to advance scientific understanding and engineering applications.

Thermal Transport in Nanocrystalline Materials

2005 ◽  
Author(s):  
Zhanrong Zhong ◽  
Xinwei Wang
Keyword(s):  
Thermal Conductivity ◽  
Specific Heat ◽  
Thermal Transport ◽  
Nanocrystalline Materials ◽  
Large Scale ◽  
Md Simulation ◽  
Fundamental Physics ◽  
Grain Sizes ◽  
Simulation Results ◽  
Thermal Phenomena

In this work, thermal transport in nanocrystalline materials is studied using large-scale equilibrium molecular dynamics (MD) simulation. Nanocrystalline materials with different grain sizes are studied to explore how and to what extent the size of nanograins affects the thermal conductivity and specific heat. Substantial thermal conductivity reduction is observed and the reduction is stronger for nanocrystalline materials with smaller grains. On the other hand, the specific heat of nanocrystalline materials shows little change with the grain size. The simulation results are compared with the thermal transport in individual nanograins based on MD simulation. Further discussions are provided to explain the fundamental physics behind the observed thermal phenomena in this work.

Monolayer and bilayer polyaniline C3N: two-dimensional semiconductors with high thermal conductivity

Nanoscale ◽  
2018 ◽  
Vol 10 (9) ◽  
pp. 4301-4310 ◽  
Author(s):  
Yang Hong ◽  
Jingchao Zhang ◽  
Xiao Cheng Zeng
Keyword(s):  
Thermal Conductivity ◽  
Thermal Transport ◽  
Md Simulation ◽  
Transport Processes ◽  
High Thermal Conductivity ◽  
Two Dimensional

Lateral and flexural thermal transport processes in monolayer and bilayer C3N are systematically investigated using MD simulation.

scholarly journals High thermal conductivity in electrostatically engineered amorphous polymers

2017 ◽  
Vol 3 (7) ◽  
pp. e1700342 ◽  
Author(s):  
Apoorv Shanker ◽  
Chen Li ◽  
Gun-Ho Kim ◽  
David Gidley ◽  
Kevin P. Pipe ◽  
...  
Keyword(s):  
Thermal Conductivity ◽  
Amorphous Polymers ◽  
High Thermal Conductivity

Effect of Colloidal Chemistry on the Thermal Conductivity of Nanofluids

2006 ◽  
Author(s):  
Ravi Prasher
Keyword(s):  
Experimental Data ◽  
Thermal Conductivity ◽  
Surface Chemistry ◽  
Thermal Transport ◽  
High Thermal Conductivity ◽  
Aggregation Kinetics ◽  
Effect Of Ph ◽  
Colloidal Chemistry ◽  
The World ◽  
Increasing Temperature

Nanofluids have attracted tremendous attention lately due to their promise as high thermal conductivity liquid and also due the inability of researchers all across the world in explaining the enhancement in the thermal conductivity. Various models and physics have been proposed and some of them have been quite successful in explaining the data, however none of the models in the literature take colloidal chemistry into account. Experimental data, however have shown dependence of thermal conductivity on pH and surface chemistry. In this paper we introduce a model which captures all the anomalies reported in the data 1) Effect of pH 2) effect of aging i.e. time 3) maxima in the thermal conductivity with respect to the diameter of the nanoparticles 4) increase and decrease in the ratio of the thermal conductivity of the nanofluids and the base fluids with increasing temperature. The model is based on the combination of aggregation kinetics with the physics of thermal transport.

scholarly journals Generation of Self-Assembled 3D Network in TPU by Insertion of Al2O3/h-BN Hybrid for Thermal Conductivity Enhancement

Materials ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 238
Author(s):  
Kai-Han Su ◽  
Cherng-Yuh Su ◽  
Po-Wei Chi ◽  
Prem Chandan ◽  
Cheng-Ta Cho ◽  
...  
Keyword(s):  
Thermal Conductivity ◽  
Composite Material ◽  
Hot Pressing ◽  
Large Scale ◽  
Hexagonal Boron Nitride ◽  
High Thermal Conductivity ◽  
Melt Mixing ◽  
Conductive Composite ◽  
3D Network ◽  
Thermally Conductive

Thermal management has become one of the crucial factors in designing electronic equipment and therefore creating composites with high thermal conductivity is necessary. In this work, a new insight on hybrid filler strategy is proposed to enhance the thermal conductivity in Thermoplastic polyurethanes (TPU). Firstly, spherical aluminium oxide/hexagonal boron nitride (ABN) functional hybrid fillers are synthesized by the spray drying process. Then, ABN/TPU thermally conductive composite material is produced by melt mixing and hot pressing. Then, ABN/TPU thermally conductive composite material is produced by melt mixing and hot pressing. Our results demonstrate that the incorporation of spherical hybrid ABN filler assists in the formation of a three-dimensional continuous heat conduction structure that enhances the thermal conductivity of the neat thermoplastic TPU matrix. Hence, we present a valuable method for preparing the thermal interface materials (TIMs) with high thermal conductivity, and this method can also be applied to large-scale manufacturing.

Chain length effect on thermal transport in amorphous polymers and a structure–thermal conductivity relation

2019 ◽  
Vol 21 (28) ◽  
pp. 15523-15530 ◽  
Author(s):  
Xingfei Wei ◽  
Tengfei Luo
Keyword(s):  
Thermal Conductivity ◽  
Chain Length ◽  
Thermal Transport ◽  
Heat Exchangers ◽  
Amorphous Polymers ◽  
Electronics Packaging ◽  
Length Effect

The physics of thermal transport in polymers is important in many applications, such as in heat exchangers and electronics packaging.

scholarly journals Rapid Prediction of Anisotropic Lattice Thermal Conductivity: Application to Layered Materials

2018 ◽  
Author(s):  
Robert McKinney ◽  
Prashun Gorai ◽  
Eric S. Toberer ◽  
Vladan Stevanovic
Keyword(s):  
Thermal Conductivity ◽  
Speed Of Sound ◽  
Thermal Transport ◽  
Large Scale ◽  
Lattice Thermal Conductivity ◽  
Layered Materials ◽  
Layered Structures ◽  
Polycrystalline Materials ◽  
Anisotropic Lattice ◽  
Average Factor

<div> <div> <div> <p>Thermal conductivity plays a crucial role in many applications; use of single-crystal and textured polycrystalline materials in such applications necessitate understanding the anisotropy in thermal transport. Measurement of anisotropic lattice thermal conductivity is quite challenging. To address this need through computations, we build upon our previously developed isotropic model for <i>k<sub>L</sub></i> and incorporate the directional (angular) dependence by using the elastic tensor obtained from <i>ab initio</i> calculations and the Christoffel equations for speed of sound. With the anisotropic speed of sound and intrinsic material properties as input parameters, we can predict the direction-dependent <i>k<sub>L</sub></i>. We validate this new model by comparing with experimental data from the literature – predicted <i>k<sub>L</sub></i> is within an average factor difference of 1.8 of experimental measurements, spanning 5 orders of magnitude in <i>k<sub>L</sub></i>. To demonstrate the utility and computational-tractability of this model, we calculate <i>k<sub>L </sub></i>of ~2200 layered materials that are expected to exhibit anisotropic thermal transport. We consider both van der Waals and ionic layered structures with binary and ternary chemistries and analyze the anisotropy in their <i>k<sub>L</sub></i>. The large-scale study has revealed many layered structures with interesting anisotropy in <i>k<sub>L</sub></i>.</p> </div> </div> </div>

scholarly journals Rapid Prediction of Anisotropic Lattice Thermal Conductivity: Application to Layered Materials

2018 ◽  
Author(s):  
Robert McKinney ◽  
Prashun Gorai ◽  
Eric S. Toberer ◽  
Vladan Stevanovic
Keyword(s):  
Thermal Conductivity ◽  
Speed Of Sound ◽  
Thermal Transport ◽  
Large Scale ◽  
Lattice Thermal Conductivity ◽  
Layered Materials ◽  
Layered Structures ◽  
Polycrystalline Materials ◽  
Anisotropic Lattice ◽  
Average Factor

<div> <div> <div> <p>Thermal conductivity plays a crucial role in many applications; use of single-crystal and textured polycrystalline materials in such applications necessitate understanding the anisotropy in thermal transport. Measurement of anisotropic lattice thermal conductivity is quite challenging. To address this need through computations, we build upon our previously developed isotropic model for <i>k<sub>L</sub></i> and incorporate the directional (angular) dependence by using the elastic tensor obtained from <i>ab initio</i> calculations and the Christoffel equations for speed of sound. With the anisotropic speed of sound and intrinsic material properties as input parameters, we can predict the direction-dependent <i>k<sub>L</sub></i>. We validate this new model by comparing with experimental data from the literature – predicted <i>k<sub>L</sub></i> is within an average factor difference of 1.8 of experimental measurements, spanning 5 orders of magnitude in <i>k<sub>L</sub></i>. To demonstrate the utility and computational-tractability of this model, we calculate <i>k<sub>L </sub></i>of ~2200 layered materials that are expected to exhibit anisotropic thermal transport. We consider both van der Waals and ionic layered structures with binary and ternary chemistries and analyze the anisotropy in their <i>k<sub>L</sub></i>. The large-scale study has revealed many layered structures with interesting anisotropy in <i>k<sub>L</sub></i>.</p> </div> </div> </div>

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