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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 1,639 records · Page 91
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Shearography for Non-Destructive Evaluation with Applications to BAT Mask Tile Adhesive Bonding and Specular Surface Honeycomb Panels

In this report we examine the applicability of shearography techniques for nondestructive inspection and evaluation in two unique application areas. In the first application, shearography is used to evaluate the quality of adhesive bonds holding lead tiles to the BAT gamma ray mask for the NASA Swift program. By exciting the mask with a vibration, the more poorly bonded tiles can be distinguished by their greater displacement response, which is readily identifiable in the shearography image. A quantitative analysis is presented that compares the shearography results with a destructive pull test measuring the force at bond failure. Generally speaking, the results show good agreement. Further investigation would be useful to optimize certain test parameters such as vibration frequency and amplitude. The second application is to evaluate the bonding between the skin and core of a honeycomb structure with a specular (mirror-like) surface. In standard shearography techniques, the object under test must have a diffuse surface to generate the speckle patterns in laser light, which are then sheared. A novel configuration using the specular surface as a mirror to image speckles from a diffuser is presented, opening up the use of shearography to a new class of objects that could not have been examined with the traditional approach. This new technique readily identifies large scale bond failures in the panel, demonstrating the validity of this approach. For the particular panel examined here, some scaling issues should be examined further to resolve the measurement scale down to the very small size of the core cells. In addition, further development should be undertaken to determine the general applicability of the new approach and to establish a firm quantitative foundation.

Lysak, Daniel B.↗
NASA NTRS2022

Robust Vision-based Multi-spacecraft Guidance Navigation and Control using CNN-based Pose Estimation

In this paper, we present an end-to-end simulation framework for tracking an uncooperative Target spacecraft in Low Earth Orbit using a CubeSat-class Ego spacecraft outfitted with a camera. Currently, capturing high-fidelity realistic images in space for this scenario is difficult and exorbitantly expensive. Therefore, we developed a framework to simulate the spacecraft orbits in Basilisk software and generate high-fidelity realistic images of spacecraft in Unreal Engine, including the effects from Sun, Earth, Moon and stars. The Ego spacecraft uses cameras to capture images of the uncooperative Target and estimates its position and attitude using a CNN based 6DOF pose estimation pipeline, eliminating need for large SWAP-C(Size, Weight, Power and Cost) sensors like LIDAR or reliance on inter-spacecraft communication, This CNN, which is motivated by ESA’s Pose Estimation challenge of 2019, is trained using simulated data from our end-to-end simulation framework. We compare the performance of two distinct CNNbased algorithms for pose estimation along a nominal trajectory. In presence of non-Gaussian modeling uncertainties, the statedependent estimation error is characterized with a quadratic upper-bound. The quadratically-bounded error can be used by a robust controller to maneuver

Rahmani, Amir↗
DOE OSTI2013

"Ask Argonne" - Edwin Campos, Research Meteorologist, Part 1

Dr. Edwin Campos is a Research Meteorologist at Argonne National Laboratory. For the last two decades, he has studied weather, and in particular, clouds. Clouds are one of the most uncertain variables in climate predictions and are often related to transportation hazards. Clouds can also impact world-class sporting events like the Olympics. You may have questions about the role of clouds, or weather, on our daily lives. How is severe weather monitored for airports? What is the impact of clouds and wind on the generation of electricity? One of the projects Edwin is working on is short-term forecasting as it relates to solar electricity. For this, Edwin's team is partnering with industry and academia to study new ways of forecasting clouds, delivering technologies that will allow the incorporation of more solar power into the electric grid. Post a question for Edwin as a comment below, and it might get answered in the follow-up video we'll post in the next few weeks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Amorphous oxide alloys as interfacial layers with broadly tunable electronic structures for organic photovoltaic cells

In diverse classes of organic optoelectronic devices, controlling charge injection, extraction, and blocking across organic semiconductor– inorganic electrode interfaces is crucial for enhancing quantum efficiency and output voltage. To this end, the strategy of inserting engineered interfacial layers (IFLs) between electrical contacts and organic semiconductors has significantly advanced organic light-emitting diode and organic thin film transistor performance. For organic photovoltaic (OPV) devices, an electronically flexible IFL design strategy to incrementally tune energy level matching between the inorganic electrode system and the organic photoactive components without varying the surface chemistry would permit OPV cells to adapt to ever-changing generations of photoactive materials. Here we report the implementation of chemically/environmentally robust, low-temperature solution-processed amorphous transparent semiconducting oxide alloys, In-Ga-O and Ga-Zn-Sn-O, as IFLs for inverted OPVs. Lastly, continuous variation of the IFL compositions tunes the conduction band minima over a broad range, affording optimized OPV power conversion efficiencies for multiple classes of organic active layer materials and establishing clear correlations between IFL/photoactive layer energetics and device performance.

25 ENERGY STORAGE↗
DOE OSTI2025

Multifunctional Polar 2D Lead Iodide Perovskites Exhibiting Persistent Spin Texture

Ferroelectric Rashba semiconductors are a rare class of multifunctional materials promising for spin–orbitronics due to the possibility of electrically switchable spin textures. Hybrid organic–inorganic metal halide perovskites offer exceptional tunability that can be harnessed to target noncentrosymmetry; however, the complex interactions between organic and inorganic components are not rationally understood. Here, we use an asymmetric spacer cation with a strong molecular dipole moment (2-fluorobenzylammonium, 2FBZ) and increase the intrinsic quantum well thickness to n > 1 to synthesize three new polar 2D lead iodide perovskites (2FBZ) 2 (A) n-1 Pb n I 3n+1 with A = methylammonium (MA) or formamidinium (FA) and n = 2, 3. Single-crystal structure analysis reveals the C 2v symmetry of these crystal structures and substantial structural distortions, which enable Rashba and Dresselhaus band splitting and persistent spin texture, confirmed by DFT calculations. Measurements of the resulting symmetry-dependent properties, such as second harmonic generation, switchable photovoltaic effect, ferroelectric polarization, and low temperature photoluminescence show switchable ferroelectric semiconducting properties. Furthermore, these results introduce a general chemical design strategy toward polar symmetry by exploiting the complex interplay between asymmetric spacer cations and A-site cations in quasi-2D (n > 1) halide perovskites to realize new classes of multifunctional materials for future spin–orbitronic applications.

Cations↗
DOE OSTI2025

DuctGPT: A Generative Transformer for Forward Screening of Ductile Refractory Multi-Principal Element Alloys

Designing ductile materials for extreme environments such as fusion reactors requires a deep understanding of the complex interplay between electronic structure, mechanical stability, and wide compositional space. Here, in this work, we introduce DuctGPT, a physics-informed, GPT-powered machine learning platform that enables rapid and accurate prediction of ductility across a wide range of refractory multi-principal element alloys (MPEAs). Trained on both experimental and high-fidelity computational data, DuctGPT integrates descriptors such as density of states at the Fermi level, elastic constants, and valence electron concentration to capture the fundamental mechanisms governing ductile versus brittle behavior. Using this framework, we screen over 1000 compositions in of body-centered cubic (BCC) MPEAs, including two new alloy classes, i.e., NbTa-rich (NbTa $>$ 50 at.%) NbTa-Ti-V and W-rich ($>$ 50 at.%) W-Ti-V MPEAs, to rapidly identify promising alloy compositions with enhanced ductility. Validation against experimental data confirms the model's ability to predict ductility with high fidelity and low uncertainty. By leveraging conversational AI and robust physical modeling, DuctGPT provides a blueprint for the next generation of alloy design assistants, enabling human-AI collaboration in the accelerated discovery of ductile, high-performance materials for fusion, aerospace, and advanced manufacturing.

AI/ML↗
DOE OSTI2017

Standard grids for high-precision integration of modern density functionals: SG-2 and SG-3

Density-functional approximations developed in the past decade necessitate the use of quadrature grids that are far more dense than those required to integrate older generations of functionals. This category of difficult-to-integrate functionals includes meta-generalized gradient approximations, which depend on orbital gradients and/or the Laplacian of the density, as well as functionals based on B97 and the popular “Minnesota” class of functionals, each of which contain complicated and/or oscillatory expressions for the exchange inhomogeneity factor. Following a strategy introduced previously by Gill and co-workers to develop the relatively sparse “SG-0” and “SG-1” standard quadrature grids, we introduce two higher-quality grids that we designate SG-2 and SG-3, obtained by systematically “pruning” medium- and high-quality atom-centered grids. The pruning procedure affords computational speedups approaching a factor of two for hybrid functionals applied to systems of ~100 atoms, without significant loss of accuracy. The grid dependence of several popular density functionals is characterized for various properties.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Discovery of multidrug efflux pump inhibitors with a novel chemical scaffold

Multidrug efflux is a major contributor to antibiotic resistance in Gram-negative bacterial pathogens. Inhibition of multidrug efflux pumps is a promising approach for reviving the efficacy of existing antibiotics. Previously, inhibitors targeting both the efflux transporter AcrB and the membrane fusion protein AcrA in the Escherichia coli AcrAB-TolC efflux pump were identified. In this work we use existing physicochemical property guidelines to generate a filtered library of compounds for computational docking. We then experimentally test the top candidate coumpounds using in vitro binding assays and in vivo potentiation assays in bacterial strains with controllable permeability barriers. We thus identify a new class of inhibitors of E. coli AcrAB-TolC. Six molecules with a shared scaffold were found to potentiate the antimicrobial activity of erythromycin and novobiocin in hyperporinated E. coli cells. Importantly, these six molecules were also active in wild-type strains of both Acinetobacter baumannii and Klebsiella pneumoniae, potentiating the activity of erythromycin and novobiocin up to 8-fold.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Materials Fingerprinting Classification

Significant progress in many classes of materials could be made with the availability of experimentally-derived large datasets composed of atomic identities and three-dimensional coordinates. Methods for visualizing the local atomic structure, such as atom probe tomography (APT), which routinely generate datasets comprised of millions of atoms, are an important step in realizing this goal. However, state-of-the-art APT instruments generate noisy and sparse datasets that provide information about elemental type, but obscure atomic structures, thus limiting their subsequent value for materials discovery. The application of a materials fingerprinting process, a machine learning algorithm coupled with topological data analysis, provides an avenue by which here-to-fore unprecedented structural information can be extracted from an APT dataset. As a proof of concept, the material fingerprint is applied to high-entropy alloy APT datasets containing body-centered cubic (BCC) and face-centered cubic (FCC) crystal structures. A local atomic configuration centered on an arbitrary atom is assigned a topological descriptor, with which it can be characterized as a BCC or FCC lattice with near perfect accuracy, despite the inherent noise in the dataset. Finally, this successful identification of a fingerprint is a crucial first step in the development of algorithms which can extract more nuanced information, such as chemical ordering, from existing datasets of complex materials.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Relationship between serum trimethylamine N-oxide and exposure to dioxin-like pollutants

Highlights: • TMAO has been linked to cardiovascular disease risk in human studies and animal models. • TMAO was positively associated with 22 indexes of dioxin-like pollutant exposures in ACHS-II. • Associations with TMAO were significant among females (except at high BMIs) but not among males. • The dioxin TEQ: TMAO association was unaltered by adjustment for independent covariates of TMAO. Trimethylamine N-oxide (TMAO) is a diet and gut microbiota-derived metabolite that has been linked to cardiovascular disease risk in human studies and animal models. TMAO levels show wide inter and intra individual variability in humans that can likely be accounted for by multiple factors including diet, the gut microbiota, levels of the TMAO generating liver enzyme Flavin-containing monooxygenase 3 (FMO3) and kidney function. We recently found that dioxin-like (DL) environmental pollutants increased FMO3 expression to elevate circulating diet-derived TMAO in mice, suggesting that exposure to this class of pollutants might also contribute to inter-individual variability in circulating TMAO levels in humans. To begin to explore this possibility we examined the relationship between body burden of DL pollutants (reported by serum lipid concentrations) and serum TMAO levels (n = 340) in the Anniston, AL cohort, which was highly exposed to polychlorinated biphenyls (PCBs). TMAO concentrations in archived serum samples from the Anniston Community Health Survey (ACHS-II) were measured, and associations of TMAO with 28 indices of pollutant body burden, including total dioxins toxic equivalent (TEQ), were quantified. Twenty-three (22 after adjustment for multiple comparisons) of the 28 indices were significantly positively associated with TMAO. Although the design of ACHS-II does not enable quantitative assessment of the contributions of previously known determinants of TMAO variability to this relationship, limited multivariate modeling revealed that total dioxins TEQ was significantly associated with TMAO among females (except at high BMIs) but not among males. Our results from this cross-sectional study indicate that exposure to DL pollutants may contribute to elevated serum TMAO levels. Prospective longitudinal studies will be required to assess the joint relationship between DL pollutant exposures, other determinants of TMAO, and health outcomes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Hydrothermal Liquefaction Biocrude Compositions Compared to Petroleum Crude and Shale Oil

We provide a direct and detailed comparison of the chemical composition of petroleum crude oil (from the Gulf of Mexico), shale oil, and three biocrudes (i.e., clean pine, microalgae Chlorella sp., and sewage sludge feedstocks) generated by hydrothermal liquefaction (HTL). Ultrahigh resolution Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) reveals that HTL biocrudes are compositionally more similar to shale oil than petroleum crude oil and that only a few heteroatom classes (e.g., N1, N2, N1O1, and O1) are common to organic sediment- and biomass-derived oils. All HTL biocrudes contain a diverse range of oxygen-containing compounds when compared to either petroleum crude or shale oil. Overall, petroleum crude and shale oil are compositionally dissimilar to HTL oils, and >85% of the elemental compositions identified within the positive-ion electrospray (ESI) mass spectra of the HTL biocrudes were not present in either the petroleum crude or shale oil (>43% for negative-ion ESI). Direct comparison of the heteroatom classes that are common to both organic sedimentand biomass-derived oils shows that HTL biocrudes generally contain species with both smaller core structures and a lower degree of alkylation relative to either the petroleum crude or the shale oil. Three-dimensional plots of carbon number versus molecular double bond equivalents (with observed abundance as the third dimension) for abundant molecular classes reveal the specific relationship of the composition of HTL biocrudes to petroleum and shale oils to inform the possible incorporation of these oils into refinery operations as a partial amendment to conventional petroleum feeds.

04 OIL SHALES AND TAR SANDS↗
DOE OSTI2015

Neurospora crassa transcriptomics reveals oxidative stress and plasma membrane homeostasis biology genes as key targets in response to chitosan

Chitosan is a natural polymer with antimicrobial activity. Chitosan causes plasma membrane permeabilization and induction of intracellular reactive oxygen species (ROS) in Neurospora crassa. In this paper, we have determined the transcriptional profile of N. crassa to chitosan and identified the main gene targets involved in the cellular response to this compound. Global network analyses showed membrane, transport and oxidoreductase activity as key nodes affected by chitosan. Activation of oxidative metabolism indicates the importance of ROS and cell energy together with plasma membrane homeostasis in N. crassa response to chitosan. Deletion strain analysis of chitosan susceptibility pointed NCU03639 encoding a class 3 lipase, involved in plasma membrane repair by lipid replacement, and NCU04537 a MFS monosaccharide transporter related to assimilation of simple sugars, as main gene targets of chitosan. NCU10521, a glutathione S-transferase-4 involved in the generation of reducing power for scavenging intracellular ROS is also a determinant chitosan gene target. Ca 2+ increased tolerance to chitosan in N. crassa. Growth of NCU10610 (fig 1 domain) and SYT1 (a synaptotagmin) deletion strains was significantly increased by Ca 2+ in the presence of chitosan. Both genes play a determinant role in N. crassa membrane homeostasis. Finally, our results are of paramount importance for developing chitosan as an antifungal.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Unconventional aliphatic fluorophores discovered as the luminescence origin in citric acid–urea carbon dots

Carbon dots (CDs) are emerging as the material of choice in a range of applications due to their excellent photoluminescence properties, ease of preparation from inexpensive precursors, and low toxicity. However, the precise nature of the mechanism for the fluorescence is still under debate, and several molecular fluorophores have been reported. In this work, a new blue fluorophore, 5-oxopyrrolidine-3-carboxylic acid, was discovered in carbon dots synthesized from the most commonly used precursors: citric acid and urea. The molecular product alone has demonstrated interesting aggregation-enhanced emission (AEE), making it unique compared to other fluorophores known to be generated in CDs. We propose that this molecular fluorophore is associated with a polymer backbone within the CDs, and its fluorescence behavior is largely dependent on intermolecular interactions with the polymers or other fluorophores. As a result, a new class of non-traditional fluorophores is now relevant to the consideration of the CD fluorescence mechanism, providing both an additional challenge to the community in resolving the mechanism and an opportunity for a greater range of CD design schemes and applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Noise-canceling quantum feedback: Non-Hermitian dynamics with applications to state preparation and magic state distillation

Time-continuous quantum measurement allows for the tracking of a quantum system in real time via sequences of short, and individually weak, measurement intervals. Such measurements are necessarily invasive, imparting backaction to the system, and allowing the observer to update their state estimate based on stochastic measurement outcomes. Feedback control then involves real-time interventions by an observer, conditioned on the time-continuous measurement signal that they receive. Here, we consider here diffusive quantum trajectories and focus on the “noise-canceling” subset of feedback protocols that aim to minimize the degree of stochasticity in the dynamics. We derive such a class of feedback operations, showing that under the idealized assumptions of pure states, unit measurement efficiency, and zero time delay in implementing feedback operations, perfectly noise-canceling feedback always exists. We consider the resulting noise-canceled dynamics generated by an effective non-Hermitian Hamiltonian; while non-Hermitian Hamiltonians from continuous monitoring generally describe rare dynamics (accessible by costly postselection), the use of noise-canceling feedback here leads to non-Hermitian dynamics that occur deterministically. We demonstrate this via examples of entangled state preparation and stabilization. We then illustrate the potential for the application of noise cancellation to boost success rates in magic state distillation protocols. We show that adding feedback based on noise cancellation into a time-continuous five-to-one distillation protocol leads to higher probabilities of successful distillation across a range of input errors and increases the threshold on input errors for which the protocol is effective. Our results highlight the efficacy of noise-canceling feedback-aided protocols for quantum state preparation and stabilization tasks.

Karmakar, Tathagata [University of California, Ber↗
DOE OSTI2015

Quantum Nonlinear Hall Effect Induced by Berry Curvature Dipole in Time-Reversal Invariant Materials

It is well known that a nonvanishing Hall conductivity requires broken time-reversal symmetry. However, we demonstrate that Hall-like currents can occur in second-order response to external electric fields in a wide class of time-reversal invariant and inversion breaking materials, at both zero and twice the driving frequency. This nonlinear Hall effect has a quantum origin arising from the dipole moment of the Berry curvature in momentum space, which generates a net anomalous velocity when the system is in a current-carrying state. The nonlinear Hall coefficient is a rank-two pseudotensor, whose form is determined by point group symmetry. We discus optimal conditions to observe this effect and propose candidate two- and three-dimensional materials, including topological crystalline insulators, transition metal dichalcogenides, and Weyl semimetals.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Computational Power of Random Quantum Circuits in Arbitrary Geometries

Empirical evidence for a gap between the computational powers of classical and quantum computers has been provided by experiments that sample the output distributions of two-dimensional quantum circuits. Many attempts to close this gap have utilized classical simulations based on tensor network techniques, and their limitations shed light on the improvements to quantum hardware required to frustrate classical simulability. In particular, quantum computers having in excess of approximately 50 qubits are primarily vulnerable to classical simulation due to restrictions on their gate fidelity and their connectivity, the latter determining how many gates are required (and, therefore, how much infidelity is suffered) in generating highly entangled states. Here, we describe recent hardware upgrades to Quantinuum’s H2 quantum computer, enabling it to operate on up to 56 qubits with arbitrary connectivity and 99.843(5)% two-qubit gate fidelity. We define a class of circuits with random geometries that become hard to classically simulate in very low depth and implement them utilizing the flexible connectivity of H2. A careful analysis demonstrating the fast saturation of classical simulation complexity with depth indicates that H2 can yield data well beyond the reach of state-of-the art classical simulation methods at unprecedented fidelities. We find that the considerable difficulty of classically simulating H2 is likely limited only by qubit number, demonstrating the promise and scalability of the quantum charge-coupled device architecture as continued progress is made toward building larger machines. Published by the American Physical Society 2025

DeCross, M.↗
DOE OSTI2025

Construction of hopfion crystals

Hopfions, three-dimensional topological solitons characterized by nontrivial Hopf indices, represent a fundamental class of field configurations that emerge across diverse areas of physics. Despite extensive studies of isolated hopfions, a framework for constructing spatially ordered arrays of hopfions, i.e., hopfion crystals, has been lacking. Here, we present a systematic approach for generating hopfion crystals with cubic symmetry by combining the Hopf map with rational mapping techniques. By superposing helical waves in ℝ 4 , we construct hopfion crystals with tunable Hopf indices and controllable topology. We demonstrate simple cubic, face-centered cubic, and body-centered cubic hopfion crystals and extend our framework to create crystals of more complex topological structures, including axially symmetric tori, torus links, and torus knots with higher Hopf indices. Our results provide a foundation for searching hopfions in real materials and studying their collective phenomena.

3-dimensional systems↗
DOE OSTI2016

Hanford Tank Farm Vapors Abatement Technology and Vendor Proposals Assessment

Suspected chemical vapor releases from the Hanford nuclear waste tank system pose concerns for worker exposure. Washington River Protection Solutions (WRPS) contracted the Savannah River National Laboratory (SRNL) to explore abatement technologies and strategies to remediate the vapors emitted through the ventilation system. In response, SRNL conducted an evaluation of technologies to abate, or reduce, vapor emissions to below 10% of the recognized occupational exposure limits (OELs). The evaluation included a review of published literature and a broadly communicated Request for Information to commercial vendors through a Federal Business Opportunities (Fed Biz Opps) web posting. In addition, SRNL conducted a workshop and post-workshop conference calls with interested suppliers (vendors) to assess proposals of relevant technologies. This report reviews applicable technologies and summarizes the approaches proposed by the vendors who participated in the workshop and teleconference interviews. In addition, the report evaluates the estimated performance of the individual technologies for the various classes of chemical compounds present in the Hanford Chemicals of Potential Concern (COPCs) list. Similarly, the report provides a relative evaluation of the vendor proposed approaches against criteria of: technical feasibility (and maturity), design features, operational considerations, secondary waste generation, safety/regulatory, and cost / schedule. These rough order-of-magnitude (ROM) cost estimates are intended to provide a comparison basis between technologies and are not intended to be actual project estimates.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗