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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

AuPd Nanoicosahedra: Atomic-Level Surface Modulation for Optimization of Electrocatalytic and Photocatalytic Energy Conversion

Modulation of bimetallic nanocatalysts with atomic precision would allow for significant increases in catalyst activity through the optimization of heteroatomic interplay. In practice, this level of control over homogeneously turning the heteroatomic states in the surface regions of catalysts remains a great challenge for practical applications requiring mass production. In this work, a one-step aqueous strategy for preparation of AuPd nanoicosahedra core–shell structures has been developed. By turning the molar ratio of Au and Pd precursors, the nanoicosahedra could be made with uniform core composition (Pd ~20%) and largely flexible surface compositions (Pd: 20–70%). Under model reactions of electrochemical ethanol oxidation (EOR) and 4-nitrophenol (4-NP) reduction, the Au 55 Pd 45 surface displayed superior activities. Here, x-ray absorption spectroscopy revealed that AuPd nanoicosahedra with Pd-poor surfaces (Au 79 Pd 21 and Au 60 Pd 40 ) maintain Au-like electronic structures while those with Pd-rich surfaces are more Pd-like. The Au 55 Pd 45 surface struck a delicate balance between the two extremes, leading to the optimal Au–Pd interplay for catalytic performance. Overall, the development of a one-step aqueous strategy for atomic-level control over bimetallic nanoparticle surface states is an important milestone for future advances in catalysis. Our findings in atomic-scale catalyst design will bring deep insights into the fields of nanosynthesis and heterogeneous catalysis, which will be beneficial for further scientific breakthroughs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Short-Wave Infrared Upconverting Nanoparticles

Optical technologies enable real-time, noninvasive analysis of complex systems but are limited to discrete regions of the optical spectrum. While wavelengths in the short-wave infrared (SWIR) window (typically, 1700-3000 nm) should enable deep subsurface penetration and reduced photodamage, there are few luminescent probes that can be excited in this region. Here, we report the discovery of lanthanide-based upconverting nanoparticles (UCNPs) that efficiently convert 1740 or 1950 nm excitation to wavelengths compatible with conventional silicon detectors. Screening of Ln3+ ion combinations by differential rate equation modeling identifies Ho3+/Tm3+ or Tm3+ dopants with strong visible or NIR-I emission following SWIR excitation. Experimental upconverted photoluminescence excitation (U-PLE) spectra find that 10% Tm3+-doped NaYF4 core/shell UCNPs have the strongest 800 nm emission from SWIR wavelengths, while UCNPs with an added 2% or 10% Ho3+ show the strongest red emission when excited at 1740 or 1950 nm. Mechanistic modeling shows that addition of a low percentage of Ho3+ to Tm3+-doped UCNPs shifts their emission from 800 to 652 nm by acting as a hub of efficient SWIR energy acceptance and redistribution up to visible emission manifolds. Parallel experimental and computational analysis shows rate equation models are able to predict compositions for specific wavelengths of both excitation and emission. These SWIR-responsive probes open a new IR bioimaging window, and are responsive at wavelengths important for vision technologies.

Qi, Xiao↗
DOE OSTI2021

Olivine Dissolution in Simulated Lung and Gastric Fluid as an Analog to the Behavior of Lunar Particulate Matter Inside the Human Respiratory and Gastrointestinal Systems

With the Artemis III mission scheduled to land humans on the Moon in 2025, work must be done to understand the hazards lunar dust inhalation would pose to humans. In this study, San Carlos olivine was used as an analog of lunar olivine, a common component of lunar dust. Olivine was dissolved in a flow-through apparatus in both simulated lung fluid and 0.1 M HCl (simulated gastric fluid) over a period of approximately 2 weeks at physiological temperature, 37°C. Effluent samples were collected periodically and analyzed for pH, iron, silicon, and magnesium ion concentrations. The dissolution rate data derived from our measurements allow us to estimate that an inhaled 1.0 μm diameter olivine particle would take approximately 24 years to dissolve in the human lungs and approximately 3 weeks to dissolve in gastric fluid. Results revealed that inhaled olivine particles may generate the toxic chemical, hydroxyl radical, for up to 5–6 days in lung fluid. Olivine dissolved in 0.1 M HCl for 2 weeks transformed to an amorphous silica-rich solid plus the ferric iron oxy-hydroxide ferrihydrite. Olivine dissolved in simulated lung fluid shows no detectable change in composition or crystallinity. Equilibrium thermodynamic models indicate that olivine in the human lungs can precipitate secondary minerals with fibrous crystal structures that have the potential to induce detrimental health effects similar to asbestos exposure. Our work indicates that inhaled lunar dust containing olivine can settle in the human lungs for years and could induce long-term potential health effects like that of silicosis.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2021

The Principal Hugoniot of Iron-Bearing Olivine to 1465 GPa

Shock compression experiments on natural compositions are imperative to accurately model planetary accretion and the interior dynamics of planets. Combining shock compression experiments from the Sandia Z Machine and the OMEGA EP laser facility with density functional theory-based molecular dynamics calculations, we report the first pressure-density-temperature (P-ρ-T) relationship of natural iron (Fe)-bearing olivine ((Mg 0.91 Fe 0.09 ) 2 SiO 4 ) on the principal Hugoniot between 166 and 1,465 GPa. Additionally, we report the first reflectivities of natural olivine liquid in this pressure range. Compared to the magnesium-endmember forsterite (Mg 2 SiO 4 ), the presence of Fe in typical mantle abundance (~9 wt% FeO) alters the U S -u P relation of olivine. Furthermore, the shock temperature and reflectivity of olivine are indistinguishable from forsterite where experimental conditions overlap. Both forsterite and olivine increase in reflectivity (and hence optical conductivity) with increasing temperature, with a maximum reflectivity of ~31% at shock velocities greater than 22 km/s (~800 GPa).

58 GEOSCIENCES↗
DOE OSTI2021

Label-free characterization of organic nanocarriers reveals persistent single molecule cores for hydrocarbon sequestration

Self-assembled molecular nanostructures embody an enormous potential for new technologies, therapeutics, and understanding of molecular biofunctions. Their structure and function are dependent on local environments, necessitating in-situ/operando investigations for the biggest leaps in discovery and design. However, the most advanced of such investigations involve laborious labeling methods that can disrupt behavior or are not fast enough to capture stimuli-responsive phenomena. We utilize X-rays resonant with molecular bonds to demonstrate an in-situ nanoprobe that eliminates the need for labels and enables data collection times within seconds. Our analytical spectral model quantifies the structure, molecular composition, and dynamics of a copolymer micelle drug delivery platform using resonant soft X-rays. We additionally apply this technique to a hydrocarbon sequestrating polysoap micelle and discover that the critical organic-capturing domain does not coalesce upon aggregation but retains distinct single-molecule cores. This characteristic promotes its efficiency of hydrocarbon sequestration for applications like oil spill remediation and drug delivery. Such a technique enables operando, chemically sensitive investigations of any aqueous molecular nanostructure, label-free.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Steps toward quantum simulations of hadronization and energy loss in dense matter

A framework for simulating the real-time dynamics of composite particles in a simple model of dense matter that is amenable to quantum computers is developed. As a demonstration, we perform classical simulations of heavy-hadrons propagating through a dense medium in the Schwinger model. Measurements of the time-dependent energy and charge density are used to identify mechanisms responsible for energy loss and hadron production (hadronization). A study of entanglement dynamics highlights the importance of quantum coherence between the particles that make up the dense medium. Throughout this work, care is taken to isolate, and remove, phenomena that arise solely from a finite lattice spacing. It is found that signatures of entanglement are more sensitive to lattice artifacts than other observables. Toward quantum simulations, we present an efficient method and the corresponding quantum circuits for preparing ground states in the presence of heavy mesons. Finally, these circuits are used to estimate the resources required to simulate in-medium energy loss and hadronization in the Schwinger model using quantum computers.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Large-signal Stability Analysis of Grid-forming Inverters with Equivalent-circuit Models

Here, this paper proposes an energy function-based direct method for large-signal stability assessment of grid-forming (GFM) inverters leveraging an equivalent-circuit representation of all involved control- and physical-layer dynamics. Three different primary controls, a standard inner-current outer-voltage cascaded-control architecture, output LCL filter, and reference-current saturation limiting are featured in the modeling and analysis framework. A composite energy function for the GFM inverter is obtained by summing up individual energy contributions gleaned from the circuit representation. The approach can readily be generalized to different primary controls, output-filter arrangements, and current limiters since it is based on a circuit-theoretic foundation. Numerical simulations validate the efficacy of the approach in estimating the critical clearing time following a large-signal disturbance.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Askival: An altered feldspathic cumulate sample in Gale crater

Askival is a light-toned, coarsely crystalline float rock, which was identified near the base of Vera Rubin Ridge in Gale crater. We have studied Askival, principally with the ChemCam instrument but also using APXS compositional data and MAHLI images. Askival and an earlier identified sample, Bindi, represent two rare examples of feldspathic cumulate float rocks in Gale crater with >65% relict plagioclase. Bindi appears unaltered whereas Askival shows textural and compositional signatures of silicification, along with alkali remobilization and hydration. Askival likely experienced multiple stages of alteration, occurring first through acidic hydrolysis of metal cations, followed by deposition of silica and possible phyllosilicates at low T and neutral-alkaline pH. Through laser-induced breakdown spectroscopy compositional analyses and normative calculations, we suggest that an assemblage of Fe-Mg silicates including amphibole and pyroxene, Fe phases, and possibly Mg-rich phyllosilicate are present. Thermodynamic modeling of the more pristine Bindi composition predicts that amphibole and feldspar are stable within an upper crustal setting. This is consistent with the presence of amphibole in the parent igneous rocks of Askival and suggests that the paucity of amphiboles in other known Martian samples reflects the lack of representative samples of the Martian crust rather than their absence on Mars.

58 GEOSCIENCES↗
DOE OSTI2025

Thermodynamics of gallium-stabilized delta-plutonium: A high-temperature drop calorimetry study

Throughout the Cold War (1947–1991), both the United States and the former Soviet Union independently derived a phase diagram for the Pu-Ga system that has different implications on Pu phase stability. In the phase diagram produced by the United States, the Pu δ-phase is thermodynamically stable at room temperatures when Ga content is between 2 and 9 at. %. The diagram produced by the Soviet Union shows the δ-phase undergoing an eutectoid decomposition into the α-Pu + α-Pu 3 Ga at 7.9 at. % Ga and 370 K. This would suggest that Ga-stabilized δ-Pu is metastable with respect to α-Pu + α-Pu 3 Ga at 298 K. To investigate this, and the thermodynamic behavior of Ga in the FCC lattice of δ-Pu, we have utilized high-temperature drop calorimetry to study the enthalpy of formation of two δ-Pu 1−x Ga x compositions. In doing so, mixing models (regular and subregular) were developed to understand the thermodynamic behavior of Ga in the FCC lattice of δ-Pu and found a strong departure from ideal conditions, which suggests Ga ordering in the FCC lattice of δ-Pu. Overall, it was found that δ-Pu 1−x Ga x is enthalpically metastable with respect to α-Pu + Pu 3 Ga at 298 K.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Direct quantification of ion composition and mobility in organic mixed ionic-electronic conductors

Ion transport in organic mixed ionic-electronic conductors (OMIECs) is crucial due to its direct impact on device response time and operating mechanisms but is often assessed indirectly or necessitates extra assumptions. Operando x-ray fluorescence (XRF) is a powerful, direct probe for elemental characterization of bulk OMIECs and was used to directly quantify ion composition and mobility in a model OMIEC, poly(3,4-ethylenedioxythiophene)-poly(styrene sulfonate) (PEDOT:PSS), during device operation. The first cycle revealed slow electrowetting and cation-proton exchange. Subsequent cycles showed rapid response with minor cation fluctuation (~5%). Comparison with optical-tracked electrochromic fronts revealed mesoscale structure–dependent proton transport. The calculated effective ion mobility demonstrated thickness-dependent behavior, emphasizing an interfacial ion transport pathway with a higher mobile ion density. The decoupling of interfacial effects on bulk ion mobility and the decoupling of cation and proton migration elucidate ion transport in conventional and emerging OMIEC-based devices and has broader implications for other ionic conductors writ large.

42 ENGINEERING↗
DOE OSTI2020

An Atmospheric Aerosol Short Course for Early Career Scientists

The first Department of Energy (DOE) Environmental and Molecular Science Laboratory (EMSL)/Atmospheric Radiation Measurement (ARM) aerosol summer school was held July 15-19, 2019 at the EMSL user facility located at Pacific Northwest National Laboratory. The school set out to provide graduate students and early-career scientists an overview of atmospheric aerosol science and an introduction to the measurement techniques available through the EMSL and ARM user facilities to address current aerosol science issues. Instructors for the course were drawn from scientists from the EMSL (Laskin et al., 2016; China et al., 2018) and ARM facilities (McComiskey and Ferrare, 2016) as well as from the DOE Atmospheric System Research (ASR) program. Student support for the summer school was also jointly provided by EMSL, ARM, and ASR. The school spanned five days with each day covering a particular theme. 25 students from 21 institutions attended morning lectures on aerosol composition, properties, theory, measurements, and modeling. During afternoons, the students explored instruments that collect and analyze aerosol samples at EMSL and PNNL’s Atmospheric Measurements Laboratory. They also tested relevant computer modeling simulations and learned about NWChem, EMSL’s open-source computational chemistry software suite.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Fundamental Investigations of Mechanical and Chemical Degradation Mechanisms in Lithium Ion Battery Materials (Final Technical Report)

The objective of our effort under the DOE EPSCoR Implementation grant is to establish a comprehensive and internationally recognized research program at Brown University and University of Rhode Island in understanding degradation mechanisms and to improve the cycle and calendar life of lithium ion battery (LIB) materials. A series of basic investigations are undertaken to characterize the mechanical and chemical degradation mechanisms, which can help enable new higher capacity and longer lasting electrode designs. Controlling mechanical and chemical degradation is the primary challenge in developing the next generation of higher energy density batteries. The development of failure resistant battery microstructures will require a fundamental understanding of the evolution of stress, deformation, damage, and electrochemistry in battery materials during cyclic charging and discharging. In addition, controlling the reactions at the electrode/electrolyte interface is critical for the formation of a stable SEI layer. We address these issues through a combination of controlled experiments on model battery materials and practical composite electrodes, together with multi-scale computations. Our effort is organized into three focus areas that encompass many critical challenges in Lithium Ion Battery Technologies: (i) Mechanical properties, fracture and damage in electrode materials; (ii) Chemistry and Mechanics of Solid Electrolyte Interphase (SEI); (iii) Mechanical and Chemical Integrity of Solid-Solid Interfaces in Practical Electrodes.

25 ENERGY STORAGE↗
DOE OSTI2020

Multiscale-Informed Modeling of High Temperature Component Response with Uncertainty Quantification

This report summarizes a joint effort between Argonne National Laboratory, Idaho National Laboratory, and Los Alamos National Laboratory to develop and deploy constitutive models targeted at predicting the life of Grade 91 alloy components subjected to high temperature environments typical of those that structural components in advanced nuclear reactors would experience. Two distinct, but complementary constitutive modeling approaches have been taken here. The first employs a phenomenological viscoplastic model for which parameters have been calibrated based on experimental data for a wide range of Grade 91 alloy that has undergone a variety of processing. A Bayesian approach was used to derive distributions of uncertain parameters for this model based on this data set. The second approach is a reduced order model suitable for engineering-scale analysis that is based on the results of a large set of mesoscale simulations. Mesoscale models allow for the microstructure and composition of a particular alloy to be directly taken into account in the computation of the viscoplastic response, but are computationally expensive, which makes it impractical to directly call those models for the material constitutive response in an engineering-scale simulation. The reduced-order representation of the response of the underlying model used here allows for an engineering-scale model to take into account the characteristics of the underlying microstructure, while only incurring a reasonable computational expense. Both of these approaches have different strengths, and are applicable for different parts of the design/analysis process. The phenomenological models can be readily parameterized based on a set of experimental data for a given class of materials and used for scoping calculations. Once a specific material is chosen and adequately characterized, the reduced order models can accurately predict the response of that specific alloy, and because the models are based on predictive models of the underlying microstructure, they can be used to more confidently predict the response under conditions in regions where there is limited experimental data. Both of these models have been integrated in the Grizzly code, which is used here to perform proof-of-concept uncertainty quantification analyses of a simple component under prototypical conditions. The built- in stochastic analysis capabilities in the MOOSE framework that Grizzly is built on are used here to run large sets of simulations for this uncertainty quantification analysis. As would be expected, because the reduced order models are developed for a much more tightly defined alloy, they predict tighter distributions of the time to failure than the phenomenological models, which are calibrated to a broader set of data. Also important is that these simulations demonstrate that a reduced order modeling approach can be successfully deployed to propagate uncertainties from the material scale to practical engineering-scale component simulations.

42 ENGINEERING↗
DOE OSTI2023

Evaluation of the 0.65 Weight Percent Sulfate Solubility Limit for Sludge Batch 10 Based on November 2022 Projections

The Defense Waste Processing Facility (DWPF) is currently preparing to initiate processing of Sludge Batch 10 (SB10), which is comprised of material from Tanks 11H, 13H, 15H, 26F, 40H (heel only), and Alternate Feed Stock-2 and Sodium Reactor Experiment material from H-Canyon. Frit 473 was recommended for sludge-only (SO) and coupled processing with the Salt Waste Processing Facility (SWPF) based on previous assessments of SB10 projections with the DWPF Product Composition Control System glass property models and their associated Measurement Acceptance Region constraints. Savannah River Mission Completion (SRMC) subsequently pursued Wash Cycle Y to further reduce the total sulfur in the sludge batch and increase processing flexibility at DWPF. In October 2022, SRMC System Planning provided an updated SB10 Tank 40H blend baseline projection based on the Tank 51 confirmation sample results. Due to the reduced Na concentration relative to previous SB10 projections, two additional projections based on the addition of 7,000 gallons of caustic were provided in November 2022.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Advanced Compact Generation Module with Fish Safe Runner Technology

Hydropower is an important contributor of stable, load-leveling renewable energy to our national grid. Increasingly, the development of new hydropower facilities or the retrofit of existing ones hinges not only on minimizing costs but also environmental impact. In this report, the analysis and testing of a modular and scalable low-head hydropower generation design using Natel Energy’s Restoration Hydro Turbine is described. This design leverages many established industry approaches for compactness and efficiency while simultaneously allowing for safe downstream fish passage through the turbines themselves. This unique approach reduces overall hydropower facility costs and enables a simpler inclusive method of project design and operation. To assess this design, mechanical and fluid computational analyses were used to study and optimize key parameters. Passage tests of important migratory species (salmonids, American eel) were conducted through representative turbines. The unique propeller geometry of the fish-safe Restoration Hydro Turbine was subjected to detailed design and testing using advanced manufacturing composite techniques. Comprehensive module cost models were developed and assessed alongside hydraulic efficiency. The results of this project show promising and economical applications for downstream passage offish through Restoration Hydro Turbine modules.

13 HYDRO ENERGY↗
DOE OSTI2025

Life Cycle Analysis of Natural Gas Extraction and Power Generation: U.S. 2020 Emissions Profile

This analysis expands upon previous life cycle analyses (LCAs) of natural gas systems performed by the National Energy Technology Laboratory (NETL). It provides a complete inventory of emissions to air and water, water consumption, and land use change. These environmental burdens are detailed for all supply chain steps from natural gas production through natural gas distribution. This package includes the report, the NETL Natural Gas Model, and appendices that include several Excel workbooks and a python script to provide transparent access to the calculations and resulting data. This is revision 1 of the 2024 study (published December 17, 2024 and updated on January 24, 2025) and corrects a modeling error in natural gas composition. See the errata on page 2 for more information.

03 NATURAL GAS↗
DOE OSTI2026

Recent progress in atomic-scale controlled plasma processing

Atomic-scale control in plasma processing is becoming increasingly critical for fabricating of advanced semiconductor devices, particularly as the industry shifts toward three-dimensional (3D) architectures and high-aspect-ratio (HAR) structures. This review presents a comprehensive overview of recent developments in atomic-scale controlled plasma processes, organized along two key directions: the hierarchical structure of plasma–surface interactions and the generational evolution of atomic layer processing (ALP) technologies. We examined the gas phase, where molecular design enables selective generation of ions and radicals; the boundary layer, where transport phenomena govern species delivery into nanoscale features, and the surface, where temperature-dependent reactions and cyclic processing determine etching selectivity and precision. Building on this foundation, we outline five generations of ALP—from thermal atomic layer deposition to transport-aware, temporally and structurally decoupled processes—highlighting the increasing sophistication of process control. The review further explores the transition from empirical recipe development to science-based, data-driven methodologies. By integrating quantum-chemical modeling, advanced diagnostics, and machine learning, we demonstrated how predictive models can link plasma species composition to process outcomes, enabling autonomous and adaptive control strategies. Finally, this review discusses the broader societal implications of plasma process innovation through the E4 quartet: energy and resource efficiency, environmental sustainability, evolutionary advancement, and educational promotion. These principles guide the development of sustainable and intelligent atomic-scale manufacturing technologies that are not only technically advanced but also socially responsible.

Ishikawa, Kenji [Nagoya Univ. (Japan)] (ORCID:0000↗
DOE OSTI2020

Using machine learning to derive cloud condensation nuclei number concentrations from commonly available measurements

Cloud condensation nuclei (CCN) number concentrations are an important aspect of aerosol–cloud interactions and the subsequent climate effects; however, their measurements are very limited. We use a machine learning tool, random decision forests, to develop a random forest regression model (RFRM) to derive CCN at 0.4 % supersaturation ([CCN0.4]) from commonly available measurements. The RFRM is trained on the long-term simulations in a global size-resolved particle microphysics model. Using atmospheric state and composition variables as predictors, through associations of their variabilities, the RFRM is able to learn the underlying dependence of [CCN0.4] on these predictors, which are as follows: eight fractions of PM 2.5 (NH 4 , SO 4 , NO 3, secondary organic aerosol (SOA), black carbon (BC), primary organic carbon (POC), dust, and salt), seven gaseous species (NO x , NH 3 , O 3 , SO 2 , OH, isoprene, and monoterpene), and four meteorological variables (temperature (T), relative humidity (RH), precipitation, and solar radiation). The RFRM is highly robust: it has a median mean fractional bias (MFB) of 4.4 % with ≈96.33 % of the derived [CCN0.4] within a good agreement range of -60% 2.5 speciation (NH 4 , SO 4 , NO 3 , and organic carbon (OC)), NO x , O 3 , SO 2 , T, and RH, as well as [CCN0.4] are available. We modify, optimize, and retrain the developed RFRM to make predictions from 19 to 9 of these available predictors. This retrained RFRM (RFRM-ShortVars) shows a reduction in performance due to the unavailability and sparsity of measurements (predictors); it captures the [CCN0.4] variability and magnitude at SGP with ≈67.02 % of the derived values in the good agreement range. This work shows the potential of using the more commonly available measurements of PM 2.5 speciation to alleviate the sparsity of CCN number concentrations' measurements.

54 ENVIRONMENTAL SCIENCES↗