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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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At least 487 records · Page 27

Thermal dynamics of P2-Na 0.67 Ni 0.33 Mn 0.67 O 2 cathode materials for sodium ion batteries studied by in situ analysis

Cobalt-free layered Na 0.67 Ni 0.33 Mn 0.67 O 2 is an attractive cathode material for sodium ion batteries. The thermal stability of cathode materials is crucial to their practical applications. In the current work, we investigate structural and morphological evolution in P2-type Na 0.67 Ni 0.33 Mn 0.67 O 2 cathode materials during annealing via in situ synchrotron X-ray diffraction and transmission electron microscopy. Insights are obtained from the two complementary in situ characterizations (at different length scales) in term of the thermal stability of P2-Na 0.67 Ni 0.33 Mn 0.67 O 2 cathode materials. Here, the results indicate that the hexagonal P2 phase remains unchanged during the heat treatment process, and thermally driven expansion/contraction of lattice parameters exhibit an anisotropic character in the a and c directions. In addition, interfaces/grain boundaries play an important role in the structural stability, which leads to the distinct morphological evolution between the polycrystalline and single-crystal particles.

25 ENERGY STORAGE↗

Generalizing HEPCloud Split Starter for Multiple Sites and Experiments

This talk discusses changes we made to the HEPCloud Split Starter to be able to reuse the software in multiple HPC sites across different experiments. I will explain the changes we made to the configuration system, how we generalized the project’s scripts, and the steps we took to reduce the application’s footprint on HPC shared storage, among other details.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Enhanced Beam Diagnostics with Existing BPPMs via GPU-powered Multi-Particle Simulation

This research aims to utilize the multi-particle code, High-Performance Simulator (HPSim), to realistically model the Side-Coupled-Cavity Linac (CCL) lattice of the LANSCE accelerator. This new model would allow us to predict the beam’s bunch length (the longitudinal spread), which is unavailable for individual accelerating modules or only accessible at the end of the linac. However, a correct bunch length is critical for the high-energy beam transport after the CCL. Its impact would be most significant in the Proton Storage Ring (PSR), where we should be able to reduce losses for the circulating beam. The PSR is scheduled to have a 25% current increase for the neutron spallation target upgrade at the Lujan Center. A highly bunched beam would be necessary to reduce the particle losses and lower the radiation levels produced from the ring. A realistic HPSim model with >1M macro-particles can help tackle the beam losses at the sub-percent level. This new work would also create a realistic surrogate model for future machine learning projects.

43 PARTICLE ACCELERATORS↗

Quantum computing and quantum information storage

Quantum storage, transmission, and processing is the future of information technology. Here, the promise of quantum hardware stems from the inherent complexity of an entangled quantum system—the size of the wave-function scales exponentially with the number of particles, whether represented in real space or in a parameter space. In contrast, a classical N-body system can be completely represented by only 6N variables (positions and momenta of all particles). This complexity of quantum systems creates a yet-unsolved challenge of modeling quantum systems by means of classical computing—the curse of dimensionality. Indeed, although we can easily write the Schrödinger equation for any system of interacting nuclei and electrons, we can only solve it exactly on classical computers for very small systems.

97 MATHEMATICS AND COMPUTING↗

Realizing Steady-State Microbunching with Optical Stochastic Crystallization

Optical Stochastic Cooling (OSC) is a state-of-the-art beam cooling technology first demonstrated in 2021 at the IOTA storage ring at Fermilab's FAST facility. A second phase of the research program is planned to run in early 2025 and will incorporate an optical amplifier to enable significantly increased cooling rates and greater operational flexibility. In addition to beam cooling, an OSC system can be configured to enable advanced control over the phase space of the beam. An example operational mode could enable crystallization, where the particles in a bunch are locked into a self-reinforcing, regular microstructure at the OSC fundamental wavelength; we refer to this as Optical Stochastic Crystallization (OSX). OSX represents a new path toward Steady-State Microbunching (SSMB), which may enable light sources combining the high brightness of a free-electron laser with the high repetition rate of a storage ring. Such a source has applications from the terahertz to the extreme ultraviolet (EUV), including high-power EUV generation for semiconductor lithography. This contribution will discuss the status of the OSC experimental program and its potential to achieve the first demonstration of SSMB during the upcoming experimental run.

43 PARTICLE ACCELERATORS↗

Tracking the evolution of processes occurring in silicon anodes in lithium ion batteries by 3D visualization of relaxation times

An unconventional electroanalytical method has been used for tracking processes in silicon anodes in lithium ion batteries: a 3D visualization of relaxation times. Impedance data of the electrodes were collected at different potentials and different cycles during cyclic voltammetry, and were treated by means of the Distribution of Relaxation Times (DRT) method. A 3D visualization of the results allowed to identify the formation of a solid electrolyte interphase on the anode, composed of two layers with different relaxation times. Such findings are not possible by conventional analysis of impedance data by modeling with equivalent circuits, nor by simple DRT alone. Additionally, it was possible to observe that the characteristic relaxation time of the lithiation of the Si anode becomes smaller upon cycling, indicating that the material experiences structural transformations that allow it to lithiate faster. The result is relevant to motivate the use of micron-sized particles in the anode.

25 ENERGY STORAGE↗

Resolving Charge Distribution for Compositionally Heterogeneous Battery Cathode Materials

The isostructural nature of Li-layered cathodes allows for accommodating multiple transition metals (TMs). However, little is known about how the local TM stoichiometry influences the charging behavior of battery particles thus impacting battery performance. In this work, we develop heterogeneous compositional distributions in polycrystalline LiNi 1–x–y Mn x Co y O 2 (NMC) particles to investigate the interplay between local stoichiometry and charge distribution. These NMC particles exhibit a broad, continuous distribution of local Ni/Mn/Co stoichiometry, which does not compromise the global layeredness. The local Mn and Ni concentrations in individual NMC particles are positively and negatively correlated with the electrochemically induced Ni oxidation, respectively, whereas the Co concentration does not impose a clear effect on the Ni oxidation. The resulting material delivers excellent reversible capacity, rate capability, and cycle life at high operating voltages. Engineering Ni/Mn/Co distribution in NMC particles may provide a path toward controlling the charge distribution and thus chemomechanical properties of polycrystalline battery particles.

25 ENERGY STORAGE↗

Tailored polyMOFs for ion transport in lithium-based battery electrolyte

Owing to their low flammability, solid-state and quasi-solid-state electrolytes are safer alternatives to liquid organic electrolytes for energy storage applications. Metal–organic frameworks (MOFs), with facile functional tunability, long-range order, and rich host–guest interactions, have been implemented as electrolyte materials in a wide range of energy storage applications. In this work, we investigate a class of MOFs called polyMOFs as quasi-solid-state electrolyte materials. Unlike MOF–polymer composites, which are physical mixtures of MOF particles and polymers, polyMOFs are composed of polymeric linkers and metal ion nodes that self-assembled into crystalline and porous framework materials. PolyMOFs thus marry the ionic transport properties of liquid electrolyte and polymers with the synthetic versatility and host–guest interactions of MOFs. We demonstrate that the functionality of the polymer backbone of the polyMOF linker can improve room-temperature ion transport in the material. The polyMOF based on poly(ethylene glycol) (PEG) exhibits greater ionic conductivity, lithium transference number, and lower activation energy than its polyethylene (PE) analog. Supported by solid-state 7 Li nuclear magnetic resonance spectroscopy, we propose these improvements are due to stronger coordination of Li + to oxide sites in PEG, allowing for dissociation of Li and its associated anion. DFT studies further reveal that the confined solvent molecule mediates Li + transport in PEG-functionalized UiO-66 via a metastable adsorption and hopping mechanism. This work lies at the interface of inorganic and polymer electrolytes, unveiling fundamental insights into the design of next-generation ion conductive materials for energy technologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Customized Bayesian optimization for efficient beam tuning at the facility for rare isotope beams

Bayesian optimization (BO) has recently emerged as a powerful approach for on-line beam tuning, and it is rapidly gaining adoption across accelerator facilities due to its flexibility and efficiency in handling complex optimization tasks. At the Facility for Rare Isotope Beams, rapid and reliable tuning is essential to support the delivery of diverse ion species. To improve the practicality of BO in this setting, we implemented several enhancements, including scalarized composite objective construction for multicriteria optimization, asynchronous evaluation for better resource utilization, prior-mean-assisted optimization to accelerate convergence, and a local search strategy for rapid completion of the task. We present the details of these methods, discuss challenges-encountered, and share our experience applying them to specific beam-tuning tasks.

Accelerators & storage rings↗

Aerosol Engineering Facility 2021-22 summary sheet [Slides]

The Aerosol Engineering Facility solves problems that involve radioactive particulates, including HEPA air filters, storage containers, exhaust stacks, and continuous air monitors. Other work includes silica dust sampling, bioaerosols, and insecticide sprays. Aerosol technology science describes the behavior of microscopic and nano-sized particles, in both molecular and continuum gas flow regimes.

36 MATERIALS SCIENCE↗

A control oriented comprehensive degradation model for battery energy storage system life prediction

In order to ensure that stationary battery energy storage systems (BESSs) provide reliable energy buffering, both for power quality and economic purposes, the degradation must be considered. Cell degradation involves various side reactions and is highly dependent on its operating conditions. To accurately track cell degradation and predict its impact on battery behavior, a comprehensive physics-based degradation model based on an electrolyte phase-enhanced single particle (SP) model is developed. Key degradation physics, namely solid electrolyte interphase (SEI) layer formation and growth, Li plating on the graphite anode, and Mn dissolution on cathode of nickel-cobalt-manganese oxide (NMC622) are considered. The model is validated against experimental capacity data. The results reveal that the deposition rate of both SEI layer and Li metal increase as the charge voltage increases. At the cathode side, the solvent oxidation rate determines the Mn dissolution rate. As a result, the volume fraction of NMC622 in the cathode continually decreases at a gradually increasing rate.

25 ENERGY STORAGE↗

Metastable nuclear isomers as dark matter accelerators

Inelastic dark matter and strongly interacting dark matter are poorly constrained by direct detection experiments since they both require the scattering event to deliver energy from the nucleus into the dark matter in order to have observable effects. We propose to test these scenarios by searching for the collisional deexcitation of metastable nuclear isomers by the dark matter particles. The longevity of these isomers is related to a strong suppression of γ- and β-transitions, typically inhibited by a large difference in the angular momentum for the nuclear transition. The collisional deexcitation by dark matter is possible since heavy dark matter particles can have a momentum exchange with the nucleus comparable to the inverse nuclear size, hence lifting tremendous angular momentum suppression of the nuclear transition. This deexcitation can be observed either by searching for the direct effects of the decaying isomer, or through the rescattering or decay of excited dark matter states in a nearby conventional dark matter detector setup. Existing nuclear isomer sources such as naturally occurring 180m Ta, 137m Ba produced in decaying Cesium in nuclear waste, 177m Lu from medical waste, and 178m Hf from the Department of Energy storage can be combined with current dark matter detector technology to search for this class of dark matter.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Electrodepositable battery electrode coating compositions having coated active particles

The present invention is directed towards an electrodepositable coating composition comprising an electrochemically active material comprising a protective coating; an electrodepositable binder; and an aqueous medium. Also disclosed herein is a method of coating a substrate, as well as coated substrates and electrical storage devices.

Oakes, Landon J.↗

Co-optimizing water-alternating-carbon dioxide injection projects using a machine learning assisted computational framework

In this report, a robust machine-learning-based computational framework that couples multi-layer neural network (MLNN) proxies and a multi-objective particle swarm optimizer (MOPSO) to design water-alternating-carbon dioxide injection (CO 2 -WAG) projects is presented. The proposed optimization protocol considers various objectives, including oil recovery and CO 2 storage volume. Expert MLNN systems are trained and employed as surrogate models of the high-fidelity compositional simulator in the optimization workflow. When multiple objective functions are considered, two approaches are employed to treat the objectives: the weighted sum method and the Pareto-front-based scheme. A field-scale implementation focusing on tertiary recovery in the Morrow B formation at Farnsworth Unit (FWU) is presented. The developed Pareto-optimal solutions indicate the maximal available oil production can be 1.64 × 10 7 barrels and maximal carbon storage can achieve 2.35 × 10 7 tons. Trade-offs factor is defined to divide the constructed Pareto front into 4 sections with the trade-off factors’ value ranges from 0.35 to 49.9. This work also compares the optimum solution found by the aggregative objective function and the solution repository covered by the Pareto front that considers the physical and operational constraints and reduces uncertainties involved by the multi-objective optimization process. Our comparison indicates multiple solutions exist to satisfy the objective criteria of the WAG design, and these results cannot be found using the traditional weighted sum method. The Pareto front solution can provide more options for project designers, but decisions regarding necessary trade-offs must be made using the solution repository to balance the project economics and CO 2 storage amount.

10 SYNTHETIC FUELS↗