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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Modified triglycine sulphate (TGS) single crystals for pyroelectric infrared detector applications

Effects of caesium and cerium, L-alanine, and caesium plus L-alanine impurities on ferroelectric and pyroelectric properties of TGS crystals are investigated. Dielectric constant and loss, pyroelectric coefficient, spontaneous polarization, and coercive field measurements of these modified crystals, as a function of temperature, are reported. Caesium and cerium did not affect the electrical properties of TGS crystals significantly, whereas L-alanine- and, especially, Cs + L-alanine-doped TGS crystals exhibited promising improvements in pyroelectric properties, up to 48 C, as compared to pure TGS crystals.

Banan, M.↗
NASA NTRS2009

Coated silicon comprising material for protection against environmental corrosion

In accordance with an embodiment of the invention, an article is disclosed. The article comprises a gas turbine engine component substrate comprising a silicon material; and an environmental barrier coating overlying the substrate, wherein the environmental barrier coating comprises cerium oxide, and the cerium oxide reduces formation of silicate glass on the substrate upon exposure to corrodant sulfates.

Hazel, Brian Thomas↗
DOE OSTI2025

A Data-Agnostic, Continuous Machine Learning Framework for Application in High Energy Physics and Beyond: Phase 1 Final Scientific/Technical Report

This Phase 1 effort has focused on the development of continual learning frameworks for use in machine learning, specifically in the applied context of High Energy Physics (HEP). Machine learning (ML) is a transformative technology by which computers, typically through the use of neural networks, are able to perform tasks with proficiency that rivals or surpasses that of human users. Model Degradation & Catastrophic Forgetting are two undesired phenomena which can occur in ML where the performance of a model degrades when either deployed on novel data streams, or trained on novel data which are sufficiently different than the data the models were initially trained on. A natural example where these sorts of effects can be observed is in the performance of detectors in harsh environments, where the detector signature may change over the lifetime of the detector as it ages and deteriorates — precisely what occurs in the experiments conducted in HEP. Real world HEP data is therefore an excellent test-ground and use-case for Continual Learning paradigms, which are techniques used in ML to counteract these problems. Ensemble learning is one such technique, where multiple smaller models are trained on subsets of the overall data and are ensembled together during inference. The intuition behind this technique is that, although there are shifts in the distributions which govern the incoming data streams, these shifts are not expected to be homogeneous or global. If a sufficient diversity in solutions within the various sub-models has been achieved, then at least one sub-model is expected to retain its performance within the overall ensemble. One further strength of this approach is that the architectures of the various models do not need to be identical, and in fact even different modalities of data can naturally be combined in this way. This work focused on applying ensemble learning techniques to derive results using two main datasets, anomaly detection in HEP data & time-series forecasting in semiconductor manufacturing data. Semiconductor manufacturing involves data with surprising similarity to that of HEP (e.g. wafer maps look very similar to digi-occupancy maps) and Cerium Lab’s prominence within the semiconductor industry makes semiconductor manufacturing a natural opportunity for commercialization of this work. Our efforts have led to two strong results. The first is that we evaluated the proposed ensembling techniques using previously proposed machine learning architectures for use in anomaly detection, namely AutoEncoder based models and their derivatives. We also developed new architectures which have not been evaluated in this context before. In fact, this work marks the first use of Vision Transformers for anomaly detection in HEP. Second, we demonstrated that ensemble learning significantly improves model performance in scenarios prone to degradation, validating its effectiveness across both HEP and semiconductor datasets. These results further support ensemble learning as a powerful strategy for mitigating catastrophic forgetting and maintaining robust performance in evolving data environments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

LDRD conclusion poster - Synthesizing Heterometallic Uranium Single Crystals to Understand the Influence of the Secondary Metals on Uranyl Axial Bond Strength

Understanding how transition metals influenced the chemistry of lanthanide and actinide (f-element) materials is critical for advancing separation technologies, materials design, and coordination chemistry. This project examined how incorporating first-row transition metals affected the structural and spectroscopic properties of f-element coordination polymers. In uranium(VI)-based systems synthesized with 2,6-pyridinedicarboxylic acid (PDC) ligands, single-crystal X-ray diffraction and Raman spectroscopy revealed that the presence of transition metals shortened the uranyl axial bond and induced a blue shift in its symmetric stretching vibration—evidence of increased bond strength. Electronic structure analysis, including Density of States (DOS) calculations using density functional theory (DFT), revealed altered orbital overlaps and highlighted the role of transition metal d-orbitals in modulating bonding. Raman modes were modeled using truncated structural fragments in collaboration with the University of Notre Dame, and although the predicted frequencies were lower than experimental values, they remained within expected ranges. In parallel, similar experiments with cerium (Ce) in the presence of cobalt (Co) and PDC demonstrated multi-step single-crystal-to-single-crystal transformations—behavior not observed in the uranium systems. Initial products included light yellow, orange, and polycrystalline materials. Single-crystal X-ray diffraction studies, conducted in collaboration with the Colorado School of Mines, identified the yellow phase as monometallic Ce(PDC)2(H2O)2·4H2O and the orange phase as heterometallic Ce2Co(PDC)4(H2O)6. After standing in solution for one week, both phases fully transformed into a dark yellow crystalline phase, [Ce3(PDC)5(H2O)8].6(H2O). Remarkably, this transformation was reversible—disturbing the equilibrium by removing some crystals caused reversion to the initial Ce(PDC)2(H2O)2·4H2O phase, highlighting dynamic behavior. All three structures were previously unreported. Solid-state UV-visible and Raman spectroscopy further distinguished these phases, revealing ligand-to-metal charge transfer involving Ce and characteristic d–d transitions from Co(II). The precise mechanism driving these transformations remained unclear; however, pH-dependent experiments confirmed that the transformation did not occur when the pH decreased. Overall, the project demonstrated that transition metals could be employed to tune bonding interactions, structural dimensionality, and optical properties in f-element materials, establishing new pathways for designing functional heterometallic systems. The work resulted in several novel structural discoveries and fostered productive collaborations with the University of Notre Dame and the Colorado School of Mines.

37 - INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL C↗
DOE OSTI2026

Marine algae growth and carbon capture augmentation by antioxidant nanozymes

Large scale commercial cultivation of microalgae year-round is limited by seasonal stress conditions. The rapid growth and high CO 2 capture of the marine microalga Picochlorum celeri is largely inhibited under winter stress conditions of low temperature and high light. Herein, we demonstrated a nanotechnology approach to enhance the biomass productivity and CO 2 capture of P. celeri under abiotic stress by interfacing with antioxidant cerium oxide nanozymes (nanoceria). Antioxidant nanoceria catalytically scavenged reactive oxygen species (ROS) generated under stress conditions, reducing damage to the microalgae photosynthetic machinery in chloroplasts. Negatively charged poly-acrylic acid-coated nanoceria (PNC, 10 μM) were biocompatible in microalgae cells and colocalized with chloroplasts. In contrast, positively charged aminated nanoceria (ANC) resulted in microalgae aggregation (>50 μM) and were toxic at all concentrations tested (≥10 μM). PNC reduction of ROS levels in microalgae (78%) and superoxide levels (26%), enhanced microalgae growth (65%), photosynthetic performance (130%), and CO 2 uptake rate (380%) under low-temperature stress (15 °C) and high light (500 μmol/m 2 /s PAR) stress relative to controls without nanoceria. Nanoceria augmentation of microalgae provides a rapid and facile technology to increase algae CO 2 capture and biomass under stress conditions.

09 BIOMASS FUELS↗
DOE OSTI2026

A comparative study on cubic and tetragonal Ce-ZrO 2 supported Rh catalysts for N 2 O decomposition

Zirconium oxide (ZrO 2 ) exhibits strong synergy with cerium oxide (CeO 2 ), acting as a structural and electronic promoter during catalytic redox reactions. As a result, Ce-ZrO 2 composite oxides are widely used as supports in various catalytic systems. In our previous work, we demonstrated that the incorporation of Zr 4+ into the CeO 2 lattice significantly enhanced Rh dispersion, improved redox ability, and stabilized surface Rh species, which collectively boosted the de-N 2 O activity of Rh/Ce-ZrO 2 catalysts. Building on these findings, the present study emphasizes that the crystallographic phase of Ce-ZrO 2 , governed by the Ce/Zr ratio, plays a decisive role in tuning the physicochemical environment of Rh active sites and thereby optimizing catalytic performance. In conclusion, tailoring the Ce/Zr ratio to favor the cubic fluorite structure emerges as a promising strategy for the rational design of highly active and stable catalysts for N 2 O decomposition and potentially other redox-sensitive environmental applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Thermodynamic modeling of countercurrent chemical looping reverse water gas shift process for redox material screening

The reverse water gas shift (RWGS) reaction is a key pathway for CO 2 utilization, particularly within Power-to-X process chains aimed at sustainable fuel and chemical production. Countercurrent chemical looping (CL-RWGS) using non-stoichiometric oxides can overcome equilibrium limitations of conventional RWGS reactors, enabling significantly higher CO 2 conversions. However, modeling the limiting performance of such systems is challenging due to their multiphase nature and coupled spatial and temporal variation in chemical composition. In this work, we present a discretized batch equilibrium model that simulates CL-RWGS reactors as a series of localized equilibrium exchanges between gas and solid elements. The model is numerically stable, computationally efficient, and free of kinetic source terms, making it well-suited for parametric studies and system-level integration. It is validated against established convection–diffusion models and shown to predict reasonable upper bounds on experimental results. Application of the model to a range of oxygen carrier materials identifies cerium–zirconium solid solutions, particularly Ce 0.80 Zr 0.20 O 2 , as a promising class offering superior oxygen storage characteristics compared to state-of-the-art La 0.6 Sr 0.4 FeO 3 . This framework provides a robust platform for materials screening, reactor sizing, and performance optimization in chemical looping systems. The model implementation is available as open-source software to support further research and development.

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

Diffusion behavior of lanthanide fission products in bcc Fe cladding: A first-principles study

Fuel-cladding chemical interaction poses significant challenges in nuclear reactors, where fission products generated from nuclear fuel interact with Fe-based cladding materials, potentially compromising their structural integrity. This study investigates the diffusion behavior of lanthanide fission products, Lanthanum (La), Cerium (Ce), Praseodymium (Pr), and Neodymium (Nd), within body-centered cubic (bcc) Fe cladding using the density functional theory, nudged elastic band method, and self-consistent mean field theory. Our results reveal significant vacancy binding energies, particularly with the 1st and 2nd nearest neighbors, which diminish beyond the 5th nearest neighbor, with La exhibiting the strongest binding affinity, followed by Nd, Ce, and Pr. The nudged elastic band calculations indicate significant high barriers for the dissociation of 1st nearest neighbor vacancy-solute pairs for all fission products. The tracer diffusion coefficients of these fission products were derived in an Arrhenius form, with a magnetic correction that accounts for the high-temperature paramagnetic state. The significant trapping effect of vacancies caused by a very dilute concentration of fission products reduces vacancy mobility, potentially leading to modifications in point defect supersaturation, void nucleation, and swelling under irradiation. These represent critical challenges for irradiated cladding materials. The tracer diffusion coefficients indicate that Nd diffuses the fastest, followed by La, Ce, and Pr. Furthermore, this study provides essential insights for understanding fission product transport in cladding materials and informs future design strategies to mitigate fuel-cladding chemical interaction, ultimately enhancing nuclear reactor safety and performance.

Diffusion↗
DOE OSTI2025

Development and characterization of an aerosol-generated multi-method analytical particle test material

Ceria (CeO 2 ) particles with low to ultra-low loading of nickel dopant were produced using an aerosol-based, droplet-to-particle synthesis via an in-line calcination technique. This aerosol-based synthesis method enables the production of particles with a monodisperse size distribution. These produced and well-characterized, multi-element, ceria-based particles demonstrate a material exemplar for multi-method analytical testing. They were prepared from a cerium nitrate feedstock where low loading nickel dopant was added at target Ni/(Ni + Ce) atomic percents of 1 %, 0.1 %, and 0.01 %, using a nickel nitrate spike. This methodology proved to produce ceria particles doped with a dynamic range of low to ultra-low loadings of nickel over a 24-h period, with consistent size distribution, morphology, and composition. The successful incorporation of nickel was demonstrated with bulk and single particle inductively coupled plasma mass spectroscopy and revealed notable particle-to-particle elemental homogeneity. X-ray photoelectron spectroscopy demonstrated the presence of a high concentration of nickel dopant incorporated preferentially toward the surface of the particles, and that this dopant aided oxidation of surface Ce(III) atoms to Ce(IV). These particle test materials were then validated through X-ray absorption near edge spectroscopy, comparing the ultra-low 0.01 % Ni and low 1 % Ni-doped ceria samples. This revealed a more-reduced oxidation state of the nickel with an increase in dopant concentration. Finally, this work demonstrates a synthesis and systematic characterization scheme to produce multi-method analytical test particulates.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Porosity, swelling, and composition evolution in high-burnup monolithic U-Mo fuel

The microstructural progression of very high-burnup (>8 × 10 21 fissions/cm 3 ) monolithic uranium-molybdenum (U-10wt.%Mo) was analyzed, providing crucial insights into the behavior of post-recrystallized nuclear fuel, where scant data exists. Three focused ion beam cuboids sourced from a fuel plate with varying local burnups of 8.86 × 10 21 , 9.05 × 10 21 , and 9.36 × 10 21 fissions/cm 3 were characterized. The porosity and composition of the samples were evaluated to characterize the evolution of the microstructure as a function of fission density and different locations on the fuel plate, while simultaneously isolating plate-specific parameters such as Zr diffusion barrier thickness, hot-isostatic-pressing conditions, enrichment, and reactor conditions. The porosity was segmented, and the three-dimensional distribution of the porosity was extrapolated from the two-dimensional segmentation. The composition was assessed and quantified using energy-dispersive X-ray spectroscopy areal mapping. The porosity fraction increased as a function of the burnup from 27.77±0.51, 35.12±1.54, and 37.71±0.44 % for 8.86 × 10 21 , 9.05 × 10 21 , and 9.36 × 10 21 fissions/cm 3 , respectively. When compared to literature, the porosity volume fraction plateaus at burnups greater than 6 × 10 21 fissions/cm 3 , while the pore size grows linearly as a function of fission density. The number of large pores increased in number density as a function of burnup, while the smallest pores (<0.3 µm) increased up to 9.05 × 10 21 fissions/cm 3 , followed by a decrease at 9.36 × 10 21 fissions/cm 3 . The delamination and cracking in the fuel plate propagated through an interconnected porosity sublayer identified ∼5 µm from the diffusion barrier. The local swelling of the specimens was within or near the prediction bounds of the Robinson-Williams model for local swelling. The fission products, strontium, barium, cerium, and cesium, precipitated into the pores, while neodymium accumulated adjacent to the pores. Furthermore, these findings have direct implications for the development of fuel performance codes and the accurate documentation of the microstructure evolution in high burnup U-Mo, thus enhancing the safety and efficiency of nuclear fuel usage.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Infiltrated electrodes for metal supported solid oxide electrolysis cells

Metal-supported solid oxide cells (MSOCs) are an alternative to conventional solid oxide cells (SOCs) based on ceramic cermets, offering lower material costs and higher operational flexibility. In this study symmetric MSOCs with infiltrated electrodes are explored for steam electrolysis operation to understand the underlying operation and degradation principles and suggest a direction for future MSOCs development. Two different fuel electrode backbones are used: an electronically-conductive lanthanum strontium co-doped iron nickel titanate (LSFNT) infiltrated with cerium-gadolinium oxide (CGO), or an ionic conductive zirconia based backbone (10ScYSZ) infiltrated with Ni:CGO. At the oxygen side, the backbone is 10ScYSZ, which is infiltrated with lanthanum-strontium co-doped cobalt oxide (LSC), or praseodymium oxide as cobalt-free alternative for comparison. This study suggests that the backbone electronic conductivity is key for good electrochemical performance as well as for boosting cell durability. Highly electronically conductive nanoparticles, especially nickel, were observed to irreversibly agglomerate driven by thermal conditions, whereas CGO proved to be a very stable electrocatalyst. At the fuel side, CGO (LSFNT) electrode showed lower ASR and degradation rate than Ni:CGO(ScYSZ) configuration with measured values of 0.50 Ω cm2 and 11 %/1000 h (at 0.60 A/cm2), and 0.70 Ω cm2 and 26 %/1000 h (at 0.50 A/cm2) at 1.30 V, respectively (700 °C, 50 % steam in hydrogen at the fuel side and air at the oxygen electrode side, LSC(ScYSZ) oxygen electrode).

25 ENERGY STORAGE↗
DOE OSTI2026

Combustion-assisted ink-jet printing of nuclear targets

Advances in target fabrication are critical to high-precision measurements in nuclear physics. This work details the preparation of patterned CeO 2 and ThO 2 architectures and thin-film targets via ink-jet deposition of combustible solutions. The produced targets were characterized by scanning electron microscopy (SEM), and by alpha-particle spectroscopy for radioactive targets to determine densities. Ink jet printing of the targets, used both ethanol and 2-methoxyethanol as solvents, with cerium or thorium nitrate as the oxidizer and acetylacetone as the fuel. Additionally, we found that the distance between each droplet dispersion (step size) played the most significant role in determining the final pattern uniformity and thickness. A 50 μm step size leads to relatively thick targets with a density of 350 μg/cm 2 . Significant overlap in droplet sizes leads to a heterogeneous target with an undesirable cracked surface structure. In contrast, 150 μm spacing yields thinner (20 μg/cm 2 ) patterned structures with excellent surface coverage. This method of Ink-jet printing provides a straightforward, scalable, and high-efficiency pathway to prepare custom made, high-quality targets for nuclear physics experiments.

CeO2↗
DOE OSTI2025

Pulsed contact glow discharge electrification for online material quantification

Real-time elemental analysis of liquids in extreme environments remains a significant challenge for sensor development, particularly in applications such as advanced nuclear reactors. Plasma-based optical emission spectroscopy offers a promising solution. In this study, we investigate pulsed contact glow discharge electrolysis (CGDE) as an alternative plasma generation method for emission-based material quantification. Using aqueous NaCl solutions, we examine the role of discharge polarity on plasma behavior, emission characteristics, and spectral output. Our results demonstrate that cathodic discharges generate more energetic plasmas, enabling the detection of ionic species such as cerium, while anodic discharges favor atomic emission. These findings reveal a potential dual-mode sensing capability controlled by circuit configuration rather than hardware changes. Through synchronized measurements of emission, current, bubble, and spectral dynamics, we present a model in which electron emission and ohmic heating drive plasma formation. This model enhances our understanding of pulsed-CGDE and supports its potential as a versatile, adaptable platform for future deployment in high-temperature liquids such as molten salts.

98 - NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL↗
DOE OSTI2025

Search for Stable and Low-Energy Ce–Co–Cu Ternary Compounds Using Machine Learning

Cerium-based intermetallics have garnered significant research attention as potential new permanent magnets. In this study, we explore the compositional and structural landscape of Ce−Co−Cu ternary compounds using a machine learning (ML)- guided framework integrated with first-principles calculations. We employ a crystal graph convolutional neural network (CGCNN), which enables efficient screening for promising candidates, significantly accelerating the material discovery process. With this approach, we predict five stable compounds, Ce 3 Co 3 Cu, CeCoCu 2 , Ce 12 Co 7 Cu, Ce 11 Co 9 Cu, and Ce 10 Co 11 Cu 4 , with formation energies below the convex hull, along with hundreds of low-energy (possibly metastable) Ce−Co−Cu ternary compounds. Firstprinciples calculations reveal that several structures are both energetically and dynamically stable. Notably, two Co-rich low-energy compounds, Ce 4 Co 33 Cu and Ce 4 Co 31 Cu 3 , are predicted to have high magnetizations.

Chemical structure↗
DOE OSTI2025

Structural Investigation of Six Quinary Sulfides Synthesized via the Flux-Assisted Boron-Chalcogen Mixture (BCM) Method: Eu 2+ Containing Members of the RE 3 MTQ 7 (M and T = Transition or Main Group Metals, Q = Chalcogens) Family

For this work, a series of six quinary rare-earth sulfides Ce 4+ 1.85 Eu 2+ 1.15 Na 0.30 SiS 7 , Ce 4+ 1.91 Eu 2+ 1.09 K 0.18 SiS 7 , Ce 4+ 1.96 Eu 2+ 1.04 Rb 0.08 SiS 7 , Ce 4+ 1.98 Eu 2+ 1.02 Cs 0.05 SiS 7 , Ce 4+ 1.97 Eu 2+ 1.03 Ag 0.06 SiS 7 , and Ce 4+ 1.50 Eu 2+ 1.50 CuSiS 7 were obtained in an alkali iodide flux using the boron-chalcogen mixture (BCM) method. Single crystal X-ray diffraction was used to determine the structures of the high quality single crystals that were grown; their elemental compositions were confirmed by energy-dispersive spectroscopy (EDS). The compounds crystallize in the hexagonal crystal system in the noncentrosymmetric space group P63. The crystal structure consists of a three-dimensional network composed of mixed cerium and europium bicapped trigonal prisms, isolated SiS4 tetrahedra, and monovalent metals (Na, K, Rb, Cs, Ag, and Cu) located in cavities created by linked Ce/EuS 8 polyhedra. The structures are charge-balanced when Ce and Eu are in their +4 and +2 oxidation states, respectively. The effective magnetic moment of Ce 1.50 4+ Eu 1.50 2+ CuSiS 7 determined from the temperature dependence of the magnetic susceptibility data is consistent with the presence of Ce 4+ and Eu 2+ . Clear correlations between the alkali ion site occupancy, the ionic radius of the alkali cations, and the average bond length of Ce 4+ /Eu 2+ –S, were established. UV–vis diffuse reflectance data were collected for Ce 1.50 4+ Eu 1.50 2+ CuSiS 7 and a band gap of 1.9(1) eV was established.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗