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At least 703 records · Page 39

The remarkable inefficiency of stratocumulus

Marine stratocumulus clouds play a central role in Earth's climate system by reflecting incoming solar radiation and exerting a strong cooling effect. Their organization into open and closed mesoscale cellular morphologies can be thought of as an example of bistable dynamics driven by aerosol–cloud interactions and mesoscale processes. From the perspective of non-equilibrium thermodynamics, these structures are an example of a far-from-equilibrium open system that continuously produces and exports entropy. While entropy production has been studied in idealized deep convective systems, it has not yet been quantified for shallow clouds. Here, we compute and decompose the internal entropy production of open- and closed-cell stratocumulus using an ensemble of large-eddy simulations. We show that the overall entropy production of stratocumulus is low, reflecting the limited vertical extent and corresponding reduced ability to utilize the energy fluxes at the system's boundaries. Moist processes dominate the overall irreversibility, which, combined with their low entropy production, leads to a mechanical efficiency about an order of magnitude smaller than in deep convective systems. Although the dominant irreversible processes differ between open- and closed-cell regimes, the distributions of total entropy production largely overlap across the ensemble, limiting the ability to distinguish the dynamics of individual cases based solely on total entropy production.

54 ENVIRONMENTAL SCIENCES↗

Microreactor Agile Nonnuclear Experimental Testbed Test Plan

Microreactors are an attractive technology option for kick-starting nuclear innovation if they can be operated at high temperature, yielding high power conversion thermal efficiencies comparable or better than in commercial light water reactors. Microreactors are currently the smallest variation of Small Modular Reactors (SMRs). SMRs are “newer generation reactors designed to generate electric power up to 300 MWe and whose components and systems can be shop-fabricated and then transported as modules to the sites for installation as demand arises.” (IAEA, 2016). Vendors are developing microreactor designs to provide an affordable, potentially mobile source of electricity - see Fig. 1 for an example of a microreactor on a semi-truck. Various microreactor designs are possible including heat pipe- and gascooled options, which are the focus of the nonnuclear testing described in this document. In heat pipe microreactors, high-temperature heat pipes using liquid sodium or potassium working fluid transport fission heat from the core to a heat removal section which in turn transfers heat to the power conversion system working fluid. In a gas-cooled design, He or other gas will flow through a solid monolith of material and transfer heat as the temperature of the gas increases through a heat exchanger to a power conversion unit. The logistics of all these processes will be examined and tested through a series of articles at the nonnuclear test bed at Idaho National Laboratory (INL), the Microreactor Agile Nonnuclear Experiment Testbed (MAGNET) facility. Microreactors designed to produce power of 0.1-20 MWt offer the potential for more affordable nuclear energy for a range of applications. In a heat pipe microreactor, heat pipes, fuel rods, and/or moderator are intermixed in the reactor core assembly. Heat pipes extend from the core region into the heat removal section where the power conversion unit working fluid flows through holes or channels, transferring heat from the heat pipes to the working fluid. In a gas-cooled microreactor, gas flows through the solid monolith region and up into the heat exchanger region, transferring heat to the working fluid. For initial testing, the heat removal working fluid can be a low pressure gas for testing that addresses thermal stresses. In the final application, heat addition to the power conversion working fluid typically occurs at high pressure, supporting operation of an air-Brayton, supercritical CO 2 (SCO2), or He-recuperated Brayton cycle. Various stages of the steps above will be demonstrated through the tests described in this report.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Prognostic simulations of mixed-phase clouds with model AC-1D v1.0: the impact of aerosol types and freezing parameterizations on ice crystal budgets

Mixed-phase clouds at high latitudes contribute to the uncertainty in predicting cloud feedbacks and climate sensitivity, mainly due to the complexity of microphysical processes that influence the partitioning between the supercooled liquid and ice phases, and hence, cloud radiative effects on regional scales. Particularly in Arctic mixed-phase clouds, the activation of ice-nucleating particles (INPs) from various aerosol populations remains a leading source of uncertainty. We developed an aerosol-cloud one-dimensional (AC-1D) model, which provides a novel framework to prognostically treat INP and ice crystal budgets while explicitly accounting for polydisperse and multicomponent aerosol that activate INPs following different freezing parameterizations. The AC-1D model is informed by large-eddy simulations to probe the impact of INP representation on predicted ice crystal number concentrations (N i ) and ice crystal budgets in mixed-phase Arctic stratus. We apply three immersion freezing (IMF) parameterizations, two time-independent (singular) and one time-dependent (classical nucleation theory), to predict the evolution of the INP reservoir and resulting ice crystal budget from polydisperse mineral dust, organic (humic-like substances), and sea spray aerosol particle size distributions. Our analysis focuses on how variations in aerosol number concentration and cloud system parameters such as cloud cooling rate, cloud-top entrainment rate, and ice crystal fall speed influence the INP reservoir and ice crystal budgets. Furthermore, this study investigates the competitive ice nucleation dynamics in mixed aerosol environments and provides a process-level quantification of the INP budget terms, which directly controls ice crystal budgets. For all studied case scenarios, the aerosol types and associated particle size distributions significantly impact INP and N i , and the choice between a time-dependent and a singular freezing description yields orders-of-magnitude differences in the predicted INP and N i over the 10 h simulation time, reflecting typical cloud lifetimes. Our results show that the influence of cloud cooling, INP entrainment, and sedimentation varies significantly depending on the chosen freezing parameterization. These findings underscore the critical need for robust IMF parameterizations and precise cloud system observations to enhance the accuracy of models in predicting mixed-phase cloud structure and evolution.

Arctic clouds↗

Extraction of Pure Plastic Resins From PCR Plastic Waste by Solvent-Targeted Recovery and Precipitation (STRAP)

For this work, we have been developing a solvent‐based plastic recycling technology called STRAP. The technology is based on dissolving a targeted plastic resin in a specific solvent that does not dissolve other resins. We have demonstrated STRAP in thousands of bench scale experiments for a large variety of wastes. Recently we have demonstrated the technology for PCR, using mixed plastic wastes (MPWs), from a wet Material Recovery Facility (MRF). The process includes (1) infrared (IR) characterization to determine the plastic composition for accurate selection of the solvent to be used for the extraction of the pure resins. (2) Shredding to the right size and aspect ratio required for flowable and fast dissolvable process. (3) Mixing the MPW in the first solvent to dissolve the first resin. (4) Filtration of the solution plastic blend, to separate the nondissolved plastic from the solution. (5) Further filtration of the solution to remove micron‐sized particle of pigments and fibers. (6) Cooling for precipitation. (7) Filtration of pure resins. (8) Drying of a pure resin. (9) Extrusion of the resin to pellets. (10) Generating films or other products from the pure resin. Steps 1–10 can be considered as one‐cycle that extracted the first resin. (11) A second resin can be extracted with a respective solvent from the plastic that did not dissolve in the first cycle and following steps 1–10 described above. The process also includes characterization of interim and final products. The effort includes building a pilot system at 25 kg/h throughput. We will present specific results for various PCR.

IR characterization↗

Multiscale and Machine Learning Modeling for Process-informed Microstructure Prediction in Additively Manufactured Materials Using MALAMUTE

Advanced Materials and Manufacturing Technologies (AMMT) program under the Department of Energy Office of Nuclear Energy, aims to develop and qualify additively-manufactured materials for nuclear applications. The key challenges to these efforts are the microstructural variabilities observed on the AM products and their impact on the properties and performance of the material in extreme environments. AMMT is using a combination of high-through-put experimental and modeling techniques to accelerate the qualification efforts. Conventionally, in-situ and ex-situ characterizations and testing are performed to correlate different aspects of the AM process to the final product and its performance. However, adopting a trial-and-error approach to experimentally evaluate the vast range of process parameters required to capture the microstructural variabilities is cost-prohibitive. Modeling and simulation provide a comparatively inexpensive way to understand and correlate the microstructural evolution to the processing conditions. The modeling and simulation work-packages within the AMMT program aims to use physics-based and machine learning modeling capabilities to develop a digital twin for AM that can correlate the process conditions to the final product and establish a process-structure-property-performance (PSPP) correlation for AM materials. The melting and subsequent solidification that occurs during the AM process is a complex phenomenon that requires multiscale multiphysics analysis. Idaho National Laboratory’s (INL) Multiphysics Object-Oriented Simulation Environment (MOOSE), specifically the MOOSE Application Library for Advanced Manufacturing UTilitiEs (MALAMUTE) software, provides an ideal platform for developing the multiphysics multiscale model to explore the intricacies of the microstructural evolution during the AM processes within a single framework. Furthermore, given that such full-fidelity simulations can be computationally intensive, reduced order models are necessary to explore the PSPP space for AM materials in an efficient, reliable, and cost-effective way. This work package focuses on understanding the role of process variabilities on the various microstructural characteristics of the AM materials. Microstructures unique to AM materials, such as compositional micro-heterogeneity and dislocation cells, are of particular interest here since they can influence the creep properties and radiation performance. In fiscal year (FY) 24, we significantly advanced upon our work in the last fiscal year, both on physics-based and ML models. The alloy solidification model available in MOOSE has been extended to incorporate the thermodynamic properties and free energy relevant to 316SS. The model demonstrates the Cr segregation that occurs during solidifcation. It is demonstrated that rate of solidification and solute segregation is primarily influence by the cooling rate dictating the level of freezing. This work captures the microstructural variabilities at the subgrain level that are often missing in the part-scale models. With an aim to connect the microstructural evolution model to realistic process conditions, a reduced order model is developed for predicting the thermal conditions around meltpool from high-fidelity process simulations. Furthermore, machine learning approach is used to accelerate the temperature prediction during the AM process. In the following years, MALAMUTE will be used to connect different aspects of the models and quantitatively predict the microstructural evolution. The developed ML-based surrogate model will consider the process conditions as the input to predict the microstructural features in a cost-effective way. The generated microstructures can be used by other work packages under AMMT to evaluate the properties and environmental response of the material at the mesoscale. Thus, this work help identify the key microstructural features at the subgrain level that are significant in property/performance prediction of the AM products. This work will provide inputs to the large-scale process variability models to reevaluate and validate assumptions/simplifications made in the part-scale models. Furthermore, through active learning this work will help identify the data need from both modeling and experimental sides for development of a robust digital twin for AM.

36 MATERIALS SCIENCE↗

Geometry and size dependent microstructure and crack formation in Rene 41 superalloy fabricated by laser powder bed fusion

This study provides a systematic investigation into the size and geometry-dependent microstructural evolution and cracking susceptibility of LPBF-fabricated Rene 41. By coupling experimental microstructural analysis with thermal modeling, this research uniquely identifies the relationship between geometry-specific thermal histories, carbide coarsening, and liquation cracking. Four different geometries with varying thickness were fabricated with the identical process parameters. It was found that the grain size and morphology are not affected by the part size. However, the thinner parts exhibited coarser sub-grain structures compared to the thicker ones. The crack formation was observed for the parts with cross-sections smaller than 1 mm, whereas thicker parts had high density without any defects. Further, the cracks were observed in the interdendritic regions, suggesting that liquation cracking was the active micro-crack formation mechanism. The detailed microstructural analysis combined with a thermal finite element analysis proved that the heat extraction efficiency was lower for thinner parts causing a lower cooling rate and coarser carbides, making them more susceptible to constitutional liquation. Microhardness measurements were conducted for each geometry and correlated with the observed microstructural variations. The findings highlight the critical need for geometry-specific optimization of LPBF process parameters to mitigate cracking and achieve microstructural uniformity, offering valuable insights into the fabrication of complex, high-performance aerospace components.

36 MATERIALS SCIENCE↗

Mitigation of distortion of Al/steel part under simulated paint baking condition: Experiment and numerical model studies

Multi-material joining of lightweight structures is essential to reduce vehicle weight for more energy savings and less greenhouse gas emission. However, mismatch of thermal expansion coefficient for dissimilar materials during the paint baking process can induce part distortion and joint failure for adhesive bonding. Here, in the present work, a thermomechanical model based on contact mechanics and large deformation theory was developed for dissimilar high-strength Al alloy and steel components to study the distortion mechanism and influential factors of the residual gap. The established model was used to optimize joint conditions, such as pitch distance and part geometry. When a weld pitch is shorter than 100 mm, the maximum gap between Al and steel part can be greatly reduced to 0.1 mm, and the local stress and plastic strain around the joint during the oven heating and cooling cycle are also substantially reduced compared with the long pitch case (900 mm). The numerical modeling results revealed that a comparable bending stiffness ratio between the steel and Al cross sections is critical to the minimization of gap and distortion under paint baking condition. Digital image correlation technique was used to measure the overall part distortion and local strain distribution that were used to validate the model prediction. Weld bonding (adhesive bonding with friction bit joining) process was successfully employed to join Al to steel component without gap opening in adhesive after the paint baking and cooling.

36 MATERIALS SCIENCE↗

Igniting Weak Interactions in Neutron Star Postmerger Accretion Disks

The merger of two neutron stars or a neutron star and a black hole typically results in the formation of a postmerger accretion disk. Outflows from disks may dominate the overall ejecta from mergers and be a major source of r-process nuclei in our universe. We explore the parameter space of such disks and their outflows and r-process yields by performing 3D general-relativistic magnetohydrodynamic simulations with weak interactions and approximate neutrino transport. We discuss the mapping between the initial binary parameters and the parameter space of the resulting disks, chiefly characterized by their initial accretion rate. We demonstrate the existence of an ignition threshold for weak interactions at around ~10 -3 M⊙ s -1 for typical parameters by means of analytic calculations and numerical simulations. We find a degenerate, self-regulated, neutrino-cooled regime above the threshold and an advection-dominated regime below the threshold. Excess heating in the absence of neutrino cooling below the threshold leads to ≳60% of the initial disk mass being ejected in outflows, with typical velocities of ~(0.1–0.2)c, compared to ≲40% at ~(0.1–0.15)c above the threshold. While disks below the threshold show suppressed production of light r-process elements, disks above the threshold can produce the entire range of r-process elements, in good agreement with the observed solar system abundances. Disks below the ignition threshold may produce an overabundance of actinides seen in actinide-boost stars. As gravitational-wave detectors start to sample the neutron star merger parameter space, different disk realizations may be observable via their associated kilonova emission.

79 ASTRONOMY AND ASTROPHYSICS↗

Acquisition and Processing Considerations for Infrared Images of Rotating Turbine Blades

Abstract As designers aim to increase efficiency in gas turbines for aircraft propulsion and power generation, spatially resolved experimental measurements are needed to validate computational models and compare improvement gains of new cooling designs. Infrared (IR) thermography is one such method for obtaining spatially resolved temperature measurements. As technological advances in thermal detectors enable faster integration times, surface temperature measurements of rotating turbine blades become possible to capture including the smallest features. This paper outlines opportunities enabled by the latest IR detector technologies for capturing spatially resolved rotating blade temperatures, while also addressing some of the challenges of implementing IR for turbine rigs such as the one in the Steady Thermal Aero Research Turbine (START) Laboratory. This paper documents critical steps in achieving accurate measurements including calibration, integration times, spatial noise, and motion blur. From these results, recommendations are provided for achieving accurate IR measurements collected in a rotating turbine facility to study film cooling.

Engineering↗

Thermal insulation versus capacitance: A simulation experiment comparing effects of shade and hyporheic exchange on daily and seasonal stream temperature cycles

In streams where water temperatures stress native biota, management of riparian shade or hyporheic exchange are both considered viable management strategies for reducing the peaks of daily and seasonal stream channel temperature cycles. Although shade and hyporheic exchange may have similar effects on stream temperatures, their mechanisms differ. Improved understanding of the heat-exchange mechanisms influenced by shade and hyporheic exchange will aid in the appropriate application of either stream temperature management strategy. To illustrate a conceptual model highlighting shade as ‘thermal insulation’ and hyporheic exchange imparting ‘thermal capacitance’ to a stream reach, we conducted an in-silico simulation modelling experiment increasing shade or hyporheic exchange parameters on an idealized, hypothetical stream. We assessed the potential effects of increasing shade or hyporheic exchange on a stream reach using an established process-based heat-energy budget model of stream-atmosphere heat exchange and incorporated an advection-driven hyporheic heat exchange routine. The model tracked heat transport through the hyporheic zone and exchange with the stream channel, while including the effects of hyporheic water age distribution on upwelling hyporheic temperatures. Results showed that shade and hyporheic exchange similarly damped diurnal temperature cycles and differentially altered seasonal cycles of our theoretical stream. In winter, hyporheic exchange warmed simulated channel temperatures whereas shade had little effect. In summer, both shade and hyporheic exchange cooled channel temperatures, though the effects of shade were more pronounced. Our simple-to-grasp analogies of ‘thermal insulation’ for shade effects and ‘thermal capacitance’ for hyporheic exchange effects on stream temperature encourage more accurate conceptualization of complex, dynamic heat exchange processes among the atmosphere, stream channel, and alluvial aquifer.

54 ENVIRONMENTAL SCIENCES↗

Initial development of a generic fluoride salt-cooled reactor model

Fluoride high-temperature reactors (FHRs) are high-temperature, low-pressure reactor concepts that use tri-structural isotropic (TRISO) fuel and molten fluoride salt coolant. These reactors have the potential to provide both electrical power and high-temperature process heat. We used generic FHR parameters for a pebble-bed FHR to develop an initial model with fresh fuel for a generic FHR (gFHR) in MELCOR and SCALE (NEWT and KENO). In this paper, we present the development of our gFHR models, which will serve as the baseline for a sensitivity and uncertainty analysis to quantify the range of possible source terms for FHRs in severe accidents. We present MELCOR results for fuel and coolant temperatures through the core, a nodalization study for the steady-state thermal hydraulic model, and development of reactor physics models in SCALE. As this work progresses, these models will be used to calculate source terms for a loss-of-forced-flow accident and to conduct a sensitivity study on this accident to establish a range of possible source terms. SCALE will provide reactor physics parameters like isotopic inventory, decay heat generation, and temperature coefficients of reactivity. Using the uncertainty quantification tools within SCALE, we will generate distributions for those parameters and will use the uncertainty quantification code RAVEN or DAKOTA to sample those distributions in MELCOR to quantify the impact of reactor physics and thermal hydraulic uncertainties on FHR source terms. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Ultrasensitive Room Temperature Infrared Photodetection Using a Narrow Bandgap Conjugated Polymer

Abstract Photodetectors operating across the short‐, mid‐, and long‐wave infrared (SWIR–LWIR, λ = 1–14 µm) underpin modern science, technology, and society in profound ways. Narrow bandgap semiconductors that form the basis for these devices require complex manufacturing, high costs, cooling, and lack compatibility with silicon electronics, attributes that remain prohibitive for their widespread usage and the development of emerging technologies. Here, a photoconductive detector, fabricated using a solution‐processed narrow bandgap conjugated polymer is demonstrated that enables charge carrier generation in the infrared and ultrasensitive SWIR–LWIR photodetection at room temperature. Devices demonstrate an ultralow electronic noise that enables outstanding performance from a simple, monolithic device enabling a high detectivity ( D *, the figure of merit for detector sensitivity) >2.44 × 10 9 Jones (cm Hz 1/2 W −1 ) using the ultralow flux of a blackbody that mirrors the background emission of objects. These attributes, ease of fabrication, low dark current characteristics, and highly sensitive operation overcome major limitations inherent within modern narrow–bandgap semiconductors, demonstrate practical utility, and suggest that uncooled detectivities superior to many inorganic devices can be achieved at high operating temperatures.

36 MATERIALS SCIENCE↗

Influence of printing parameters on the mechanical behavior of 3D-printed SS316L parts manufactured using laser hot wire directed energy deposition

Hybrid manufacturing combines the simultaneous benefits of additive manufacturing (complex geometries, part consolidation, and mass customization) with the advantages of subtractive manufacturing (superior surface finish and enhanced dimensional accuracies) by integrating a suite of complementary traditional processes into a base platform of additive manufacturing. The use of hybrid technology has grown in recent years given its capabilities on repairing metallic structures, producing parts with conformal cooling features, and manufacturing functionally graded products. These kinds of capabilities are of great interest to the medical implant, energy, automotive, maritime, and aerospace industry sectors, among many other fields. This work investigated the mechanical properties of stainless steel (SS) 316L as a function of different tool paths strategies using an integrated 5-axis CNC hybrid Mazak system with a laser hot wire deposition system (LHWDS). This study includes the evaluation of different printing parameters and their impact on the quality of the printed bead as well as the incorporation of a structure–property material relationship based on the mechanical performance of the manufactured coupons.

36 MATERIALS SCIENCE↗

Revealing and Engineering Assembly Pathways of 3D DNA Origami Crystals

Recent developments in nanomaterial self-assembly demonstrate the capability to create tailored nanostructures by engineering both the binding coordination and specificity of interactions between material subunits. DNA origami frames allow for the design and fabrication of a broad variety of ordered 3D nanoscale architectures through self-assembly, facilitated by frame-to-frame bonds with designable strength and specificity. While the bond design is critical to lattice formation, the assembly process itself is often dependent on a thermal pathway. Highly ordered nanoscale frameworks, assembled from DNA frames, are predominantly crystallized through thermal annealing pathways that typically follow a “slow” cooling approach, with experiments on the time scale of days yielding DNA origami crystals in the range of 1−10 μm. This extended assembly time scale hinders the study of crystal formation pathways, necessitating a deeper understanding of factors governing successful annealing. Lack of insight into time scale also presents a practical limitation for material fabrication. Here, we investigate key factors affecting lattice assembly pathways and demonstrate that precise engineering of assembly conditions greatly reduces assembly times by up to nearly 2 orders of magnitude. We evaluate the nucleation and growth of crystals via optical and electron microscopy, and small-angle X-ray scattering techniques, mapping the time−temperature-transformation of superlattices from the melt through single-crystal optical tracking. The results show that origami frame assembly can be described by classical nucleation and growth theory, which can, in turn, be used to prescribe the growth of the crystals. Lastly, these findings are applied to demonstrate thermal pathway-dependent assembly, forming distinct assemblies based on different thermal annealing profiles.

36 MATERIALS SCIENCE↗

Reaching the equilibrium state of the frustrated triangular Ising magnet Ca 3 Co 2 O 6

Ca 3 Co 2 O 6 is a frustrated magnet consisting of a triangular arrangement of chains of Ising spins. It shows regular magnetization steps versus magnetic field every 1.2 T that are metastable with very slow dynamics. This has puzzled the community for many years and given rise to numerous potential theories. Here we approach the problem by seeking the elusive magnetic equilibrium state at T=2 K. To this end, we explore two approaches: (1) bypassing the slow dynamics produced by changing fields by instead field-cooling directly to the target temperature and (2) quantum annealing in transverse magnetic fields. While we observe no measurable effect of the quantum annealing in fields up to 7 T, which is likely due to the large Ising anisotropy of Co spins in this material, we find that for the field cooling in longitudinal fields we achieve the predicted equilibrium 1/3 magnetization. We perform Monte Carlo simulations of the ground state phase diagram and we also simulate the quantum annealing process and find good agreement between experiment and theory. Thus we present an investigation of the elusive ground state properties of the canonical frustrated triangular system Ca 3 Co 2 O 6 .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Deconvoluting thermomechanical effects in X-ray diffraction data using machine learning

X-ray diffraction is ideal for probing the sub-surface state during complex or rapid thermomechanical loading of crystalline materials. However, challenges arise as the size of diffraction volumes increases due to spatial broadening and because of the inability to deconvolute the effects of different lattice deformation mechanisms. Here, we present a novel approach that uses combinations of physics-based modeling and machine learning to deconvolve thermal and mechanical elastic strains for diffraction data analysis. The method builds on a previous effort to extract thermal strain distribution information from diffraction data. The new approach is applied to extract the evolution of the thermomechanical state during laser melting of an Inconel 625 wall specimen which produces significant residual stress upon cooling. A combination of heat transfer and fluid flow, elasto-plasticity and X-ray diffraction simulations is used to generate training data for machine-learning (Gaussian process regression, GPR) models that map diffracted intensity distributions to underlying thermomechanical strain fields. First-principles density functional theory is used to determine accurate temperature-dependent thermal expansion and elastic stiffness used for elasto-plasticity modeling. The trained GPR models are found to be capable of deconvoluting the effects of thermal and mechanical strains, in addition to providing information about underlying strain distributions, even from complex diffraction patterns with irregularly shaped peaks.

36 MATERIALS SCIENCE↗

An assessment of the global cooling supply chain and implications for critical minerals

The global room air conditioner (AC) industry has undergone rapid growth, and the U.S. and India now face new supply chain risks due to China’s dominant role in manufacturing and driving demand. As India’s room AC market and related electricity consumption increases with continued economic development, it faces dual challenges of supply chain vulnerabilities and power grid blackouts from higher peak loads. To mitigate supply chain vulnerabilities for high-efficiency cooling equipment and critical mineral inputs to AC components, there is an increasing need to diversify the supply chain and address energy security and peak load risks to both the U.S. and India. This report assesses the potential for diversifying supply chains and scaling up manufacturing of highly efficient cooling equipment technologies and related critical mineral inputs in the U.S. and India. Successful cooperation on these technologies will enable the U.S., India, and their Quadrilateral Security Dialogue (Quad) partners to diversify AC supply chains while meeting India’s large and growing demand for efficient cooling. In the similarly concentrated supply chain for critical minerals, the U.S. and India can work with Japan and Australia to leverage each country’s strengths in diversifying mining, processing, and refining while pursuing alternatives to materials with high supply chain risks and supporting increased recycling and circular economy approaches.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Development of in situ thickness sensor for vapor diffused Nb3Sn films

Fermilab is one of the leaders in development of vapor diffused Nb3Sn films inside niobium cavities. This material has a higher critical temperature (Tc) than niobium, enabling cavity operation at 4.2 K. This higher operational temperature significantly reduces the infrastructure required for cooling compared to 2 K systems, making superconducting radio-frequency (SRF) technology more accessible. Current deposition methods have relied on iterative testing to determine nominal film thickness, a process that can be time-consuming and imprecise. To address this, we are developing a sensor to measure the thickness of Nb3Sn thin film in situ during vapor diffusion. Our design involves the resistance measurement of a thin film of niobium. During coating, the change in resistance reflects the conversion of the film to Nb3Sn, which allows simple integration with the current furnace infrastructure. This sensor would allow real time measurement of the thickness, allowing for increased precision in future depositions.

Howard, K. [Unlisted] (ORCID:0000000325613308)↗