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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Fe-Exchanged Small-Pore Zeolites as Ammonia Selective Catalytic Reduction (NH 3 -SCR) Catalysts

Cu-exchanged small-pore zeolites have been extensively studied in the past decade as state-of-the-art selective catalytic reduction (SCR) catalysts for diesel engine exhaust NOx abatement for the transportation industry. During this time, Fe-exchanged small-pore zeolites, e.g., Fe/SSZ-13, Fe/SAPO-34, Fe/SSZ-39 and high-silica Fe/LTA, have also been investigated but much less extensively. In comparison to their Cu-exchanged counterparts, such Fe/zeolite catalysts display inferior low-temperature activities, but improved stability and high-temperature SCR selectivities. Such characteristics entitle these catalysts to be considered as key components of highly efficient emission control systems to improve the overall catalyst performance. In this short review, recent studies on Fe-exchanged small-pore zeolite SCR catalysts are summarized, including (1) the synthesis of small-pore Fe/zeolites; (2) nature of the SCR active Fe species in these catalysts as determined by experimental and theoretical approaches, including Fe species transformation during hydrothermal aging; (3) SCR reactions and structure-function correlations; and (4) a few aspects on industrial applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Thirty Minutes Before the Dawn

The Trinity test of July 16, 1945, marked the scientific apex of the Manhattan Project. Often recognized as the symbolic birth of the nuclear age, Trinity’s multifaceted legacy remains just as captivating and complex today as it did 75 years ago. This paper examines why the test was necessary from a technical standpoint, shows how Los Alamos scientists planned the event, and explores the physical and emotional aftermaths of Trinity. The author also uses rarely accessed original records to reconstruct the story of Trinity’s health hazards, as seen through the eyes of radiation technicians and medical doctors as events unfolded. Trinity was conducted as the Potsdam Conference began, weeks after the collapse of Nazi Germany. It was considered necessary to let President Harry S. Truman know whether the United States possessed a nuclear capability ahead of his negotiations with Joseph Stalin, the Soviet premier. The author examines the competing priorities that drove the timetable for the test: international politics, security, and safety. Three weeks after Trinity, a gun-assembled enriched-uranium bomb called Little Boy was used against the Japanese city of Hiroshima. Three days later, Fat Man, a weaponized version of the imploding Trinity device, was dropped on Nagasaki. The author briefly examines these strikes and what impact they may have had on the Japanese surrender. The paper concludes by examining the legacy of the Trinity test 75 years into the age it helped usher in.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2024

PINN surrogate of Li-ion battery models for parameter inference, Part II: Regularization and application of the pseudo-2D model

Bayesian parameter inference is useful to improve Li-ion battery diagnostics and can help formulate battery aging models. However, it is computationally intensive and cannot be easily repeated for multiple cycles, multiple operating conditions, or multiple replicate cells. To reduce the computational cost of Bayesian calibration, numerical solvers for physics-based models can be replaced with faster surrogates. A physics-informed neural network (PINN) is developed as a surrogate for the pseudo-2D (P2D) battery model calibration. For the P2D surrogate, additional training regularization was needed as compared to the PINN single-particle model (SPM) developed in Part I. Both the PINN SPM and P2D surrogate models are exercised for parameter inference and compared to data obtained from a direct numerical solution of the governing equations. A parameter inference study highlights the ability to use these PINNs to calibrate scaling parameters for the cathode Li diffusion and the anode exchange current density. By realizing computational speed-ups of ~2250x for the P2D model, as compared to using standard integrating methods, the PINN surrogates enable rapid state-of-health diagnostics. Finally, in the low-data availability scenario, the testing error was estimated to ~2 mV for the SPM surrogate and ~10 mV for the P2D surrogate which could be mitigated with additional data.

25 ENERGY STORAGE↗
DOE OSTI2024

Superoxide Radicals in Uranyl Peroxide Solids: Lasting Signatures Identified by Electron Paramagnetic Resonance Spectroscopy

Abstract U(VI) peroxide phases (studtite and meta‐studtite) are found throughout the nuclear fuel cycle and exist as corrosion products in high radiation fields. Peroxides are part of a family of reactive oxygen species (ROS) that include hydroperoxyl and superoxide species and are produced during alpha radiolysis of water. While U(VI) peroxides have been thoroughly investigated, the incorporation and stability of ROS species within studtite have not been validated. In the current study, electron paramagnetic resonance (EPR) spectroscopy was used to identify the presence of free radicals within a series of U(VI) peroxide samples containing depleted, highly enriched, and natural uranium. Density functional theory calculations indicated that the predicted EPR signals matched well with a superoxide (O 2 − ⋅) species incorporated into the studtite structure, confirming the presence of ROS in the material. Further analysis of samples that were synthesized between 1945 and 2023 indicated that there is a correlation between the radical signal and the product of specific activity multiplied by age of the sample.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Using Explainable Artificial Intelligence to Predict Perovskite Solar Cell Electrical Metastability from Operando Photoluminescence Images in Accelerated Stress Testing

Metal halide perovskite (MHP) solar cells exhibit a metastable response to bias governed by coupled ionic–electronic processes, complicating the conventional reciprocity relation between luminescence intensity and device open-circuit voltage (V oc ). This limits the use of luminescence as a diagnostic for device screening or accelerated stress testing, motivating new approaches that can interpret photoluminescence (PL) signals under nonequilibrium conditions. From the artificial intelligence perspective, we develop an explainable deep learning framework that integrates convolutional neural networks (CNN), long short-term memory (LSTM) layers, and an attention mechanism to learn spatiotemporal features from operando photoluminescence PL image sequences. The model achieves a mean absolute error of ±0.027 V in predicting open-circuit voltage transients and reduces extreme-tail errors by up to 78% compared to physics-based reciprocity calculations. Gradient-weighted Class Activation Mapping (Grad-CAM) provides interpretability by highlighting physically meaningful regions such as electrode edges and emergent defect features. From the engineering application perspective, this framework enables accurate, contactless prediction of device V oc and identification of degradation-relevant features during accelerated aging of perovskite solar cells. This approach demonstrates how explainable AI can enhance operando diagnostics and reliability analysis in photovoltaic devices under nonequilibrium conditions.

14 SOLAR ENERGY↗
DOE OSTI2024

PINN surrogate of Li-ion battery models for parameter inference, Part I: Implementation and multi-fidelity hierarchies for the single-particle model

To plan and optimize energy storage demands that account for Li-ion battery aging dynamics, techniques need to be developed to diagnose battery internal states accurately and rapidly. Here, this study seeks to reduce the computational resources needed to determine a battery's internal states by replacing physics-based Li-ion battery models - such as the single-particle model (SPM) and the pseudo-2D (P2D) model - with a physics-informed neural network (PINN) surrogate. The surrogate model makes high-throughput techniques, such as Bayesian calibration, tractable to determine battery internal parameters from voltage responses. This manuscript is the first of a two-part series that introduces PINN surrogates of Li-ion battery models for parameter inference (i.e., state-of-health diagnostics). In this first part, a method is presented for constructing a PINN surrogate of the SPM. A multi-fidelity hierarchical training, where several neural nets are trained with multiple physics-loss fidelities is shown to significantly improve the surrogate accuracy when only training on the governing equation residuals. The implementation is made available in a companion repository (https://github.com/NREL/PINNSTRIPES). The techniques used to develop a PINN surrogate of the SPM are extended in Part II for the PINN surrogate for the P2D battery model, and explore the Bayesian calibration capabilities of both surrogates.

25 ENERGY STORAGE↗
DOE OSTI2021

Facility Cybersecurity Framework Best Practices Version 2.0

Federal facilities are increasingly adopting automation and connecting to the Internet creating an energy-internet-of-things environment that converges operational technology (OT) and information technology (IT). Today's buildings increasingly weave together networked sensors and cyber and physical systems that enable data to be collected, aggregated, exchanged, stored and monetized in new ways. Building technological advances have created new energy technology, services, markets and value creation opportunities (e.g. transactive energy, two-way grid communications, machine learning, and increased use of renewable and distributed energy resources). But as larger data sets are being exchanged at faster speeds between an increasing number of OT systems, it becomes more difficult to protect the security of the data lifecycle and the physical equipment it interacts with. These challenges are especially difficult to overcome because the economic and environmental gain (interoperability, big data, social networks and ubiquitous information sharing) are driving these prominent trends in the digital age. Often cybersecurity is an afterthought.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Facility Cybersecurity Framework Best Practices Version 2.0

Federal facilities are increasingly adopting automation and connecting to the Internet creating an energy-internet-of-things environment that converges operational technology (OT) and information technology (IT). Today's buildings increasingly weave together networked sensors and cyber and physical systems that enable data to be collected, aggregated, exchanged, stored and monetized in new ways. Building technological advances have created new energy technology, services, markets and value creation opportunities (e.g. transactive energy, two-way grid communications, machine learning, and increased use of renewable and distributed energy resources). But as larger data sets are being exchanged at faster speeds between an increasing number of OT systems, it becomes more difficult to protect the security of the data lifecycle and the physical equipment it interacts with. These challenges are especially difficult to overcome because the economic and environmental gain (interoperability, big data, social networks and ubiquitous information sharing) are driving these prominent trends in the digital age. Often cybersecurity is an afterthought.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Frequency Domain Reflectometry (FDR) Simulation Techniques for Digital Twin Representation of an Electrical Cable

Simulation of cable system response to frequency domain reflectometry (FDR) tests can be instrumental to understanding these tests and the nature and influence of various cable anomalies on test signatures. Reflectometry simulations are based upon a finite element representation of cable conductors and insulation to produce an S-parameter at each evaluated frequency. The aggregate collection of cable model S-parameters can simulate the influence on a test signal injected into a physical cable. Such an approach was undertaken in this work to produce a digital twin simulation of a low-voltage electrical cable. The electrical cable digital twin examined the influence of test simulation parameters and the relative influence of cable anomalies, including thermal aging, water or moisture exposure, water or moisture ingress, and other anomalies. The digital twin in this work included modeling of the conductors, insulation, jacket, and surrounding environment (air, water, etc.). The digital twin could be expanded to include cable bends, junctions and splices, branch or T systems, and termination impedances of motors or instruments. Observations and conclusions of this work include: 1. Fully 3D digital twin simulation of an electrical cable using an FDR approach is possible. However, there are tradeoffs between simulation fidelity and solution time, which must be balanced to ensure the simulation solves in an adequate amount of time (e.g., less than 20 minutes). Simulation parameters to balance include frequency bandwidth, number of frequencies, mesh density, connection impedance, and permittivity tolerance. 2. The digital twin simulation can explain FDR sensitivity to various cable anomalies, including entry and exit from an oven or water bath. 3. The digital twin simulation FDR response attenuates with distance along the cable and is further affected by the frequency bandwidth, which is similar to that observed with physical measurements. 4. The resolution of the digital twin FDR peaks increased with increasing bandwidth and with increasing number of frequencies, again similar to physical measurements. 5. The presence of multiple anomalies in the digital twin does not substantially attenuate the FDR response to anomalies located beyond the first encountered anomaly and impedance mismatch. 6. Spectral variation of the permittivity did not have a significant effect on the FDR response compared to a fixed nominal value. 7. Extension of the digital twin to 1000 ft still allowed for detection of distal anomalies near the far end of the electrical cable from the instrument connection point. 8. The ARENA test bed facilitates efficient NDE evaluations of well understood cable anomalies with various NDE methods without risking actual plant damage.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Upgrading Fermilab’s accelerator control system with ACORN

The Fermilab Accelerator Complex is the largest national user facility in the Office of High Energy Physics (DOE/HEP) program and the only national user facility operating at Fermilab. Fermilab serves as the host to the Long Baseline Neutrino Facility/Deep Underground Neutrino Experiment (LBNF/DUNE), the laboratory’s flagship project for neutrino science that is under construction. LBNF/DUNE will be powered by megawatt beams from an upgraded accelerator, the Proton Improvement Plan II (PIP-II) that will replace the laboratory’s aging linear accelerator with a new one based on superconducting radio-frequency cavities. The Accelerator Controls Operations Research Network (ACORN) Project will support LBNF/DUNE and PIP-II by modernizing the accelerator control system. The project is at the conceptual design phase and looking to achieve Critical Decision 1 (CD-1) later this year. The scope and structure of the project will be presented, along with an overview of how that has changed in the past year. Current design and technology choices will be shared. Specific challenges facing the project will be addressed, along with current thinking on solutions.

Roehrig, Christian [Fermilab]↗
DOE OSTI2022

BBN photodisintegration constraints on gravitationally produced vector bosons

Gravitational production of massive particles due to cosmic expansion can be significant during the inflationary and reheating period of the Universe. If the particle also has non-gravitational interactions that do not significantly affect its production, numerous observational probes open up, including cosmological probes. In this work, we focus on the gravitational production of light vector bosons that couple feebly to the Standard Model (SM) particles. Due to the very feeble coupling, the light vector bosons never reach thermal equilibrium, and if the Hubble scale at the end of inflation is above 10 8 GeV, the gravitational production can overwhelm the thermal production via the freeze-in mechanism by many orders of magnitude. As a result, much stronger constraints from the Big Bang Nucleosynthesis (BBN) can be placed on the lifetime and mass of the vector bosons compared to the scenario where only thermal production is considered. As an example, we study the sub-GeV scale dark photons, which couple to the SM only through kinetic mixing, and derive constraints on the mass and kinetic mixing parameter of the dark photon from the photodisintegration effects on the light element abundances relevant at the end of the BBN when the cosmic age was around 10 4 s.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Fast Semi-automated Filtration Method for Non-targeted LC-QTOF Data of Aged Nitroplasticizer Samples

A full dataset of aged nitroplasticizer (NP) is composed of more than 2000 unique mass-to-charges (m/z) when combining the non-targeted data obtained from both positive and negative electrospray ionization modes in time-of-flight mass spectrometry. Therefore, manual processing of these data often takes days, weeks, or even months to scrutinize for mechanistic insights. To effectively extract meaningful signals that represent vital degradation intermediates in the early NP degradation mechanism, a semi-automated postprocessing workflow for data filtering, tailored to the aging experiment of NP, has been developed. The automated portion of this workflow is written in a Python code (using pandas, numpy, and matplotlib libraries), which removes more than 65% of potential false signals within seconds via four threshold-based adjustable filters: signal sensitivity, coefficient of variation, number of measurements, and retention time variability. As for the manual portion, a pattern-based inspection method is employed to reduce another 23% or more false positives, which greatly simplifies data visualization and results in less than 3% of potential candidate m/z needing in-depth data interpretation. As a positive control, known compounds are verified. Using this semi-automated data reduction method, the amount of time required is reduced to a matter of hours for data filtering in the non-targeted datasets of aged NP, which saves more time and effort for compound identification.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Unveiling the Stability of Encapsulated Pt Catalysts Using Nanocrystals and Atomic Layer Deposition

Platinum exhibits desirable catalytic properties, but it is scarce and expensive. Optimizing its use in key applications such as emission control catalysis is important to reduce our reliance on such a rare element. Supported Pt nanoparticles (NPs) used in emission control systems deactivate over time because of particle growth in sintering processes. Here, in this work, we shed light on the stability against sintering of Pt NPs supported on and encapsulated in Al 2 O 3 using a combination of nanocrystal catalysts and atomic layer deposition (ALD) techniques. We find that small amounts of alumina overlayers created by ALD on preformed Pt NPs can stabilize supported Pt catalysts, significantly reducing deactivation caused by sintering, as previously observed by others. Combining theoretical and experimental insights, we correlate this behavior to the decreased propensity of oxidized Pt species to undergo Ostwald ripening phenomena because of the physical barrier imposed by the alumina overlayers. Furthermore, we find that highly stable catalysts can present an abundance of under-coordinated Pt sites after restructuring of both Pt particles and alumina overlayers at a high temperature (800 °C) in C 3 H 6 oxidation conditions. The enhanced stability significantly improves the Pt utilization efficiency after accelerated aging treatments, with encapsulated Pt catalysts reaching reaction rates more than two times greater than those of a control supported Pt catalyst.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Directly Determined Properties of HD 97658 from Interferometric Observations

We conducted interferometric observations with the CHARA Array of transiting super-Earth host HD 97658 and measured its limb-darkened angular diameter to be θ {sub LD} = 0.314 ± 0.004 mas. The combination of the angular diameter with the Gaia EDR3 parallax value with zero-point correction (π = 46.412 ± 0.022 mas, d =21.546 ± 0.011 pc) yields a physical radius of R {sub ·} = 0.728 ± 0.008 R {sub ⊙}. We also measured the bolometric flux of the star to be F {sub bol} = 2.42 ± 0.05 × 10{sup -8} erg s{sup -1} cm{sup -2}, which, together with angular size, allows a measurement of the effective temperature T {sub eƒƒ} = 5212 ± 43 K. Our directly determined physical stellar properties are in good agreement with previous estimates derived from spectroscopy. We used our measurements in combination with stellar evolutionary models and properties of the transit of HD 97658 b to determine the mass and age of HD 97658 as well as constrain the properties of the planet. Our results and our analysis of the TESS light curve on the planet (TOI-1821) corroborate previous studies of this system with tighter uncertainties.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Sociodemographic effects on pandemic fatigue are multifaceted and context-specific: A longitudinal analysis of physical distancing adherence

Pandemic fatigue emerged early during the COVID-19 pandemic and remains a concern as new variants emerge and ongoing public health measures are needed to control them. A wide range of factors can affect pandemic fatigue, but empiric research indicating which may be most important to adherence in specific populations is lacking. We conducted a longitudinal study of changes in physical distancing in two cohorts: adults living with children <18 years and adults ≥50 years old. Six types of non-work, non-household contacts were ascertained at six times from April to October 2020. We used generalized estimating equations Poisson regression to estimate the one-week change in contact rate and how this differed based on sociodemographic characteristics. The rate of all contact types increased during the middle of the study period and decreased toward the end. Changes in contact rates over time differed according to several sociodemographic characteristics, including age, gender, race/ethnicity, education, household composition, and access to transportation. Furthermore, the factors influencing the rate of change in contact rates differed by the type or setting of the contact, for example contacts as a result of visiting another person’s home versus during a retail outing. These results provide evidence for potential mechanisms by which pandemic fatigue has resulted in lower physical distancing adherence.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

A Transient-Response methodology based on experiments and modeling for Cu-Redox Half-Cycle kinetic analysis on a Cu-SSZ-13 SCR catalyst

In this report the Standard SCR reaction catalyzed by Cu-SSZ-13 is a redox process consisting of a reduction half cycle (RHC) and an oxidation half cycle (OHC) that cycle the active Cu sites between the Cu(II) and Cu(I) states. In the current work, a transient-response methodology consisting of experimental transient response Cu-redox (TRCR) measurements and kinetic modeling was developed for detailed study of individual SCR Cu-redox half cycles. The TRCR protocol allows quantification of the reducible Cu density, Cu(II)-Cu(I) partitioning, relative native RHC and OHC rates, and limiting half cycle during SCR. The half-cycle kinetics are studied over a wide (170–450 °C) temperature, and in differential segments along the catalyst length using spatially resolved capillary inlet mass-spectrometry (SpaciMS). The protocol alone provides two independent measures indicating that OHC increases faster than RHC with temperature, and that at all but the lowest temperature SCR is RHC limited. Introducing the transient kinetic models allows half-cycle reaction pathways, orders and activation energies to be studied and determined; e.g., RHC involves surface and gas-phase NH 3 routes, and OHC with O 2 involves dimer formation. Application of the full methodology provides further confirmation and quantification of the protocol conclusions, and specifically the first measurements of RHC and OHC activation energies; specifically for parallel RHC surface and gas-phase routes, and experimentally obtained OHC activation energy vs. first-principle calculations in the literature. Beyond insights related to the degreened catalyst studied here, the methodology provides a broadly available approach for quantifying how aging processes selectively impact RHC and OHC.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

The effect of hardness on polymer-bonded pentaerythritol tetranitrate (PETN) explosive impact sensitivity

Handling sensitivity is an important property to assess when working with explosive samples and can be measured using a variety of tests, including drop-weight impact sensitivity. There exists a longstanding interest in the explosives community on the importance of measurable chemical, physical, and mechanical properties of explosives in impact sensitivity. However, most recent work in this area has explored chemical attributes rather than physical and mechanical properties of explosives. In this study, we measure hardness of explosive samples of pentaerythritol tetranitrate and Sylgard binder (XTX) during the curing process. The samples have been characterized for particle morphology through scanning electron microscopy and handling sensitivity through drop-weight impact testing. The relative importance of states of cure, methods of curing, morphology, and age of material are discussed. The data indicate that although there is a notable difference in morphology and mechanical properties for the samples as the polymer-bonded mixtures cure, the resulting changes to mechanical properties have a minimal effect on the sensitivity of the XTX.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗