Design and test of shape memory alloy fins for self-adaptive liquid cooling device

Thermal management complexity increases in high-performance chips, where the heat loads vary spatially and temporally, while liquid cooling systems are usually designed for most stringent stationary conditions. Several works developed heat transfer enhancement techniques to increase the cooling capacity of liquid cooled heat sinks, but pumping power is increased in a permanent way due to the addition of elements within the channels. Here, a liquid cooling self-adaptive heat sink that can efficiently adapt the distribution of its heat extraction capacity to time dependent and non-uniform heat load scenarios is proposed. Numerical design of the mesoscale cooling device with bimorph metal/SMA fins, definition of the fabrication and training procedure of the SMA fins to reach the desired behavior and experimental assessment is presented. The capacity of the self-adaptive fins to locally boost the heat transfer is numerically and experimentally demonstrated. Results obtained show that the self-adaptive fins can improve the temperature uniformity by 63% with respect to plain channel. The reduction in thermal resistance using bimorph metal/SMA fins sample allows the surface maximum temperature gradient to remain almost constant although heat flux increases. Energy savings are maximized in applications where partial load intervals contributes significantly to the overall operating period.The research leading to these results has been performed within the project Indústria del Coneixement 2018, PROD-00071 “Experimental demonstration and commercial viability of an energy efficient universal cooling scheme”. It has been co-financed by the European Union through the European Regional Development Fund (FEDER) and has the support of the Secretaria d’Universitats i Recerca from Departament d’Empresa i Coneixement of the Generalitat de Catalunya

Fundamental Characterization of Low Dimensional Carbon Nanomaterials for 3D Electronics Packaging

Transistor miniaturization has over the last half century paved the way for higher value electronics every year along an exponential pace known as \u27Moore\u27s law\u27. Now, as the industry is reaching transistor features that no longer makes economic sense, this way of developing integrated circuits (ICs) is coming to its definitive end. As a solution to this problem, the industry is moving toward higher hanging fruits that can enable larger sets of functionalities and ensuring a sustained performance increase to continue delivering more cost-effective ICs every product cycle. These design strategies beyond Moore\u27s law put emphasis on 3D stacking and heterogeneous integration, which if implemented correctly, will deliver a continued development of ICs for a foreseeable future. However, this way of building semiconductor systems does bring new issues to the table as this generation of devices will place additional demands on materials to be successful. The international roadmap of devices and systems (IRDS) highlights the need for improved materials to remove bottlenecks in contemporary as well as future systems in terms of thermal dissipation and interconnect performance. For this very purpose, low dimensional carbon nanomaterials such as graphene and carbon nanotubes (CNTs) are suggested as potential candidates due to their superior thermal, electrical and mechanical properties. Therefore, a successful implementation of these materials will ensure a continued performance to cost development of IC devices.This thesis presents a research study on some fundamental materials growth and reliability aspects of low dimensional carbon based thermal interface materials (TIMs) and interconnects for electronics packaging applications. Novel TIMs and interconnects based on CNT arrays and graphene are fabricated and investigated for their thermal resistance contributions as well electrical performance. The materials are studied and optimized with the support of chemical and structural characterization. Furthermore, a reliability study was performed which found delamination issues in CNT array TIMs due to high strains from thermal expansion mismatches. This study concludes that CNT length is an important factor when designing CNT based systems and the results show that by further interface engineering, reliability can be substantially improved with maintained thermal dissipation and electrical performance. Additionally, a heat treatment study was made that enables improvement of the bulk crystallinity of the materials which will enable even better performance in future applications

Impact of the gate oxide reliability of SiC MOSFETs on the junction temperature estimation using temperature sensitive electrical parameters

Bias temperature instability (BTI) is more problematic in SiC power MOSFETs due to the occurrence of higher interface state traps and fixed oxide traps compared to traditional silicon MOS interfaces where there are no carbon atoms degrading the atomically smooth Si/SiO2 interface. The use of temperature sensitive electrical parameters (TSEPs) for measuring the junction temperature and enabling health monitoring based on junction temperature identification is a promising technique for increasing the reliability of power devices, however in the light of increased BTI in SiC devices, this must be carefully assessed. This paper evaluates how BTI of SiC power MOSFETs under high temperature gate bias stresses affects the electrical parameters used as TSEPs and its impact on condition monitoring

An experimental assessment of computational fluid dynamics predictive accuracy for electronic component operational temperature

Ever-rising Integrated Circuit (IC) power dissipation, combined with reducing product development cycles times, have placed increasing reliance on the use of Computational Fluid Dynamics (CFD) software for the thermal analysis of electronic equipment. In this study, predictive accuracy is assessed for board-mounted electronic component heat transfer using both a CFD code dedicated to the thermal analysis of electronics, Flotherm, and a general-purpose CFD code, Fluent. Using Flotherm, turbulent flow modelling approaches typically employed for the analysis of electronics cooling, namely algebraic mixing length and two-equation high-Reynolds number k-e models, are assessed. As shown, such models are not specific for the analysis of forced airflows over populated electronic boards, which are typically classified as low-Reynolds number flows. The potential for improved predictive accuracy is evaluated using candidate turbulent flow models more suited to such flows, namely a one-equation SpalartAllmaras model, two-layer zonal model and two equation SST k-co model, all implemented in Fluent. Numerical predictions are compared with experimental benchmark data for a range of componentboard topologies generating different airflow phenomena and varying degrees of component thermal interaction. Test case complexity is incremented in controlled steps, from single board-mounted components in free convection, to forced air-cooled, multi-component board configurations. Apart from the prediction of component operational temperature, the application of CFD analysis to the design of electronic component reliability screens and convective solder reflow temperature profiles is also investigated. Benchmark criteria are based on component junction temperature and component-board surface temperature profiles, measured using thermal test chips and infrared thermography respectively. This data is supplemented by experimental visualisations of the forced airflows over the boards, which are used to help assess predictive accuracy. Component numerical modelling is based on nominal package dimensions and material thermal properties. To eliminate potential numerical modelling uncertainties, both the test component geometry and structural integrity are assessed using destructive and non-destructive testing. While detailed component modelling provides the à priori junction temperature predictions, the capability of compact thermal models to predict multi-mode component heat transfer is also assessed. In free convection, component junction temperature predictions for an in-line array of fifteen boardmounted components are within ±5°C or 7% of measurement. Predictive accuracy decays up to ±20°C or 35% in forced airflows using the k-e flow model. Furthermore, neither the laminar or k-e turbulent flow model accurately resolve the complete flow fields over the boards, suggesting the need for a turbulence model capable of modelling transition. Using a k-co model, significant improvements in junction temperature prediction accuracy are obtained, which are associated with improved prediction of both board leading edge heat transfer and component thermal interaction. Whereas with the k-e flow model, prediction accuracy would only be sufficient for the early to intermediate phase of a thermal design process, the use of the k-co model would enable parametric analysis of product thermal performance to be undertaken with greater confidence. Such models would also permit the generation of more accurate temperature boundary conditions for use in Physics-of-Failure (PoF) based component reliability prediction methods. The case is therefore made for vendors of CFD codes dedicated to the thermal analysis of electronics to consider the adoption of eddy viscosity turbulence models more suited to the analysis of component heat transfer. While this study ultimately highlights that electronic component operational temperature needs to be experimentally measured to quality product thermal performance and reliability, the use of such flow models would help reduce the current dependency on experimental prototyping. This would not only enhance the potential of CFD as a design tool, but also its capability to provide detailed insight into complex multi-mode heat transfer, that would otherwise be difficult to characterise experimentally

Towards a More Flexible, Sustainable, Efficient and Reliable Induction Cooking: A Power Semiconductor Device Perspective

Esta tesis tiene como objetivo fundamental la mejora de la flexibilidad, sostenibilidad, eficiencia y fiabilidad de las cocinas de inducción por medio de la utilización de dispositivos semiconductores de potencia: Dentro de este marco, existe una funcionalidad que presenta un amplio rango de mejora. Se trata de la función de multiplexación de potencia, la cual pretende resolverse de una manera más eficaz por medio de la sustitución de los comúnmente utilizados relés electromecánicos por dispositivos de estado sólido. De entre todas las posibles implementaciones, se ha identificado entre las más prometedoras a aquellas basadas en dispositivos de alta movilidad de electrones (HEMT) de Nitruro de Galio (GaN) y de aquellas basadas en Carburo de Silicio (SiC), pues presentan unas características muy superiores a los relés a los que se pretende sustituir. Por el contrario, otras soluciones que inicialmente parecían ser muy prometedoras, como los MOSFETs de Súper-Unión, han presentado una serie de comportamientos anómalos, que han sido estudiados minuciosamente por medio de simulaciones físicas a nivel de chip. Además, se analiza en distintas condiciones la capacidad en cortocircuito de dispositivos convencionalmente empleados en cocinas de inducción, como son los IGBTs, tratándose de encontrar el equilibrio entre un comportamiento robusto al tiempo que se mantienen bajas las pérdidas de potencia. Por otra parte, también se estudia la robustez y fiabilidad de varios GaN HEMT de 600- 650 V tanto de forma experimental como por medio de simulaciones físicas. Finalmente se aborda el cálculo de las pérdidas de potencia en convertidores de potencia resonantes empleando técnicas de termografía infrarroja. Por medio de esta técnica no solo es posible medir de forma precisa las diferentes contribuciones de las pérdidas, sino que también es posible apreciar cómo se distribuye la corriente a nivel de chip cuando, por ejemplo, el componente opera en modo de conmutación dura. Como resultado, se obtiene información relevante relacionada con modos de fallo. Además, también ha sido aprovechar las caracterizaciones realizadas para obtener un modelo térmico de simulación.This thesis is focused on addressing a more flexible, sustainable, efficient and reliable induction cooking approach from a power semiconductor device perspective. In this framework, this PhD Thesis has identified the following activities to cover such demands: In view of the growing interest for an effective power multiplexing in Induction Heating (IH) applications, improved and efficient Solid State Relays (SSRs) as an alternative to the electromechanical relays (EMRs) are deeply investigated. In this context, emerging Gallium Nitride (GaN) High‐Electron‐Mobility Transistors (GaN HEMTs) and Silicon Carbide (SiC) based devices are identified as potential candidates for the mentioned application, featuring several improved characteristics over EMRs. On the contrary, other solutions, which seemed to be very promising, resulted to suffer from anomalous behaviors; i.e. SJ MOSFETs are thoroughly analysed by electro‐thermal physical simulations at the device level. Additionally, the Short Circuit (SC) capability of power semiconductor devices employed or with potential to be used in IH appliances is also analysed. On the one hand, conventional IGBTs SC behavior is evaluated under different test conditions so that to obtain the trade‐off between ruggedness and low power losses. Moreover, ruggedness and reliability of several normally‐off 600‐650 V GaN HEMTs are deeply investigated by experimentation and physics‐based simulation. Finally, power losses calculation at die‐level is performed for resonant power converters by means of using Infrared Thermography (IRT). This method assists to determine, at the die‐level, the power losses and current distribution in IGBTs used in resonant soft‐switching power converters when functioning within or outside the Zero Voltage Switching (ZVS) condition. As a result, relevant information is obtained related to decreasing the power losses during commutation in the final application, and a thermal model is extracted for simulation purposes.<br /

Exploration of Graphene-like 2D Materials for Energy Management and Interface Enhancement Applications

Ever since the discovery of graphene in 2004, graphene-like 2D materials and their derivatives have attracted extensive investigations because of their exceptional physical and chemical properties. At present, the study of graphene-like 2D materials is at a stage where most of their outstanding physical and chemical properties have been discovered, but the technology for incorporating them into practical commercial products is rarely revealed. For the potential practical industrial applications of graphene-like 2D materials, energy management and interface enhancement are two of the most promising areas. So far, the behavior of the commercialized graphene-like 2D material products is far from their theoretical performance and expectations as a result of defects and π-π agglomeration, etc. In this regard, there is plenty of research room at the bottom for exploring their practical industrial applications. At present, surface modification is the most widely used strategy to cope with agglomerations. While to be widespread in market, developing low-cost, uniform, and high-quality preparation technology, and encountering the intrinsic agglomeration issues of graphene-like 2D materials are two of the main challenges. To focus on the above two issues, we developed the functionalization method for graphene-like 2D materials, including graphene and hexagonal boron nitride, and explored their potential industrial applications in energy management and interface enhancement. Further, mass production technology and industrial demonstration for graphene and hexagonal boron nitride were explored in some chapters. The main scientific conclusions and innovations of this thesis are listed as below:At first, Chapter 2 presents the experimental research study on using graphene-like 2D materials for energy management, especially in heat dissipation. With the rapid development of microelectronics and 5G communications, efficient heat dissipation is severely demanded for future electronics. To improve heat dissipation efficiency of electronics, based on the ultrahigh thermal conductivity of graphene-like 2D materials, this chapter explored two experimental works, including lightweight and high-performance graphene enhanced heat pipe and hexagonal boron nitride enhanced thermally conductive and electrically insulation heat spreader. (1) Graphene Enhanced Heat PipeIn this work, a unique lightweight and high thermal performance graphene heat pipe were firstly designed and developed. At first, the inner structures of graphene enhanced heat pipe were optimized, including the wicker structures, the filling volume of working fluids and the preparation of high thermal conductivity graphene film. Compared to the conventional copper-based heat pipe, our graphene enhanced heat pipe improves the specific cooling capacity more than 3 times. Further, COMSOL Multiphysics was used to establish the cooling model for graphene enhanced heat pipe. And the equation for quantifying the contribution factor from container and phase change was established. Finally, a graphene/copper composite heat pipe was studied to further improve reliability and mechanical strength. (2) Hexagonal Boron Nitride Enhanced Heat SpreaderIn this work, a hexagonal boron nitride based heat spreader was prepared by electrospinning with polyvinylpyrrolidone. After electrospun, the hexagonal boron nitride nanosheets are aligned along the fiber, and thus increasing the thermal conductivity. At first, the exfoliation technology was investigated. The result shows that a mixture of water and isopropanol (Vwater:VIPA=1:3) shows the highest exfoliation efficiency. With the optimized hexagonal boron nitride particle geometry and loading, the in-plane thermal conductivity of hexagonal boron nitride based heat spreader reaches 22 W m-1 K-1, this value is comparable to most of the reported work. Particularly, such electrospinning process is constant and scalable, showing high potential for mass-production.Chapter 3 still focuses on the application of utilizing graphene-like 2D materials for energy management but specifically in energy storage. Based on the ultrahigh electric mobility, large surface area, flexible, lightweight properties, graphene is an attractive option for energy storage. Therefore, graphene was investigated for electrical double layer capacitors and in-plane micro-supercapacitors in this chapter.(1) Graphene Enhanced Electric Double-layer CapacitorIn this work, a scalable soft template strategy was developed to prepare graphene foam with high electrochemical performance as electrode for supercapacitors. The specific surface areas and wettability of graphene foam is tailored by doping. Further, density functional theory simulation reveals why increasing the polarity of graphene largely improves its wettability. Afterwards, the unique porous structure, low ohm resistance, and high electrical conductivity largely improve the electrochemical performance of graphene foam electrodes and thus achieve ultrahigh specific ca pa city (550 F g-1), cycling sta bility ( 96.1% ca pa city retention after 10 000 cycles at a high current density of 10 A g-1), and outstanding rate capability (308 \ua0\ua0F \ua0\ua0g-1 a \ua0t 100 \ua0\ua0A \ua0\ua0g-1). (2) Graphene Based In-plane Micro-supercapacitorIn this work, graphene assembled film was used to replace the conventional silicon wafer for fabricating flexible and high thermal performance micro-supercapacitors. The result shows that such replacement decreases the surface temperature of micro-supercapacitors by 4 \ub0C, and the graphene based micro-supercapacitor present a similar electrochemical behavior with the referenced silicon based micro-supercapacitor. In addition, the graphene assembled film substrate can work as heat spreader for micro-supercapacitor, thus saving spaces and optimizing the following packaging procedures. This work paves the way for utilizing graphene assembled film in semiconductors.Chapter 4 presents the application of using functional graphene-like 2D materials for interface enhancements due to their high Young’s module, large surface area, anti-friction, etc. Graphene-like 2D materials enhanced composites and bio-application are two of the main categories for the commercialization of interface enhancement. However, the graphene-like 2D materials suffer from π-π agglomeration, which leads to poor dispersibility in solvents and matrix. As a result, graphene-like 2D materials enhanced composites exhibit lower property than their theoretical expectations. At present, surface functionalization is the most effective strategy to encounter the π-π agglomeration. Therefore, this chapter explored the application of using functional graphene-like 2D materials in composites, including graphene enhanced water-borne epoxy coatings and hexagonal boron nitride enhanced cement repair materials.(1) Graphene Enhanced Water-borne Epoxy CoatingGraphene was used to lower the coefficient of friction and extend the lifetime of the water-borne epoxy coating in this work. To improve the dispersibility and the compatibility with epoxy, p-hydroxybenzene diazonium salt was prepared to functional graphene. With the optimized geometry and loading, 30 times less coefficient of friction than graphene-free coatings were achieved. And the wear-out time is more than 2 times longer than the three commercial graphene oxide enhanced coatings. This result is confirmed by Applied Nanosurface AB, Sweden. Besides, mass production technology up to 300 g per batch was developed for the functional graphene. The geometry of graphene was optimized, and the result shows that with the same functional groups, the larger graphene sheets show higher tribological performance than their smaller encounters. Finally, this functionalization strategy was further developed to improve the dispersibility of carbon nanotubes too. (2) Hexagonal Boron Nitride Enhanced Cement Repair MaterialThis work explored the application of using hexagonal boron nitride to enhance cement repair materials. To improve the dispersibility in cement repair materials and the adhesion with substrates, hexagonal boron nitride was functionalized by carboxymethyl cellulose. After functionalization, the surface zeta potential of hexagonal boron nitride decrease from -5.61 mV to -55.07 mV, and thus largely improves its dispersibility. Results show the incorporation of hexagonal boron nitride improve mechanical strength of cement repair materials by contributing to forming alite. Besides, for the repair material containing h-BN, most of the failure happened at the interface repair material/concrete, while the failure is mainly happening in the concrete for the sample containing FBN. Cooperated with a local cement company (Lanark AB), this work has demonstrated the commercial application as repair materials for walls.Besides, we studied the functional graphene quantum dots for mRNA based drug delivery platform. After complexed with mRNA, the transfection efficiency of the graphene quantum dots based drug delivery platform is 25% with a formation concentration as 4000 ng mL-1. A comparable transfection efficiency could be achieved at much lower doses if the ratio between the carrier and the cargo is optimized. This graphene quantum dots based drug delivery platform exhibits excellent processability. This work describes a potentially strategy for prepare stable and effective mRNA delivery systems

Reduced-Order Thermal Behavioral Model Based on Diffusive Representation

14 páginas, 15 figuras, 2 tablas.-- et al.The virtual prototyping of power electronic converters requires electrothermal models with various abstraction levels and easy identification. Numerous methods for the construction of compact thermal models have been presented in this paper. Few of them propose state-space models, where the model order can be controlled according to the necessity of the virtual prototyping analyses. Moreover, the model reduction methods require the experience of the engineer and previous calibration. Diffusive representation (DR) is proposed here as an original and efficient method to build compact thermal models as state-space models. The model reduction is obtained through the model parameter identification and/or the time horizon of the measurement data provided for the identification. Instead of eigenvalue elimination, the method enables to specify adequately inside the model the frequency domain wished for the virtual analysis at hand. The proposed method is particularly dedicated to the system optimization phases. Experimental and simulation results are in good agreement. The advantages and limitations of the DR are discussed in comparison to published methods.Peer reviewe