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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 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Multiferroic and Related Hysteretic Behavior in Ferromagnetic Shape Memory Alloys

In this work, we combine a Ginzburg–Landau model for a ferroelastic transition with the theory of micromagnetism to study the magnetostructural behavior leading to multicaloric effects in ferromagnetic shape memory alloys. We analyze the ferroelastic transition under different conditions of temperature, stress and magnetic field and establish the corresponding phase diagram. On the one hand, our results show that the proper combination of both fields may be used to reduce the transition hysteresis and thus improve the reversibility of the related elastocaloric effects, superelasticity and stress-mediated magnetocaloric effects. On the other hand, the stress-free magnetic field-driven and thermally driven magnetostructural evolution provides physical insight into the low-temperature field-induced domain reorientation, from which we derive strategies to modify the operational temperature ranges and thus the corresponding (magnetic) shape-memory effect.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Quantum Fokker-Planck modeling of degenerate electrons

In this work, an implicit and conservative numerical scheme is proposed for the isotropic quantum Fokker-Planck equation describing the evolution of degenerate electrons subject to elastic collisions with other electrons and ions. The electron-ion and electron-electron collision operators are discretized using a discontinuous Galerkin method, and the electron energy distribution is updated by an implicit time integration method. The numerical scheme is designed to satisfy all conservation laws exactly. Numerical tests and comparisons with other modeling approaches are shown to demonstrate the accuracy and conservation properties of the proposed method.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Determining the effects of U/Pu ratio on subsolidus phase transitions in U-Pu-Zr metallic fuel alloys

Here, ternary alloys consisting primarily of uranium, plutonium, and zirconium (U-Pu-Zr) are among the leading candidate fuel systems considered for fast spectrum nuclear reactors. Despite historical operation data from the testing of U-Pu-Zr rods in the Experimental Breeder Reactor-II, considerable uncertainty about the evolution of phases and microstructure across the ternary composition space exists. Due to sluggish kinetics and other difficulties in handling metal actinide specimens, quantitative measurements of phase-transitions in U-Pu-Zr alloys remain sparse in scientific literature, with most investigators reporting either phase-transition temperatures or phase identification data, but not both from the same specimens. The purpose of this paper is to critically compare experimental and calculated phase transition data and correlate with the microstructure and phase characterization data of as-cast and annealed U-Pu-Zr alloys. Phase transition peaks were measured using differential scanning calorimetry in the subsolidus regions (723-948 K) of three ternary U-Pu-Zr alloys with the same zirconium concentration but various U/Pu ratios. Overlapping peaks were deconvoluted using a Frazier-Suzuki peak fitting algorithm, and the critical peak temperatures and enthalpies were calculated. In general, increasing concentrations of Pu were associated with enhanced thermal stability of the body-centered cubic γ phase upon both heating and cooling. Experimental phase transition temperatures in this study tended to agree well with the predictions of the established ternary phase diagrams and other reported phase transition temperatures in literature. Additionally, the TAF-ID thermodynamic database was used to calculate a U-Pu-40 at.% Zr pseudobinary diagram as well as ternary diagrams from 773 to 973 K. The equilibrium phase transition temperatures tended to be considerably lower than measured peak temperatures upon both heating and cooling. Recommendations for improving the quality of data in future U-Pu-Zr characterization studies are also discussed.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Kinetically versus thermodynamically controlled factors governing elementary pathways of GaP(111) surface oxidation

GaP and related III-V semiconductors have attracted interest as high-efficiency photoelectrochemical electrodes for solar water splitting. However, their efficacy is linked to the presence, identity, and integrity of native surface oxides, which are structurally and chemically complex and evolve during operation. Using ambient pressure X-ray photoelectron spectroscopy (APXPS) coupled with ab initio simulations, we track key chemical motifs expressed during evolution of GaP(111) surface oxides, their associated reaction kinetics, and their correlations with electronic properties. We identify two distinct thermal regimes corresponding to kinetically and thermodynamically controlled oxidation. Below 600 K, exposure to O2 generates kinetically facile Ga-O-Ga configurations, whereas higher temperatures cause activated oxygen to insert into Ga–P bonds as part of a thermodynamically driven transformation into a complex, heterogeneous 3D network of surface POx (1≤x ≤ 4) groups and Ga2O3 species, the latter of which eventually dominates upon depletion of surface phosphorus. Here our study highlights the critical competition between kinetic and thermodynamic factors during GaP oxidation, yielding insights for fabricating stable III-P-based photoelectrodes with precisely engineered surface properties.

08 HYDROGEN↗
DOE OSTI2025

Thermodynamics, local structure, and transport of protons in triple-conducing oxide, BaCo 0.4 Fe 0.4 Zr 0.1 Y 0.1 O 3-δ (BCFZY4411)

Triple-conducting oxides (TCOs) are an emerging class of mixed ionic and electronically conducting materials that show great promise for oxygen reduction/oxygen evolution (ORR/OER) electrocatalysis—primarily in high-temperature ceramic electrochemical cells— but also in aqueous alkaline environments. Their high activity is attributed, at least in part, to their ability to incorporate and transport three mobile charge carriers: protons, oxygen vacancies, and electron-holes Despite their promise, fundamental studies of TCOs are challenging, as transport dynamics from three charge carriers cannot be fully disentangled via traditional electrical measurement techniques. Characterizing proton dynamics in TCOs is particularly difficult as protons are generally the minority carrier, and their conduction response is typically obscured by the oxygen vacancies and electron holes. Here, we demonstrate successful isolation of the proton behavior in an archetypal TCO, BaCo 0.4 Fe 0.4 Zr 0.1 Y 0.1 O 3-δ (BCFZY4411), using a combination of non-electrical techniques. We determine proton uptake and oxygen non-stoichiometry (δ) using thermogravimetric analysis (TGA). X-ray absorption near edge structure (XANES) and neutron diffraction (ND) are used to validate the oxidation state of Co and the δ values obtained through TGA. We apply 1H solid-state magic-angle-spinning (MAS) nuclear magnetic resonance (NMR) to provide insights into local structure, dynamics, and proton kinetics. Finally, the proton transport properties are further quantified using tracer isotope exchange with time-of-flight secondary ion mass spectrometry (ToF-SIMS). Despite the very low proton concentrations in BCFZY4411 (<0.2% under most conditions), our analysis suggests that the oxygen Manuscript File Click here to view linked References 2 reduction and evolution reactions are nevertheless limited by the oxygen ion kinetics (e.g., oxygen surface exchange) rather than the proton kinetics at the reduced operating temperatures (<500 °C) that are targeted for electrochemical cell applications. These findings provide a comprehensive understanding of proton behavior in BCFZY4411 and pave the way for advancing the fundamental study of TCOs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Potential Control of Oxygen Non-Stoichiometry in Cerium Oxide and Phase Transition Away from Equilibrium

Cerium oxide (ceria, CeO 2 ) is a technologically important material for energy conversion applications. Its activities strongly depend on redox states and oxygen vacancy concentration. Understanding the functionality of chemical active species and behavior of oxygen vacancy during operation, especially in high-temperature solid-state electrochemical cells, is the key to advance future material design. Herein, the structure evolution of ceria is spatially resolved using bulk-sensitive operando X-ray diffraction and spectroscopy techniques. During water electrolysis, ceria undergoes reduction, and its oxygen non-stoichiometry shows a dependence on the electrochemical current. Cerium local bonding environments vary concurrently to accommodate oxygen vacancy formation, resulting in changes in Ce-O coordination number and Ce 3+ /Ce 4+ redox couple. When reduced enough, a crystallographic phase transition occurs from α to an α' phase with more oxygen vacancies. Nevertheless, the transition behavior is intriguingly different from the one predicted in the standard phase diagram of ceria. This work demonstrates a feasible means to control oxygen non-stoichiometry in ceria via electrochemical potential. It also sheds light on the mechanism of phase transitions induced by electrochemical potential. For electrochemical systems, effects from a large-scale electrical environment should be taken into consideration, besides effective oxygen partial pressure and temperature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Cation Crossover Limits Accessible Current Densities for Zero-Gap Alkaline CO2 Reduction to Ethylene

Traditional CO2 reduction systems often fail in an alkaline environment due to the interaction of CO2 with a high-pH electrolyte, where carbonate and bicarbonate ion formation results in potassium-containing salt precipitation. The presence of the salt crystals causes a reduction in the selectivity of the electrolyzer toward CO2 conversion. Here, the critical operational variables, which elicit the salting out process, are investigated (i.e., ion transport). When the electrolyzer exceeds a critical current density, H2 evolution dominates CO2 reduction due to salt formation, which is confirmed by postmortem cross-sectional SEM-EDS of the electrode. The critical current density decreases with an increasing membrane thickness or anolyte ionic strength. Cathode salt formation is mediated by the unmitigated crossover of cations from the anolyte to the cathode across an anion exchange membrane, through which cations are imperfectly excluded. It is likely that electric field-driven migration promotes an increase in concentration of potassium across the membrane, until, at the critical current density for that electrolyzer arrangement, the concentration of potassium and bicarbonate ions exceeds the solubility limit of KHCO3, leading to salt precipitation.

CO2 reduction↗
DOE OSTI2026

Machine learning pipeline for denoising low signal-to-noise ratio and out-of-distribution transmission electron microscopy datasets

High-resolution transmission electron microscopy (HRTEM) is crucial for observing material’s structural and morphological evolution at Angstrom scales, but the electron beam can alter these processes. Devices such as CMOS-based direct-electron detectors operating in electron-counting mode can be utilized to substantially reduce the electron dosage. However, the resulting images often lead to a low signal-to-noise ratio, which requires frame integration that sacrifices temporal resolution. Several machine learning (ML) models have been recently developed to successfully denoise HRTEM images. Yet, these models are often computationally expensive, and their inference speeds on GPUs are outpaced by the imaging speed of advanced detectors, precluding in situ analysis. Furthermore, the performance of these denoising models on datasets with imaging conditions that deviate from the training datasets has not been evaluated. To mitigate these gaps, we propose a new self-supervised ML denoising pipeline specifically designed for time-series HRTEM images. This pipeline integrates a blind-spot convolution neural network with pre-processing and post-processing steps, including drift correction and low-pass filtering. Results demonstrate that our model outperforms various other ML and non-ML denoising methods in noise reduction and contrast enhancement, leading to improved visual clarity of atomic features. Additionally, the model is drastically faster than U-Net-based ML models and demonstrates excellent out-of-distribution generalization. The model’s computational inference speed is in the order of milliseconds per image, rendering it suitable for application in in-situ HRTEM experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Probabilistic machine learning for battery health diagnostics and prognostics—review and perspectives

Abstract Diagnosing lithium-ion battery health and predicting future degradation is essential for driving design improvements in the laboratory and ensuring safe and reliable operation over a product’s expected lifetime. However, accurate battery health diagnostics and prognostics is challenging due to the unavoidable influence of cell-to-cell manufacturing variability and time-varying operating circumstances experienced in the field. Machine learning approaches informed by simulation, experiment, and field data show enormous promise to predict the evolution of battery health with use; however, until recently, the research community has focused on deterministic modeling methods, largely ignoring the cell-to-cell performance and aging variability inherent to all batteries. To truly make informed decisions regarding battery design in the lab or control strategies for the field, it is critical to characterize the uncertainty in a model’s predictions. After providing an overview of lithium-ion battery degradation, this paper reviews the current state-of-the-art probabilistic machine learning models for health diagnostics and prognostics. Details of the various methods, their advantages, and limitations are discussed in detail with a primary focus on probabilistic machine learning and uncertainty quantification. Last, future trends and opportunities for research and development are discussed.

25 ENERGY STORAGE↗
DOE OSTI2017

Stochastic optimization of GeantV code by use of genetic algorithms

GeantV is a complex system based on the interaction of different modules needed for detector simulation, which include transport of particles in fields, physics models simulating their interactions with matter and a geometrical modeler library for describing the detector and locating the particles and computing the path length to the current volume boundary. The GeantV project is recasting the classical simulation approach to get maximum benefit from SIMD/MIMD computational architectures and highly massive parallel systems. This involves finding the appropriate balance between several aspects influencing computational performance (floating-point performance, usage of off-chip memory bandwidth, specification of cache hierarchy, etc.) and handling a large number of program parameters that have to be optimized to achieve the best simulation throughput. This optimization task can be treated as a black-box optimization problem, which requires searching the optimum set of parameters using only point-wise function evaluations. Here, the goal of this study is to provide a mechanism for optimizing complex systems (high energy physics particle transport simulations) with the help of genetic algorithms and evolution strategies as tuning procedures for massive parallel simulations. One of the described approaches is based on introducing a specific multivariate analysis operator that could be used in case of resource expensive or time consuming evaluations of fitness functions, in order to speed-up the convergence of the black-box optimization problem.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Photon-odderon interference in exclusive χ c charmonium production at the Electron-Ion Collider

Exclusive C = + 1 scalar, axial-vector, and tensor quarkonium production in high-energy electron-proton scattering requires a C -odd t -channel exchange of a photon or a three-gluon ladder. We derive the expressions for the corresponding amplitudes. The relative phase of the photon vs three-gluon exchange amplitudes is determined by the sign of the light-front matrix element of the eikonal color current operator d a b c J + a J + b J + c at moderate x , and is not affected by small- x QCD evolution. Model calculations predict constructive interference, which is particularly strong for momentum transfer | t | ∼ 1 GeV 2 where the cross section for χ c J production exceeds that for pure photon exchange by up to a factor of 4. Exclusive χ c J electroproduction at the high luminosity Electron-Ion Collider occurs with well measurable rates and measurements of these processes should find evidence for the perturbative odderon exchange. We also compute the total electroproduction cross section as a function of energy and provide first estimates of the number of χ c J events per month at the Electron-Ion Collider design luminosity. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

Properties of infrared extrapolations in a harmonic oscillator basis

Here, the success and utility of effective field theory (EFT) in explaining the structure and reactions of few-nucleon systems has prompted the initiation of EFT-inspired extrapolations to larger model spaces in ab initio methods such as the no-core shell model (NCSM). In this contribution, we review and continue our studies of infrared (ir) and ultraviolet (uv) regulators of NCSM calculations in which the input is phenomenological NN and NNN interactions fitted to data. We extend our previous findings that an extrapolation in the ir cutoff with the uv cutoff above the intrinsic uv scale of the interaction is quite successful, not only for the eigenstates of the Hamiltonian but also for expectation values of operators, such as r 2 , considered long range. The latter results are obtained with Hamiltonians transformed by the similarity renormalization group (SRG) evolution. On the other hand, a possible extrapolation of ground state energies in the uv cutoff when the ir cutoff is below the intrinsic ir scale is not robust and does not agree with the ir extrapolation of the same data or with independent calculations using other methods.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Benchmarking Solid-State Batteries Containing Sulfide Separators: Effects of Electrode Composition and Stack Pressure

Integrating sulfide separators into solid-state batteries (SSBs) containing high energy cathodes typically requires one or more materials and engineering solutions including: (i) applying interfacial coatings to mitigate electrolyte decomposition, (ii) applying high stack pressures to form robust solid-solid contacts, and (iii) using alloying anodes to avoid Li dendrite formation. Despite the promise of these approaches, a lack of standardized testing protocols makes it difficult to directly compare results among different studies. To address this problem, the present work benchmarks the performance of SSBs containing β-Li 3 PS 4 (LPS) separators and composite cathodes. By systematically varying the anode/cathode composition and stack pressure, this work demonstrates that cathode design is a major bottleneck for solid-state cells cycled at low rates (<100 µA cm -2 ). Operando stack pressure measurements show that, while mechanical confinement generally promotes higher active material utilization and cycling stability, this strategy alone does not address interfacial reactivity between LPS and high voltage cathodes. Here, these results also demonstrate that stress evolution during cycling is dominated by volume changes at the Li metal anode. Finally, we show that FeS 2 cathodes with moderate operating voltages (<3 V vs Li/Li + ) exhibit superior cycling performance compared to high voltage cathodes by facilitating formation of stable cathode/electrolyte interfaces.

25 ENERGY STORAGE↗
DOE OSTI2019

Conceptual Design of the Belgian Geological Disposal Facility for Category B and C Wastes - 19341

For more than 40 years, ONDRAF/NIRAS (the federal agency responsible for managing radioactive waste and enriched fissile materials in Belgium) has been studying the concept of a geological disposal facility (GDF), within poorly indurated clays, as an option for the long-term management of both category B waste (low-level and intermediate-level long-lived waste - LILW-LL) and category C waste (high-level waste - HLW and spent fuel). The proposed Belgian reference option for disposal of such waste is a GDF within poorly indurated clays, located at a depth of between 200 m and 600 m. Within the framework of the first Safety and Feasibility Case (SFC-1) undertaken by ONDRAF/NIRAS, the former GDF layout, which dates back from 2003 has been updated. The first part of the paper describes the main drivers behind the evolution of the former 2003 GDF design towards the current reference SFC-1 design. It also details how these drivers, related to operational and constructional constraints, have affected the GDF layout, such as the disposal gallery length, the crossing shapes of the GDF galleries and the layout of access and waste shafts. The second part of the paper focuses on the engineering and construction challenges generated by GDF development within poorly indurated clays. This includes discussion of the impact of the specific mechanical characteristics such poorly indurated clays have on the construction methods used for the shafts, the rock support (concrete lining), the drift connections, the crossings and the global GDF design. These construction methods have been selected based on research conducted at the underground research laboratory HADES in Mol (Belgium). Finally, the main axes for further development of the GDF design within the SFC-1 framework is presented. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

A mechanistic damage model for solid oxide fuel cell ceramic materials - Part I: Constitutive modeling

A multiscale mechanistic damage model for solid oxide fuel cell (SOFC) ceramics that combines micromechanics of stiffness reduction due to material porosity change and microcracking with a continuum damage mechanics (CDM) description for the evolution of microcracks up to fracture is developed in this work. The model also accounts for volumetric swelling of the anode due to redox cycling. Porosity change and swelling during redox combined with normal operating thermomechanical loads could increase the stress, strain and damage distributions in SOFC stacks leading them to failure. The proposed model involves three governing parameters: (i) the porosity in terms of the pore or void volume fraction, (ii) material swelling magnitude prescribed at a given loading step, and (iii) the damage variable that describes microcracking caused by thermomechanical loads and swelling. Pores and microcracks in the ceramics are modeled as randomly distributed ellipsoidal inclusions with negligible stiffness by an Eshelby-Mori-Tanaka formulation combined with an inclusion orientation distribution method. Microcracking damage evolution is described by a CDM formulation. Volumetric swelling is treated in a similar way to thermal expansion in the constitutive relations. After validation and numerical checks, the damage model is used to analyze a simplified SOFC positive-electrode/electrolyte/negative-electrode (PEN) structure subjected a redox cycle in addition to thermomechanical loads experienced during normal operation of a SOFC stack.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2021

CUORE opens the door to tonne-scale cryogenics experiments

The past few decades have seen major developments in the design and operation of cryogenic particle detectors. This technology offers an extremely good energy resolution – comparable to semiconductor detectors – and a wide choice of target materials, making low temperature calorimetric detectors ideal for a variety of particle physics applications. Rare event searches have continued to require ever greater exposures, which has driven them to ever larger cryogenic detectors, with the CUORE experiment being the first to reach a tonne-scale, mK-cooled, experimental mass. CUORE, designed to search for neutrinoless double beta decay, has been operational since 2017 at a temperature of about 10 mK. This result has been attained by the use of an unprecedentedly large cryogenic infrastructure called the CUORE cryostat: conceived, designed and commissioned for this purpose. In this article the main characteristics and features of the cryogenic facility developed for the CUORE experiment are highlighted. In this work, a brief introduction of the evolution of the field and of the past cryogenic facilities are given. The motivation behind the design and development of the CUORE cryogenic facility is detailed as are the steps taken toward realization, commissioning, and operation of the CUORE cryostat. The major challenges overcome by the collaboration and the solutions implemented throughout the building of the cryogenic facility will be discussed along with the potential improvements for future facilities. The success of CUORE has opened the door to a new generation of large-scale cryogenic facilities in numerous fields of science. Broader implications of the incredible feat achieved by the CUORE collaboration on the future cryogenic facilities in various fields ranging from neutrino and dark matter experiments to quantum computing will be examined.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

Complex fracture nucleation and evolution with nonlocal elastodynamics

In this study, a mechanical model is introduced for predicting the initiation and evolution of complex fracture patterns without the need for damage variable or law. The model, a continuum variant of Newton's second law, uses integral rather than partial differential operators where the region of integration is over finite domain. The force interaction is derived from a novel nonconvex strain energy density function, resulting in a nonmonotomic material model. The resulting equation of motion is proved to be mathematically well-posed. The model has the capacity to simulate nucleation and growth of multiple, mutually interacting dynamic fractures. In the limit of zero region of integration, the model reproduces the classic Griffith model of brittle fracture. The simplicity of the formulation avoids the need for supplemental kinetic relations that dictate crack growth or the need for an explicit damage evolution law.

36 MATERIALS SCIENCE↗
DOE OSTI2016

ADMS State of the Industry and Gap Analysis

An Advanced distribution management system (ADMS) is a platform for optimized distribution system operational management. This platform comprises of distribution management system (DMS) applications, supervisory control and data acquisition (SCADA), outage management system (OMS), and distributed energy resource management system (DERMS). One of the primary objectives of this work is to study and analyze several ADMS component and auxiliary systems. All the important component and auxiliary systems, SCADA, GISs, DMSs, AMRs/AMIs, OMSs, and DERMS, are discussed in this report. Their current generation technologies are analyzed, and their integration (or evolution) with an ADMS technology is discussed. An ADMS technology state of the art and gap analysis is also presented. There are two technical gaps observed. The integration challenge between the component operational systems is the single largest challenge for ADMS design and deployment. Another significant challenge noted is concerning essential ADMS applications, for instance, fault location, isolation, and service restoration (FLISR), volt-var optimization (VVO), etc. There are a relatively small number of ADMS application developers as ADMS software platform is not open source. There is another critical gap and while not being technical in nature (when compared the two above) is still important to consider. The data models currently residing in utility GIS systems are either incomplete or inaccurate or both. This data is essential for planning and operations because it is typically one of the primary sources from which power system model are created. To achieve the full potential of ADMS, the ability to execute acute Power Flow solution is an important pre-requisite. These critical gaps are hindering wider Utility adoption of an ADMS technology. The development of an open architecture platform can eliminate many of these barriers and also aid seamless integration of distribution Utility legacy systems with an ADMS.

24 POWER TRANSMISSION AND DISTRIBUTION↗