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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Tidal frequencies and quasiperiodic subsurface water level variations dominate redox dynamics in a salt marsh system

Salt marshes are hotspots of nutrient processing en route to sensitive coastal environments. Whilst our understanding of these systems has improved over the years, we still have limited knowledge of the spatiotemporal variability of critical biogeochemical drivers within salt marshes. Sea-level rise will continue to force change on salt marsh functioning, highlighting the urgency of filling this knowledge gap. Our study was conducted in a central California estuary experiencing extensive marsh drowning and relative sea-level rise, making it a model system for such an investigation. Here we instrumented three marsh positions subjected to different degrees of tidal inundation (6.7%, 8.9%, and 11.2% of the time for the upper, middle, and lower marsh positions, respectively), providing locations with varied biogeochemical characteristics and hydrological interactions at the site. We continuously monitored redox potential (Eh) at depths of 0.1, 0.3, and 0.5 m, subsurface water levels (WL), and temperature at 0.7 m depth at each marsh position. To understand how drivers of subsurface biogeochemical processes fluctuate across tidal cycles, we used wavelet analyses to explain the interactions between Eh and WL. We found that tidal forcing significantly affects key drivers of biogeochemical processes by imparting controls on Eh variability, likely driving subsurface hydro-biogeochemistry of the salt marsh. Wavelet coherence showed that the Eh-WL relationship is nonlinear, and their lead–lag relationship is variable. We found that precipitation events perturb Eh at depth over timescales of hours, even though WL shows relatively minimal change during events. Furthermore, this work highlights the importance of high frequency in situ measurements, such as Eh, to help explain factors that govern subsurface biogeochemistry and hydrological processes in salt marshes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Evaluation of the ring tension test (RTT) for robust determination of material strengths

The ring tension test (RTT) is an experimental method for determining mechanical behavior in a material’s circumferential or hoop direction. It is a crucial test for testing anisotropic materials with tube geometry, such as nuclear fuel cladding or irradiated pipes. Several RTT configurations exist, each with their own advantages and disadvantages. However, this test is significantly more complex than traditional tensile testing and can be especially sensitive to small differences and inconsistencies in the test setup and geometry, ultimately affecting the derived mechanical properties. Previous research has focused on method development, and little work has been done on understanding the subtle differences between an ideal test and experiments, specifically when the tests are performed on highly irradiated materials in hot cells. In this work, a finite element-based investigation of the RTT is conducted to fill this gap. The two most used test configurations are investigated, comparing their ability to determine accurate material strengths through plastic deformation. Several non-ideal conditions and uncontrollable effects which are likely to occur during experimental testing such as machining tolerances, variations of specimen geometry from nominal dimensions, rotation of specimens and fixturing, and other test setup discrepancies are studied. The sensitivity of measured strengths to these conditions is presented. A mechanics-based approach to describing and correcting raw data to determine actual strengths is also included for one of the configurations, resulting in a robust correction method with highly accurate material strength measurements. Finally, based on these analyses, the hemicylindrical mandrel configuration is recommended with a gauge region oriented at a 45° angle.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Physics-informed machine learning assisted uncertainty quantification for the corrosion of dissimilar material joints

Jointing techniques like the Self-Piercing Riveting (SPR), Resistance Spot Welding (RSW) and Rivet-Weld (RW) joints are used for mass production of dissimilar material joints due to their high performance, short cycle time, and adaptability. However, the service life and safety usage of these joints can be largely impacted by the galvanic corrosion due to the difference in equilibrium potentials between the metals with the presence of electrolyte. Here, in this paper, we focus on Al-Fe galvanic corrosion and develop physics-informed machine learning based surrogate model for statistical corrosion analysis, which enables the reliability analysis of dissimilar material joints under corrosion environment. In this study, a physics-based finite element (FE) corrosion model has been developed to simulate the galvanic corrosion between a Fe cathode and an Al anode. Geometric and environmental factors including crevice gap, roughness of anode, conductivity, and the temperature of the electrolyte are investigated. Further, a thorough Uncertainty Quantification (UQ) analysis is conducted for the overall corrosion behavior of the Fe-Al joints. It is found that the electrolyte conductivity has the largest effects on the material loss and needs to be managed closely for better corrosion control. This will help in designing and manufacturing joints with improved corrosion performance.

42 ENGINEERING↗
DOE OSTI2021

Lithium thiostannate spinels: air-stable cubic semiconductors.

Lithium chalcogenide materials have been studied less than other alkali metal analogs and are of interest as ion conductors and semiconductors capable of thermal neutron detection. Herein, we describe the structural, thermal, magnetic, electronic, and ionic properties of a new family of cubic lithium thiospinels Li2MSn3S8 (M = Mg, Fe, Mn, Ni, Co) and Li1.66CuSn3.33S8. All compounds crystallize in the Fd (3) over barm space group and exhibit site occupancy disorder with Sn and M on the octahedral site for M = Mg, Fe, Mn, Ni, Co. The Li1.66CuSn3.33S8 compound also exhibits occupancy disorder on the tetrahedral sites between Li and Cu, as well as on the octahedral sites between Li and Sn. We demonstrate the ability to tune the physical properties of the compounds by changing their composition. By tuning the identity of the transition metal in the structure, the optical band gaps can vary between 0.91(2) and 2.19(2) eV, and electrical resistivities between 2.8 x 10(3) Omega-cm and 2.2 x 10(7)Omega-cm can be achieved. Density functional theory calculations for Li2MgSn3S8 and Li1.66CuSn3.33S8 suggest that both materials have indirect band gaps and significantly dispersive conduction bands. A bandwidth dispersion of 0.75 and 0.70 eV along the Gamma -> M direction in the conduction band are predicted for Li2MgSn3S8 and Li1.66CuSn3.33S8, respectively, with an electron effective mass of 0.49 and 0.55 m(e) at the Gamma point. The hole effective mass in the valence band is calculated to be 1.25 me at the M point and 0.75 me at the L point for Li2MgSn3S8 and Li1.66CuSn3.33S8, respectively. The ionic/electronic conductivity of each compound was determined using AC electrochemical impedance spectroscopy.

Quintero, Michael A.↗
DOE OSTI2021

Relaxed Current Matching Requirements in Highly Luminescent Perovskite Tandem Solar Cells and Their Fundamental Efficiency Limits

Perovskite-based tandem solar cells are of increasing interest as they approach commercialization. Here we use experimental parameters from optical spectroscopy measurements to calculate the limiting efficiency of perovskite–silicon and all-perovskite two-terminal tandems, employing currently available bandgap materials, as 42.0% and 40.8%, respectively. We show luminescence coupling between subcells (the optical transfer of photons from the high-bandgap to low-bandgap subcell) relaxes current matching when the high-bandgap subcell is a luminescent perovskite. We calculate that luminescence coupling becomes important at charge trapping rates (=10 6 s -1 ) already being achieved in relevant halide perovskites. Luminescence coupling increases flexibility in subcell thicknesses and tolerance to different spectral conditions. For maximal benefit, the high-bandgap subcell should have the higher short-circuit current under average spectral conditions. This can be achieved by reducing the bandgap of the high-bandgap subcell, allowing wider, unstable bandgap compositions to be avoided. Lastly, we visualize luminescence coupling in an all-perovskite tandem through cross-section luminescence imaging.

14 SOLAR ENERGY↗
DOE OSTI2025

Controlled Synthesis of SnO 2 Nanocrystals with Tunable Band Gaps

Tin(IV) oxide nanocrystals (SnO 2 NCs) have significant potential in various applications, with their performance closely related to their band gap. The band gap is influenced by the size and shape of the NCs, which can be precisely controlled by adjusting reaction conditions. In this study, we present deliberately designed synthesis protocols to produce high-quality SnO 2 NCs with tunable band gaps using different methods. Key factors affecting the synthesis include control of the oxidizing agent, reaction temperature, solvent selection, and reaction time optimization. The resulting NCs were characterized by using TEM, XRD, XPS, and optical spectroscopy. Notably, SnO 2 NCs synthesized by controlling the oxidizing agent (air injection) in a hot organic solution were smaller in size and exhibited abundant oxygen vacancies. In contrast, extending the reaction time or using ethanol as a solvent in hydrothermal systems facilitated larger spherical or rod-like SnO 2 NCs with fewer oxygen vacancies. Further analysis of the band gap and valence band maximum energy revealed that the abundant vacancies in SnO 2 NCs synthesized with the air-controlled hot organic solution method resulted in a narrower band gap and an upshifted valence band. These synthetic strategies illustrate the potential for deliberately designing SnO 2 NCs with optimized electronic structures for various applications.

band gap↗
DOE OSTI2023

Electromagnetic signatures of a chiral quantum spin liquid

Quantum spin liquids (QSL) have emerged as a captivating subject within interacting spin systems that exhibit no magnetic ordering even at the lowest temperature accessible experimentally. However, definitive experimental evidence remains elusive. In light of the recent surge in theoretical and experimental interest in the half-filled Hubbard model on a triangular lattice, which offers the potential for stabilizing a chiral QSL, we investigate the electromagnetic signatures of this phase to facilitate experimental detection. Utilizing a combination of parton mean-field theory and unbiased density-matrix renormalization group calculations, we systematically examine the electrical charge and orbital electrical current associated with a spinon excitation in the chiral QSL. Additionally, we calculate the longitudinal and transverse optical conductivities below the Mott gap. Furthermore, employing quantum field theory analysis, we unravel the connection between spinon excitations and emergent as well as physical gauge fields. Our results demonstrate that the chiral QSL phase exhibits a distinct electromagnetic response, even within a Mott insulator regime. This finding holds great potential for enabling the experimental detection of this long-sought-after phase.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Chiral electronic excitations in the quasi-two-dimensional Rashba system BiTeI

The optical transitions between spin-polarized bands of the quasi-two-dimensional Rashba system BiTeI are investigated using polarization-resolved resonant Raman spectroscopy. We detect chiral excitations between states with opposite helicity and compare spectra to calculations within a three-band model. Using the resonant Raman excitation profile, we deduce the Rashba parameters and band gaps of the higher conduction bands near the Fermi level, and compare the parameters to values obtained by ab initio density functional theory.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Indirect Tool Condition Monitoring Using Ensemble Machine Learning Techniques

Abstract Tool condition monitoring (TCM) has become a research area of interest due to its potential to significantly reduce manufacturing costs while increasing process visibility and efficiency. Machine learning (ML) is one analysis technique which has demonstrated advantages for TCM applications. However, the commonly studied individual ML models lack generalizability to new machining and environmental conditions, as well as robustness to the unbalanced datasets which are common in TCM. Ensemble ML models have demonstrated superior performance in other fields, but have only begun to be evaluated for TCM. As a result, it is not well understood how their TCM performance compares to that of individual models, or how homogeneous and heterogeneous ensemble models’ performances compare to one another. To fill in these research gaps, milling experiments were conducted using various cutting conditions, and the model groups were compared across several performance metrics. Statistical t-tests were also used to evaluate the significance of model performance differences. Through the analysis of four individual ML models and five ensemble models, all based on the processes’ sound, spindle power, and axial load signals, it was found that on average, the ensemble models performed better than the individual models, and that the homogeneous ensembles outperformed the heterogeneous ensembles.

Engineering↗
DOE OSTI2022

Uncertainty Quantification for Dissimilar Material Joints Under Corrosion Environment

Abstract Self-Piercing Riveting (SPR) is one of the most commonly used methods for joining dissimilar materials in the automotive industry. These joints are popular due to their adaptability, high performance and short cycle time. However, since these joints involve two dissimilar materials, they are susceptible to galvanic corrosion in the presence of an electrolyte which is driven by the difference in the equilibrium potential of the metals. This can affect the safety and resilience of these joints. In this paper, we focus on galvanic corrosion in Al-Fe SPR joints. A Machine learning (ML) based surrogate model, which is based off of FE simulations, for statistical corrosion analysis is developed. This model enables the resilience and reliability analysis of SPR joints under corrosion environment. In this study, first a physics-based finite element (FE) corrosion model has been developed to simulate the galvanic corrosion between a Fe cathode and an Al anode of a SPR joint. This model takes into account the effect of the crystal microstructure of the Al anode and the precipitation of the corrosion product. Several geometric and environmental factors including crevice gap, roughness of anode, conductivity, pH and the temperature of the electrolyte that effect corrosion are investigated. A thorough Uncertainty Quantification (UQ) analysis is conducted for the overall corrosion behavior of the Fe-Al SPR joints using a novelistic Probabilistic Confidence-Based Adaptive Sampling (PCAS) technique. PCAS is used to train the surrogate model by identifying the critical sampling points and thus reducing the overall computational costs. It is found that the electrolyte temperature has the largest effects on the material loss and needs to be managed closely for better corrosion control. By understanding the corrosion performance and resultant uncertainty impact on SPR joints, the reliability and resilience of these joints can be improved.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Application of artificial intelligence methods in the international roughness index prediction of rigid and composite pavements: a systematic review

The International Roughness Index (IRI) is a widely adopted metric for quantifying pavement roughness, directly influencing vehicle safety, ride comfort, and overall roadway performance. In recent years, the use of Machine Learning (ML) models for IRI prediction has gained momentum, with the goal of improving the allocation of maintenance and rehabilitation resources by enabling accurate assessments of pavement conditions. Most prior reviews, however, have concentrated on flexible pavements, leaving a notable gap regarding rigid and composite pavements. To address this gap, the present study conducts a systematic review of Artificial Intelligence (AI) methods applied to IRI prediction for rigid and composite pavements. Literature published between 2004 and 2025 is synthesized to highlight prevailing trends, methodological contributions, and directions for future research. Particular attention is given to the types of models employed, the datasets used for training and validation, and the role of input variables and data-processing strategies. Across the included studies, ensemble learning methods (especially gradient boosting variants such as XGBoost), artificial neural networks, and hybrid architectures frequently achieved high predictive skill, with several models reporting test-set coefficients of determination approaching 0.9–0.96, indicating strong potential for capturing the influence of traffic, pavement structure, and climatic factors. Since these results are obtained from heterogeneous datasets and evaluation protocols, they are interpreted qualitatively rather than as strict cross-study rankings. Analysis of input variables revealed that pavement age and initial IRI were included in 91% (21 of 23) and 78% (18 of 23) of studies, respectively. Climatic variables such as the freezing index appeared in 57% (13 of 23), while traffic-related factors were considered in 65% (15 of 23). The findings underscore the importance of standardized, high-quality datasets, such as those from the Long-Term Pavement Performance (LTPP) program, along with data consistency, model interpretability, computational efficiency, and replicability in enhancing IRI prediction. Future research should focus on incorporating input variable selection techniques to identify the most influential predictors, thereby improving accuracy and robustness. Integrating these approaches with advanced non-linear data-driven models, coupled with robust hyperparameter optimization, holds considerable promise for strengthening the reliability of IRI prediction and supporting resilient pavement management strategies.

42 ENGINEERING↗
DOE OSTI2022

Onboarding in a Virtual Environment

A need for a standardized Division 10000 onboarding program for virtual hires was identified by management to formalize the way employees and interns are onboarded and trained into Division 10000. This white paper provides effective short and long-term suggestions in the efforts of improving virtual onboarding. Data suggests that remote work is going to become the forefront of many industry practices, which indicates the need of a standardized virtual onboarding practices. With our research, gap assessments, benchmarking, and conducting interviews both internally and externally, we found that clarity, culture, and connection proved to be the strongest solutions in order to maintain Sandia’s competitive edge and sustain workers both remote and in-person.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

De-tuning tolerant loop antenna

A loop antenna is described herein that is suitable for operation in free space or in proximity to a ground plane. The loop antenna comprises a looped conductive element with a gap formed therein and a tab extending toward the gap. A length of the tab of the loop antenna is selected such that a detuning loss of the loop antenna from operation in free space to operation in proximity to a ground plane is low. In an exemplary embodiment, the length of the tab is selected such that a reactance of the loop antenna in free space is within a threshold level of a reactance of the loop antenna when the antenna is in proximity to a ground plane.

42 ENGINEERING↗
DOE OSTI2020

Topological nonmagnetic impurity states in topological Kondo insulators

We examine here the presence of nonmagnetic impurities in a hybridization gap model of a Kondo insulator which has band inversion. The model has been used to predict that SmB 6 is a topological insulator. We show that there are two types of nonmagnetic impurity states in a Kondo insulator. The type of states can be categorized as deep impurity states, similar to the impurity states in an ordinary metal, and impurity states which have energies within the hybridization gap. Unlike the deep impurity states which only form if the impurity potential exceeds a critical value of the order of the conduction bandwidth, the in-gap impurity states form for exceptionally small values of the impurity potential comparable to the hybridization gap. This finding may explain why Kondo insulators are found to be exceptionally sensitive to impurities. We demonstrate that these in-gap states are caused by band inversion and have properties similar to those expected for impurities in a topological insulator.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Signatures of superconducting triplet pairing in Ni–Ga-bilayer junctions

Ni–Ga bilayers are a versatile platform for exploring the competition between strongly antagonistic ferromagnetic and superconducting phases. We characterize the impact of this competition on the transport properties of highly-ballistic Al/Al 2 O 3 (/EuS)/Ni–Ga tunnel junctions from both experimental and theoretical points of view. While the conductance spectra of junctions comprising Ni (3 nm)–Ga (60 nm) bilayers can be well understood within the framework of earlier results, which associate the emerging main conductance maxima with the junction films’ superconducting gaps, thinner Ni (1.6 nm)–Ga (30 nm) bilayers entail completely different physics, and give rise to novel large-bias (when compared to the superconducting gap of the thin Al film as a reference) conductance-peak subseries that we term conductance shoulders. These conductance shoulders might attract considerable attention also in similar magnetic superconducting bilayer junctions, as we predict them to offer an experimentally well-accessible transport signature of superconducting triplet pairings that are induced around the interface of the Ni–Ga bilayer. We further substantiate this claim performing complementary polarized neutron reflectometry measurements on the bilayers, from which we deduce (1) a nonuniform magnetization structure in Ga in a several nanometer-thick area around the Ni–Ga boundary and can simultaneously (2) satisfactorily fit the obtained data only considering the paramagnetic Meissner response scenario. While the latter provides independent experimental evidence of induced triplet superconductivity inside the Ni–Ga bilayer, the former might serve as the first experimental hint of its potential microscopic physical origin. Finally, we introduce a simple phenomenological toy model to confirm also from the theoretical standpoint that superconducting triplet pairings around the Ni–Ga interface can indeed lead to the experimentally observed conductance shoulders, which convinces that our claims are robust and physically justified. Arranging our work in a broader context, we expect that Ni–Ga-bilayer junctions could have a strong potential for future superconducting-spintronics applications whenever an efficient engineering of triplet-pairing superconductivity is required.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Experimental investigation of power transient flow boiling

To advance the mechanistic understanding of power transients in flow boiling, experimental investigations are performed to capture the thermal response of four different kinds of cladding materials, including FeCrAls, to Fuchs reactivity initiated accident transients and linear ramp power transients. The transition boiling regime is phenomenologically reflected in power-transient flow boiling, which is different from steady-state boiling. In light of this, the critical heat flux that is usually featured with temperature overshooting does not indicate thermal safety margin of cladding materials as conservatively as the maximum heat flux, which is greater than critical heat flux in the power transient boiling curve. This is physically attributed to the thermal energy deposition on the cladding wall. In addition, the thermal energy released from the cladding wall results in different boiling heat transfer coefficient for the decreasing and increasing power stages respectively during the Fuchs power transient. The maximum heat flux difference gap, which appears due to changes in cladding materials and transient time scales, is appreciable under an intermediate heat convection regime. However, this difference gap is gradually weakened by the progressive increasing of mass flux and/or inlet subcooling due to the enhanced dominance of heat convection over heat conduction. Finally, the small difference gap of maximum heat flux is found to be insignificant under the weak heat convection because of power transient induced annular flow instability.

42 ENGINEERING↗
DOE OSTI2024

Heat transfer coefficients of moving particle beds from flow-dependent thermal conductivity and near-wall resistance

Accurate determination of heat transfer coefficients for flowing packed particle beds is essential to the design of particle heat exchangers and other thermal and thermochemical equipment. While such dense granular flows mostly fall into the well-known plug-flow regime, the discrete nature of granular materials alters the thermal transport processes in both the near-wall and bulk regions of flowing particle beds from their stationary counterparts. As a result, heat transfer correlations based on the stationary particle bed thermal conductivity could be inadequate for flowing particles in a heat exchanger. Most earlier works have achieved a reasonable agreement with experiments by treating granular heat transfer media as a plug-flow continuum with a near-wall thermal resistance in series. However, the thermal conductivity values of the continuum were often obtained from measurements on stationary beds owing to the difficulty of flowing bed measurements. In this work, it was found that the properties of a stationary bed are highly sensitive to the method of particle packing and there is a decrease in the particle bed thermal conductivity and increase in the near-wall thermal resistance, measured as an effective air gap thickness, on the onset of particle flow. These variations in thermal conductivity of stationary and flowing particle beds can lead to errors in heat transfer coefficient calculations. Therefore, the heat transfer coefficients for granular flows were calculated using experimentally determined flowing particle bed thermal conductivity and near-wall air gap for ceramic particles – CARBO CP 40/100 (mean diameter = 275 µm), HSP 40/70 (404 µm) and HSP 16/30 (956 µm); at velocities of 5–15 mm·s –1 ; and temperatures of 300–650 °C. The thermal conductivity and air gap values for CP 40/100 and HSP 40/70 were further used to calculate heat transfer coefficients across different particle bed temperatures and velocities for different parallel-plate heat exchanger dimensions. Furthermore, these calculations, which show good agreement with measured HTC values reported in literature, can be used as a guide for heat exchanger designs. Graphical abstract

14 SOLAR ENERGY↗
DOE OSTI2020

Band-edge Engineering to Eliminate Radiation-Induced Defect States in Perovskite Scintillators

Under radiative environments such as extended hard X- or γ-rays, degradation of scintillation performance is often due to irradiation-induced defects. To overcome the effect of deleterious defects, novel design mitigation strategies are needed to identify and design more resilient materials. The potential for band-edge engineering to eliminate the effect of radiation-induced defect states in rare-earth-doped perovskite scintillators is explored, taking Ce 3+ -doped LuAlO 3 as a model material system, using density functional theory (DFT)-based DFT + U and hybrid Heyd–Scuseria–Ernzerhof (HSE) calculations. Furthermore, from spin-polarized hybrid HSE calculations, the Ce 3+ activator ground-state 4f position is determined to be 2.81 eV above the valence band maximum in LuAlO 3 . Except for the oxygen vacancies which have a deep level inside the band gap, all other radiation-induced defects in LuAlO 3 have shallow defect states or are outside the band gap, that is, relatively far away from either the 5d 1 or the 4f Ce 3+ levels. Finally, we examine the role of Ga doping at the Al site and found that LuGaO 3 has a band gap that is more than 2 eV smaller than that of LuAlO 3 . Specifically, the lowered conduction band edge envelopes the defect gap states, eliminating their potential impact on scintillation performance and providing direct theoretical evidence for how band-edge engineering could be applied to rare-earth-doped perovskite scintillators.

36 MATERIALS SCIENCE↗