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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Revealing the effect of local stresses on twin growth mechanisms in titanium using synchrotron X-ray diffraction

Deformation twinning has a significant impact on the evolution of microstructure and mechanical response in hexagonal close packed (hcp) metals. Understanding the physical mechanisms associated with twin nucleation and growth processes is important to enable the broad use of hcp metals. While both nucleation and growth are conditioned by the local stress state, few studies have quantified it in bulk deformed samples. In this study, we reveal the effects of local stresses on twin thickening using in-situ synchrotron experiments with differential aperture X-ray microscopy. High purity Ti is deformed under four-point bending to activate {1012} tensile twins. Further, 3D stress fields with a spatial resolution of 0.5μm are mapped in the vicinity of low and high macroscopic Schmid factor (MSF) twins growing inside a grain. Reconciling this experimental analysis with recent twin growth models reveals that the growth of low MSF twins is limited by the nucleation of twin growth defects in the high-purity Ti sample. While growth-inducing defect nucleation may occur in many places on the interface of the high resolved shear stress (RSS)/MSF twin, the nucleation rate of twinning disconnections for the low MSF twin is high only at the end of the twin near a stress concentration. Once nucleated, these defects easily propagate into lower RSS regions of the grain resulting in twin growth. This work highlights the importance of stress concentrations not only for twin (embryo) nucleation, but also to the growth process of twins, particularly in low MSF twins.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Long-term leaf C:N ratio change under elevated CO 2 and nitrogen deposition in China: Evidence from observations and process-based modeling

Climate change, elevating atmosphere CO 2 (eCO 2 ) and increased nitrogen deposition (iNDEP) are altering the biogeochemical interactions between plants, microbes and soils, which further modify plant leaf carbon-nitrogen (C:N) stoichiometry and their carbon assimilation capability. Many field experiments have observed large sensitivity of leaf C:N ratio to eCO 2 and iNDEP. However, the large-scale pattern of this sensitivity is still unclear, because eCO 2 and iNDEP drive leaf C:N ratio toward opposite directions, which are further compounded by the complex processes of nitrogen acquisition and plant-and-microbial nitrogen competition. Here, we attempt to map the leaf C:N ratio spatial variation in the past 5 decades in China with a combination of data-driven model and process-based modeling. These two approaches showed consistent results. Over different regions, we found that leaf C:N ratio had significant but uneven changes between 2 time periods (1960-1989 and 1990-2015): a 5% ± 8% increase for temperate grasslands in northern China, a 3% ± 6% increase for boreal grasslands in western China, and by contrast, a 7% ± 6% decrease for temperate forests in southern China, and a 3% ± 5% decrease for boreal forests in northeastern China. Additionally, the structural equation models indicated that the leaf C:N change was sensitive to ΔNDEP, ΔCO 2 and ΔMAT rather than ΔMAP and ecosystem types. In this work, process-based modeling suggested that iNDEP was the main source of soil mineral nitrogen change, dominating leaf C:N ratio change in most areas in China, while eCO 2 led to leaf C:N ratio increase in low iNDEP area. This study also indicates that the long-term leaf C:N ratio acclimation was dominated by climate constraint, especially temperature, but was constrained by soil N availability over decade scale.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

The impact of sampling scale: A comparison of methods for estimating external contaminant exposure in free-ranging wildlife

The impacts of contaminants on wildlife are dose dependent, and thus being able to track or predict exposure following contamination events is important for monitoring ecosystem health. However, the ability to track exposure in free-ranging wildlife is often severely limited. Consequently, researchers have predominantly relied on simple methods for estimating contaminant exposures in wildlife with little regard for spatial contaminant heterogeneity or an animal’s use of diverse habitats. We evaluated the influence sampling scale (i.e., how finely contaminant distribution and organism’s spatial use of the landscape is mapped) has on (1) realism and (2) conservativeness of exposure estimates. To do this, we monitored the actual exposure of wild boar (Sus scrofa) in Fukushima, Japan to radioactive contamination using GPS27 coupled contaminant monitors placed on individual animals. We compared empirical exposures to estimates generated by combining varying amounts of information about an individual boar’s location and/or movement, with the distribution of contamination on the landscape. Here we found that the most realistic exposure estimates were produced when finer-scale contaminant distribution surveys (e.g., airborne surveys) were combined with more accurate estimates of an individual’s space use (e.g., home ranges or core areas). Importantly, estimates of exposure based on single point surveys at a trap site (a simple method commonly used in the literature), did not correlate with actual exposure rates, suggesting dose-effects studies using this method may result in spurious conclusions. These results suggest that researchers seeking realistic estimates of exposure, such as in dose-effect studies, should ensure they have adequately accounted for fine-scale contaminant distribution patterns and areas of higher use by study organisms. However, conservative estimates of exposure i.e., intentionally over-predicting exposure as is done in initial tiers of ecological risk analyses) were not as scale sensitive and could be achieved with a single known location and coarse contaminant distribution maps.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2021

Imaging Charged Exciton Localization in van der Waals WSe 2 /MoSe 2 Heterobilayers

Exciton localization in transition-metal dichalcogenide monolayers is behind a variety of interesting phenomena and applications, including broad-spectrum solar cells and singlephoton emissions. Strain fields at the periphery of topographically distinct features such as nanoscopic bubbles were recently associated with localized charge-neutral excitons. Here, we use tip-enhanced photoluminescence (PL) to visualize excitons in WSe 2 /MoSe 2 heterobilayers (HBL). We find strong optical emission from charged excitons, particularly positively charged trions, in HBL supported by interlayer charge transfer. Our results reveal strong trion confinement, with a localization length scale comparable to the trion size, at the apex region inside individual nanoscopic bubbles. Nano-PL mapping also shows sub-10 nm spatial variations in the localized trion emission spectra, which stem from atomic-scale potential energy fluctuations. These findings demonstrate the possibility of confining charged exciton complexes that are electrically tunable, opening up further opportunities to probe many-body exciton physics, and to explore additional possible sites for strong exciton localization that can lead to quantum emissions.

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

Characterization of Materials Used as Face Coverings for Respiratory Protection

Use of masks is a primary tool to prevent the spread of the novel COVID-19 virus resulting from unintentional close contact with infected individuals. However, detailed characterization of the chemical properties and physical structure of common mask materials is lacking in the current literature. In this study, a series of commercial masks and potential mask materials, including 3M Particulate Respirator 8210 N95, a material provided by Oak Ridge National Laboratory Carbon Fiber Technology Facility (ORNL/CFTF), and a Filti Face Mask Material, were characterized by a suite of techniques, including scanning electron microscopy, X-ray diffraction, Raman spectroscopy, and X-ray photoelectron spectroscopy. Wetting properties of the mask materials were quantified by measurements of contact angle with a saliva substitute. Mask pass-through experiments were performed using a dispersed metal oxide nanoparticle suspension to model the SARS-CoV-2 virus, with quantification via spatially resolved X-ray fluorescence mapping. Notably, all mask materials tested provided a strong barrier against respiratory droplet breakthrough. The comparisons and characterizations provided in this study provide useful information when evaluating mask materials for respiratory protection.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Elucidating the Discharge Behavior of Aqueous Zinc Sulfur Batteries in the Presence of Molybdenum(IV) Chalcogenide Catalyst: The Criticality of Interfacial Electrochemistry

The aqueous zinc-sulfur battery holds promise for significant capacity and energy density with low cost and safe operation based on environmentally benign materials. However, it suffers from the sluggish kinetics of the conversion reaction. Here, we highlight the efficacy of molybdenum(IV) sulfide (MoS 2 ) to reduce the overpotential of S-ZnS conversion in aqueous electrolytes and study the discharge products formed at the solid-solid and solid-liquid interfaces using experimental and theoretical approaches. Specifically, the MoS 2 -catalyzed electrochemical conversion reaction is characterized via ex situ X-ray diffraction (XRD), transmission electron microscopy (TEM) with energy dispersive spectroscopy (EDS), Raman spectroscopy, synchrotron-based Mo K-edge X-ray absorption spectroscopy (XAS), and in situ synchrotron-based X-ray computed tomography (XCT). Additionally, operando synchrotron-based S K-edge XAS and X-ray fluorescence (XRF) maps are collected to determine the spatial evolution of sulfur-based species at the electrode-electrolyte interface. Further, coupling the operando S K-edge XAS data with the simulated spectra and fitting the data suggested a possible ZnS 2 intermediate phase.

25 ENERGY STORAGE↗
DOE OSTI2022

2D Reconstruction of Magnetotail Electron Diffusion Region Measured by MMS

Models for collisionless magnetic reconnection in near-Earth space are distinctly characterized as 2D or 3D. In 2D kinetic models, the frozen-in law for the electron fluid is usually broken by laminar dynamics involving structures set by the electron orbit size, while in 3D models the width of the electron diffusion region is broadened by turbulent effects. We present an analysis of in situ spacecraft observations from the Earth's magnetotail of a fortuitous encounter with an active reconnection region, mapping the observations onto a 2D spatial domain. While the event likely was perturbed by low-frequency 3D dynamics, the structure of the electron diffusion region remains consistent with results from a 2D kinetic simulation. As such, the event represents a unique validation of 2D kinetic, and laminar reconnection models.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Three Decades of Wetland Methane Surface Flux Modeling by Earth System Models–Advances, Applications, and Challenges

Earth System Models (ESMs) simulate the exchange of mass and energy between the land surface and the atmosphere, with a key focus on modeling natural greenhouse gas feedbacks. Methane is the second most important greenhouse gas after carbon dioxide. There are growing concerns over the rapidly increasing methane concentration in the atmosphere, underscoring the need for accurate global modeling of its emissions using ESMs. Of the multitude of sources of methane globally, wetlands are the largest natural emitters for methane, leading to significant efforts targeting their representation in ESMs with a special focus on their methane emissions. In this review, we first provide a historical overview of including wetland–methane components in ESMs and how methane modeling approaches have evolved over time. Second, we discuss recent modeling advancements that show promise for improvements in methane emissions predictions, namely the coupling of surface and atmospheric modules of ESMs, the representation of microtopography and transport mechanisms, the resolution of microbial processes at different spatial–temporal scales, and the improved mapping of wetland area extent across the different wetland types. Third, we shed light on the different challenges hindering accurate estimations of wetland–methane emissions, as shown by the consistent discrepancy between bottom–up and top–down models' predictions. Finally, we emphasize that more detailed representation of biogeochemistry and dynamic hydrology while resolving the within–wetland vegetation heterogeneity should improve model predictions, especially when coupled with expanding ground–based measurement networks and high–resolution remote sensing mapping of methane–relevant variables, such as water elevation, water table depth, and methane concentration.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

In situ plant materials hyperspectral imaging by multimodal scattering near-field optical microscopy

Plant cells are elaborate three-dimensional polymer nano-constructs with complex chemistry. The bulk response of plants to light, in the far-field, is ultimately encoded by optical scattering from these nano-constructs. Their chemical and physical properties may be acquired through their interaction with a modulated nano-tip using scattering scanning near-field optical microscopy. Here, using this technique, we present 20 nm spatial resolution mechanical, spectral and optical mappings of plant cell walls. We first address the problem of plant polymers tracking through pretreatment and processing. Specifically, cellulose and lignin footprints are traced within a set of delignified specimen, establishing the factors hindering complete removal of lignin, an important industrial polymer. Furthermore, we determine the frequency dependent dielectric function ${\epsilon }(\omega)={(n+ik)}^{2}$ of plant material in the range 28 ≤ ω ≤ 58 THz, and show how the environmental chemical variation is imprinted in the nanoscale variability of n and k . This nanometrology is a promise for further progress in the development of plant-based (meta-)materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Residual stress analysis of aluminum nitride piezoelectric micromachined ultrasonic transducers using Raman spectroscopy

In this study, the Raman biaxial stress coefficients K II and strain-free phonon frequencies ω 0 have been determined for the E 2 (low), E 2 (high), and A 1 (LO) phonon modes of aluminum nitride, AlN, using both experimental and theoretical approaches. The E 2 (high) mode of AlN is recommended for the residual stress analysis of AlN due to its high sensitivity and the largest signal-to-noise ratio among the studied modes. The E 2 (high) Raman biaxial stress coefficient of ₋3.8 cm₋1/GPa and strain-free phonon frequency of 656.68 cm ₋1 were then applied to perform both macroscopic and microscopic stress mappings. For macroscopic stress evaluation, the spatial variation of residual stress was measured across an AlN-on-Si wafer prepared by sputter deposition. A cross-wafer variation in residual stress of ~150 MPa was observed regardless of the average stress state of the film. Microscopic stress evaluation was performed on AlN piezoelectric micromachined ultrasonic transducers (pMUTs) with submicrometer spatial resolution. These measurements were used to assess the effect of device fabrication on residual stress distribution in an individual pMUT and the effect of residual stress on the resonance frequency. At ~20 μm directly outside the outer edge of the pMUT electrode, a large lateral spatial variation in residual stress of ~100 MPa was measured, highlighting the impact of metallization structures on residual stress in the AlN film.

36 MATERIALS SCIENCE↗
DOE OSTI2021

AFM-IR and s-SNOM-IR measurements of chemically addressable monolayers on Au nanoparticles

The performance of catalysts depends on their nanoscale properties, and local variations in structure and composition can have a dramatic impact on the catalytic reactivity. Therefore, probing the localized reactivity of catalytic surfaces using high spatial resolution vibrational spectroscopy, such as infrared (IR) nanospectroscopy and tip-enhanced Raman spectroscopy, is essential for mapping their reactivity pattern. Two fundamentally different scanning probe IR nanospectroscopy techniques, namely, scattering-type scanning near-field optical microscopy (sSNOM) and atomic force microscopy-infrared spectroscopy (AFM-IR), provide the capabilities for mapping the reactivity pattern of catalytic surfaces with a spatial resolution of ~20 nm. Herein, we compare these two techniques with regard to their applicability for probing the vibrational signature of reactive molecules on catalytic nanoparticles. For this purpose, we use chemically addressable self-assembled molecules on Au nanoparticles as model systems. We identified significant spectral differences depending on the measurement technique, which originate from the fundamentally different working principles of the applied methods. While AFM-IR spectra provided information from all the molecules that were positioned underneath the tip, the s-SNOM spectra were more orientation-sensitive. Due to its field-enhancement factor, the s-SNOM spectra showed higher vibrational signals for dipoles that were perpendicularly oriented to the surface. The s-SNOM sensitivity to the molecular orientation influenced the amplitude, position, and signal-to-noise ratio of the collected spectra. Ensemble-based IR measurements verified that differences in the localized IR spectra stem from the enhanced sensitivity of s-SNOM measurements to the adsorption geometry of the probed molecules.

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

Resolving surface potential variation in Ge/MoS 2 heterostructures with Kelvin probe force microscopy

In this work, we employ an atomic force microscopy-based technique, Kelvin probe force microscopy, to analyze heterogeneities of four different 2D/3D Ge/MoS 2 heterostructures with Ge chemical vapor deposition (CVD) time. High-contrast spatially resolved contact potential difference (CPD) maps reveal the evolution of the samples by Ge deposition. The CPD map in an as-prepared sample does not display any heterogeneity, but CPD contrasts along the grain boundaries are obviously noticed as Ge is deposited on MoS 2 . With a sufficiently long Ge CVD deposition time, strong grain-to-grain CPD variations over the 2D/3D heterostructures are observed. The results show the variations of the work function from grain to grain that are attributed to the strain induced by the Ge island formation on the cracked MoS2 initiated by sulfur vacancies.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Efficient simulation of open quantum systems coupled to a reservoir through multiple channels

It is challenging to simulate open quantum systems that are connected to a reservoir through multiple channels. For example, vibrations may induce fluctuations in both energy gaps and electronic couplings, which represent two independent channels of system–bath couplings. Systems of this kind are ubiquitous in the processes of excited state radiationless decay. Combined with density matrix renormalization group (DMRG) and matrix product states (MPS) methods, we develop an interaction-picture chain mapping strategy for vibrational reservoirs to simulate the dynamics of these open systems, resulting in time-dependent spatially local system–bath couplings in the chain-mapped Hamiltonian. This transformation causes the entanglement generated by the system–bath interactions to be restricted within a narrow frequency window of vibrational modes, enabling efficient DMRG/MPS dynamical simulations. We demonstrate the utility of this approach by simulating singlet fission dynamics using a generalized spin-boson Hamiltonian with both diagonal and off-diagonal system–bath couplings. This approach generalizes an earlier interaction-picture chain mapping scheme, allowing for efficient and exact simulation of systems with multi-channel system–bath couplings using matrix product states, which may further our understanding of nonlocal exciton–phonon couplings in exciton transport and the non-Condon effect in energy and electron transfer.

Chemistry↗
DOE OSTI2024

Quasiparton distributions in massive QED2: Toward quantum computation

We analyze the quasiparton distributions of the lightest 𝜂′ meson in massive two-dimensional quantum electrodynamics (QED2) by exact diagonalization. The Hamiltonian and boost operators are mapped onto spin qubits in a spatial lattice with open boundary conditions. The lowest excited state in the exact diagonalization is shown to interpolate continuously between an anomalous 𝜂′ state at strong coupling, and a nonanomalous heavy meson at weak coupling, with a cusp at the critical point. The boosted 𝜂′ state follows relativistic kinematics but with large deviations in the luminal limit. The spatial quasiparton distribution function and amplitude for the 𝜂′ state are computed numerically for increasing rapidity both at strong and weak coupling, and compared to the exact light front results. The numerical results from the boosted form of the spatial parton distributions, compare fairly with the inverse Fourier transformation of the luminal parton distributions, derived in the lowest Fock space approximation. Our analysis points out some of the limitations facing the current lattice program for the parton distributions.

Lattice field theory↗
DOE OSTI2023

Pharmacological Profiling of a Brugia malayi Muscarinic Acetylcholine Receptor as a Putative Antiparasitic Target

The diversification of anthelmintic targets and mechanisms of action will help ensure the sustainable control of nematode infections in response to the growing threat of drug resistance. G protein-coupled receptors (GPCRs) are established drug targets in human medicine but remain unexploited as anthelmintic substrates despite their important roles in nematode neuromuscular and physiological processes. Bottlenecks in exploring the druggability of parasitic nematode GPCRs include a limited helminth genetic toolkit and difficulties establishing functional heterologous expression. In an effort to address some of these challenges, we profile the function and pharmacology of muscarinic acetylcholine receptors in the human parasite Brugia malayi, an etiological agent of human lymphatic filariasis. While acetylcholine-gated ion channels are intensely studied as targets of existing anthelmintics, comparatively little is known about metabotropic receptor contributions to parasite cholinergic signaling. Using multivariate phenotypic assays in microfilariae and adults, we show that nicotinic and muscarinic compounds disparately affect parasite fitness traits. We identify a putative G protein-linked acetylcholine receptor of B. malayi (Bma-GAR-3) that is highly expressed across intramammalian life stages and adapt spatial RNA in situ hybridization to map receptor transcripts to critical parasite tissues. Tissue-specific expression of Bma-gar-3 in Caenorhabditis elegans (body wall muscle, sensory neurons, and pharynx) enabled receptor deorphanization and pharmacological profiling in a nematode physiological context. Finally, we developed an image-based feeding assay as a reporter of pharyngeal activity to facilitate GPCR screening in parasitized strains. We expect that these receptor characterization approaches and improved knowledge of GARs as putative drug targets will further advance the study of GPCR biology across medically important nematodes.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Self-Supervised T-GCN for Detection of Disturbance and Propagation in Power Grid

Urban power systems increasingly rely on dense sensing to monitor grid reliability, yet disturbance labels are scarce and events are rare. We present a self-supervised spatio-temporal method that detects, localizes, and characterizes grid frequency disturbances across urban areas using only unlabeled data. Our approach trains a tiny Temporal Graph Convolutional Network (T-GCN) to forecast per-site frequency residuals (deviation from 60 Hz). The sensor graph is constructed directly from signals using pre-event Pearson correlation with a cross-correlation lag penalty without geocoding. At inference, node-level anomalies are the model's forecast errors; region-level alarms arise from connected components of high-score nodes. We estimate disturbance propagation by computing per-node arrival times (first persistent exceedance), then fit a planar or time-of-arrival model to obtain direction, speed, and an epicenter proxy. With only three real events collected at decisecond resolution across U.S. cities, we evaluate the T-GCN and report time-to-detect, footprint size, and propagation consistency. We further show that short-window embeddings from the T-GCN's hidden states enable few-shot event-vs-background recognition via a simple prototypical classifier. Despite minimal data and no labels, our system yields fast, spatially coherent detection and interpretable propagation maps, offering a practical, lightweight pathway to city-scale grid resilience analytics.

Niu, Haoran [ORNL] (ORCID:0000000155228297)↗
DOE OSTI2020

FieLDS

Field Landscape Decision Support (FieLDS) is a decision support tool that assists agricultural producers and farm managers in selecting parts of the field that can be converted to bioenergy plants, like perennial grasses, from the conventional use, like corn or soybean growth. That conversion of parts of the field is done based on the specific landscape properties and the agricultural producer’s priorities. The decision support tool generates a map of the field layout and spatially marks where to place each plant based on the spatial input from the user. Also, the user selects which priorities (sustainability indicators) are most relevant to them in their decision-making. By allowing the user to set the weights among the priorities, the tool empowers the user to generate field designs specific to their needs instead of imposing the developer’s set of priorities, and increases the transparency of the decision process.

Vazhnik, Veronika↗