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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Optical stochastic cooling at Fermilab’s IOTA ring
Stochastic cooling (SC) constitutes one of the greatest conceptual and technological achievements in particle beam cooling. Numerous SC systems have been built in the microwave regime and used to extend the science reach of accelerator facilities worldwide. The ability to sense and correct the particle ensemble using high-bandwidth feedback systems is at the core of the concept. Here, we describe the first realization of SC at optical frequencies and bandwidths. The demonstration was recently carried out at Fermilab’s integrable optics test accelerator (IOTA) storage ring using the transit-time method of optical stochastic cooling (OSC) and achieved an integrated system bandwidth of approximately 20 THz, which is more than 2000 times that of conventional SC systems. This demonstration establishes the foundation for more advanced OSC experiments with high-gain amplification, currently underway at Fermilab, and the eventual application of OSC to colliders and other accelerator facilities.
Abrasion wear at high temperature in particle receiver type Concentrating Solar Power Systems
The use of solid particles as a heat transfer fluid in receivers for concentrating solar powerplants has garnered much attention in the past decade. Particles are not only stable at temperatures above 700 °C but are also able to absorb solar energy directly, which gives them a distinct advantage over conventional molten salts. The use of particles can, however, cause material degradation from the flow of hot or cold particles through discharge hoppers or along the inner receiver surfaces and other system components (e.g. tubes, valves etc.), depending on operating mode of the receiver. Stainless steel alloy 316, nickel-based alloy Inconel® 740H®, Haynes 230, and a 60% alumina, low-cement refractory castable from Allied Mineral Products were tested for wear from first-of-a-kind high-temperature low-velocity abrasion-erosion experiments. The tests are designed to simulate potential conditions in Generation 3 falling particle Concentrating Solar Power (CSP) systems. Simultaneous experiments were conducted at room temperature as well to draw comparison on the role of temperature on abrasion wear rates. It was noted that the abrasion wear rate in candidate materials was driven by the oxidation resistance of the material. The findings from these experiments will be used to determine life-time of critical components in particle receiver concentrated solar powerplants.
Reinforcement Learning for In-Spill Optimization of the Mu2e Resonant Extraction: Compensating Non-Stationarity
We present design considerations and challenges for the fast machine learning component of a third-order resonant beam extraction regulation system being commissioned to deliver steady beam rates to the mu2e experiment at Fermilab. Dedicated quadrupoles drive the tune toward the 29/3 resonance each spill, extracting beam at kV multiwire septa. The overall Spill Regulation System consists of (1) a “slow” process using ~100-spill averages to adjust the base quad ramp infrequently, (2) a feedforward harmonic content compensator, and (3) the “fast” ML agent reacting during each ongoing spill with on-the-fly additive corrections to the sum of (1) and (2). We have demonstrated improved beam-rate steadying for a fast ML agent compared to a PID controller using a quasi-physical spill simulation, and demonstrated distillation of that simulation into a predictive surrogate model. Current work includes a data-and-training pipeline to generate data-aware surrogates with real-world dynamics, even as the dynamics shift unpredictably. The surrogates are to act as RL environments against which to train our fast ML control agents before deploying them on FPGA in the live system. Further current efforts focus on modeling and controlling beam loss around the storage ring, understanding additional available hardware inputs to the model, and the interplay of these with beam-steadying performance.
Microstructure Quantification and Random Forest Regression Models for Li4Ti5O12–Ni Property Prediction
All-solid-state structural lithium-ion batteries are sought to enable all-electric propulsion in next generation aerospace concepts through improved safety and systems level weight savings. In this work, the influence of processing conditions on microstructural evolution was evaluated for anode composites of strain-free Li4Ti5O12 and metallic nickel current collector. Beyond size distributions, this study explored methods of quantifying microstructural features that describe changes in the spatial distribution and coalescence of nickel particles as a function of sample composition and sintering conditions. Processing-microstructure-property relationships were described by microstructure quantifiers including nickel particle count per area, nearest neighbor distance distribution, and edge-to-edge distance distribution. Machine learning methods were applied to compare the relative influence of processing conditions and microstructural features on electrical conductivity and mechanical strength to optimize for simultaneous energy storage and load bearing performance. Insights gained from this work inform future evaluation of alternative energy storage materials and microstructures for multifunctional performance, and generation of microstructural descriptors strengthens modeling across length scales.
One Year in the Extreme Isolation of Antarctica—Is This Enough to Modulate an “Allergic” Sensitization?
(1) Background: After spending a year wintering in Antarctica, individual expedition members have reported increased or even new allergic reactions to environmental allergens after their return. (2) Methods: Blood samples from five overwintering crews were analyzed using the chip based multiplex ALEX Allergy Explorer (MacroArray Diagnostics GmbH, Austria). (3) Results: About one third of the 39 participants displayed specific IgEs against pollen. In most individuals, kinetics showed a reduction in the specific IgE at the time about nine months after deployment to Antarctica. Five participants had the highest specific IgE levels after returning to the “normal” world. The examination of the specific IgE relative to house dust mites and storage mites showed different kinetics. Six out of 10 had the highest specific IgE concentrations at the inner Antarctic measurement time point. These data corresponded well to the general situation in the stations. At the stations themselves, there were almost no pollen particle load, especially at Concordia. (4) Conclusions: Antarctic long-term confinement can induce an altered immune function, which is in some individuals pronounced after return to the familiar allergen environment. Future prospective studies in larger cohorts are needed to further specify these first results.
Computational modeling and validation of a modified Marple cascade impactor
Oak Ridge National Laboratory (ORNL) is investigating respirable aerosol fractions from failed high-burnup (HBU) commercial spent nuclear fuel (CSNF) rods (Montgomery et al., 2022). The work aims to characterize the source term of radioactive aerosols that could result from mechanical failure and handling of failed fuel rods during storage and/or transportation. The experiment involves capturing and characterizing aerosols from a four-point bending experiment of fueled rod segments at ORNL’s Irradiated Fuels Examination Laboratory (IFEL). For this, a Marple cascade impactor (Series 290) with the ability to collect particles up to aerodynamic equivalent diameters of ~15 μm was tested for feasibility. The commercially available Marple cascade impactor design was modified for the experiment, where the cascade inlet was replaced with a 3D printed inlet nozzle. Collection efficiency curves were then generated with the modified impactor, and the cascade’s performance was tested using ISO dust capture experiments followed by SEM analysis of the collection and computational modeling. The current work highlights the performance testing and experimental validation of this modified Marple Impactor for spent nuclear fuel aerosol collection.
Estimation of General Area Dose Rates During Closure Weld Operations on the DOE Standard Canister Pacific Basin Nuclear Conference 2024
The Department of Energy (DOE) Spent Nuclear Fuel (SNF) Road Ready Demonstration Project is an effort to package DOE-managed SNF for road-ready dry storage. A key operation in this demonstration is performing the closure weld on the DOE Standard Canister after it has been loaded with the SNF. Planning the closure weld operations is ongoing and must consider what parts of the operations (if any) can be done manually and what parts must be done remotely. A key parameter to inform the evolving planning of these operations is the dose rate in the vicinity of the canister and the dose hazard posed to the closure weld operators and collocated workers. This study developed a Monte Carlo N-Particle (MCNP) model of the closure weld operation, which was used to estimate general area dose rates as well as dose rates to the welding location, weld operators, and collocated workers. These estimates provide some insight into the potential radiation exposure hazard for workers during the operations and are a factor to be considered in the ongoing development of designs, technology, processes, and administrative controls for packaging DOE-managed SNF for road-ready dry storage.
Neural Network Enhanced RKPM for Electrochemical-Mechanical Coupled Damage Modeling of Energy Storage Materials
Energy storage materials undergo significant charge cycling, which makes understanding their reliability and durability fundamental in predicting performance and service life. Strong electrochemical-mechanical coupling and highly anisotropic material properties contribute to the formation and propagation of micro-cracking, largely along material interfaces and grain boundaries. For Li-ion batteries, for example, lithium moving between electrodes during charging and discharging process causes expansion and contraction of grains, and the strongly anisotropic and nonlinearly [Li]-dependent grain material properties can cause grains to expand into and contract away from each other, leading to chemo-mechanical cracking. In the first part of this work, a RKPM based computational framework for solving the coupled solid-phase lithium conservation with Fickian diffusion and the lithium concentration dependent anisotropic mechanical problem subjected to a highly nonlinear Butler-Volmer boundary condition is introduced. The choice of RKPM completeness conditions for lithium concentration and mechanical deformation fields, and the variational consistency condition for the domain integration of the coupled problem is first determined. In the second part of this work, a neural network-enhanced reproducing kernel particle method (NN-RKPM) [1] is leveraged to accurately capture damage and crack propagation throughout the material, by learning the location, orientation, and sharpness of discontinuity while allowing for a coarser nodal distribution than that is necessary for capturing sharp solution transitions using traditional mesh-based methods. NN-RKPM is used to inform how crack opening and closure in turn affect the coupled chemical equations and material microstructure.
Development of Composite Photocatalyst Materials that are Highly Selective for Solar Hydrogen Production and their Evaluation in Z-Scheme Reactor Designs
The key technology gap preventing a vertically stacked dual-bed particle suspension reactor from achieving the DOE MYRD&D ultimate cost target for H 2 production remains the lack of materials in particle form factor that exhibit ≥10% solar-to-H 2 energy conversion (STH) efficiency as a suspension. Therefore, our project goals centered around strategies to increase the STH efficiency by enhancing photophysical properties of perovskite oxide particles including increased visible-light absorption, increased selectivity for electrocatalysis of the H 2 evolution reaction (HER) and the O 2 evolution reaction (OER) through development of ultrathin oxide coatings, correlating composition and structure to function, and improving understanding of multiscale transport and kinetic processes.
A perspective on single-crystal layered oxide cathodes for lithium-ion batteries
As the demand for lithium-ion batteries grows exponentially to feed the nascent electric-vehicle and grid-storage markets, the need for higher energy density and longer cycle life becomes more apparent. Increasing the nickel content in the layered-oxide cathodes has been a dominant strategy to increase energy density, but this has exacerbated the surface reactivity concerns. Furthermore, the high states of charge associated with increased capacity lead to cracking of the polycrystalline cathode particles, which exposes fresh surfaces and accelerates capacity fade. Single-crystal cathode particles with low susceptibility to cracking have recently taken on intense interest due to their remarkable cyclability. Many different approaches to single-crystal synthesis have been explored, but there has been no systematic analysis of the different techniques to date. Additionally, many reports have taken on a trial-and-error approach, ignoring well established literature on grain growth outside the battery field. This perspective reviews the literature on single-crystal cathode synthesis through the lens of classic grain growth theories, providing insight and hopefully accelerating the adoption of the promising single-crystal cathode morphology.
Deciphering the Conflict Between Ion and Electron Percolating Networks in Solid-State Battery Cathodes
High-energy- and power-density solid state batteries require an optimal cathode composition and microstructural arrangement of cathode active material, solid-state electrolyte, conductive carbon, and binder to simultaneously support lithium-ion transport, electron conduction, and storage capacity. The ion and electron conducting phases in solid-state cathodes counteract each other's percolating networks as their mass ratios increase or decrease relative to each other. Here, we investigate targeted mass ratio variations of argyrodite solid electrolyte and two different types of conductive carbon (particles and fibers) in composite LiNi0.8Mn0.1Co0.1O2 (NMC811) solid-state cathodes to ascertain the ionic-electronic tradeoffs in cathode performance. Through ionic and electronic conductivity measurements on composite cathodes, as well as rate-testing and cycling performance in full cells, it is shown that the conductive carbon fibers form a percolative electronic network within the composite at a lower mass ratio (3-5 wt%) than particulate carbon (>5 wt%). The threshold to achieve electronic percolation coincides with higher accessible capacity in the cathode as the active material particles become electronically connected. However, carbon loadings beyond this percolation threshold lead to increased ion transport resistance, arising from disruptions to ionic conduction pathways and degraded contact at the interface between the electrolyte and active materials. Imaging, spectroscopy, and physics-based models quantitatively describe the relationship between carbon and electrolyte compositions and the cell's capacity and rate performance through percolation theory. This work demonstrates the importance of quantitatively understanding percolating networks in solid-state cells and that strategic engineering of conductive carbon morphologies can further increase the energy- and power-density of solid-state cells.
Enhancing nanostructured nickel-rich lithium-ion battery cathodes via surface stabilization
Layered, nickel-rich lithium transition metal oxides have emerged as leading candidates for lithium-ion battery (LIB) cathode materials. High-performance applications for nickel-rich cathodes, such as electric vehicles and grid-level energy storage, demand electrodes that deliver high power without compromising cell lifetimes or impedance. Nanoparticle-based nickel-rich cathodes seemingly present a solution to this challenge due to shorter lithium-ion diffusion lengths compared to incumbent micrometer-scale active material particles. However, since smaller particle sizes imply that surface effects become increasingly important, particle surface chemistry must be well characterized and controlled to achieve robust electrochemical properties. Moreover, residual surface impurities can disrupt commonly used carbon coating schemes, which result in compromised cell performance. Using x-ray photoelectron spectroscopy, here we present a detailed characterization of the surface chemistry of LiNi0.8Al0.15Co0.05O2 (NCA) nanoparticles, ultimately identifying surface impurities that limit LIB performance. With this chemical insight, annealing procedures are developed that minimize these surface impurities, thus improving electrochemical properties and enabling conformal graphene coatings that reduce cell impedance, maximize electrode packing density, and enhance cell lifetime fourfold. Overall, this work demonstrates that controlling and stabilizing surface chemistry enables the full potential of nanostructured nickel-rich cathodes to be realized in high-performance LIB technology.
Design and Preliminary Testing of a High Performance Antiproton Trap (HiPAT)
Antimatter represents the pinnacle of energy density, offering the potential to enhance current fusion/fission concepts enabling various classes of deep space missions. Current production rates are sufficient to support proof-of-concept evaluation of many key technologies associated with antimatter-derived propulsion. Storage has been identified as a key enabling technology for all antimatter-related operations, and as such is the current focus of this NASA-MSFC effort to design and fabricate a portable device capable of holding up to 10(exp 12) particles. Hardware has been assembled and initial tests are underway to evaluate the trap behavior using electron gun generated, positive hydrogen ions. Ions have been stored for tens of minutes, limited by observed interaction with background gas. Additionally, radio frequency manipulation is being tested to increase lifetime by stabilizing the stored particles, potentially reducing their interaction with background gas, easing requirements on ultimate trap vacuum and precision mechanical alignment.
Dynamic Aperture Evaluation for the Hadron Storage Ring in the Electron-Ion Collider
The Electron-Ion Collider (EIC) is aiming at a design luminosity of 1e34 cm⁻²s⁻¹. To maintain such a high luminosity, both beams in the EIC need an acceptable beam lifetime in the presence of the beam-beam interaction. For this purpose, we carried out weak-strong element-by-element particle tracking to evaluate the long-term dynamic aperture for the hadron ring lattice design. We improved our simulation code SimTrack to treat some new lattice design features, such as radially offset on-momentum orbits, coordinate transformations in the interaction region, etc. In this article, we will present the preliminary dynamic aperture calculation results with β^{*}- function scan, radial orbit shift, crossing angle collision, and magnetic field errors.
Slug-flow synthesis of NCMA: Effect of substitution of cobalt with aluminum on the electrochemical performance of Ni-rich cathode for lithium-ion battery
Nickle-rich Li[Ni 1-x-y Co x Mn y ]O 2 (x, y≤0.1) (NCM) layered materials are known as promising cathode materials for next-generation lithium-ion batteries and electric vehicles owing to their high-reversible capacity and operating voltage of up to 3.6 vs Li/Li + . However, issues, such as irreversible phase transition, cation mixing, microcrack formation, thermal and structural stability of the material prevent its widespread adoption. Although, cation doping is a well-known technique to enhance the electrochemical performance of the NCM-based cathode material, the performance of the material is very sensitive to the doping amount. In this study, three Al-doped quaternary Ni-rich cathode materials Li[Ni 0.85 Co (0.1-x) Mn 0.05 Al x ]O 2 (where, x=0–0.04) (NCMA) are synthesized through three-phase slug-flow based continuous manufacturing process followed by high temperature calcination to study the effect of Aldoping on the performance of the cathode material while reducing Co. The slug flow-based production platform has several advantages, like particle size uniformity, high production rate, and homogeneity in elemental distribution. It is found that with an increase in Al content, the specific capacity decreases but the cyclic stability and rate capability increases. Furthermore, optimum Al-doping not only compensates for the adverse effect of low Co by decreasing the extent of cation mixing, but it also minimizes the electrode polarization and cracking of the particles.
Realizing high-capacity all-solid-state lithium-sulfur batteries using a low-density inorganic solid-state electrolyte
Abstract Lithium-sulfur all-solid-state batteries using inorganic solid-state electrolytes are considered promising electrochemical energy storage technologies. However, developing positive electrodes with high sulfur content, adequate sulfur utilization, and high mass loading is challenging. Here, to address these concerns, we propose using a liquid-phase-synthesized Li 3 PS 4 -2LiBH 4 glass-ceramic solid electrolyte with a low density (1.491 g cm −3 ), small primary particle size (~500 nm) and bulk ionic conductivity of 6.0 mS cm −1 at 25 °C for fabricating lithium-sulfur all-solid-state batteries. When tested in a Swagelok cell configuration with a Li-In negative electrode and a 60 wt% S positive electrode applying an average stack pressure of ~55 MPa, the all-solid-state battery delivered a high discharge capacity of about 1144.6 mAh g −1 at 167.5 mA g −1 and 60 °C. We further demonstrate that the use of the low-density solid electrolyte increases the electrolyte volume ratio in the cathode, reduces inactive bulky sulfur, and improves the content uniformity of the sulfur-based positive electrode, thus providing sufficient ion conduction pathways for battery performance improvement.