Thermal Management Research Articles

Thermal transport in disordered wurtzite ScAlN alloys using machine learning interatomic potentials

Disordered wurtzite ScAlN alloy is an emerging material with a strong piezoelectric coefficient that promotes its application in 5G communication devices. To extend the service lifetime of the device, it is an urgent task to understand the thermal transport properties of this alloy for thermal management. Yet a thorough understanding of the thermal transport in the disordered ScAlN alloy is hindered by the inaccuracy of empirical interatomic potentials adopted for atomistic simulations. Herein, we developed an accurate and efficient neuro-evolution potential and combined it with Allen and Feldman theory and molecular dynamics to investigate thermal transport properties of disordered ScAlN alloys with varying ratios. This potential is shown to have the same computational accuracy as first principles by comparing the phonon spectrum and radial distribution function. Based on the homogeneous non-equilibrium molecular dynamics simulations, the lattice thermal conductivity of the disordered alloys reaches its maximum value (less than 12W/m·K) at room temperature. Further investigation of the temperature effects on the vibrational modes shows that it affects the mode lifetimes for the propagons and the mode heat capacities for the diffusions. In addition, it was found that both mode lifetime and diffusivity decrease with increasing Sc concentration. This work aims to train a universal machine learning interatomic potential of disordered ScAlN alloys, seeking to accelerate the thermal management design of related devices.

Enhancing heat transfer performance of aluminum-based vapor chamber with a novel bionic wick structure fabricated using additive manufacturing

Given the lightweight nature and excellent thermal conductivity of aluminum, it offers significant potential for light-weighting of phase-change cooling components. To further enhance the thermal performance of aluminum-based vapor chambers, this study utilized selective laser melting (SLM) to design and integrally manufacture the slightly oleophilic wick for the condenser of the aluminum-based vapor chamber, along with three different superoleophilic wick structures for the evaporator: the gyroid bionic composite porous wick vapor chamber (GBCPVC), the groove composite porous wick vapor chamber (GCPVC), and the uniform porous wick vapor chamber (UPVC). A water-cooling experimental setup was established, and the effects of wick structure, cooling water flow rate, and cooling water temperature on the maximum heat load, temperature uniformity, and thermal resistance of vapor chambers were systematically investigated. The results indicated that the gyroid bionic porous wick structure significantly enhanced the thermal performance of the vapor chamber. Under the same conditions, GBCPVC exhibited lower thermal resistance and superior temperature uniformity, achieving a higher heat load than GCPVC and UPVC. When the cooling water temperature was decreased, its maximum heat load significantly increased. Specifically, at 15 °C, the maximum heat load for GBCPVC reached 300 W, an increase of 33.33 % and 53.33 % compared to 25 °C and 35 °C, respectively. Conversely, a rise in cooling water temperature enhanced the temperature uniformity and reduced thermal resistance of CBCPVC. At 35 °C and a heat load of 120 W, GBCPVC achieved a minimum thermal resistance of 0.034 K/W and a maximum temperature difference of 1.46 °C. Additionally, an increased flow rate enhanced the maximum heat load of GBCPVC, and under high heat loads, it could also reduce the thermal resistance and improve temperature uniformity. This study provides new insights and solutions for the thermal management of phase-change cooling components in aerospace electronic devices.

An innovative approach for the passive cooling of batteries: An empirical investigation of copper deposition on polyurethane foam for the enhancement of phase change material

A proof-of-concept utilising Copper-Plated Polyurethane Foam (CPPF) and Phase Change Material (PCM) for passive thermal management of lithium-ion batteries is demonstrated in this study. The aim of this research is to assess the effectiveness of CPPF when utilised as a constituent substance in PCM/Foam composites. Six distinct configurations of PCM/Foam composites are presented in this work using 10-pore-per-inch foam. A total of four deposition foam samples were produced. Of these, three were created by gradually increasing the immersion time in an electroless copper plating solution. For the fourth sample, an electroless plating technique was utilised for 80 min, followed by an electroplating procedure to deposit an additional layer of copper. The evaluation entails examining each plated sample in comparison to a copper foam that is commercially available with a purity level of 99.99 %. The findings reveal that the electroless-plated specimens exhibit improved effectiveness after being subjected to a prolonged plating period of 80 min. The electroplated sample exhibited the greatest degree of effectiveness, as evidenced by a 64.4 % reduction in battery cell surface temperature(10.98 °C), which is almost identical to the 64.5 % decrease in temperature (11.03 °C) observed with commercial foam but coupled with 88.1 % decrease in mass. The results suggest that the CPPF-PCM composites offer effective passive cooling properties for batteries.

Evaluation on capillary performance of multifunctional ultra-thin composite wick

Vapor chamber technology offers an effective solution for addressing challenges in battery thermal management due to its superior heat transfer efficiency per unit volume. However, achieving a lightweight and ultra-thin VC, which relies significantly on the wick structure, is crucial for its practical application. Nonetheless, reducing the thickness of the wick compromises its capillary performance, thereby impacting the thermal performance of the VC. To overcome this challenge, this paper proposes a Multifunctional Ultra-Thin Composite Wick (MUTCW) which is an integration of cover shell and wicks, aimed at enhancing capillary properties while simultaneously reducing wick thickness. A series of capillary rate-of-rise experiments were conducted to comprehensively evaluate the performance of the MUTCW. The results demonstrate that a MUTCW sintered with a 0.1 mm #200 mesh layer exhibits the most favorable capillary performance, with a wick coefficient of 19.299, an average capillary velocity of 3.5 mm/s, and an average mass flow rate of 3.32 mg/s.

Modelling of the microstructure and thermal conductivity of SiC bonded diamond materials

Materials with high thermal conductivity are required in a wide range of thermal management applications. Silicon carbide (SiC) bonded diamond materials, which can be produced without pressure, are a possible candidate for such applications. They exhibit thermal conductivities > 650 W/(m·K) depending on the diamond content, diamond grain size and residual silicon content. It is difficult to experimentally determine the influence of these factors on the thermal conductivity separately, as changing one of these parameters affects the other parameters. Therefore, a method for generating digital microstructures of SiC bonded diamond materials was developed and the thermal conductivity was calculated as a function of the grain size These data were compared with real structures.

Self-cleaning PTFE nanofiber membrane for long-term passive daytime radiative cooling

Passive daytime radiative cooling (PDRC) is an innovative, eco-friendly, and electricity-free cooling strategy that involves spontaneously cooling a surface by reflecting sunlight and radiating heat to cold outer space. Currently, many kinds of research focus on the effects of material design and structure construction on PDRC performance. However, the PDRC suffers a significant challenge of performance degradation arising from surface contamination and poor long-term outdoor durability. Herein, we developed a simple, efficient, and scalable strategy to prepare a superhydrophobic poly-(tetrafluoroethylene) (PTFE) nanofiber membrane (SNM-PTFE) with outstanding radiative cooling and self-cleaning performance for various practical applications. The SNM-PTFE has an average infrared emissivity 95.8 % and reflects 95.4 % of solar irradiance. It brought about a sub-ambient cooling performance of ∼ 14.4 °C under direct sunlight. Moreover, it demonstrated excellent above-ambient cooling performance by reducing ∼ 9. °C under sunlight, which exhibited unprecedented heat dissipation and solar heat-shielding properties. The self-cleaning surface of SNM-PTFE maintained its good cooling performance after being exposed to outdoor conditions for a full month. SNM-PTFE showed great promise for PDRC, which can further extend the application for residential, industrial applications, and human thermal management.

Spherical Fe3O4 morphology modulation for enhancing infrared emissivity and radiant heat dissipation

Radiant heat dissipation has emerged as a critical technique for effective thermal management, offering energy efficiency, cost-effectiveness, and adaptability to various shapes while promoting environmental sustainability. However, the intricate relationship between material structures and emissivity remains inadequately understood. This study primarily utilizes a straightforward and economical solvothermal method to regulate the synthesis of Fe3O4 ferrite, exploring its structural relationship with infrared radiation performance. By adjusting the solvent ratio of ethylene glycol and diethylene glycol in the solvothermal system, we successfully synthesized uniformly dispersed Fe3O4 nanospheres ranging from 10 to 800 nm. Notably, our research revealed a positive correlation between infrared emissivity and the particle size. Submicron hollow spheres with a size of 800 nm exhibit an exceptionally high emissivity of 0.992 within the 8∼13 μm wavelength range. Morphological and size variations induced alterations in lattice strain, oxygen vacancies, and phonon lifetimes, which consequently influencing the lattice vibration absorption and infrared emissivity. Moreover, the device surface with a composite coating formed by combining 15wt% Fe3O4 particles with organic matter, achieves a temperature difference of 17.6 °C under a 4 W input power condition compared to blank device. This finding contributes to further revealing the process of material radiative heat dissipation, driving the application of high-emissivity materials for heat dissipation in high-power electronic devices.

Expression of concern for article entitled “Numerical analysis of pressure drop and heat transfer of a non-Newtonian nanofluids in a Li-ion battery thermal management system (BTMS) using bionic geometries”

Expression of concern for article entitled “Numerical analysis of pressure drop and heat transfer of a non-Newtonian nanofluids in a Li-ion battery thermal management system (BTMS) using bionic geometries”

Analysis and design of module-level liquid cooling system for rectangular Li-ion batteries

To promote energy conservation and emission reduction, the electric vehicles (EVs) are developing rapidly. An effective battery thermal management system (BTMS) can extend the service life of batteries and avoid thermal runaway. In this study, a liquid-cooling management system of a Li-ion battery (LIB) pack (Ni-Co-Mn, NCM) is established by CFD simulation. The effects of liquid-cooling plate connections, coolant inlet temperature, and ambient temperature on thermal performance of battery pack are studied under different layouts of the liquid-cooling plate. Then, A new heat dissipation scheme, variable temperature cooling of the inlet coolant, is proposed. Results indicate that connecting two sets of liquid coolant plates in a 3-series, 1-parallel configuration can effectively reduce the maximum temperature of the battery pack from 48.73 ℃ to 30.75 ℃, while controlling the maximum temperature difference to 3.98 ℃ at the end of discharge. Simultaneously, the proposed cooling scheme reduces the maximum temperature difference within the battery pack by 36.09 % at the beginning of the discharge period. This study provides a valuable reference into advancing BTMSs of battery pack-level for EVs.

Design and Implement a BTMS using Phase Change Material - A Review

Abstract: This paper presents a comprehensive review of the design and implementation of Battery Thermal Management Systems (BTMS) utilizing Phase Change Materials (PCM). The thermal management of batteries is crucial for ensuring optimal performance, safety, and longevity, particularly in electric vehicles and renewable energy storage applications. Phase change materials offer unique advantages for thermal management, including high latent heat storage capacity, thermal conductivity, and temperature regulation capabilities. This review discusses the fundamentals of PCM-based BTMS design, including PCM selection, integration methods, and system optimization techniques. Additionally, recent advancements, challenges, and future directions in PCM-based BTMS are explored, providing valuable insights for researchers, engineers, and industry practitioners in the field of energy storage systems.

Thermal management lithium-ion battery for electric vehicles with using cold plate

Lithium-ion batteries are widely employed as the primary energy storage solution for electric vehicles (EVs). Effective thermal management of these batteries within EVs is important to ensure their safety, optimal performance, and longevity. Lithium-ion batteries are sensitive to fluctuations in temperature, and if not managed correctly, these temperature variations can lead to issues like overheating, reduced efficiency, and even safety risks. This study aims to investigate the effectiveness of a cooling method for a prismatic NMC battery used in electric vehicles. It emphasizes the significance of maintaining the battery's temperature within a specific range, typically between 15 °C and 35 °C, to prevent capacity loss and extend the battery's life. The design of the minichannel cold plate allows for precise thermal control with the 7 °C temperature difference. It efficiently absorbs heat generated during battery operation and releases it, preventing the battery from reaching undesirable temperature levels. Furthermore, the study underscores the importance of optimizing the contact area between the coolant and the battery stack for superior performance of the liquid cooling system. At higher discharge rates of the battery, a greater flow rate is required to achieve efficient cooling, with certain limitations due to the cooling system's efficiency. Overall, the study highlights the advantages of employing a liquid cooling system for proficient temperature regulation and effective heat dissipation in battery stacks for EVs.

Optimization and analysis of chassis for heavy electric truck under different condition

The design of heavy electric truck chassis is a critical aspect of developing sustainable and efficient transportation solutions. Heavy electric trucks, which are powered by electric motors and rely on large battery packs for energy storage. the structural integrity and strength of the chassis are of utmost importance. the integration of the battery pack into the chassis is a critical consideration. The chassis needs to accommodate the size, weight, and distribution of the battery pack while ensuring proper thermal management and protection. the unique challenges posed by these vehicles. By considering factors such as structural integrity, battery integration, lightweight materials, and other relevant design considerations, it is possible to develop efficient and sustainable heavy electric trucks that meet the demands of modern transportation.

Thermal Transport Properties of Two-Dimensional Janus MoXSiN2 (X = S, Se, and Te).

The design of Janus materials offers an effective means of regulating both their physical and chemical properties, leading to their application in various fields. However, the underlying mechanism governing the modulation of the thermal transport characteristics through the construction of Janus materials remains unclear. In this work, we introduce VI-group elements into the MoSi2N4 structure, yielding two-dimensional Janus MoXSiN2 (X = S, Se, and Te) and systematically investigate their thermal transport properties based on first-principles calculation methods. Our findings reveal that the lattice thermal conductivities (κl) of MoSSiN2, MoSeSiN2, and MoTeSiN2 are 47.2, 24.3, and 40.6 W/mK at 300 K, respectively, significantly lower than that of MoSi2N4 (224 W/mK). Such low κl values mainly come from the introduction of X atoms, which enhances phonon scattering and reduces phonon vibration frequencies. In addition, MoTeSiN2 exhibits a higher κl compared to MoSeSiN2, contrary to the trend observed in most materials containing VI-group elements, where κl decreases gradually from S to Te. This anomalous behavior can be attributed to the competitive result between its lower phonon vibrational frequency and weaker phonon anharmonicity of MoTeSiN2. This work elucidates the inherent mechanism governing the modulation of thermal transport properties in Janus materials, thereby enhancing the potential application of Janus MoXSiN2 in engineering thermal management.

Experimentally thermal management of low-concentrated photovoltaic via new configurations of dimple/trapezoidal heat spreaders of different sizes

ABSTRACT This study experimentally investigates the influence of dimple (DHS), flat plate (FHS), and trapezoidal heat spreader (THS) cooling systems on thermal regulation of low concentrated solar cell (LCPV). It is performed at 1.5 and 2 HS/PV area ratio and HS thicknesses 1 and 2 cm under 3100 W/m2 solar irradiance. Results reveal that using DHS outperforms other cooling systems in terms of cell temperature and electric performance. Increasing HS area ratio and thickness significantly enhances PV performance. DHS, PHS, and THS achieve maximum PV temperature reduction of 44.4, 43.2, and 41°C and PV efficiency improvement of 16.89%, 14.87%, and 13.9%, respectively.

Enhancing thermal management efficiency in robotics engineering: Exploring mechanisms, techniques, and modeling approaches

Thermal management is pivotal in robotics engineering, ensuring optimal performance and reliability of robotic systems. This comprehensive review explores various heat dissipation mechanisms, cooling techniques, and thermal modeling approaches employed in robotics engineering. Key topics include conduction-based, convection-based, and radiation-based heat transfer mechanisms, alongside liquid cooling, air cooling, and phase-change cooling techniques. Analytical thermal models, computational fluid dynamics (CFD) simulations, and finite element analysis (FEA) modeling are discussed for their roles in predicting thermal behaviors and optimizing heat dissipation strategies. By synthesizing these advancements, this review provides valuable insights into enhancing thermal management efficiency and ensuring the longevity of robotic systems.

High-Performance Bioinspired Hierarchical Microgroove Wick for Ceramic Vapor Chambers Achieved by Nanosecond Pulsed Lasers.

Directly integrating ceramic vapor chambers into the insulating substrate of semiconductor power devices is an effective approach to solve the problem of heat dissipation. Microgrooves that could be machined directly on the shell plate without contact thermal resistance and mechanical dislocation offer exciting opportunities to achieve high-performance ceramic vapor chambers. In this study, a bioinspired hierarchical microgroove wick (BHMW) containing low ribs via one-step nanosecond pulsed laser processing was developed, as inspired by the Sarracenia trichome. The superwicking behavior of microgrooves with different structural parameters was investigated using capillary rise tests and droplet-spreading experiments. The BHMW exhibited excellent capillary performance and anisotropic hemiwicking performance. At a laser scanning spacing of 30 μm, the BHMW achieved a capillary wicking height of 114 mm within 20 s. The optimized BHMW demonstrated a capillary parameter (ΔPc·K) and an anisotropic hemiwicking ratio of 4.46 × 10-7 N and 11.93, respectively, which were 1182 and 946% higher than references, as achieved through nanosecond pulsed laser texturing under identical parameters. This work not only develops a high-performance hierarchical alumina microgroove wick structure but also outlines design guidelines for high-performance ceramic vapor chambers for thermal management in semiconductor power devices.

Multidisciplinary design optimisation of lattice-based battery housing for electric vehicles

Batteries with high energy densities become essential with the increased uptake of electric vehicles. Battery housing, a protective casing encapsulating the battery, must fulfil competing engineering requirements of high stiffness and effective thermal management whilst being lightweight. In this study, a graded lattice design framework is developed based on topology optimisation to effectively tackle the multidisciplinary objectives associated with battery housing. It leverages the triply periodic minimal surfaces lattices, aiming for high mechanical stiffness and efficient heat dissipation considering heat conduction and convection. The effectiveness of the proposed framework was demonstrated through the battery housing design, showcasing its ability to address multidisciplinary objectives as evidenced by the analysis of the Pareto front. This study identifies the potential of lattices in lightweight applications incorporating multiphysics and offers an efficient lattice design framework readily extended to other engineering challenges.

Practical design of an optical filter for thermal management of photovoltaic modules

AbstractThis work presents a practical approach to designing an optical filter for thermal management for photovoltaic modules. The approach emphasizes the practicality of manufacturing over optical performance. Simulation work demonstrates that, for an interdigitated back contact solar cell architecture, complete rejection of infrared radiation offers limited thermal benefits requiring highly complex optical filter designs. An alternative approach consists of reducing thermalization losses by providing reflectance at lower wavelength values. An optical filter design that fulfills this requirement is possible using simple structures based on two materials and taking advantage of the harmonics present in quarter wavelength optical thickness designs. The filter is later optimized for angular performance via second‐order algorithms, resulting in a device consisting of only 15 thin‐film layers. Performance simulations on two locations, Delft (the Netherlands) and Singapore, estimate a temperature reduction of 2.20°C and 2.45°C, respectively. In a single year, the optical loss produced by the filter is not compensated via temperature reduction. However, improvements in the annual degradation rate show that in Singapore, the overall effect of the filter on the lifetime DC energy yield is positive.

Optimizing electrical and thermal performance in AlGaN/GaN HEMT devices using dual‐metal gate technology

AbstractThe investigation of aluminum gallium nitride/gallium nitride high electron mobility transistor (AlGaN/GaN HEMT) devices with a dual‐metal gate (DMG) structure encompasses both electrical and thermal characteristics. As efforts to enhance heat dissipation progress, there is a concurrent exploration of novel semiconductor materials boasting high thermal conductivity, like boron arsenide and phosphide. Combining these materials into a model and measuring their interface achieves efficient energy transport. Minimizing the self‐heating impact in AlGaN/GaN HEMTs is essential for enhancing device efficiency. This research exposes the heterogenous combination of boron arsenide and phosphide cooling substrates with metals, GaN semiconductors and HEMT. In this research, the autoencoder deep neural network techniques in GaN HEMT for self‐heat reduction is driven by the ability to effectively analyze and model the thermal behavior of the device. Autoencoders learn complex relationships within temperature data and identify patterns associated with self‐heating. By leveraging these learned representations, the deep neural network optimizes control strategies to mitigate self‐heating effects in GaN HEMT devices, ultimately contributing to improved thermal management and enhanced overall performance. In this research, the use of genetic algorithms in GaN HEMT aims to optimize device parameters systematically, to minimize self‐heating effects and enhance overall thermal performance. The structure also enhances electron mobility within the channel. Results show DMG structures, exhibiting higher saturation output currents and transconductance despite self‐heating. The DMG exhibits a maximum gm value of 0.164 S/mm, which is 10% higher significantly enhancing GaN‐based HEMTs for improved reliability and efficiency in various applications.

Rapid heat source layout optimization in three‐dimensional integrated circuits using artificial neural network reduced‐order model in combination with Bayesian optimization

AbstractIn this study, an efficient optimization framework was developed to determine the parameters of through‐silicon vias and the layout of heat sources in three‐dimensional integrated circuits (3D ICs), employing an artificial neural network (ANN) reduced‐order model in conjunction with a Bayesian optimization (BO) algorithm. The proposed method effectively predicts the temperature distribution in 3D ICs and refines their thermal parameters, offering solutions to thermal management challenges. Latin hypercube sampling was utilized for data sampling, enhancing the previously established rapid thermal analysis method through parameterization of heat source locations. The temperature distribution data for varying hotspot locations in 3D ICs were fitted using an appropriately defined objective function, leading to the development of a reduced‐order ANN model that accelerates temperature prediction. The computational results demonstrate that the neural network model exhibits a deviation in predicted values of less than 2%, and the coefficient of determination R2 approximately 0.93, underscoring high predictive accuracy. Additionally, the optimization outcomes and the efficiency of the selected BO algorithm were thoroughly evaluated. Notably, the BO algorithm achieved the global optimum in just 4.07 s across 250 iterations, demonstrating an effective power distribution strategy for the 3D ICs model.