Zhiqiang Li

Microchannel boiling heat transfer offers a promising solution to address extreme high heat flux in miniaturized and high-density integrated electronic devices. In this work, we performed numerical studies to elucidate the complex flow boiling process in a square microchannel using the open-source platform OpenFOAM. The governing equations of the two-phase flow was solved based on the finite volume framework, and the surface tension together with phase change models were incorporated to study the wettability and conjugate heat transfer in the microchannel. First, the stability of the liquid film shows that smaller contact angles lead to thicker and stable liquid films near the solid wall, while larger contact angles result in thinner and fragile films. Second, the heat transfer, represented by the dimensionless parameter Nu, shows that smaller contact angles result in higher and more uniform distribution of Nu. The velocity gradient causes the Nu to be higher for the sidewalls than for the bottom wall. The contact angle also affects the peak value of Nu. Small contact angles result in large solid wall temperature gradients and more efficient heat transfer. Finally, the simulation results show that smaller thermal conductivity of the solid results in larger temperature gradient in the flow direction, implying that the conjugate heat transfer is less efficient. Overall, the present numerical findings provide useful guidance for efficient thermal management in electronic devices.

The opposing effects of interface effect on phonon heat conduction and microwave absorption hinder the integration of thermal conduction with microwave absorption. Reconciling this contradiction by rationally optimizing the material structure remains a challenge. Herein, Fe ₂ N@CNTs with heterogeneous interfaces and multi‐dimensional encapsulated structures are fabricated through in situ chemical vapor deposition (CVD) to realize excellent thermal conductivity and microwave absorption. When the mass fraction of active material is 40 wt.%, the thermal conductivity ( λ _// ) of Fe ₂ N@CNTs composite films is 6.69 W m ⁻¹ K ⁻¹ . The minimum reflection loss (RL _min ) is up to −54.55 dB at a thickness of 3.43 mm, and the effective absorption bandwidth (EAB) is 5.52 GHz at 1.82 mm. The well‐designed Fe ₂ N@CNTs is an ideal model for gaining insight into electron transportation and phonon multi‐dimensional heat transport. Heterogeneous interface improves the dielectric loss and facilitates microwave and phonon absorption and conversion. The multi‐dimensional encapsulation structure increases the electron transport path and phonon heat transport paths making axial and radial co‐transfer possible. The multi‐dimensional encapsulation structure demonstrates extremely high microwave absorption and thermal management capabilities, which open up new possibilities for multifunctional applications in host materials with internal hollows.

Exploring interfacial thermal transport of a heterojunction interface is crucial to achieving advanced thermal management for gallium nitride-based high electron mobility transistor devices. The current research primarily focuses on material enhancements and microstructure design at the interfaces of epitaxial layers, buffer layers, and substrates, such as the GaN/SiC interface and GaN/AlN interface. Yet, the influence of different concentrations of Al/Ga atoms and interface roughness on the interfacial thermal conductance (ITC) of AlGaN/GaN interface, the closest interface to the hot spot, is still poorly understood. Herein, we focus on the rough AlGaN/GaN interface and evaluate the changes in ITC under different Al–Ga atomic concentrations and interface roughness using atomistic simulations. When the interface is completely smooth and AlGaN and GaN are arranged according to common polarization characteristic structures, the ITC gradually increases as the proportion of Al atoms decreases. When the proportion of Al atoms is reduced to 20%–30%, the impact of the interface structure on heat transfer is almost negligible. For interface models with different roughness levels, as the interface roughness increases, the ITC drops from 735.09 MW m−2 K−1 (smooth interface) to 469.47 MW m−2 K−1 by 36.13%. The decrease in ITC is attributed to phonon localization induced by rough interfaces. The phonon modes at the interface are significantly different from those in bulk materials. The degree of phonon localization is most pronounced in the frequency range that contributes significantly to heat flux. This work provides valuable physical insights into understanding the thermal transfer behaviors across the rough AlGaN/GaN interfaces.

Water dissociation on TiO2 surfaces has been known for decades and holds great potential in various applications, many of which require a proper understanding of thermal transport across the TiO2–H2O interface. Molecular dynamics (MD) simulations play an important role in characterizing complex systems’ interfacial thermal transport properties. Nevertheless, due to the imprecision of empirical force field potentials, the interfacial thermal transport mechanism involving water dissociation remains to be determined. To cope with this, a deep potential (DP) model is formulated through the utilization of ab initio datasets. This model successfully simulates interfacial thermal transport accompanied by water dissociation on the TiO2 surfaces. The trained DP achieves a total energy accuracy of ∼238.8 meV and a force accuracy of ∼197.05 meV/Å. The DPMD simulations show that water dissociation induces the formation of hydrogen bonding networks and molecular bridges. Structural modifications further affect interfacial thermal transport. The interfacial thermal conductance estimated by DP is ∼8.54 × 109 W/m2 K, smaller than ∼13.17 × 109 W/m2 K by empirical potentials. The vibrational density of states (VDOS) quantifies the differences between the DP model and empirical potentials. Notably, the VDOS disparity between the adsorbed hydrogen atoms and normal hydrogen atoms demonstrates the influence of water dissociation on heat transfer processes. This work aims to understand the effect of water dissociation on thermal transport at the TiO2–H2O interface. The findings will provide valuable guidance for the thermal management of photocatalytic devices.

The microwave (MW) dielectric permittivity of gallium oxide (β-Ga2O3) fundamentally determines its interaction with an electromagnetic wave in bulk power. Yet, there is a lack of experimental data due to limitations of high-temperature MW dielectric measurements and the large uncertainty under variable-temperature conditions. Herein, we develop a deep potential (DP) based on density functional theory (DFT) results and apply deep potential molecular dynamics (DPMD) for accurately predicting temperature-dependent MW dielectric permittivity of β-Ga2O3. The predicted energies and forces by DP demonstrate excellent agreement with DFT results, and DPMD successfully simulates systems up to 1280 atoms with quantum precision over nanosecond scales. Overall, the real part of the MW dielectric permittivity decreases with rising frequency, but the dielectric loss increases. The MW dielectric permittivity gradually increases as the temperature increases, which is closely related to the reduced dielectric relaxation time and increased static and high-frequency dielectric constants. Besides, the oxygen vacancy defects significantly reduce the relaxation time; however, augmenting the defect concentration will cause a slight rise in relaxation time. The electron localization function analysis reveals that more free electrons and low localization of electrons produced by high defect concentrations facilitate the increased relaxation time. This study provides an alternative route to investigate the temperature-dependent MW permittivity of β-Ga2O3, which attains prime importance for its potential applications in RF and power electronics.

Nanoscale thermal transport at solid–liquid interfaces plays an essential role in many engineering fields. This work performs deep potential molecular dynamics (DPMD) simulations to investigate thermal transport across copper–water interfaces. Unlike traditional classical molecular dynamics (CMD) simulations, we independently train a deep learning potential (DLP) based on density functional theory (DFT) calculations and demonstrated its high computational efficiency and accuracy. The trained DLP predicts radial distribution functions (RDFs), vibrational densities of states (VDOS), density curves, and thermal conductivity of water confined in the nanochannel at a DFT accuracy. The thermal conductivity decreases slightly with an increase in the channel height, while the influence of the cross-sectional area is negligible. Moreover, the predicted interfacial thermal conductance (ITC) across the copper–water interface by DPMD is 2.505 × 10⁸ W m⁻² K⁻¹, the same order of magnitude as the CMD and experimental results but with a high computational accuracy. This work seeks to simulate the thermal transport properties of solid–liquid interfaces with DFT accuracy at large-system and long-time scales.