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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
NASA NTRS1973

Computer enhancement of radiographs

Examination of three relevant noise processes and the image degradation associated with Marshall Space Flight Center's (MSFC) X-ray/scanning system was conducted for application to computer enhancement of radiographs using MSFC's digital filtering techniques. Graininess of type M, R single coat and R double coat X-ray films was quantified as a function of density level using root-mean-square (RMS) granularity. Quantum mottle (including film grain) was quantified as a function of the above film types, exposure level, specimen material and thickness, and film density using RMS granularity and power spectral density (PSD). For various neutral-density levels the scanning device used in digital conversion of radiographs was examined for noise characteristics which were quantified by RMS granularity and PSD. Image degradation of the entire pre-enhancement system (MG-150 X-ray device; film; and optronics scanner) was measured using edge targets to generate modulation transfer functions (MTF). The four parameters were examined as a function of scanning aperture sizes of approximately 12.5 25 and 50 microns.

Dekaney, A.↗
DOE OSTI2023

Ionothermally Synthesized Nanoporous Ti 0.95 W 0.05 Nb 2 O 7 : a Novel Anode Material for High-Performance Lithium-Ion Batteries

Although TiNb 2 O 7 is regarded as a fast-rechargeable lithium-ion battery (LIB) anode material, the intrinsic poor electrochemical kinetics of TiNb 2 O 7 still dramatically impedes its development. Herein, an ionothermal synthesis-assisted doping strategy is proposed for the preparation of a new W 6+ -doped TiNb 2 O 7 material (Ti 0.95 W 0.05 Nb 2 O 7 ) with nanoporous structure (denoted as NPTWNO). The improved Li + diffusion coefficient of NPTWNO suggests that the ionic-liquid-templated nanoporous architecture improves the Li+ diffusion kinetics. The density functional theory computational study reveals that the doped W 6+ successfully boosts the electronic conductivity due to the narrowed conduction-valance bandgap resulted from charge redistribution, which is reflected by the electrochemical impedance spectroscopy data. With the simultaneously enhanced Li+ diffusivity and electronic conductivity, NPTWNO achieves fast-rechargeability in LIBs. So this work indicates the potential of ionothermal synthesis-assisted doping strategy on energy storage materials and offers NPTWNO material with promising electrochemical performance.

25 ENERGY STORAGE↗
DOE OSTI2026

Atomic‐Scale Surface Imaging of Bulk Epitaxial CsPbBr 3 Perovskite Single Crystals on Mica Using Light Assisted Scanning Tunneling Microscopy at Low‐Temperature (80 K)

Epitaxial single-crystalline CsPbBr 3 perovskite films on mica, prepared ex situ, are explored using a low-temperature scanning tunneling microscope (STM) by probing the unoccupied electronic states of their surface in ultra-high vacuum (UHV) at 80 K. Light-assisted STM measurements under a broadband illumination with visible light were employed to enhance and stabilize surface conductivity. STM imaging across the surface of macroscopic bulk CsPbBr 3 films reveals large flat terraces characterized by a specific type of surface reconstruction, consisting of parallel rows of U-shaped atomic nanostructures. These structures are spaced by 12 Å and exhibit an internal feature size of 5.1 Å. Density functional theory (DFT) calculations reproduce the experimental observations and reveal a competition between different orthorhombic CsPbBr 3 (110) surface reconstructions: a Cs-rich structure, identified as the most energetically stable, and three alternative Pb–Br-rich reconstructions, which are slightly higher in energy yet remain consistent with the STM data. Additional analyses that explicitly account for the mica substrate exclude the cubic CsPbBr 3 phase and other orthorhombic surface orientations, while showing that variations in the mica surface termination do not alter the preferred CsPbBr 3 (110) reconstruction. In conclusion, this combined approach thereby confirms our assignment and resolves previous STM interpretations of CsPbBr 3 .

36 MATERIALS SCIENCE↗
DOE OSTI2026

Photoresponsive Rotaxanes Switch Lipid Bilayer Neuromorphic Behavior with Light

A rotaxane consisting of a macrocycle ring with two azobenzene units mechanically interlocked onto a bolaamphiphilic axle was incorporated into droplet interface bilayers (DIBs). The azobenzene groups on the ring underwent quasi-reversible, photoisomerization-induced cycling between 1-E and 1-Z configurations when irradiated with 370 and 467 nm light, respectively, enabling programmable access to different history-dependent electrical behaviors from the same membrane. In the 1-E configuration, bilayers exhibited type-IIactive memristance that coincided with increasingly elevated ionic conduction, associated with progressively enhanced bilayer permeability during voltage cycling. In the 1-Z configuration, bilayers displayed type-I, passive memcapacitive behavior, reflecting tighter lipid packing and reduced ionic permeability. Photoswitching also yielded a nonvolatile, photoresponsive memcapacitor that could be modulated repetitively with negligible loss, likely via reversible changes in membrane thickness. Concurrent ohmic leakage currents across the membrane were less than 0.3%. These results agree with previous studies with increasing membrane permeability using photoswitchable rotaxanes and provide new insights into the coupling between volatile and nonvolatile memcapacitance during photoisomerization. More broadly, they demonstrate a new strategy for the manipulation of neuromorphic behaviors in soft materials using light, with implications for brain-inspired computation and sensing.

droplet interface bilayers↗
DOE OSTI2025

Physics-informed machine learning for building performance simulation-A review of a nascent field

Building performance simulation (BPS) is critical for understanding building dynamics and behavior, analyzing the performance of the built environment, optimizing energy efficiency, improving demand flexibility, and enhancing building resilience. However, conducting BPS is not trivial. Traditional BPS relies on accurate building energy models, which are primarily physics-based and heavily dependent on detailed building information, expert knowledge, and case-by-case model calibrations, significantly limiting their scalability. With the development of sensing technology and the increased availability of data, there is growing attention and interest in data-driven BPS. However, purely data-driven models often suffer from limited generalization ability and a lack of physical consistency, resulting in poor performance in real-world applications. To address these limitations, recent studies have begun integrating physics priors into data-driven models, a methodology known as physics-informed machine learning (PIML). PIML is an emerging field where its definitions, methodologies, evaluation criteria, application scenarios, and future directions remain open. To bridge those gaps, this study systematically reviews the state-of-the-art PIML for BPS, offering a comprehensive definition of PIML and comparing it to traditional BPS approaches regarding data requirements, modeling effort, performance, and computational cost. We also summarize the commonly used methodologies, validation approaches, application domains, available data sources, open-source packages, and testbeds. In addition, this study provides a general guideline for selecting appropriate PIML models based on BPS applications. Finally, this study identifies key challenges and outlines future research directions, providing a solid foundation and valuable insights to advance R&D of PIML in BPS.

Jiang, Zixin↗
DOE OSTI2022

Porous condensers can double the efficiency of membrane distillation

Among membrane distillation (MD) configurations, air gap MD (AGMD) has superior energy efficiency at high salinity. However, flooding of the gap prevents optimal thin gap depths as water removal is a challenge. To address these challenges, this work provides the first analysis of efficiency enhancement via porous wicking conductive condensers in MD. To do so, we examined performance with experiments and comprehensive thermo-fluid numerical models; we find that the porous wick condenser significantly improves thermal efficiency, gain output ratio (GOR), and flux. MD experiments show that the porous copper foam improves the thermal efficiency of air gap membrane distillation up to 40 % and water flux up to 144 %. Numerical modeling shows the porous copper foam improves the GOR of membrane distillation in high salinity by 98.7 %, outperforming air gap MD, permeate gap MD, and conductive gap MD. Furthermore, the optimized thickness and permeability of porous condensers significantly help eliminate the risk of flooding in AGMD.

42 ENGINEERING↗
DOE OSTI2025

Advancements in active filler-contained polymer solid-state electrolytes for lithium-metal batteries: A concise review

Lithium-metal batteries (LMBs) usually are regarded as the pinnacle of next-generation energy storage due to the high specific capacity and low redox potential of the Li-metal anode. However, their development is hindered by safety hazards related to flammable electrolytes and uncontrolled side reactions within the battery. Both polymer and solid-state inorganic electrolytes, despite their potential, exhibit shortcomings that limit their practical applications. Active filler-containing polymer electrolytes (AFPEs) offer a promising solution by combining the benefits of both types. Enhanced by supramolecular interactions between the polymer matrix and active fillers, AFPEs demonstrate superior electrochemical performance over traditional polymer electrolytes. This review discusses the progress in active fillers and various polymer matrices, examining the factors that enhance performance, particularly ionic conductivity. It also outlines the future research directions of AFPEs, aiming to broaden the application of solid electrolytes in high-performance LMBs.

All solid-state batteries↗
DOE OSTI2023

Ni Anchored to Hydrogen-Substituted Graphdiyne for Lithium Sulfide Cathodes in Lithium–Sulfur Batteries

Lithium–sulfur (Li–S) batteries are promising candidates for next-generation energy storage systems due to their high theoretical energy density and the low cost of sulfur. However, slow conversion kinetics between the insulating S and lithium sulfide (Li 2 S) remains as a technical challenge. In this work, we report a catalyst featuring nickel (Ni) single atoms and clusters anchored to a porous hydrogen-substituted graphdiyne support (termed Ni@HGDY), which is incorporated in Li 2 S cathodes. The rapidly synthesized catalyst was found to enhance ionic and electronic conductivity, decrease the reaction overpotential, and promote more complete conversion between Li 2 S and sulfur. The addition of Ni@HGDY to commercial Li 2 S powder enabled a capacity of over 516 mAh g Li 2 S –1 at 1 C for over 125 cycles, whereas the control Li 2 S cathode managed to maintain just over 200 mAh g Li 2 S –1 . In conclusion, these findings highlight the efficacy of Ni as a metal catalyst and demonstrate the promise of HGDY in energy storage devices.

25 ENERGY STORAGE↗
DOE OSTI2024

Summertime Continental Shallow Cumulus Cloud Detection Using GOES‐16 Satellite and Ground‐Based Ceilometer at North Alabama

Abstract Accurate simulations of boundary layer cloud processes remain challenging in Earth system modeling. Observations are essential to evaluate and improve models of such processes. This study introduces a comprehensive validation framework for a satellite‐based detection algorithm of continental shallow cumulus (ShCu) clouds during the daytime, which was initially developed using ground‐based observations of stereo cameras at the Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains site (J. Tian et al., 2021, https://doi.org/10.3390/rs13122309 , 2022, https://doi.org/10.1029/2021gl097070 ). To validate this algorithm, the framework employs ground‐based ceilometer measurements from North Alabama (NA) where ShCu populations are prevalent. This study first generates clear‐sky surface reflectance maps at NA and identifies ShCu pixels with a detection threshold using Geostationary Operational Environmental Satellite (GOES) reflectance data. The obtained cloud fractions (CFs) are then compared against CFs from a ground‐based ceilometer, considering factors such as observed area differences, satellite parallax issue, and systematic biases. We found that with a detection threshold (∆R) of 0.05, the ShCu detection algorithm is effective for NA, enabling the reproduction of hourly ShCu CFs using GOES. Our framework is straightforward and easily repeatable to evaluate the effectiveness of a ∆R threshold for detecting ShCu clouds in various geographic regions where ceilometers are deployed. This satellite detection of ShCu provides a crucial regional context for ground‐based measurements, facilitating the tracking of convection initiation and its coupling with land surface conditions. Integrating localized ground‐based and regional satellite data will enhance our ability to conduct thorough studies of cloud morphology and land‐atmosphere interactions in North Alabama.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Protonated phosphonic acid electrodes for high power heavy-duty vehicle fuel cells

We report that state-of-the-art automotive fuel cells that operate at about 80 °C require large radiators and air intakes to avoid overheating. High-temperature fuel cells that operate above 100 °C under anhydrous conditions provide an ideal solution for heat rejection in heavy-duty vehicle applications. Here we report protonated phosphonic acid electrodes that remarkably improve the performance of high-temperature polymer electrolyte membrane fuel cells. The protonated phosphonic acids comprise tetrafluorostyrene-phosphonic acid and perfluorosulfonic acid polymers, where a perfluorosulfonic acid proton is transferred to the phosphonic acid to enhance the anhydrous proton conduction of fuel cell electrodes. By using this material in fuel cell electrodes, we obtained a fuel cell exhibiting a rated power density of 780 mW cm -2 at 160 °C, with minimal degradation during 2,500 h of operation and 700 thermal cycles from 40 to 160 °C under load.

25 ENERGY STORAGE↗
DOE OSTI2022

Control of chiral orbital currents in a colossal magnetoresistance material

Colossal magnetoresistance (CMR) is an extraordinary enhancement of the electrical conductivity in the presence of a magnetic field. It is conventionally associated with a field-induced spin polarization that drastically reduces spin scattering and electric resistance. Ferrimagnetic Mn 3 Si 2 Te 6 is an intriguing exception to this rule: it exhibits a seven-order-of-magnitude reduction in ab plane resistivity that occurs only when a magnetic polarization is avoided 1,2 . Here, we report an exotic quantum state that is driven by ab plane chiral orbital currents (COC) flowing along edges of MnTe 6 octahedra. The c axis orbital moments of ab plane COC couple to the ferrimagnetic Mn spins to drastically increase the ab plane conductivity (CMR) when an external magnetic field is aligned along the magnetic hard c axis. Consequently, COC-driven CMR is highly susceptible to small direct currents exceeding a critical threshold, and can induce a time-dependent, bistable switching that mimics a first-order ‘melting transition’ that is a hallmark of the COC state. Further, the demonstrated current-control of COC-enabled CMR offers a new paradigm for quantum technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Electron-nuclear decoupling at a spin clock transition

The ability to design quantum systems that decouple from environmental noise sources is highly desirable for development of quantum technologies with optimal coherence. The chemical tunability of electronic states in magnetic molecules combined with advanced electron spin resonance techniques provides excellent opportunities to address this problem. Indeed, so-called clock transitions have been shown to protect molecular spin qubits from magnetic noise, giving rise to significantly enhanced coherence. Here we conduct a spectroscopic and computational investigation of this physics, focusing on the role of the nuclear bath. Away from the clock transition, linear coupling to the nuclear degrees of freedom causes a modulation and decay of electronic coherence, as quantified via electron spin echo signals generated experimentally and in silico. Meanwhile, the effective hyperfine interaction vanishes at the clock transition, resulting in electron-nuclear decoupling and an absence of quantum information leakage to the nuclear bath, providing opportunities to characterize other decoherence sources.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2022

Halide sublattice dynamics drive Li-ion transport in antiperovskites

Here, in this work, we resolve how proton dynamics and halide mixing enhance or impede ionic conduction in protonated lithium antiperovskites (pLiAP) at compositions near the eutectic points of the halide salts. As a material class, pLiAPs of the form Li 3-x OH x X, (X = Cl, Br) show vast compositional design freedom; however, the resulting properties are susceptible to synthesis and processing methodologies. Proton incorporation and halide mixing stabilize the perovskite cubic phase at low temperatures (<50 °C) and using halide mixtures near the eutectic points (~250 to 300 °C) offer possibilities of lower temperature and faster synthesis and processing conditions (<1 h). Mixed-halide compositions such as Li 2 OHCl 0.37 Br 0.63 lead to a 30-fold improvement in room temperature ionic conductivity of a single halide structure, 1.5 × 10 -6 vs. 4.9 × 10 -8 S cm -1 (Li 2 OHCl). We combine infrared spectroscopy and nuclear magnetic resonance with first-principles density functional theory calculations to deconvolute halide mixing effects from local proton dynamics on Li-ion transport. In contrast to what has been supposed, our findings suggest that the halide sublattice dynamics, besides the OH rotation, correlate strongly with the fast-ion conduction at high temperatures.

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

Non-covalent planarizing interactions yield highly ordered and thermotropic liquid crystalline conjugated polymers

Controlling the multi-level assembly and morphological properties of conjugated polymers through structural manipulation has contributed significantly to the advancement of organic electronics. In this work, a redox active conjugated polymer, TPT–TT, composed of alternating 1,4-(2-thienyl)-2,5-dialkoxyphenylene (TPT) and thienothiophene (TT) units is reported with non-covalent intramolecular S⋯O and S⋯H–C interactions that induce controlled main-chain planarity and solid-state order. As confirmed by density functional theory (DFT) calculations, these intramolecular interactions influence the main chain conformation, promoting backbone planarization, while still allowing dihedral rotations at higher kinetic energies (higher temperature), and give rise to temperature-dependent aggregation properties. Thermotropic liquid crystalline (LC) behavior is confirmed by cross-polarized optical microscopy (CPOM) and closely correlated with multiple thermal transitions observed by differential scanning calorimetry (DSC). This LC behavior allows us to develop and utilize a thermal annealing treatment that results in thin films with notable long-range order, as shown by grazing-incidence X-ray diffraction (GIXD). Specifically, we identified a first LC phase, ranging from 218 °C to 107 °C, as a nematic phase featuring preferential face-on π–π stacking and edge-on lamellar stacking exhibiting a large extent of disorder and broad orientation distribution. A second LC phase is observed from 107 °C to 48 °C, as a smectic A phase featuring sharp, highly ordered out-of-plane lamellar stacking features and sharp tilted backbone stacking peaks, while the structure of a third LC phase with a transition at 48 °C remains unclear, but resembles that of the solid state at ambient temperature. Furthermore, the significance of thermal annealing is evident in the ∼3-fold enhancement of the electrical conductivity of ferric tosylate-doped annealed films reaching 55 S cm −1 . More importantly, thermally annealed TPT–TT films exhibit both a narrow distribution of charge-carrier mobilities (1.4 ± 0.1) × 10 −2 cm 2 V −1 s −1 along with a remarkable device yield of 100% in an organic field-effect transistor (OFET) configuration. This molecular design approach to obtain highly ordered conjugated polymers in the solid state affords a deeper understanding of how intramolecular interactions and repeat-unit symmetry impact liquid crystallinity, solution aggregation, solution to solid-state transformation, solid-state morphology, and ultimately device applications.

Chemistry↗
DOE OSTI2021

RF surface resistance tuning of superconducting niobium via thermal diffusion of native oxide

Recently, Nb superconducting radio frequency cavities vacuum heat treated between 300 and 400°C for a few hours have exhibited very high quality factors (~5 × 10 10 at 2.0 K). Secondary ion mass spectrometry measurements of O, N, and C show that this enhancement in RF surface conductivity is primarily associated with interstitial O alloying via dissolution and diffusion of the native oxide. We use a theory of oxide decomposition and O diffusion to quantify previously unknown parameters crucial in modeling this process. RF measurements of a vacuum heat-treated Nb superconducting radio frequency cavity confirm the minimized surface resistance (higher Q 0 ) previously expected only from 800 °C diffusive alloying with N.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Itinerant G-type antiferromagnet SrCr 2 As 2 studied by magnetization, heat capacity, electrical resistivity, and NMR measurements

Here, the physical properties of itinerant antiferromagnetic (AFM) SrCr 2 As 2 with body-centered tetragonal ThCr 2 Si 2 structure were investigated in single crystalline and polycrystalline forms by electrical resistivity ρ, heat capacity C p , magnetic susceptibility χ versus temperature T, and magnetization M versus applied magnetic field H isotherm measurements as well as 75 As and 53 Cr nuclear magnetic resonance (NMR) measurements in the wide temperature range T = 1.6–900 K. From the χ(T) and 75 As NMR measurements, the G-type AFM state below T N = 615(15) K has been determined, consistent with the previous neutron-diffraction measurements. Direct evidence of magnetic ordering of the Cr spins was shown by the observation of the 53 Cr NMR spectrum under H = 0. From the χ( T) measurements on single-crystal SrCr 2 As 2 under the two different magnetic field directions H|| ab and H || c in the AFM state, the Cr ordered moments are shown to align along the c axis in the G-type AFM state. The metallic state is directly evidenced by the ρ, C p , and NMR measurements, and the density of states at the Fermi energy $\mathscr{D}$(E F ) in the AFM state is estimated to be 7.53 states/eV f.u. for both spin directions which is almost twice the bare $\mathscr{D}$(E F ) estimated from first-principles calculations, suggesting an enhancement of the conduction-carrier mass by a factor of two in the AFM state. The $\mathscr{D}$(E F ) is found to be nearly constant below at least 100 K and is independent of H. The ρ(T) is found to show T-linear behavior above T N and exhibits positive curvature below T N where significant loss of spin-disorder scattering upon magnetic ordering is observed. The resistivity anisotropy of the compound remains moderate ρ c /ρ a ~ 9 through most of the magnetically ordered phase but shows a rapid increase below 50 K.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Deep Analysis Net with Causal Embedding for Coal-fired Power Plant Fault Detection and Diagnosis (DANCE4CFDD)

Fault detection and diagnosis is critical to power plant operation to ensure attaining high reliability while reducing operation cost. As more renewable power is introduced to the power grid, traditional fossil power plants take on the extra burden of excessive load cycling to compensate the generation variability from renewable power. Such load cycling will pose more reliability challenges to power plant operation. There are a number of challenges faced by today’s asset health management system in coal- fired (or gas) power plants: 1) high-dimensional nonlinear interaction among multiple time series measurements; 2) high measurement variance induced by operational conditions/modes; 3) variation among asset types and plant configurations; and 4) a small number of faulty events to learn from. To cope with these challenges, today’s fielded asset health management systems rely heavily on manual efforts from domain experts and hand-crafted features or rules based on domain knowledge. Despite its role in plant reliability, such a practice is costly and hinders its scalability and sustainability, particularly when a plant undergoes modifications. The objective of this project is to develop a novel end-to-end AI learning system that is trainable (i.e., the AI representation of a complex system behavior can be directly learned from properly labeled data) for accurate fault detection and root cause analysis. The ability to create a fault detection model directly from time series could alleviate the efforts associated with today’s asset management solution development. In the course of this project, we have achieved the following: Created an AI model development environment incorporating state-of-the-art neural network architectures for rapid model development and evaluation; Developed novel learning strategies for training of fault detection model; Developed special-purpose neural network architecture embedded with variable association graph aiming for better interpretability; Developed a learning strategy to leverage a small number of faulty events for enhanced fault detection capability; Conducted detailed experimental study based on public benchmark datasets and demonstrated the effectiveness of the proposed solution; and Validated the developed system with data from both a coal-fired plant boiler dynamic simulation model and real-world coal-fired power plant covering multiple asset and fault types. Overall, the project attained a technology readiness level of TRL 5 from TRL 2 at the beginning of the project.

20 FOSSIL-FUELED POWER PLANTS↗