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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 109 records · Page 6

Duality defect in a deformed transverse-field Ising model

Physical quantities with long lifetimes have both theoretical significance in the study of quantum many-body systems and practical implications for quantum technologies. In this manuscript, we investigate the roles played by topological defects in the construction of quasiconserved quantities, using as a prototypical example the Kramers-Wannier duality defect in a deformed one-dimensional quantum transverse-field Ising model. We construct the duality defect Hamiltonian in three different ways: half-chain Kramers-Wannier transformation, utilization of techniques in the Ising fusion category, and defect-modified weak integrability breaking deformation. The third method is also applicable for the study of generic integrable defects under weak integrability breaking deformations. We also work out the deformation of defect-modified higher charges in the model and study their slower decay behavior. Furthermore, we consider the corresponding duality defect twisted deformed Floquet transverse-field Ising model and investigate the stability of the isolated zero mode associated with the duality defect in the integrable Floquet Ising model, under such weak integrability breaking deformation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Bayesian learning for rapid prediction of lithium-ion battery-cycling protocols

Advancing lithium-ion battery technology requires the optimization of cycling protocols. A new data-driven methodology is demonstrated for rapid, accurate prediction of the cycle life obtained by new cycling protocols using a single test lasting only 3 cycles, enabling rapid exploration of cycling protocol design spaces with orders of magnitude reduction in testing time. We achieve this by combining lifetime early prediction with a hierarchical Bayesian model (HBM) to rapidly predict performance distributions without the need for extensive repetitive testing. The methodology is applied to a comprehensive dataset of lithium-iron-phosphate/graphite comprising 29 different fast-charging protocols. HBM alone provides high protocol-lifetime prediction performance, with 6.5% of overall test average percent error, after cycling only one battery to failure. Here, by combining HBM with a battery lifetime prediction model, we achieve a test error of 8.8% using a single 3-cycle test. In addition, the generalizability of the HBM approach is demonstrated for lithium-manganese-cobalt-oxide/graphite cells.

25 ENERGY STORAGE↗

LDRD for a high-current polarized-beam photogun

The electron accelerator driving the Ce+BAF conversion target requires a spin-polarized photogun capable of delivering a CW beam current of at least 1 mA. As the high beam current limits the useful operating time of the gun between photocathode reactivations due to ion back-bombardment, it is critical to increase the charge lifetime. A Jefferson Lab LDRD project aims to calibrate the simulation models needed to predict photocathode lifetime as a function of electrostatic optics and drive laser parameters in order to design a gun providing at least 1000 C charge lifetime. A prototype gun demonstrating the validity of the scaling predictions will be built and tested at the Gun Test Stand. I will describe the background and progress of this project and give an outlook on the expected performance.

Bruker, Max [Thomas Jefferson National Accelerator↗

Comparing Parallel Plastic‐to‐X Pathways and Their Role in a Circular Economy for PET Bottles

Abstract The United States generates the most plastic waste of any country and is a top contributor to global plastic pollution. Multiple end‐of‐life strategies must be implemented to minimize environmental impacts and retain valuable plastic material, but it is challenging to compare options that generate products with different lifetimes and utilities. Herein, they present a material flow model equipped with consequential life cycle assessment, cost analysis, and a plastic circularity indicator that considers product quality and lifetime. The model is used to estimate the greenhouse gas (GHG) emissions, circularity, and cost of polyethylene terephthalate (PET) bottle mechanical downcycling to lower‐quality resin, closed‐loop glycolysis to food‐grade PET, upcycling to glass fiber‐reinforced plastic, and conversion to non‐plastic products (electricity, oil) on a United States economy‐wide basis for the year 2020. A brute force algorithm suggests that a combination of 68% glycolysis, 11% mechanical recycling, 6% upcycling, 9% landfilling, and 5% incineration can minimize the cost and GHG emissions and maximize the circularity of the current PET economy. However, uncertainty around transportation distances, materials recovery facility efficiencies, and recycling yields can result in different “optimal” pathway mixes. This flexible framework enables informed decision‐making to move toward a cost‐ and environment‐conscious circular economy for plastic.

09 BIOMASS FUELS↗

Thermomechanical Stress and Creep-Fatigue Analysis of a High-Temperature Prototype Receiver for Heating Particles

This work presents a three-dimensional (3D) thermomechanical model of a prototype-scale enclosed light trapping solar receiver for heating particles. Results of the thermoelastic model are used to estimate receiver lifetime under maximum flux conditions. A computational fluid dynamics (CFD) model is first developed to predict the temperature fields in a multi-panel assembly under steady operating conditions. Solar flux distributions on the receiver are obtained from the software package SolTrace and applied to the 3D thermal model. The subsequent particle heating is captured through a simplified 1D energy balance. Panel reradiation is considered through a surface-to-surface radiation model and natural convection loss to the surrounding air is captured in a representative fluid domain surrounding the receiver. The resulting temperature fields from the CFD analysis are used as inputs for a thermoelastic mechanical model with representative boundary conditions. With the resultant temperature and stress fields, a creep-fatigue damage and lifetime analysis is performed using the linear damage accumulation (LDA) theory. The Manson-Coffin formula and Larson Miller correlation are used to calculate the fatigue and creep, respectively. A maximum damage (corresponding to a 30-year service life) is defined for design assessment. The model was first developed and verified in detail by comparing with published results in the literature (temperature and stress profiles and distributions, and creep/fatigue damage fractions) for tubular solar receivers with supercritical carbon dioxide as the working fluid. It was then implemented to model a planar-cavity receiver with various design parameters. Specifically, three different design geometries are considered, and the results show that a maximum temperature of approximately 1200 K could be reached for each design with the given incident solar flux, with the main difference being the distribution of these temperatures. Preliminary resulting stresses for the small-scale prototype without design optimization vary from 20 MPa to 250 MPa for each design, with the maximum stresses occurring on the front face and concave geometry on the side of the panel. In future work, the developed methodology shown here will be applied to analyze a full-scale (50-150 MWth) receiver.

concentrated solar power↗

Lifetime of actin-dependent protein nanoclusters

Protein nanoclusters (PNCs) are dynamic collections of a few proteins that spatially organize in nanometer-length clusters. PNCs are one of the principal forms of spatial organization of membrane proteins, and they have been shown or hypothesized to be important in various cellular processes, including cell signaling. PNCs show remarkable diversity in size, shape, and lifetime. In particular, the lifetime of PNCs can vary over a wide range of timescales. The diversity in size and shape can be explained by the interaction of the clustering proteins with the actin cytoskeleton or the lipid membrane, but very little is known about the processes that determine the lifetime of the nanoclusters. In this paper, using mathematical modeling of the cluster dynamics, we model the biophysical processes that determine the lifetime of actin-dependent PNCs. In particular, we investigated the role of actin aster fragmentation, which had been suggested to be a key determinant of the PNC lifetime, and we found that it is important only for a small class of PNCs. A simple extension of our model allowed us to investigate the kinetics of protein-ligand interaction near PNCs. We found an anomalous increase in the lifetime of ligands near PNCs, which agrees remarkably well with experimental data on RAS-RAF kinetics. In particular, analysis of the RAS-RAF data through our model provides falsifiable predictions and novel hypotheses that will not only shed light on the role of RAS-RAF kinetics in various cancers, but also will be useful in studying membrane protein clustering in general.

59 BASIC BIOLOGICAL SCIENCES↗

How Long Does the Hydrogen Atom Live?

It is possible that the proton is stable while atomic hydrogen is not. This is the case in models with new particles carrying baryon number which are light enough to be stable themselves, but heavy enough so that proton decay is kinematically blocked. Models of new physics that explain the neutron lifetime anomaly generically have this feature, allowing for atomic hydrogen to decay through electron capture on a proton. We calculate the radiative hydrogen decay rate involving the emission of a few hundred keV photon, which makes this process experimentally detectable. In particular, we show that the low energy part of the Borexino spectrum is sensitive to radiative hydrogen decay, and turn this into a limit on the hydrogen lifetime of order 10 30 s or stronger. For models where the neutron mixes with a dark baryon, X, this limits the mixing angle to roughly 10 –11 , restricting the n → XY branching to 10 –4 , over a wide range of parameter space.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Early calendar life and health prediction of silicon batteries via machine learning with uncertainty quantification

Lithium-ion batteries with silicon anodes promise high energy density but are limited by calendar lifetime. Reducing the long iteration time to obtain experimental results requires predicting calendar lifetime early in a cell's life. In this study, we demonstrate that lightweight machine learning models with feature engineering can provide calendar lifetime estimates from early electrochemical signals. After 1 month of electrochemical aging, the best models achieve 10% error in calendar-life prediction and can separate "bad" from "good" lifetime cells with a mean F1 score of 0.857. As battery systems exhibit inherent variability, four methods for uncertainty quantification are compared, and confidence intervals are demonstrated with an uncertainty of +-3.6 months in lifetime prediction. A feature importance analysis indicates that early patterns in voltage decay are the strongest indicators of calendar lifetime. Finally, this modeling approach has high error when generalizing to new electrode chemistries or testing conditions but with appropriately low confidence.

25 ENERGY STORAGE↗

State-dependent motion of a genetically encoded fluorescent biosensor

Genetically encoded biosensors can measure biochemical properties such as small-molecule concentrations with single-cell resolution, even in vivo. Despite their utility, these sensors are “black boxes”: Very little is known about the structures of their low- and high-fluorescence states or what features are required to transition between them. We used LiLac, a lactate biosensor with a quantitative fluorescence-lifetime readout, as a model system to address these questions. X-ray crystal structures and engineered high-affinity metal bridges demonstrate that LiLac exhibits a large interdomain twist motion that pulls the fluorescent protein away from a “sealed,” high-lifetime state in the absence of lactate to a “cracked,” low-lifetime state in its presence. Understanding the structures and dynamics of LiLac will help to think about and engineer other fluorescent biosensors.

Rosen, Paul C. (ORCID:000000017414454X)↗

Multiphysics Modeling of Hydrokinetic Turbine Energy Conversion System

Hydrokinetic turbines (HKTs) hold great promise as a renewable energy source, but high maintenance costs and limited energy output hinder their widespread adoption. The lack of comprehensive research on HKT drivetrain designs creates a knowledge gap in enhancing generation efficiency and cost reduction. A model of the HKT system with a focus on electric drivetrains and power converters is required to address this knowledge gap. This paper first introduces a MATLAB-averaged model integrating electrical-mechanical-thermal domains and aging behaviors within multi-time frames. Then a PLECS model, which incorporates maximum power point tracking and dq reference framed control for AC-DC-AC power converters, is enriched by a dynamic thermal model to predict fast transients accurately. These models optimize the design at the component level, resulting in improved integrated system performance. Furthermore, the validation of the models is carried out through hardware experiments for the averaged model and hardware-in-the-loop testing for the dynamic model.

ADVANCED PROPULSION SYSTEMS,HYDRO ENERGY↗

Uranium-hydrogen reaction mechanism and numerical model

We have developed a numerical model to help predict lifetimes of uranium parts in situations where the uranium surface is exposed to hydrogen in the gas headspace. Assessments can be made based on hydrogen pressure and on an upper limit of size of a surface breached hydride spot (volume of hydride corrosion product produced). The model assumes development of a hydride nucleus at a single arbitrary subsurface location associated with an arbitrary surface defect and follows the development of the hydride nucleus to the break-through phase and further growth to the upper limit of acceptable volume of corrosion product. The model has been developed from an understanding of the hydriding mechanism outlined below in 10 steps and measured rates of hydrogen ingress at several types (chemically) of uranium surfaces at ambient temperature and variable pressure. The key points are 1) that the hydrides nucleate only at locations where a surface defect allows hydrogen ingress (reactant delivery) into the uranium metal subsurface (beyond the oxide), and 2) that the hydrides which eventually reach surface break-through status, nucleate and grow in the near surface (few 10s of micron depth maximum) – those beyond ~50 micron have arrested growth and never reach break-through status.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Diagnostics, Prognostics, and Optimization for Lithium-Ion Battery Systems

Health management of lithium-ion battery systems presents a host of challenges due to their complex physics, large numbers of components, and a wide variety of degradation behaviors across different battery types. Dr. Paul Gasper will present on research from the Electrochemical Energy Storage Group on Lithium-ion battery diagnostics, prognostics, and optimization. Diagnostics research, including state-estimation via machine-learning from electrochemical impedance spectroscopy and DC pulses as well as continuous state-estimation via Kalman filters, will highlight the ongoing challenges for accurately measuring the state of batteries without performing time-consuming characterization tests. NLR's industry-recognized battery prognostics work, which predicts real-world battery degradation by identifying degradation rate models from accelerated aging data using statistical modeling and machine-learning, will be used to demonstrate the critical impact of battery controls, thermal management, and operating strategy on durability and lifetime. Finally, the use of prognostic models for financial or lifetime optimization will be discussed.

25 ENERGY STORAGE↗

Simulation of the NuScale SMR and Investigation of the Effect of Load-Following on Component Lifetimes

The NuScale SMR has been modelled using the Virtual Environment for Reactor Applications (VERA) multiphysics environment and the results compared with the publicly reported data in the Design Certification Application (DCA). The results show an excellent agreement for the compared axial and radial power distributions, temperature coefficients of reactivity, boron and control rod worths, and fast neutron flux. This NuScale model is then used to investigate the effect of different operational modes on reactor components to determine how flexible load-following operation may affect control rod and reactor pressure vessel (RPV) lifetimes. The control rod degradation is confirmed to primarily affect the silver-indium-cadmium (AIC) rod tip. The degradation rate is observed to follow a non-linear function of core power level where the increase in degradation decreases with insertion depth. For the variation in core power levels expected with current load-following schemes, the total control rod degradation is found to be mild, at 5-10% of usable life per cycle for a reactor operating at <80% power. Nonetheless, this enables load following strategies to be confirmed and/or modified to ensure that control rods do not need to be replaced during the 60+ year life of the reactor. The RPV degradation was found to be almost directly proportional to the core power level and was not overly sensitive to flux shape perturbations. Future work is planned using these damage functions to optimize operation over multiple NuScale SMR units and develop strategies for prognostics and health management.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Interplay of freeze-in and freeze-out: Lepton-flavored dark matter and muon colliders

We study a lepton-flavored dark matter model and its signatures at a future muon collider. We focus on the less-explored regime of feeble dark matter interactions, which suppresses the dangerous lepton-flavor-violating processes, gives rise to dark matter freeze-in production, and leads to long-lived particle signatures at colliders. We find that the interplay of dark matter freeze-in and its mediator freeze-out gives rise to an upper bound of around TeV scales on the dark matter mass. The signatures of this model depend on the lifetime of the mediator and can range from generic prompt decays to more exotic long-lived particle signals. In the prompt region, we calculate the signal yield, study useful kinematics cuts, and report tolerable systematics that would allow for a 5 σ discovery. In the long-lived region, we calculate the number of charged tracks and displaced lepton signals of our model in different parts of the detector and uncover kinematic features that can be used for background rejection. We show that, unlike in hadron colliders, multiple production channels contribute significantly, which leads to sharply distinct kinematics for electroweakly charged long-lived particle signals. Ultimately, the collider signatures of this lepton-flavored dark matter model are common among models of electroweak-charged new physics, rendering this model a useful and broadly applicable benchmark model for future muon collider studies that can help inform work on detector design and studies of systematics. Published by the American Physical Society 2024

Astronomy & Astrophysics↗

Energy Migration Processes in Re(I) MLCT Complexes Featuring a Chromophoric Ancillary Ligand

We present herein the synthesis, structural characterization, electronic structure calculations, and ultrafast and supra-nanosecond photophysical properties of a series of five Re(I) bichromophores exhibiting metal to ligand charge transfer (MLCT) excited states based on the general formula fac -[Re(N ^ N)(CO) 3 (PNI-py)]PF 6, where PNI-py is 4-piperidinyl-1,8-naphthalimidepyridine and N ^ N is a diimine ligand ( Re1 – 5 ), along with their corresponding model chromophores where 4-ethylpyridine was substituted for PNI-py ( Mod1 – 5 ). The diimine ligands used include 1,10-phenanthroline (phen, 1 ), 2,9-dimethyl-4,7-diphenyl-1,10-phenanthroline (bcp, 2 ), 4,4'-di- tert -butyl-2,2'-bipyridine (dtbb, 3 ), 4,4'-diethyl ester-2,2'-bipyridine (deeb, 4 ), and 2,2'-biquinoline (biq, 5 ). In these metal–organic bichromophores, structural modification of the diimine ligand resulted in substantial changes to the observed energy transfer efficiencies between the two chromophores as a result of the variation in 3 MLCT excited-state energies. The photophysical properties and energetic pathways of the model chromophores were explored in parallel to accurately track the changes that arose from introduction of the organic chromophore pendant on the ancillary ligand. All relevant photophysical and energy transfer processes were probed and characterized using time-resolved photoluminescence spectroscopy, ultrafast and nanosecond transient absorption spectroscopy, and time-dependent density functional theory calculations. Of the five bichromophores in this study, four ( Re1 – 4 ) exhibited a thermal equilibrium between the 3 PNI-py and the 3 MLCT excited state, drastically extending the lifetimes of the parent model chromophores.

14 SOLAR ENERGY↗

Data for "Gold-Induced Chemical Perturbations in CdTe-Based Photovoltaic Cells"

Back contacting p-type CdTe has been identified as one of the major areas of loss in CdTe photovoltaic (PV) power conversion efficiency (PCE). In research settings, Au is a common contact material due to its ease of use and decent performance. This work provides a detailed investigation into using gold for back contacting As-doped, CdCl2 treated, polycrystalline CdTe that has been exposed to air after absorber processing, another routine practice. First, X-ray photoemission spectroscopy (XPS) is used to determine the native oxide to be 1.6 nm of CdTeO3 using a combination of angle-resolved XPS and the cadmium modified Auger parameter. During gold metallization of CdTe, oxygen and oxidized tellurium are eliminated from the thin CdTeO3 native oxide. The fate of the released oxygen and possibly cadmium and tellurium are not known, but these reaction byproducts can enter the absorber bulk or grain boundaries, stay at the interface, or dissolve in the Au. Interfacial hole barriers between CdTe and Au are measured for samples with and without the native oxide present prior to metallization. Results show that the thin CdTeO3 alleviates the downward band bending by 40 meV from 470 meV to 430 meV even though it is consumed during interface formation. The implications of these chemical reactions on the device are assessed through photoluminescence (PL) spectroscopy which shows losses in internal open circuit voltage (iVoc) from 820 meV to 795 meV, carrier lifetime from 123 ns to 45 ns, and PL quantum yield from 2.9x10-5 to 1.2x10-5. Modeling time-resolved PL lifetimes demonstrates the back surface recombination velocity due to metallization reduces minority carrier lifetimes. These results identify the native oxide and show that it plays an important role in mediating downward band bending along with how the back interface reaction can negatively impact device-scale parameters and reduce PV PCE.

14 SOLAR ENERGY↗

Thermomechanical Cleave of Polycrystalline CdTe Solar Cells and its Applications: A Review

One of the primary research challenges for cadmium telluride (CdTe) solar cells is addressing its open‐circuit voltage ( V OC ) deficit. While theoretical studies and single crystal work show V OC > 1 V is possible, devices remain stubbornly low at ≈800–900 mV. As absorber opto‐electronic properties (e.g., hole density, carrier lifetime) are improved, device modeling suggests that interfaces become limiting. Because CdTe‐based devices are typically grown in the superstrate configuration, the back interface is relatively accessible for manipulation and study, while the front interface (i.e., the heterojunction region) is buried under microns of material and inaccessible. NREL has developed a novel technique to thermomechanically cleave polycrystalline CdTe device stacks directly at the front interface, enabling characterization and controlled manipulation of this important region. Herein, recent work, primarily from NREL, will be reviewed, including considerations for achieving successful delamination; key scientific discoveries about the front interface that have been enabled by this technique; and practical applications, such as flexible, low‐cost solar with high power‐to‐weight ratio.

14 SOLAR ENERGY↗

Optimizing trigger-level track reconstruction for sensitivity to exotic signatures

Many compelling beyond the Standard Model scenarios predict signals that result in unconventional charged particle trajectories. Signatures for which unusual tracks are the most conspicuous feature of the event pose significant challenges for experiments at the Large Hadron Collider (LHC), particularly for the trigger. This article presents a study of track-based triggers for a representative set of long-lived and unconventional signatures at the upcoming High Luminosity LHC, as well as resulting recommendations for the target parameters of a hardware-based tracking system. Scenarios studied include large multiplicities of low-p T tracks produced in a soft-unclustered-energy-pattern model, displaced leptons and anomalous prompt tracks predicted in a Supersymmetry model with long-lived staus, and displaced hadrons predicted in a Higgs portal scenario with long-lived scalars.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗