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At least 307 records · Page 17

ORNL Design Engineering Library: Validated Thermoelectric Digital Twins

Radioisotope thermoelectric generators (RTGs) serve a crucial role in supplying thermal and electrical energy for reliable and long-duration power in remote and extreme environments. The thermal energy is provided by the decay of radioisotopes and is converted into electrical energy using the steady-state thermoelectric process by exploiting the Seebeck effect. Maintaining a thermal gradient through the material is necessary to drive current production. Modern predictive multi-physics tools are able to effectively describe the complex and strongly coupled phenomena needed for accurate model-based system engineering efforts needed to develop higher performing RTGs. Experimental validation of model simulations is essential to confirm the accuracy, reliability, and applicability of predictive multiphysics tools. Validation fosters confidence among users, helps meet regulatory requirements, and contributes to the ongoing improvement of simulation techniques, ultimately leading to better, safer, and more efficient designs and processes. Validated models can then be used as digital twins and can be interrogated to understand and quantify the performance gaps between theoretical and physical systems. These insights can be used to build higher performing systems.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Design and Analysis of an Integrated Additively Manufactured Test Article for Plasma-Facing Components

Current plasma-facing components (PFCs) used in helium-cooled divertor modules are complex structures with tungsten tile, steel sleeve components, and cartridges, all assembled in a helium-cooled multiple jet (HEMJ) structure. The goal of this project is to simplify the complex PFC design using additive manufacturing techniques to create a single integrated tungsten test article. Apart from the flexibility this opens up in exploring a wide array of geometries for the article, having a single integrated article significantly reduces the number of joints and parts in the article, thus reducing chances of leaks. A process called electron beam melting has shown to produce very high-density samples and unique geometries, enabling HEMJ or similar designs. To validate and optimize this novel design, the model underwent a series of computational fluid dynamics and finite element analysis simulations to replicate steady-state heat flux in the divertors. The simulations presented in this study consider a steady-state base heat flux of 5 MW/m 2 , with water serving as the coolant. Future research will explore the use of helium as a coolant, simulate edge-localized-mode conditions, and include experimental validation. Since 3D-printed tungsten is anisotropic, the build direction versus build plane of the article are taken into consideration for the test article strength. Because of the high operating temperatures and low ductility of tungsten, thermal creep and brittle fracture are important failure mechanisms to consider. In conclusion, the cap is evaluated with various flow velocities and nozzle diameters, and an optimal design choice is made for which this cap will survive the divertor conditions with a conservative safety margin.

Divertor↗

Ab-initio molecular dynamics study of eutectic chloride salt: MgCl2–NaCl–KCl

Ionic liquid materials are viable candidates as a heat transfer fluid (HTF) in a wide range of applications, notably within concentrated solar power (CSP) technology and molten salt reactors (MSRs). For next-generation CSP and MSR technologies that strive for higher power generation efficiency, a HTF with wide liquid phase range and energy storage capabilities is crucial. Studies have shown that eutectic chloride salts exhibit thermal stability at high temperatures, high heat storage capacity, and are less expensive than nitrate and carbonate salts. However, the experimental data needed to fully evaluate the potential of eutectic chloride salts as a HTF contender are scarce and entail large uncertainties. Considering the high cost and potential hazards associated with the experimental methods used to determine the properties of ionic liquids, molecular modeling can be used as a viable alternative resource. In this study, the eutectic ternary chloride salt MgCl 2 –NaCl–KCl is modeled using ab-initio molecular dynamics simulations (AIMDs) in the liquid phase. Using the simulated data, the thermophysical and transport properties of eutectic chloride salt can be calculated: density, viscosity, heat capacity, diffusion coefficient, and ionic conductivity. For an initial model validation, experimental pair-distribution function data were obtained from X-ray total scattering techniques and compared to the theoretical pair-distribution function. Additionally, theoretical viscosity values are compared to experimental viscosity values for a similar system. The results provide a starting foundation for a MgCl 2 –NaCl–KCl model that can be extended to predict other fundamental properties.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Regio- and Stereoselective Lactone Polymerization: Divergent Effect of Catalyst Modification and Monomer Structure

Selective ring-opening polymerization (ROP) of chiral lactones enables access to biodegradable polyesters with precisely controlled microstructures. Here, combined DFT modeling and experimental validation elucidate how fine-tuning of enantiopure SalBinam aluminum catalysts (through introduction of bromine atoms and tert-butyl groups, respectively, in ortho- and para-positions) modulates regio- and stereocontrol in the ROP of methyl glycolide (MeG) and lactide (LA). Computations reveal that regioselectivity in MeG polymerization arises mainly from steric repulsion, with a small contribution from weak stabilizing C-H···Br interactions that favor ring-opening at the glycolic site, consistent with the experimentally enhanced regioselectivity for (R)-MeG. In contrast, the same steric congestion at the ligand’s ortho positions destabilizes the key transition states in rac-LA polymerization, reducing the calculated stereoselectivity. Experiments confirm the predicted loss of stereocontrol, yielding nearly atactic PLA under standard conditions. Extension of the computational framework to rac-MeG polymerization promoted by racemic catalyst identified a low-barrier, stepwise polymer chain exchange pathway that rationalizes the experimentally observed syndiotacticity of poly(lactic-co-glycolic acid).

DFT calculations↗

Bioinformatics-aided identification, characterization and applications of mushroom linalool synthases

Enzymes empower chemical industries and are the keystone for metabolic engineering. For example, linalool synthases are indispensable for the biosynthesis of linalool, an important fragrance used in 60–80% cosmetic and personal care products. However, plant linalool synthases have low activities while expressed in microbes. Aided by bioinformatics analysis, four linalool/nerolidol synthases (LNSs) from various Agaricomycetes were accurately predicted and validated experimentally. Furthermore, we discovered a linalool synthase (Ap.LS) with exceptionally high levels of selectivity and activity from Agrocybe pediades, ideal for linalool bioproduction. It effectively converted glucose into enantiopure (R)-linalool in Escherichia coli, 44-fold and 287-fold more efficient than its bacterial and plant counterparts, respectively. Phylogenetic analysis indicated the divergent evolution paths for plant, bacterial and fungal linalool synthases. More critically, structural comparison provided catalytic insights into Ap.LS superior specificity and activity, and mutational experiments validated the key residues responsible for the specificity.

59 BASIC BIOLOGICAL SCIENCES↗

A Review of Quantum Computing Technologies in Power System Optimization

As modern power grids increasingly integrate variable renewable generation, distributed energy resources, and energy storage systems, classical optimization techniques are facing unprecedented challenges. This review examines the emerging application of quantum computing to overcome these challenges in power system optimization, including optimal power flow (OPF), unit commitment (UC), economic dispatch (ED), and intelligent switching and topology optimization (IS-TO). Recent research has introduced various quantum methodologies—such as gate-based, annealing-based, variational algorithms, and quantum-inspired algorithms—to address the combinatorial complexity inherent in grid reconfiguration and energy management. The review summaries the quantum algorithms, quantum devices and the power system test cases, highlighting hybrid quantum–classical strategies that leverage the complementary strengths of both paradigms. Some quantum advantages have been observed, including theoretical speedup, accurate simulation results, scalable qubit usage, efficient QUBO mapping. In particular, the review emphasizes the importance of integrating quantum optimization techniques with classical control frameworks, these hybrid approaches demonstrate the potential to improve real-time grid management and operational reliability. A significant portion of the analysis is devoted to the practical limitations of current quantum devices. Present-day quantum hardware, operating in the noisy intermediate-scale quantum (NISQ) era, remains highly sensitive to noise and limited in qubit connectivity, which constrains the scale and accuracy of implemented algorithms. The review delves into specific challenges such as the need for qubit-efficient encoding techniques and error mitigation strategies that are critical for handling real-world grid optimization problems. In addition, the work draws attention to the performance discrepancies between theoretical quantum speedups and experimental validations, underscoring the importance of rigorous benchmark studies using representative power grid test cases. In summary, this review highlights both the promise and limitations of quantum computing for power system optimization. It provides a comprehensive overview of the state-of-the-art technologies, categorizes recent advancements in algorithm design, and discusses practical considerations for implementation, and serves as an informative resource on current research. Future research directions include developing robust hybrid frameworks, advancing qubit-efficient formulations, and scaling up experimental demonstrations to confirm the theoretical advantages of quantum methods in large-scale power system operations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Evaluating E. coli genome‐scale metabolic model accuracy with high‐throughput mutant fitness data

Abstract The Escherichia coli genome‐scale metabolic model (GEM) is an exemplar systems biology model for the simulation of cellular metabolism. Experimental validation of model predictions is essential to pinpoint uncertainty and ensure continued development of accurate models. Here, we quantified the accuracy of four subsequent E. coli GEMs using published mutant fitness data across thousands of genes and 25 different carbon sources. This evaluation demonstrated the utility of the area under a precision–recall curve relative to alternative accuracy metrics. An analysis of errors in the latest (iML1515) model identified several vitamins/cofactors that are likely available to mutants despite being absent from the experimental growth medium and highlighted isoenzyme gene‐protein‐reaction mapping as a key source of inaccurate predictions. A machine learning approach further identified metabolic fluxes through hydrogen ion exchange and specific central metabolism branch points as important determinants of model accuracy. This work outlines improved practices for the assessment of GEM accuracy with high‐throughput mutant fitness data and highlights promising areas for future model refinement in E. coli and beyond.

59 BASIC BIOLOGICAL SCIENCES↗

Enhanced Interfacial Bonding of Graft Copolymers

To understand how thermoplastic welding strength can be tuned through chemical modifications and macromolecular topology, we combined coarse-grained molecular dynamics (MD) simulations with experimental validation. Our simulations examined the diffusion dynamics of both linear and graft polymers across representative interfaces, revealing that diffusion-controlled interdigitation follows a power law, with the exponent decreasing from 0.34 to 0.11 as grafting density increases from 7.5 to 196% (with side chains grafted to both sides of a monomer unit). The addition of side chains enhances welding efficiency, as dense bottlebrush polymers with high grafting density reach maximum rupture strength faster than linear polymers. However, their saturated rupture strength is lower. This observation is subsequently corroborated by experimental lap-shear tests comparing linear polyethylene with octene grafted polyethylene elastomers. Our MD simulations show that unlike linear polymers, where backbone entanglements dominate, the grafted side chains introduce mechanisms in addition to entanglement dilution. The rapid interdigitation of side chains creates a dense mesh of entropic van der Waals contacts, which can also enhance the film welding. Furthermore, our MD simulations reveal a brittle rupture behavior in linear and comb-like (mildly grafted) polymers, while bottlebrush (densely grafted) polymers display elastomeric behavior with a pronounced stress plateau prior to fracture. Our simulations deconvolute the influence of polymer topology on deformation behavior. The rate of polymer deformation becomes lower than the applied strain rate prior to rupture, and the onset of this deviation is progressively delayed from linear to bottlebrush polymers. This trend highlights the critical role of molecular architecture in governing the mechanical response. In conclusion, these results provide deeper insight into the underlying welding mechanisms of topological polymers and present a potential approach for mitigating the interface anisotropy that is inherent in advanced manufacturing techniques such as fused filament fabrication.

graft copolymers↗

Chemical looping air separation with Sr 0.8 Ca0.2Fe 0.9 Co 0.1 O 3-δ perovskite sorbent: Packed bed modeling, verification, and optimization

Chemical looping air separation (CLAS) represents a promising approach for efficient O 2 production from the air. This present study aims at optimizing the absorber/desorber operations and the separation process with extensive experimental validation. Specifically, a one-dimensional packed bed model was developed to investigate the CLAS operation with a Sr 0.8 Ca 0.2 Fe 0.9 Co 0.1 O 3-δ perovskite sorbent. The redox thermodynamics of perovskite sorbent was measured by TGA and then incorporated into a linear driving force model to describe the O 2 absorption and desorption rates. Both 4-step and 5-step air separation cycle configurations, with various cyclic structures, were performed in a subpilot-scale packed bed. The model predicted O2 purity and productivity were consistent with experimental results, supporting its accuracy and applicability. Parametric analysis and multi-objective optimization were further carried out to assess the performance of CLAS. Both O 2 purity and recovery increased monotonically with the cycle time, airflow rate, steam flow rate, and absorption pressure. Meanwhile, optimal O 2 productivity and power consumption can only be achieved by specific combinations of these parameters. The optimized results showed that CLAS can be highly competitive when compared to conventional pressure swing adsorption (PSA) or cryogenic distillation. The 5-step cycle configuration achieved a minimum power consumption of 118 kW·h for producing 1 ton O 2 with ≥ 95% purity. The maximum O 2 productivity reached 0.0932 g O2 /(g sorbent ·h) with 390 kW·h/ton O 2 of energy consumption (95% pure). The optimization results also indicate that CLAS can potentially be more efficient than cryogenic distillation even when the required O 2 purity is above 99%.

42 ENGINEERING↗

Design, fabrication, and testing of diamond axicons for X-ray microscopy applications

This work presents the design, fabrication, and experimental validation of a refractive diamond axicon for X-ray beam shaping. The diamond axicon was developed to overcome the limitations of polymer-based axicons particularly for application in Transmission X-ray Microscopy (TXM) systems, offering superior mechanical strength, thermal stability, and radiation resistance, making it ideal for synchrotron applications. The axicon was fabricated using femtosecond laser ablation and tested at 11 keV under various coherence conditions. Results demonstrated that the axicon efficiently transformed the X-ray beam into a ring-shaped profile with over 80% transmission. Simulations confirmed the experimental findings and highlighted the potential for further improvements. This work paves the way for the use of diamond axicons in next-generation synchrotron facilities, with future efforts focusing on optimizing fabrication and testing the axicon in full TXM systems.

Samadi, Nazanin↗

Machine-Guided Design of Oxidation-Resistant Superconductors for Quantum Information Applications

Decoherence in superconducting qubits has long been attributed to two-level systems arising from the surfaces and interfaces present in real devices. A recent significant step in reducing decoherence was the replacement of superconducting niobium by superconducting tantalum, resulting in a tripling of transmon qubit lifetimes (T1). The identity, thickness, and quality of the native surface oxide, is thought to play a major role, as tantalum only has one oxide whereas niobium has several. Here we report the development of a thermodynamic metric to rank materials based on their potential to form a well-defined, thin, surface oxide. We first computed this metric for known binary and ternary metal alloys using data available from the Materials Project and experimentally validated the strengths and limits of this metric through the preparation and controlled oxidation of eight known metal alloys. Then we trained a convolutional neural network to predict the value of this metric from atomic composition and atomic properties. This allowed us to compute the metric for materials that are not present in the Materials Project, including a large selection of known superconductors, and, when combined with Tc, allowed us to identify new candidate superconductors for quantum information science and engineering (QISE) applications. We tested the oxidation resistance of a pair of these predictions experimentally. Our results are expected to lay the foundation for the tailored and rapid selection of improved superconductors for QISE.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Development of an Advanced Hydrogen Energy Storage System using Aerogel in a Cryogenic Flux Capacitor

The Cryogenic Flux Capacitor (CFC) is a cold, dense fluid storage core with integrated design features that afford the designer flexibility and provide new possibilities for the storage and discharge of energy. The stored energy, in this case, is represented by hydrogen physically bonded within the nanoscale pores within the aerogel composite blanket material, and the process of bonding or debonding is governed by the principles of physical adsorption (physisorption) and thermodynamics. The large surface area afforded by the nanoporous aerogel (~1,000 m 2 /g) allows for storage densities close to, or in some cases exceeding, that of normal boiling point liquids. Its performance easily exceeds what can be achieved via ambient temperature and high-pressure gas storage for an equivalent volume. CFC storage is predicted to be easily scalable, constructed from readily available commercial materials, and lends itself to a range of pressure applications. The project team designed and manufactured the CFC, integrating it into a set of temperature-controlled flow loops. The CFC test setup was validated against existing data from previous NASA work. Tests used bottled hydrogen gas for test validation. A cryogenic fluid, nitrogen, flowed through a metered control system. Hydrogen temperature, pressure, and flow rates, as well as the temperature control targets, provided all necessary control targets. The team analyzed the recorded data and updated the Technology Maturation Plan based on the results of the test, making recommendations for a follow-up test, scale-up, and maturation pathway. For the engineering development and maturation of CFC hydrogen storage technology, a Techno-Economic Assessment (TEA) and Commercialization Plan for the integration of this technology with various power generation assets were produced. A companion analytical model was developed, experimentally validated, compared against performance metric, and used to tune the model and scale up the technology.

08 HYDROGEN↗

A review of experimental methods to determine bioaerosol transfer in energy recovery ventilators

Increasing ventilation is an effective method to reduce indoor airborne disease transmission. An Energy recovery ventilator (ERV) is a passive energy recovery device used to reduce the energy consumption of heating, ventilation and air-conditioning (HVAC) systems for conditioning the ventilation air. It preconditions the ventilation air by transferring energy from building exhaust air. Therefore, the ventilation and exhaust air streams interact directly/indirectly in the ERV for energy transfer. It is surmised that the ERV may transfer bioaerosols (with pathogens) from the exhaust air to ventilation air, resulting in the spread of infectious diseases. Consequently, many pandemic HVAC guidelines recommend that the use of ERVs be limited. This is a highly unsustainable direction given the increased energy requirements associated with the high ventilation provision advocated for pandemic operation. It must be noted that no validated experimental evidence exists in literature for bioaerosol transfer in ERVs. Hence, it is necessary to conduct extensive bioaerosol transfer research before adopting the unsustainable practice of limiting the utilization of ERVs. The main objective of this review study is to summarize the experimental methods and instrumentation for bioaerosol transfer research in ERVs. This comprehensive article provides a detailed overview of the generation, sampling, and analysis of bioaerosols for conducting the experiments. Further, it explains the possible mechanisms for bioaerosol transfer in various types of ERVs based on which the ERVs that need immediate attention are identified. The main contribution of this research paper is that it provides a novel experimental method which encompasses the biosafety aspects, instrumentation, performance parameters and uncertainties in conducting virus contained bioaerosol transfer study in ERVs. The findings from this review will be helpful in designing bioaerosol transfer experiments and developing future ERV test standards for such experiments.

42 ENGINEERING↗

Demonstration of reconstruction-free static magnetic control of DIII-D plasma with deep reinforcement learning

This paper presents the development and experimental validation of a reinforcement learning (RL)-based magnetic controller on the DIII-D tokamak. The controller directly maps raw magnetic diagnostic signals to actuator commands, replacing the traditional isoflux control algorithm based on equilibrium reconstruction. Four RL controllers are trained using the Soft Actor–Critic algorithm with an asymmetric Actor–Critic architecture in the NSFsim simulator. All controllers are deployed in the DIII-D Plasma Control System and operated with a 4 kHz feedback loop. Two randomization strategies are evaluated during training: evolving kinetic profiles and fixed kinetic profiles within each episode. The latter approach is found to better capture experimental deviations in the current density profile and to provide overall improved control performance. Robust operation is demonstrated across heating power scans in both L- and H-mode plasmas, as well as during transient events such as L–H transitions and pellet injections. Control errors in plasma shape and radial position remained within 1.5–2.0 cm and 1 cm, respectively. A notable discrepancy was observed in the vertical X-point position, with errors of up to approximately 4 cm, attributed to the current density distribution mismatches between simulations and experiments.

DIII-D↗

Development of Additive Manufacturing for Ceramic Matrix Composite Vanes

This report discusses the development of additive manufacturing for polymer-derived ceramic materials to create novel cooled gas turbine airfoils made from ceramics. Gas turbine engines have extremely high temperatures in the hot section of the engine that exceed the melting point of nickel superalloy materials that the engine is made from. Advanced cooling technologies have been developed over decades for metallic parts. Ceramic materials have higher temperature capabilities than superalloys, but are difficult to shape in the complex designs used in modern turbines. Several thrusts were investigated during the project, including development of higher material strength resins, improvement of ultraviolet (UV) photopolymerization and post-processing techniques to increase survivability of ceramic parts, thermomechanical modeling of novel ceramic airfoil designs for higher cooling effectiveness, and experimental validation of the modeling and manufacturing in a turbine vane test facility at nondimensional conditions that are relevant to modern gas turbines. Some major findings of the work include a significant increase in ceramic survivability during pyrolysis (a high temperature process that converts the organic material to a ceramic) by adjusting the composition ratios of the resins, as well as a tolulene soak after printing to remove unreacted polymer material. Thermomechanical optimization of the internal cooling structure indicated that a high density pin fin array would enable an 80% increase in overall cooling effectiveness relative to a baseline geometry, which was later verified during experimental testing in a high speed linear cascade. Ceramic vanes were tested at Mach numbers of up to 0.9 which is relevant to modern gas turbines. High temperature capability of the ceramic vanes was not tested in this work.

36 MATERIALS SCIENCE↗

Development and validation of a software for simulating γ-γ coincidence emission and detection probabilities

Gamma-gamma coincidence spectrometers have the potential to significantly enhance detection sensitivity for ultra-trace radionuclide measurements. The implementation of these spectrometers, however, is limited by the complexity of acquisition hardware, data processing and quantification. This work reports development of a novel radionuclide quantification software for γ-γ coincidence measurements. For any radionuclide, the software parses the Evaluated Nuclear Structure Data File (ENSDF) database, recursively simulating all possible γ-γ coincidence signatures and their respective emission and detection probabilities. Implemented using Python programming language, the software employs several strategies to boost overall computational performance. Since coincidence-based spectrometers are of notable interest in monitoring compliance for the Comprehensive Nuclear-Test-Ban Treaty (CTBT), the software’s execution was tested for 84 CTBT-relevant radionuclides. To date, the software has been experimentally validated for 15 radionuclides using the Advanced Radionuclide Gamma spectrOmeter (ARGO) at Pacific Northwest National Laboratory, USA (PNNL). Notably, the software can be operated in convergence mode, whereby coincidence detection efficiency’s convergence behavior can help avoid unreliable radionuclide activity estimates. With growing number of coincidence spectrometers worldwide, this paper aims to assist the radiation metrology community in developing similar software for their system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Unraveling fundamental mechanisms of silicon nitride crystallization in microelectronics manufacturing

This research project investigates the fundamental mechanisms of silicon nitride (SiN) crystallization, aiming to enhance the understanding of this critical material in microelectronics manufacturing. Through a collaborative effort between Sandia National Laboratories, the University of Tennessee, and the University of Florida, we developed a comprehensive framework that integrates experimental techniques, atomistic modeling, meso-scale simulations, and an integrated multi-scale model to capture this physical phenomenon on multiple time and length scales . The project developed a new machine learning based atomistic potential and utilized advanced phase field modeling to capture the complexities of polycrystalline growth and the influence of mechanical stresses on crystallization dynamics. By employing a grain tracker algorithm, the meso-scale model effectively identified and tracked individual crystal grains, enabling the simulation of anisotropic growth behaviors reflective of SiN’s physical properties. The integration of atomistic simulations with meso-scale modeling created a powerful multi-scale framework that validated atomistic inputs and enhanced predictive accuracy for crystallization dynamics at larger scales, validated experimentally. This adaptable modeling capability not only accelerates development times by informing manufacturing processes but also serves as a valuable starting point for understanding crystallization physics in similar materials. The insights gained from this research unlock new opportunities for the development of advanced materials tailored for future microelectronics and photonics applications. Overall, this project represents a significant advancement in understanding of fundamental physics of SiN and establishes a foundation for future research in material science, bridging the gap between atomic-level phenomena and macroscopic material behaviors for practical applications.

36 MATERIALS SCIENCE↗

Numerical and Experimental Study of a Novel Additively Manufactured Metal-Polymer Composite Heat-Exchanger for Liquid Cooling Electronics

In order to meet increasing power-dissipation requirements of the electronics industry, compact, low-cost, and lightweight heat exchangers (HXs) are desired. With proper design, materials, and manufacture, polymer composite heat exchangers could meet these requirements. This paper presents a novel crossflow air-to-water, low-cost, and lightweight metal-polymer composite HX. This HX, which is entirely additively manufactured, utilizes a novel cross-media approach that provides direct heat exchange between air and liquid sides by using connecting fins. A robust numerical model was developed, which includes the dimensional effects of additive manufacturing. The study consists of a simplified 3D CFD model based on ellipsoidal-shaped staggered tube banks for the laminar range. It then uses an analytical approach to compute entire HX performance. The model is validated experimentally within 8% for thermal performance, 12% for air-side impedance, and 18% for water-side impedance. Finally, HX is compared with a conventional CPU radiator and performs within 10% of the conventional unit for reasonable flow rates and pressure-drop ranges. Moreover, HX also provides added design and cost advantages over the conventional unit, which makes the HX a potential candidate for electronic cooling applications.

30 DIRECT ENERGY CONVERSION↗