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At least 307 records · Page 17

Design, Analysis, Comparison, and Experimental Validation of Insulated Metal Substrates for High-Power Wide-Bandgap Power Modules

Direct bonded copper (DBC) substrates used in power modules have limited heat spreading and manufacturing capability due to ceramic properties and manufacturing technology. The ceramic and copper bonding is also subject to high mechanical stress due to coefficient of thermal expansion mismatch between the copper and the ceramic. For wide-bandgap (WBG) devices, it is of interest exploring new substrate technologies that can overcome some of the challenges of direct bonded copper substrates. In this technical paper, the design, analysis, and comparison of insulated metal substrates (IMSs) for high-power wide-bandgap semiconductor-based power modules are discussed. This paper starts with technical description and discussion of state-of-the-art DBC substrates with different ceramic insulators such as aluminum nitride (AlN), Al 2 O 3 , and Si 3 N 4 . Next, an introduction of IMSs and their material properties, and a design approach for SiC (silicon carbide) metal-oxide-semiconductor field-effect transistor (MOSFET)-based power modules for high-power applications is provided. The influence of dielectric thickness on the power handling capability of the substrate are also discussed. The designed IMS and DBC substrates were characterized in terms of steady-state and transient thermal performance using finite element simulation. Finally, the performance of the IMS and DBC are validated in an experimental setup under different loading and cooling temperature conditions. We report the simulation and experimental results showed that the IMS can provide high steady-state thermal performance for high-power modules based on SiC MOSFETs. Furthermore, the IMS provided enhanced transient thermal performance, which provided a reduced junction temperature when the module is operated at low fundamental output frequencies in traction drive systems.

42 ENGINEERING↗

Analysis of Planar-Cavity Receiver Reactor for Solar Thermochemical Dry-Reforming

Concentrating solar thermal (CST) systems can be leveraged to provide not only heat for power generation, but also for energy storage and thermochemical fuel production. Such solar thermochemical processes have been studied conceptually, from solar thermochemical hydrogen production (STCH) and thermochemical energy storage (TCES), to gasification, reforming, and fuel upgrading by various means. The solar receiver and reactor are critical components in the conversion of solar energy into chemical energy in the form of 'solar fuels'. For effective conversion of solar energy within a coupled solar receiver-reactor, extremely high temperatures are required, thereby demanding a high solar concentration ratio (CR) for efficient operation. This creates a design challenge for the receiver-reactor, as many thermochemical processes involve gas or gas-solid systems that are limited by low heat transfer coefficients. A unique receiver design is proposed that has the potential to incorporate various high-temperature thermochemical processes such as TCES-assisted power generation, methane reforming, or STCH processes. Modeling this receiver and its potential applications requires a full three-dimensional model that accurately captures the interconnected effects of receiver geometry, spatial solar irradiance, complex radiation, reaction kinetics, fluid dynamics, and heat transfer. In this paper we analyze a CST system integrated with this unique planar-cavity receiver-reactor design using the developed model. The model presented in this paper showed where improved thermal management was needed to achieve suitable receiver performance when a dry-methane reforming process is implemented.

14 SOLAR ENERGY↗

Ultralow Thermal Conductivity, Multiband Electronic Structure and High Thermoelectric Figure of Merit in TlCuSe

The entanglement of lattice thermal conductivity, electrical conductivity, and Seebeck coefficient complicates the process of optimizing thermoelectric performance in most thermoelectric materials. Semiconductors with ultralow lattice thermal conductivities and high power factors at the same time are scarce but fundamentally interesting and practically important for energy conversion. In this work, an intrinsic p-type semiconductor TlCuSe that has an intrinsically ultralow thermal conductivity (0.25 W m -1 K -1 ), a high power factor (11.6 μ W cm -1 K -2 ), and a high figure of merit, ZT (1.9) at 643 K is described. The weak chemical bonds, originating from the filled antibonding orbitals p-d* within the edge-sharing CuSe 4 tetrahedra and long Tl-Se bonds in the PbClF-type structure, in conjunction with the large atomic mass of Tl lead to an ultralow sound velocity. Strong anharmonicity, coming from Tl + lone-pair electrons, boosts phonon-phonon scattering rates and further suppresses lattice thermal conductivity. The multiband character of the valence band structure contributing to power factor enhancement benefits from the lone-pair electrons of Tl + as well, which modify the orbital character of the valence bands, and pushes the valence band maximum off the Gamma-point, increasing the band degeneracy. The results provide new insight on the rational design of thermoelectric materials.

36 MATERIALS SCIENCE↗

Flow reversal benchmark of a one-sided heated narrow rectangular channel with CATHARE and RELAP5

Flow reversal in narrow coolant channels can be a crucial phenomenon for the safety of research reactors with a downward nominal flow direction. During a loss of forced flow accident, the downward flow stagnates briefly before transitioning into an upward natural circulation flow. The fuel may be damaged if dryout occurs and threshold fuel and/or cladding temperatures are exceeded. A comprehensive study is provided for flow reversal in narrow rectangular channels by examining experimental data and conducting software model analyses. The literature on flow reversal was reviewed, and selected experimental datasets were used to benchmark against CATHARE and RELAP5 models and also compare the code calculations with each other. The experimental data comes from flow reversal tests conducted with a narrow rectangular channel with one-sided heating. The results were compared with experimental data for successful flow reversal tests and predicted dryout power for dryout conditions. Also, the study examined the effects of the pump coastdown period, inlet liquid temperature, system pressure, and localized pressure drops. The experimental results showed that shorter coastdown periods, reduced pressure drops, and lower coolant inlet temperatures increased the dryout power. However, the system pressure did not noticeably affect the results. The simulation results showed that both CATHARE and RELAP5 agreed with experimental data, capturing the trends of the experimental results. Slight differences between each code calculation, as well as the predicted and measured dryout powers, were attributed to experimental uncertainties and the modeling of physical phenomena such as wall nucleation, interfacial heat transfer, drag coefficients, and critical heat flux. Overall, this study provides an understanding of flow reversal and the prediction capabilities of thermal-hydraulics software models. In conclusion, a future study of the flow reversal benchmark of a narrow rectangular channel with two-sided heating may provide additional valuable insights.

CATHARE↗

Intermediate scattering potential strength in electron-irradiated YBa 2 Cu 3 O 7-δ from London penetration depth measurements

Temperature-dependent London penetration depth, λ(T), of a high quality optimally-doped YBa 2 Cu 3 O 7-δ single crystal was measured using tunnel-diode-resonator technique. Controlled artificial disorder was induced by low-temperature 20 K irradiation by 2.5 MeV electrons at two large doses of 3.8 x 10 19 and 5.3 x 10 19 electrons per cm 2 . The irradiation caused significant suppression of the superconductor's critical temperature, T c , from 94.6 K to 90.0 K, and to 78.7 K, respectively. The low-temperature behavior of λ(T) evolves from a T-linear in pristine state to a T 2 behavior after irradiation, expected for a line-nodal d-wave superconductor. However, the original theory that explained such behavior assumed a unitary limit of the scattering potential, whereas usually in normal metals and semiconductors, Born scattering is sufficient to describe the experiment. To estimate the scattering potential strength, we calculated the superfluid density, ρ s (t = T/T c ) = λ 2 (0)/λ 2 (T), varying the amount and strength of non-magnetic scattering using a self-consistent t-matrix theory. Fitting the obtained curves to a power law, ρ s = 1 - Rt n , and to a polynomial, ρ s = 1 - At - Bt 2 , and comparing the coefficients n in one set and A and B in another with the experimental values, we estimate the phase shift to be around 70 and 65°, respectively. We correlate this result with the evolution of the density of states with nonmagnetic disorder.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Thermodynamic Limit for Excitonic Light-Emitting Diodes

Here, we derive the thermodynamic limit for organic light-emitting diodes (OLEDs), and show that strong exciton binding in these devices requires a higher voltage to achieve the same luminance as a comparable inorganic LED. The OLED overpotential, which does not reduce the power conversion efficiency, is minimized by having a small exciton binding energy, a long exciton lifetime, and a large Langevin coefficient for electron-hole recombination. Based on these results, it seems likely that the best phosphorescent and thermally activated delayed fluorescence OLEDs reported to date approach their thermodynamic limit. The framework developed here is broadly applicable to other excitonic materials, and should therefore help guide the development of low voltage LEDs for display and solid-state lighting applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Transformational challenge reactor design characteristics

The Transformational Challenge Reactor (TCR) program was conceived with the goal to reduce costs and time frames associated with advanced reactor deployment by leveraging developments in advanced manufacturing, advanced materials, data science, and rapid prototyping and testing. The final deliverable of the TCR program was to be an operational test of a novel reactor design. The TCR core design incorporates a dense tri-structural-isotropic/SiC fuel form and volumetrically efficient yttrium hydride moderator, both of which were manufactured and characterized under the TCR program. The TCR is a 3 MW{sub th} He-cooled experimental nuclear reactor designed to reach a total integrated burnup of less than 24 effective full-power hours to keep the radioactive source term to a very low level. TCR design process revealed a positive moderator coefficient; however, the negative doppler coefficients for the fuel and thermal expansion of fuel, moderator, and core support plate yield an overall negative reactivity coefficient. Calculated fuel element temperatures and stresses are well within safety margins. The maximum hypothetical accident (i.e., de-pressurized loss of forced cooling) yields only a modest increase in reactor temperatures that are all within safety margins. This paper summarizes the high-level TCR design characteristics, which were derived from neutronics, thermohydraulics, thermomechanics, and safety analyses.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Modeling and Validation of a Residential Multi-Functional Variable Refrigerant Flow Heat Pump System with Heat Recovery

To bridge the existing gap in modeling the variable refrigerant flow heat pump systems with heat recovery (VRFHR), we developed a suite of dynamic VRFHR system models in Modelica. These models are specifically tailored for residential multi-functional VRFHR (MF-VRFHR) applications, including space conditioning and domestic hot water (DHW) heating, utilizing both the TIL library for HVAC equipment and the Buildings library for thermal load calculations. The development comprises essential component models, including the newly developed heat recovery unit (HRU), along with system models that integrate the heat pump system and building envelope. These system models accommodate various operational modes such as heating-only, cooling-only, and heating-recovery (including heating-dominant and cooling-dominant) modes. Furthermore, we propose an efficient optimization-based model calibration method that identifies critical model parameters while utilizing a small amount of data obtained from either real systems or manufacturer's specifications. We demonstrate the effectiveness of these models and the proposed calibration method for a MF-VRFHR system installed in Richland, WA. The developed models are calibrated and validated using data collected under different operational modes during both heating and cooling seasons. The results show that the models capture the system dynamics and achieve high accuracy, with the coefficient of the variation of the root-mean-square-error less than 15% for variables such as outdoor unit power consumption, compressor speed, space temperature and DHW temperature. The validated models serve as a reliable representation of the MF-VRFHR system, facilitating the development and validation of optimized controls needed to realize the full benefits of integrated heat pump systems. Future research will utilize these models to develop advanced controls and optimize system performance for improved energy efficiency and demand flexibility.

Modeling, Variable refrigerant flow (VRF) systems,↗

Improving air leakage prediction of buildings using the fan pressurization method with the Weighted Line of Organic Correlation

In many countries, the fan pressurization method is the most frequently chosen approach for measuring the air leakage of houses. The measurements are usually performed at pressures that far exceed pressures to which buildings are exposed to under normal conditions. A fit of these tests to the power-law formulation allows an extrapolation to data points outside the measured pressure range. With the Ordinary Least Square (OLS) fitting method, the pressure exponent and flow coefficient can be determined. However, the measurement results are highly sensitive to uncertainties induced by external factors like changing wind conditions during the tests, which is neglected by OLS. This may lead to errors in the prediction of flows at lower pressures. The Weighted Line of Organic Correlation (WLOC) is an alternative approach and takes measurement uncertainty into account. In this paper, a statistical analysis of an extensive data set of pressurization measurements has been performed. Both regression techniques have been compared for almost 7500 fan pressurization measurements of six houses in 109 different house leak configurations. The variability in predicting pressure exponent and flow coefficient for both WLOC and OLS regression was analyzed using probability density functions. It was found that the Weighted Line of Organic Correlation significantly decreases the uncertainty in predicting pressure exponent, flow coefficient, and other low-pressure air leakage metrics compared to the Ordinary Least Square fitting. Here, the authors highly recommend the implementation of WLOC in current measurement standards and test equipment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Integrated Traction Drive Thermal Management: Keystone Project 3

The presentation was developed for the U.S. Department of Energy (DOE) Vehicle Technologies Program 2020 Annual Merit Review and Peer Evaluation Meeting. It reports on progress and accomplishments of DOE funded Integrated Traction Drive Thermal Management project. Highlighted are NREL's research accomplishments during FY 2020. Challenges associated with thermal management of integrated traction drives for electric vehicles arise due to the limited packaging space, coolant distribution, electrical connections, and ambient temperatures. For this project at NREL, research focuses on enabling thermal management technologies to support a modular, compact, self-contained integrated electric drive unit with motor and power electronics. Integration approaches, based on packaging location and coolant options for power electronics integrated with candidate motor technologies to reduce cables and connectors, are reviewed and compared using finite element analysis (FEA) tools. Automatic transmission fluid (ATF) jet impingement cooling characterization is carried out experimentally (measuring heat transfer coefficients) and using computational fluid dynamics (CFD) modeling.

47 OTHER INSTRUMENTATION↗

Automated power-following control for nuclear thermal propulsion startup and shutdown using MOOSE-based applications

This paper describes an investigation of various automated control strategies applied to a full-core multiphysics Griffin/Bison/RELAP-7 model of a prototypical nuclear thermal propulsion system. In all cases, control is achieved by actuating control drums based on the demanded power and predicted quantities from the numerical model. One key finding is that hybrid proportional integral derivative controllers – a novel type of controller that uses both power and reactivity predicted signals – can demonstrate a level of performance rivaling that of period-generated control. The former requires parameter tuning, while the latter mostly necessitates providing reactivity coefficients and temperature rates of change, which could be very challenging to accurately measure in real-time. In addition, decay heat plays an important role in determining cooling requirements during cooldown phases. A decay heat model, accounting for burn time and throttling, was derived, and is incorporated within the model to simulate the steady-state and shutdown phases and satisfyingly follow the power demand. However, temperature overshoots and non-constant specific impulse during throttling will necessitate further improvements.

33 ADVANCED PROPULSION SYSTEMS↗

Carrier confinement and alloy disorder exacerbate Auger–Meitner recombination in AlGaN ultraviolet light-emitting diodes

The quantum efficiency of AlGaN ultraviolet light-emitting diodes declines (droops) at increasing operating powers due to Auger–Meitner recombination (AMR). Using first-principles density-functional theory, we show that indirect AMR mediated by electron–phonon coupling and alloy disorder can induce bulk C coefficients as large as ~10 –31 cm 6 /s. Furthermore, we find that the confinement of carriers by polarization fields within quantum wells severely relaxes crystal-momentum conservation, which exacerbates the rate of AMR over radiative recombination by an order of magnitude relative to the bulk. Furthermore, this results in a striking decrease in quantum efficiency at high power. Suppressing polarization fields and jointly increasing the well width would greatly mitigate AMR and efficiency droop.

36 MATERIALS SCIENCE↗

Leveraging Natural Language Processing and Generative Models in Molecular Chemistry: Property Prediction and Novel Compound Generation

The accurate prediction of molecular properties is important for the rational design and the advancement of green chemistry and sustainable materials research. However, the predictive power of traditional computational chemistry methods is limited due to computational restrictions. Here, in this study, we examine an alternative approach to the accurate prediction of properties of organic compounds: natural language processing (NLP)-based molecular embedding. Using viscosity, partition coefficient (log P), and enthalpy of vaporization as test properties through a survey of comprehensive datasets comprising 5695 data points for viscosity, 25 870 data points for log P, and 2296 data points for enthalpy of vaporization. These are important properties for the design of greener, safer, and sustainable chemical processes. Models were trained using NLP methods such as Mol2vec and fine-tuned ChemBERTa, and results were compared with traditional input featurization techniques such as Morgan fingerprints and quantum chemistry derived sigma profiles and DFT features. Among the various machine learning models, Mol2vec demonstrated superior predictive capabilities, achieving the highest correlation coefficient (R 2 = 0.945) and lowest RMSE (0.106 mPa s) for viscosity, as well as high accuracy for log P and enthalpy of vaporization predictions. These findings establish the Mol2vec featurization technique, graph-convolutional neural networks (GCNN), and fine-tuned ChemBERTa model as powerful tools for predictive modeling of organic compounds properties, offering a significant improvement over previously used featurization techniques and opening up strategies for very-high-throughput computational screening. Finally, we integrated ML models with hybrid language-model-based generative adversarial networks (LM-GAN) to generate novel molecular sequences with desirable properties for different research applications. The ability to computationally design solvents with lower viscosity, lower log P, and lower enthalpy of vaporization offers a data-driven route to accelerating the discovery of sustainable alternatives to traditionally toxic solvents.

ChemBERTa↗

Mass transfer coefficients, kL, and air-CO2 ingassing rates in 3.4 m2 and 1-acre raceway ponds.

The US DOE 2016 Billion Ton Update (Langholtz 2016) projected that CO2 in flue-gas from power plants or similar sources would limit U.S. algal biofuel potential to under 5 billion gallons gasoline equivalent (gge) per year, due to lack of sufficient land, water and other requirements near such flue gas sources. 2nd generation carbon capture technologies are proposed to overcome this constraint (Davis 2017), and could expand this resource potential nearly 10-fold, assuming CO2 costs near the future, 2025 DOE NETL, goal of $40/metric ton CO2. An alternative pathway is the direct uptake of air CO2 into the algal ponds through an increase in the air-CO2 transfer rate resulting from the reaction of CO2 with hydroxide ions. However, such a ‘chemical enhancement’ in mass transfer depends on a high pH in the culture, and, by extension, the ability of microalgae to maintain high rates of carbon assimilation under such conditions. Abiotic experiments characterized the air-CO2 mass-transfer rate in 1-acre and 3.4 m2 raceway ponds as a function of pH, with rates approaching 10 g C/m2-day at pH 12 in the brackish water tested, equivalent to a biomass productivity potential of near 20 g AFDW/m2-day (@ 0.47 g C/g AFDW). The mass transfer rate was found to be nearly independent of the mass-transfer coefficient, indicating that at turbulence levels achievable in typical raceway ponds, the system is reaction rate, rather than diffusion limited. In biotic trials with an unknown green microalga, biomass productivity in ponds receiving CO2 from only direct surface air-CO2 exchange averaged 5 +/- 0.5 g AFDW/m2-day in August - September central California conditions, about half-that of experimental controls fertilized with supplemental CO2. pH in the air-only treatment reached a maximum of 10.5, supporting a model predicted air-CO2 ingassing rate between 2-3 g C/m2-day, consistent with the observed biomass carbon assimilation rate. Results suggest that unique alkaliphilic strains are required if reliant on direct in-pond air-CO2 transfer for algal inorganic carbon supply, and that reaching an economically viable biomass productivity will require strains that thrive at pH 11 and above.

09 BIOMASS FUELS↗

Enhancement of operational Flexibility of Power Plants Using IN740

Headers are crucial components within diverse industries, especially in the energy sector, as they enable the efficient transfer of fluids. The selection of materials for headers is determined by their specific applications; for example, Grade 91 and Grade 92 steels are commonly utilized. In our research, we recommend the adoption of INCONEL alloy 740 due to its exceptional robustness and heat-resistant characteristics. One critical parameter in header systems is the heat transfer coefficient, which directly influences the efficiency of heat exchange processes and can thereby impact the structural integrity of the headers. This coefficient is closely linked with factors such as the Nusselt number, which is influenced by fluid flow characteristics and thermal properties. The flow direction within headers, whether unidirectional or multidirectional—significantly affects the overall dynamics of heat transfer. This research focuses on exploring the behavior of headers, a specific pipeline system component, using ANSYS simulation software. The study aims to predict heat transfer and mechanical behavior within headers under various conditions through steady-state and transient simulations (parts 1 and 2 of the report). Key parameters such as heat transfer coefficient, velocity, and temperature are examined with the goal of optimizing header design. Part 3 of the report addresses the critical yet underexplored relationship between pressure drop and heat transfer coefficients in the transient flow regime within headers, specifically focusing on smooth horizontal circular tubes. Limited experimental work has been conducted in this area, prompting the need for comprehensive analysis. By leveraging machine learning techniques, this research aims to establish a correlation between pressure drop and heat transfer across various flow conditions, including laminar, transient, quasi-turbulent, and turbulent regimes. The data utilized for this analysis were meticulously gathered from existing literature, capturing simultaneous measurements of pressure drops and heat transfer. Part 4: In the context of power plants, header pipes are essential components that significantly influence system performance by facilitating the collection and distribution of steam. This report highlights the critical role of header pipes in enhancing reliability, efficiency, and overall power plant performance. A key aspect of this investigation is shape optimization, which aims to maximize performance while minimizing material usage. By focusing on shape optimization, this research contributes to improved efficiency and a reduced environmental footprint for power plant installations. The methodology developed in this study emphasizes optimizing header shapes to decrease reliance on expensive alloy materials and lower maintenance costs. Furthermore, a case study was conducted using a header from an operational power plant to validate the proposed optimization techniques. Finally, part 5 addresses the challenges associated with flexible operations in boiler systems, the study outlines several strategies for enhancing the durability and reliability of steam headers. Key approaches include material selection, which involves utilizing advanced materials with superior high-temperature properties and enhanced fatigue resistance to extend the lifespan of steam headers. Design modifications are also recommended, focusing on implementing changes that mitigate thermal stress and cyclic loading to reduce the likelihood of failures under varying operating conditions. Additionally, the study emphasizes the importance of regular inspection and monitoring by establishing rigorous protocols to detect early signs of damage, allowing for timely maintenance and minimizing the risks of catastrophic failures. Furthermore, operational guidelines are developed to minimize the frequency and severity of thermal transients, ensuring stable and efficient operations. Collectively, these strategies provide a robust framework for overcoming the unique challenges posed by flexible operation in boiler systems, ultimately contributing to improved reliability and performance in power plant operations. Through this comprehensive approach, the study not only enhances the understanding of pressure drop and heat transfer relationships but also promotes advancements in design and operation that will benefit the entire power generation industry.

01 COAL, LIGNITE, AND PEAT↗

Impact of nuclear data covariance libraries on uncertainty quantification of sodium cooled fast reactor simulation

Uncertainty quantification in core modelling to assess reactor performance is a regular practice to identify design safety limits. Best-estimate plus uncertainty (BEPU) methods are commonly used to propagate uncertainties to core responses from input parameters, characterized by variance-covariance libraries. This study evaluates the impact of different covariance libraries on the uncertainty associated with core safety parameters and their propagation through reactor transient modelling for a metallic core (ABR-1000). The COMAC-1.0, COMMARA-2.0, and COMMARA-2.1 covariance libraries are used to propagate nuclear data uncertainties to neutron feedback coefficients using the Generalized Perturbation Theory, then through transient safety analyses to establish the confidence interval for safety performance of the reactor using stochastic sampling. The considered transients include Unprotected Transient Over Power and Unprotected Loss Of Flow. Most influential nuclide and reaction pairs in different variance-covariance libraries are identified and their impact on the uncertainty of safety parameters are evaluated. Significant differences were observed between uncertainties from COMAC compared to COMMARA libraries. Uncertainties from COMMARA libraries were consistently larger than COMAC for all cases. For structure, coolant density feedback coefficients and control rod worth, total nuclear data uncertainties were approximately 50% larger for COMMARA than COMAC. Differences were also observed in identification of top contributors of uncertainty in terms of reaction-cross sections. For instance, largest contribution to total uncertainty of radial expansion coefficient from COMMARA-2.0 and 2.1 originates from Na{sup 23} P1 Elastic cross section (0.81%) but from Pu{sup 239} Fission (0.53%) with COM C-1.0. Such differences are evaluated in this research for all quantities of interest. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Interdiffusion and Formation of Intermetallic Compounds in High-Temperature Power Electronics Substrate Joints Fabricated by Transient Liquid Phase Bonding

Power electronics packages typically comprise a dielectric substrate bonded to a metal layer and attached to heat sinks using a low-thermal-conductivity solder. These multiple layers increase the effective thermal resistance of the package and are responsible for package failures under cyclic thermal loads. Bonding the aluminum nitride dielectric layer (AlN) directly to a low coefficient of thermal expansion (CTE) aluminum silicon carbide (AlSiC) cold plate using copper-aluminum (Cu-Al) transient liquid phase (TLP) bonding has been shown to improve the mechanical reliability of the power electronic packages while making the package more compact by bringing the cooling solutions closer to the devices. This study aims to characterize the Cu-Al bonds formed during the TLP bonding of AlSiC with three different power electronics substrates: pure aluminum nitride (AlN), aluminum (DBA), and copper (DBC). The material compositions and microstructures of the bonds were analyzed using scanning electron microscopy (SEM), x-ray spectroscopy (EDS), confocal scanning acoustic microscopy (C-SAM), and x-ray diffraction (XRD). ..alpha..-Al solid compound was identified as the dominant phase in AlN-AlSiC and Al-AlSiC, with a notable presence of SiC particles. In contrast, three intermetallic phases - ..theta..-CuAl2, ..eta..-CuAl, and ..gamma..'- Cu9Al4 - were observed in the Cu-AlSiC bond. A computational solid-state diffusion model was developed to predict the intermetallic compounds (IMCs) formed during Cu-Al TLP bonding in each system, which supported the observation that an initial Cu volume fraction of 20 % in the material layers produced a final bond composition of >95 % Al with minimal IMC growth. However, increased Cu concentrations produced higher concentration gradients, leading to increased growth of IMCs, Kirkendall voids, and interstitial cracks.

DIRECT ENERGY CONVERSION↗

Non-linear flow modes of identified particles in Pb-Pb collisions at $ \sqrt{s_{\mathrm{NN}}} $ = 5.02 TeV

The pT-differential non-linear flow modes, v 4,22 , v 5,32 , v 6,33 and v 6,222 for π ± , K ± , K$^0_S$ , $p + \bar{p}, Λ + \bar{Λ}$ and ϕ-meson have been measured for the first time at $\sqrt{s_{NN}}$ = 5.02 TeV in Pb-Pb collisions with the ALICE detector at the Large Hadron Collider. The results were obtained with a multi-particle technique, correlating the identified hadrons with reference charged particles from a different pseudorapidity region. These non-linear observables probe the contribution from the second and third order initial spatial anisotropy coefficients to higher flow harmonics. All the characteristic features observed in previous p T -differential anisotropic flow measurements for various particle species are also present in the non-linear flow modes, i.e. increase of magnitude with increasing centrality percentile, mass ordering at low p T and particle type grouping in the intermediate p T range. Hydrodynamical calculations (iEBE-VISHNU) that use different initial conditions and values of shear and bulk viscosity to entropy density ratios are confronted with the data at low transverse momenta. These calculations exhibit a better agreement with the anisotropic flow coefficients than the non-linear flow modes. These observations indicate that non-linear flow modes can provide additional discriminatory power in the study of initial conditions as well as new stringent constraints to hydrodynamical calculations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗