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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Intertwined density waves in a metallic nickelate

Nickelates are a rich class of materials, ranging from insulating magnets to superconductors. But for stoichiometric materials, insulating behavior is the norm, as for most late transition metal oxides. Notable exceptions are the 3D perovskite LaNiO 3 , an unconventional paramagnetic metal, and the layered Ruddlesden-Popper phases R 4 Ni 3 O 10 , (R = La, Pr, Nd). The latter are particularly intriguing because they exhibit an unusual metal-to-metal transition. Here, we demonstrate that this transition results from an incommensurate density wave with both charge and magnetic character that lies closer in its behavior to the metallic density wave seen in chromium metal than the insulating stripes typically found in single-layer nickelates like La 2-x Sr x NiO 4 . We identify these intertwined density waves as being Fermi surface-driven, revealing a novel ordering mechanism in this nickelate that reflects a coupling among charge, spin, and lattice degrees of freedom that differs not only from the single-layer materials, but from the 3D perovskites as well.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Low-temperature formation of Ti2AlN during post-deposition annealing of reactive multilayer systems

M n+1 AXn-phase Ti 2 AlN thin-films were synthesized using reactive sputtering-based methods involving the deposition of single-layer TiAlN, and Ti/AlN and TiN/TiAl multilayers of various modulation periods at ambient temperature and subsequent annealing at elevated temperatures. Ex situ and in situ x-ray diffraction measurements were used to characterize the Ti 2 AlN formation temperature and phase fraction. During annealing, Ti/AlN multilayers yielded Ti 2 AlN at a significantly lower in situ temperature of 650 °C compared to TiN/TiAl multilayers or single-layer TiAlN (750 °C). The results suggest a reactive multilayer mechanism whereby distinct Ti and AlN layers react readily to release exothermic energy resulting in lower phase transition temperatures compared to TiN and TiAl layers or mixed TiAlN. With a modulation period of 5 nm, however, Ti/AlN multilayers yielded Ti 2 AlN at a higher temperature of 750 °C, indicating a disruption of the reactive multilayer mechanism due to a higher fraction of low-enthalpy interfacial TiAlN within the film.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Revealing multiscale competing processes in the solid-state synthesis of single-crystalline layered oxide positive electrodes

Solid-state synthesis involves a web of coupled chemical reactions and physical changes that unfold across multiple scales. Efforts to fine-tune its parameters have historically followed heuristic, trial-driven workflows that demand significant time and resources. In this study, we aimed to open this black box by employing multiscale in situ synchrotron imaging and diffraction. Using LiNi 0.5 Mn 0.3 Co 0.2 O 2 battery positive electrode material as a model system and Ba-based sintering aids, we reveal dopant segregation, intergranular mass transport, and porosity evolution as key drivers of single-crystalline particle formation. Notably, we uncovered a dynamic competition between particle-level grain coalescence and atomic-scale cation disordering, both of which are thermally activated yet have opposing impacts on battery performance. These findings highlight the coupled, multiscale nature of structure development and offer a mechanistic basis for optimizing the solid-state synthesis process. This framework provides a path toward more controlled, efficient, and scalable production of high-performance battery positive electrode materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Escalated Phase Separation Driven Enhanced Magnetoresistance in Manganite/Iridate Epitaxial Heterostructures

Phase separation in manganites leads to unique magnetic and electronic properties. 50% Ca-doped LaMnO 3 (LCMO), at the boundary of ferromagnetic (FM) and antiferromagnetic (AFM) states in La 1-x Ca x MnO 3 (0 ≤ x ≤ 1), is an ideal system to study phase separation behavior. The investigation reveals the effect of a 5d-metal perovskite SrIrO 3 (SIO) on the phase separation, magnetic, and magnetoresistance (MR) properties of LCMO. Single-layer and bilayer LCMO films, both appear purely ferromagnetic along the in-plane (IP) magnetic field direction, but show the tendency of temperature-dependent ferromagnetic and antiferromagnetic or charge-ordered (CO) phase separation with the out-of-plane (OOP) applied field. The MR, and colossal magnetoresistance (CMR), observed in LCMO/SIO bilayers are two orders and an order of magnitude (in %) larger, respectively than that in the single-layer film. The coexistence of FM and AFM/CO phases is responsible for the CMR and MR enhancement in the LCMO/SIO bilayer, pointing toward the importance of the phase separation and competition of both the individual materials in enhancing their magnetic and electronic properties.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Selected Area Manipulation of MoS 2 via Focused Electron Beam-Induced Etching for Nanoscale Device Editing

Here we demonstrate direct-write patterning of single and multilayer MoS 2 via a focused electron beam-induced etching (FEBIE) process mediated with the XeF 2 precursor. MoS 2 etching is performed at various currents, areal doses, on different substrates, and characterized using scanning electron and atomic force microscopies as well as Raman and photoluminescence spectroscopies. Scanning transmission electron microscopy reveals a sub-40 nm etching resolution and the progression of point defects and lateral etching of the consequent unsaturated bonds. The results confirm that the electron beam-induced etching process is minimally invasive to the underlying material in comparison to ion beam techniques, which damage the subsurface material. Single-layer MoS 2 field-effect transistors are fabricated, and device characteristics are compared for channels that are edited via the selected area etching process. The source–drain current at constant gate and source–drain voltage scale linearly with the edited channel width. Moreover, the mobility of the narrowest channel width decreases, suggesting that backscattered and secondary electrons collaterally affect the periphery of the removed area. Focused electron beam doses on single-layer transistors below the etching threshold were also explored as a means to modify/thin the channel layer. The FEBIE exposures showed demonstrative effects via the transistor transfer characteristics, photoluminescence spectroscopy, and Raman spectroscopy. While strategies to minimize backscattered and secondary electron interactions outside of the scanned regions require further investigation, here, we show that FEBIE is a viable approach for selective nanoscale editing of MoS 2 devices.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Imaging gate-tunable Tomonaga–Luttinger liquids in 1H-MoSe 2 mirror twin boundaries

One-dimensional electron systems exhibit fundamentally different properties than higher-dimensional systems. For example, electron-electron interactions in one-dimensional electron systems have been predicted to induce Tomonaga-Luttinger liquid behaviour. Naturally occurring grain boundaries in single-layer transition metal dichalcogenides exhibit one-dimensional conducting channels that have been proposed to host Tomonaga-Luttinger liquids, but charge density wave physics has also been suggested to explain their behaviour. Clear identification of the electronic ground state of this system has been hampered by an inability to electrostatically gate such boundaries and tune their charge carrier concentration. Here we present a scanning tunnelling microscopy and spectroscopy study of gate-tunable mirror twin boundaries in single-layer 1H-MoSe 2 devices. Gating enables scanning tunnelling microscopy and spectroscopy for different mirror twin boundary electron densities, thus allowing precise characterization of electron-electron interaction effects. Visualization of the resulting mirror twin boundary electronic structure allows unambiguous identification of collective density wave excitations having two velocities, in quantitative agreement with the spin-charge separation predicted by finite-length Tomonaga-Luttinger liquid theory.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Modeling Spectrally-Selective Reflection for Thermal Management in Monofacial and Bifacial Modules

Parasitic absorption in photovoltaic modules is a major source of waste heat, which drives operating temperatures 20-30K above ambient. Spectrally-selective sub-bandgap reflection can reduce parasitic absorption, thereby improving module efficiency and power output. Here, we investigate the performance of 1-D spectrally-selective mirrors in monofacial Al BSF and PERC modules, and bifacial PERC modules. In monofacial modules, these mirrors offer >1.2% increase in energy yield compared to single-layer anti-reflection coatings, while cooling by over 1K on average. Mirrors reduced bifacial module parasitic absorption by up to 34 W/m2 out of 1240 W/m2 incident.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2020

Macro-physical Properties of Shallow Cumulus from Integrated ARM Observations (Final Report)

Fair-weather shallow cumuli (ShCu) play an important role in many climate-related processes. Irregular geometry of ShCu and their strong temporal and spatial variability make it challenging to observe ShCu holistically and to represent them correctly in climate models. To improve ShCu parameterizations, information on both vertically and horizontally resolved cloud properties is required. Commonly, the vertically resolved cloud properties are provided by zenith pointing lidar-radar observations with a very narrow field of view (FOV). Thus, these “pencil-beam” properties may not be representative of a larger surrounding area. Limited number of areal-averaged cloud properties, such as fractional sky cover (FSC), are offered typically by wide-FOV observations. The main goal of our project was to integrate advantages of the narrow-FOV (vertical structure of clouds) and wide-FOV (spatial arrangement of clouds) observations for an improved characterization of single-layer ShCu observed at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site for an 18-yr period (2000-2017). There are four major accomplishments of our project, First, an updated operational cloud classification for days with ShCu has been suggested and evaluated through a detailed comparison with the manually curated records. Our classification extends successfully the latest ARM cloud type Value Added Product (VAP) based on the Active Remote Sensing of Clouds (ARSCL) cloud product by incorporating both cloud fraction (CF) provided by narrow-FOV ceilometer data and FSC from wide-FOV images offered by a Total Sky Imager (TSI). Moreover, our classification allows one to identify impact of instrumentation changes at the SGP site, namely the transition to KAZRARSCL with the updated cloud radar, on the identification of periods with single-layer ShCu. Second, a new approach that resolves cloud area distributions for a given region (up to 4x4 km 2 ) has been suggested and cloud equivalent diameters (CEDs) have been estimated for the first time. These estimations have been performed over a wide range of cloud sizes (about 0.01–3.5 km) with high temporal resolution (30s) using wide-FOV TSI images and cloud base height (CBH) provided by complementary narrow-FOV lidar measurements. Our simple and computationally inexpensive approach offers a previously unavailable dataset for process studies in the convective boundary layer and evaluation of ShCu parameterizations in cloud-resolving models. Third, a long-term integrated record of ShCu macrophysical properties has been developed. The developed record represents the longest available compilation of events with ShCu and includes (i) a novel visualization of the spatial variability in cloud cover both along- and across-wind directions, (ii) updated estimates of narrow-FOV CF and wide-FOV FSC, (iii) updated narrow-FOV CBH, and (iv) complementary data, such as wind speed and direction from the 915-MHz Radar Wind Profiler (RWP) data. The developed record has been used successfully to assess conventional observational estimates of cloud cover and their sensitivity to the following two factors: (i) instrument-dependent cloud detection and data merging criteria and (ii) FOV configuration. Fourth, co-variability of the ShCu macrophysical properties and environmental parameters has been analyzed for a 3-yr period (2016-2018). Our initial analysis includes diurnal changes of FSCs obtained for clouds with small, moderate and large CEDs and several environmental parameters, such as lifted condensation level (LCL) and mixed layer height (zi). Preliminary results of our analysis suggest that the horizontal extent of ShCu is controlled substantially by the sign and magnitude of difference between these two parameters (zi-LCL): the CED tends to grow with increase of this difference (zi exceeds LCL). We have initiated relationships between the ShCu and key atmospheric parameters that control both the development and evolution of ShCu using our new data product, which combines effectively the advantages of narrow-FOV data offered by zenith pointing cloud radars and lidars and wide-FOV TSI images. While the latest instrumentation at the ARM sites may address these challenging relationships in the future, we believe that the historical ARM data at the SGP site has not yet been fully utilized. Overall, our data product can be used by researchers working on a wide range of climate-related projects. These projects may include (i) a comprehensive evaluation of outputs from the Large-Eddy Simulation (LES) and single-column models for their future improvement, (ii) the representativeness of “short-period” results obtained from the previous model and observational studies and (iii) the planning of future field campaigns with focus on improved understanding of the diurnal cycle of cumulus convection.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Dual-map framework for noise characterization of quantum computers

In order to understand the capabilities and limitations of quantum computers, it is necessary to develop methods that efficiently characterize and benchmark error channels present on these devices. In this paper, we present a method that faithfully reconstructs a marginal (local) approximation of the effective noise (MATEN) channel, that acts as a single layer at the end of the circuit. We first introduce a dual-map framework that allows us to analytically derive expectation values of observables with respect to noisy circuits. These findings are supported by numerical simulations of the quantum approximate optimization algorithm (QAOA) that also justify the MATEN, even in the presence of nonlocal errors that occur during a circuit. Finally, we demonstrate the performance of the method on Rigetti's Aspen-11 quantum computer for QAOA circuits up to six qubits, successfully predicting the observed measurements on a majority of the qubits.

Sud, James↗
DOE OSTI2022

Optimizing feed modulation for coupled methane and NO x conversion over Pd-Pt/Mn 0.5 Fe 2.5 O 4 /Al 2 O 3 monolith catalyst

Here the impacts of feed modulation (frequency, amplitude) and catalyst design (composition and architecture) parameters are reported for the conversion of methane and NO x over a dual-layer Pt+Pd/Al 2 O 3 + Mn 0.5 Fe 2.5 O 4 /Al 2 O 3 monolith. CH 4 and NO x conversion data show that the dual-layer catalyst outperforms single-layer samples having the same catalyst loadings, with and without spinel. Close proximity of the PGM and MFO functions in the mixed-layer catalyst lowers the CH 4 conversion at high temperature while separating the PGM and spinel layers with an intermediate Al 2 O 3 layer does not. Methane conversion enhancement is linked to its nonmonotonic dependence on O 2 . The performance gains are tied to a transient activity spike that occurs during the lean-to-rich feed transition when water is present in the feed. The transient spike is attributed to the removal of CO and H 2 products via reactions with stored O 2 in the spinel, eliminating inhibition of methane steam reforming.

03 NATURAL GAS↗
DOE OSTI2025

Polarization-Controlled Structural Modulation in the Single Atomic Layer at the PbZr 0.2 Ti 0.8 O 3 /LaNiO 3 Interface

Conductivity modulation via ferroelectric polarization coupling with LaNiO 3 (LNO) is demonstrated at an epitaxial ferroelectric–LNO interface. Conductivity measurements, varying the thickness of the LNO channel, show that this phenomenon is confined to a few atomic layers at the interface. Combining in situ biasing and off-axis holography, we mapped out electrostatic potentials at the PbZr 0.2 Ti 0.8 O 3 (PZT)/LNO/SrTiO 3 (STO) heterostructure upon polarization switching. Using aberration-corrected STEM, the interfacial atomic structures were investigated for the two different PZT polarization states. Polarization in PZT induces a significant change in the in-plane O–Ni–O bond angles, with a 37° modulation in the topmost 1 or 2 LNO unit cells, driven by strain in the oxygen sublattice for the two opposite polarization directions in PZT. Both oxygen and cation sublattices exhibit strain responses exceeding 10% upon switching. This atomic-layer structural modulation highlights a mechanism for functional oxide heterostructure development, offering pathways for advancements in nonvolatile memory, sensors, and energy-efficient transistors.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

In Situ Neutron Reflectometry Reveals the Interfacial Microenvironment Driving Electrochemical Ammonia Synthesis

Electrified interfaces are critical to the performance of energy systems and often demonstrate substantial complexity under operating conditions. A nanoscale understanding of the interfacial microenvironment, i.e., the solid-electrolyte interphase (SEI), in lithium-mediated nitrogen reduction (Li–N 2 R) is key for realizing efficient ammonia (NH 3 ) production. Herein, we used time-resolved neutron reflectometry (NR) to observe SEI formation under Li–N 2 R conditions. We found that the LiBF 4 -based electrolyte provided a substantially more well-defined SEI layer than previous SEI NR interrogations that used LiClO 4 , highlighting the underlying chemistry that dictates electrolyte design and enabling new NR-based studies. Using in situ NR, we found that the LiBF 4 -derived SEI under Li–N 2 R conditions comprises a thick, diffuse outer layer and a thin, compact inner layer at low current cycling (<2 mA/cm 2 ), revealing a structure which ex situ studies have not been able to probe. Increased current cycling and sustained current cycling led to the merging of the layers into a single-layer SEI. Here, we used isotope contrast methods with d 6 -EtOH and d 8 -THF to drive time-resolved tracking of SEI growth at low current cycling, revealing that the proton donor modifies the inner layer, and the solvent modifies the outer layer. Li dendritic growth was observed in the absence of a proton donor. Neutron absorption also indicated the presence of boron in the SEI, underscoring the value of neutron-based interrogation. Our results inform Li-based systems and reaction microenvironments, and these methods can be applied broadly to interfacial energy technologies.

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

TMAP modeling of D release from baked multi-layer Be–D co-deposits

Single-layer Beryllium–Deuterium (Be–D) co-deposits were analyzed using Thermal Desorption mass Spectrometry (TDS) as outlined in the companion paper. This work details the TMAP modeling and the analysis of selected samples that received double-layer (DL) coatings to study co-deposit thickness and prior bake effects. Here, TDS data were simulated with detrap energies 0.8, 0.9, and 1.0 eV. In DLs formed at 393 K, modeling revealed that under-layers baked at 623 K for either 2 or 20 h had little pumping effect on over-layers, suggesting empty trap removal during bake. Extrapolated to ITER, data and analysis suggest less impact on the ongoing ITER bake efficiency than previously predicted.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Comparison of Machine Learning-Based Predictive Models of the Nutrient Loads Delivered from the Mississippi/Atchafalaya River Basin to the Gulf of Mexico

Predicting nutrient loads is essential to understanding and managing one of the environmental issues faced by the northern Gulf of Mexico hypoxic zone, which poses a severe threat to the Gulf’s healthy ecosystem and economy. The development of hypoxia in the Gulf of Mexico is strongly associated with the eutrophication process initiated by excessive nutrient loads. Due to the complexities in the excessive nutrient loads to the Gulf of Mexico, it is challenging to understand and predict the underlying temporal variation of nutrient loads. The study was aimed at identifying an optimal predictive machine learning model to capture and predict nonlinear behavior of the nutrient loads delivered from the Mississippi/Atchafalaya River Basin (MARB) to the Gulf of Mexico. For this purpose, monthly nutrient loads (N and P) in tons were collected from US Geological Survey (USGS) monitoring station 07373420 from 1980 to 2020. Machine learning models—including autoregressive integrated moving average (ARIMA), gaussian process regression (GPR), single-layer multilayer perceptron (MLP), and a long short-term memory (LSTM) with the single hidden layer—were developed to predict the monthly nutrient loads, and model performances were evaluated by standard assessment metrics—Root Mean Square Error (RMSE) and Correlation Coefficient (R). The residuals of predictive models were examined by the Durbin–Watson statistic. The results showed that MLP and LSTM persistently achieved better accuracy in predicting monthly TN and TP loads compared to GPR and ARIMA. In addition, GPR models achieved slightly better test RMSE score than ARIMA models while their correlation coefficients are much lower than ARIMA models. Moreover, MLP performed slightly better than LSTM in predicting monthly TP loads while LSTM slightly outperformed for TN loads. Furthermore, it was found that the optimizer and number of inputs didn’t show effects on the LSTM performance while they exhibited impacts on MLP outcomes. This study explores the capability of machine learning models to accurately predict nonlinearly fluctuating nutrient loads delivered to the Gulf of Mexico. Further efforts focus on improving the accuracy of forecasting using hybrid models which combine several machine learning models with superior predictive performance for nutrient fluxes throughout the MARB.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Integration of CeO 2 -Based Memristor with Vertically Aligned Nanocomposite Thin Film: Enabling Selective Conductive Filament Formation for High-Performance Electronic Synapses

The CeO 2 -based memristor has attracted significant attention due to its intrinsic resistive switching (RS) properties, large on/off ratio, and great plasticity, making it a promising candidate for artificial synapses. However, significant challenges such as high power consumption and poor device reliability hinder its broad application in neuromorphic microchips. To tackle these issues, in this work, we design a novel bilayer (BL) memristor by integrating a CeO 2 -based memristor with a Co-CeO 2 vertically aligned nanocomposite (VAN) layer and compare it with the single layer (SL) memristor. Preliminary electrical testing reveals that the BL memristor offers a reduced set/reset voltage (~67% lower), a higher on/off ratio (~5 × 10 2 ), enhanced device reliability, and improved device-to-device variation compared to the SL memristor. Insight from COMSOL simulation, coupled with microstructural analysis, provides a comprehensive elucidation on how the VAN layer facilitates the selective conductive filament (CF) formation. Subsequently, the plasticity of the BL memristor is evaluated through long-term potentiation/depression (LTP/LTD), paired-pulse facilitation (PPF), and spike-time-dependent plasticity (STDP). The spiking neural network (SNN) built upon the BL memristor achieves remarkable accuracy (~94%) after only 12 iterations, underscoring its potential for high-performance neural networks.

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

Resonance ultrasound prediction of residual stress within a hybrid layer for additively manufactured samples

Hybrid additive manufacturing (AM) involves secondary processes or energy sources to alter specified locations within the build volume. Each hybrid step can refine the grain size, increase dislocation density, or modify residual stresses. Typically, the changes in mechanical properties are not confined within a single layer but have a compounding effect on preceding layers. Existing methods of measuring AM residual stress are limited in terms of their sensitivity, or they are destructive measurements. We propose using resonant ultrasound spectroscopy (RUS) to measure the residual stress in hybrid-AM components noninvasively, based on changes to the resonances, compared to a stress-free component. In this paper, we use finite element models to simulate residual stress in hybrid-AM components and to examine the sensitivity of RUS measurements in terms of frequency shifts and mode shapes with respect to single hybrid layers. Then, the RUS results are used to predict stress for a layer at a known location with unknown stress. Here, the approach highlights the capabilities of RUS to address an AM characterization challenge.

36 MATERIALS SCIENCE↗