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Graphene/hexagonal boron nitride (h-BN) van der Waals (vdW) heterostructure has aroused great interest because of the unique Moiré pattern. In this study, we use molecular dynamics simulation to investigate the influence of the interlayer rotation angle θ on the interfacial thermal transport across graphene/h-BN heterostructure. The interfacial thermal conductance G of graphene/h-BN interface reaches 509 MW/(m2K) at 500 K without rotation, and it decreases monotonically with the increase of the rotation angle, exhibiting around 50% reduction of G with θ = 26.33°. The phonon transmission function reveals that G is dominantly contributed by the low-frequency phonons below 10 THz. Upon rotation, the surface fluctuation in the interfacial graphene layer is enhanced, and the transmission function for the low-frequency phonon is reduced with increasing θ, leading to the rotation angle-dependent G. This work uncovers the physical mechanisms for controlling interfacial thermal transport across vdW heterostructure via interlayer rotation.
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We present experimental measurements of the thermal boundary conductance (TBC) from 78-500 K across isolated heteroepitaxially grown ZnO films on GaN substrates. This data provides an assessment of the underlying assumptions driving phonon gas-based models, such as the diffuse mismatch model (DMM), and atomistic Green's function (AGF) formalisms used to predict TBC. Our measurements, when compared to previous experimental data, suggest that TBC can be influenced by long wavelength, zone center modes in a material on one side of the interface as opposed to the '"vibrational mismatch"' concept assumed in the DMM; this disagreement is pronounced at high temperatures. At room temperature, we measure the ZnO/GaN TBC as 490[+150,-110] MW m-2 K-1. The disagreement among the DMM and AGF, and the experimental data at elevated temperatures, suggests a non-negligible contribution from other types of modes that are not accounted for in the fundamental assumptions of these harmonic based formalisms, which may rely on anharmonicity. Given the high quality of these ZnO/GaN interfaces, these results provide an invaluable, critical, and quantitative assessment of the accuracy of assumptions in the current state of the art computational approaches used to predict phonon TBC across interfaces.
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With the development of energy science and electronic technology, interfacial thermal transport has become a key issue for nanoelectronics, nanocomposites, energy transmission, and conservation, etc. The application of thermal interfacial materials and other physical methods can reliably improve the contact between joined surfaces and enhance interfacial thermal transport at the macroscale. With the growing importance of thermal management in micro/nanoscale devices, controlling and tuning the interfacial thermal resistance (ITR) at the nanoscale is an urgent task. This Review examines nanoscale interfacial thermal transport mainly from a theoretical perspective. Traditional theoretical models, multiscale models, and atomistic methodologies for predicting ITR are introduced. Based on the analysis and summary of the factors that influence ITR, new methods to control and reduce ITR at the nanoscale are described in detail. Furthermore, the challenges facing interfacial thermal management and the further progress required in this field are discussed.
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Due to the minimization and integration of micro/nano-devices, the high density of interfaces becomes a significant challenge in various applications. Phonon modes at interface resulting from the mismatch between inhomogeneous functional counterparts are crucial for interfacial thermal transport and overall thermal management of micro/nano-devices, making it a topic of great research interest recently. Here, we comprehensively review the recent advances on the theoretical and experimental investigations of interfacial phonon mode and its impact on interfacial thermal transport. Firstly, we summarize the recent progresses of the theoretical and experimental characterization of interfacial phonon modes at various interfaces, along with the overview of the development of diverse methodologies. Then, the impact of interfacial phonon modes on interfacial thermal transport process are discussed from the normal modal decomposition and inelastic scattering mechanisms. Meanwhile, we examine various factors influencing the interfacial phonon modes and interfacial thermal transport, including temperature, interface roughness, interfacial mass gradient, interfacial disorder, and so on. Finally, an outlook is provided for future studies. This review provides a fundamental understanding of interfacial phonon modes and their impact on interfacial thermal transport, which would be beneficial for the exploration and optimization of thermal management in various micro/nano-devices with high density interfaces.
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HYPOTHESIS: Recent advances in deep learning (DL) have enabled high level of real-time prediction of thermophysical properties of materials. On the other hand, molecular dynamics (MD) have been long used as a numerical microscope to observe detailed interfacial conditions but require separate simulations that are computationally costly. Hence, it should be possible to combine MD and DL to obtain high resolution interfacial details at a low computational cost. EXPERIMENT: We proposed a novel DL encoding-decoding convolutional neural network (CNN) coupled with MD to realize the mapping from micro solid-liquid interface geometry to molecular temperature and density distribution of liquid containing surfactant. A multi-nanoscale optimization scheme was further proposed to reduce the uncertainty of DL prediction at the expense of local details to obtain more resilient predictors. FINDINGS: The statistical results showed that the proposed CNN had high prediction accuracy and could reproduce the heat transfer and adsorption phenomena under the influence of various factors including liquid composition, wettability, and solid surface roughness, while the computational efficiency was greatly improved. Our DL method with the support of multi-nanoscale learning strategies can achieve the fast and accurate visualization and prediction of various interfacial properties of liquid and assist for interfacial material design.
Assuntos
Aprendizado Profundo , Surfactantes Pulmonares , Adsorção , Redes Neurais de Computação , TensoativosRESUMO
In this work, the defects (local stress generated) induce the formation of graphene/h-BN planar heterostructure (Gr-hBN-PH) to form "unsteady structure". Then, the coupling effects of external field (heat flow direction, strain and temperature field) and internal field (defect number, geometry shape and interfacial configuration) on the interface thermal conductivity (ITC) of Gr-hBN-PH were studied. The results show phonon transmission is less affected by compression deformation under the action of force-heat-defect coupling, while phonon transmission of heterostructure is more affected by tensile deformation. The non-harmonic interaction of the atoms in the composite system is strengthened, causing the softening of high-frequency phonons. The greater reduction of thermal transport at the interface of heterostructures will be. The interface bonding morphology plays a significant role on the ITC of the Gr-hBN-PH. The relationship between structure and properties in the low dimension is analyzed from the perspective of defect energy. It is helpful for us to understand the physical mechanism of low-dimensional structure, realize multiple structural forms, and even explore new uses.