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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Investigation of thin/well-tunable liquid/gas diffusion layers exhibiting superior multifunctional performance in low-temperature electrolytic water splitting

Liquid/gas diffusion layers (LGDLs), which are located between the catalyst layer (CL) and bipolar plate (BP), play an important role in enhancing the performance of water splitting in proton exchange membrane electrolyzer cells (PEMECs). They are expected to transport electrons, heat, and reactants/products simultaneously with minimum voltage, current, thermal, interfacial, and fluidic losses. Here in this study, the thin titanium-based LGDLs with straight-through pores and well-defined pore morphologies are comprehensively investigated for the first time. The novel LGDL with a 400 μm pore size and 0.7 porosity achieved a best-ever performance of 1.66 V at 2 A cm -2 and 80 °C, as compared to the published literature. The thin/well-tunable titanium based LGDLs remarkably reduce ohmic and activation losses, and it was found that porosity has a more significant impact on performance than pore size. In addition, an appropriate equivalent electrical circuit model has been established to quantify the effects of pore morphologies. The rapid electrochemical reaction phenomena at the center of the PEMEC are observed by coupling with high-speed and micro-scale visualization systems. Lastly, the observed reactions contribute reasonable and pioneering data that elucidate the effects of porosity and pore size on the PEMEC performance. This study can be a new guide for future research and development towards high-efficiency and low-cost hydrogen energy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Combined effects of emitter–emitter and emitter–plasmonic surface separations dictate photoluminescence enhancement in a plasmonic field

The brightness of an emitter can be enhanced by metal-enhanced fluorescence, wherein the excitonic dipole couples with the electromagnetic field of the surface plasmon. In this report, we experimentally map the landscape of photoluminescence enhancement (EF exp ) of emitters in a plasmonic field as a function of the emitter–emitter separation, s, and the emitter–plasmon distance, t. We use Au nanoparticles overcoated with inert spacers as plasmonic systems and CdSe/ZnS quantum dots (QDs) as an emitter bearing opposite surface charges. The t and s are varied by changing the spacer thickness and number density of QDs on the plasmonic surface, respectively. The electrostatic binding of emitters on the plasmonic surface and their number density are established by following the variation of zeta-potential. EF exp is high, when t is short and s is large; nevertheless, it decreases when the emitter–emitter interaction dominates due to plasmon assisted nonradiative processes. In the absence of a plasmonic field, the enhancement observed is attributed to environmental effects and is independent of s, confirming the role of the electric field. Indeed, the distance dependence of EF exp closely follows the decay of the plasmonic field upon dilution of the emitter concentration on nanoparticles’ surface (s = 18 nm). The QD–plasmon system is visualized in the framework of the Thomson problem, and classical electrodynamics calculations give the trends in t and s dependence of the photoluminescence. Being the first report on the simultaneous dependence of t and s on plasmon-enhanced photoluminescence, the results presented herein will open newer opportunities in the design of hybrid systems with a high brightness.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Communication: Unambiguous comparison of many-electron wavefunctions through their overlaps

A simple and powerful method for comparing many-electron wavefunctions constructed at different levels of theory is presented. By using wavefunction overlaps, it is possible to analyze the effects of varying wavefunction models, molecular orbitals, and one-electron basis sets. The computation of wavefunction overlaps eliminates the inherent ambiguity connected to more rudimentary wavefunction analysis protocols, such as visualization of orbitals or comparing selected physical observables. Instead, wavefunction overlaps allow processing the many-electron wavefunctions in their full inherent complexity. The presented method is particularly effective for excited state calculations as it allows for automatic monitoring of changes in the ordering of the excited states. A numerical demonstration based on multireference computations of two test systems, the selenoacrolein molecule and an iridium complex, is presented.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Direct Observation of Twin van der Waals Molecular Chains

The van der Waals (vdW) assemblies are the most common structures of materials. However, directly mapping intermolecular electron clouds of a vdW assembly has never been obtained, even though the intramolecular electron clouds were visualized by atomic-resolution techniques. In this report, we unprecedently mapped the intermolecular electron cloud of the assembles of ethanol molecules via ethyl groups with noncontact atomic force microscopy at 5 K, leading to the first visualization of vdW molecular chains, in which ethanol molecules assemble into twin vdW molecular chains in a reverse parallel configuration on Ag(111) plane. Furthermore, spontaneous order-disorder transitions in the chain were dynamically observed, suggesting its unusual properties different from 2D vdW materials. In conclusion, these findings provide an "eye" to see the atomic world of vdW materials.

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

STORM Super-Resolution Visualization of Self-Assembled γPFD Chaperone Ultrastructures in Methanocaldococcus jannaschii

Gamma-prefoldin (γPFD), a unique chaperone found in the extremely thermophilic methanogen Methanocaldococcus jannaschii, self-assembles into filaments in vitro, which so far have been observed using transmission electron microscopy and cryo-electron microscopy. Utilizing three-dimensional stochastic optical reconstruction microscopy (3D-STORM), here we achieve ~20 nm resolution by precisely locating individual fluorescent molecules, hence resolving γPFD ultrastructure both in vitro and in vivo. Through CF647 NHS ester labeling, we first demonstrate the accurate visualization of filaments and bundles with purified γPFD. Next, by implementing immunofluorescence labeling after creating a 3xFLAG-tagged γPFD strain, we successfully visualize γPFD in M. jannaschii cells. Through 3D-STORM and two-color STORM imaging with DNA, we show the widespread distribution of filamentous γPFD structures within the cell. These findings provide valuable insights into the structure and localization of γPFD, opening up possibilities for studying intriguing nanoscale components not only in archaea but also in other microorganisms.

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

A Taxonomic Classification Approach for Global Spatio-temporal Data

The World Bank, World Health Organization, and other major vendors collectively provide thousands of global time series datasets that focus on issues of the environment, public health, economics, violence, education, and national security. Sorting these data into meaningful information requires the use of data mining techniques to cluster trends into an orderly and manageable number of cases. The World SpatioTemporal Analytics and Mapping (WSTAMP) project database (wstamp.ornl.gov) was developed to spatiotemporally harmonize global vendor data (23,300+ attributes, 200+ locations, 50+ years). Within the WSTAMP analytical environment, Dynamic Time Warping (DTW) has been a highly effective data-driven approach for clustering and mapping these time series into national spatiotemporal behavior maps. Two significant properties have surfaced from this work. First, several recognizable cluster patterns have emerged and persist across a range of locations, attributes, and time frames (e.g., increasing, decreasing, rebounding, peak, oscillating). Secondly, practitioners engaging WSTAMP have noted the explanatory and anticipatory value of these patterns and articulated particular interest in detecting them within the spatiotemporal cube. This need was addressed by shifting DTW-based clustering from an open ended, data-driven implementation to a taxonomic pattern matching approach. This paper presents the method including implementation strategies for visualization and human computer interaction and applies the approach to a sample data set and concludes with next steps.

Stewart, Robert↗
DOE OSTI2019

Quantification of Soil Organic Carbon in Biochar-Amended Soil Using Ground Penetrating Radar (GPR)

The application of biochar amendments to soil has been proposed as a strategy for mitigating global carbon (C) emissions and soil organic carbon (SOC) loss. Biochar can provide additional agronomic benefits to cropping systems, including improved crop yield, soil water holding capacity, seed germination, cation exchange capacity (CEC), and soil pH. To maximize the beneficial effects of biochar amendments towards the inventory, increase, and management of SOC pools, nondestructive analytical methods such as ground penetrating radar (GPR) are needed to identify and quantify belowground C. The use of GPR has been well characterized across geological, archaeological, engineering, and military applications. While GPR has been predominantly utilized to detect relatively large objects such as rocks, tree roots, land mines, and peat soils, the objective of this study was to quantify comparatively smaller, particulate sources of SOC. This research used three materials as C sources: biochar, graphite, and activated C. The C sources were mixed with sand—12 treatments in total—and scanned under three moisture levels: 0%, 10%, and 20% to simulate different soil conditions. GPR attribute analyses and Naïve Bayes predictive models were utilized in lieu of visualization methods because of the minute size of the C particles. Significant correlations between GPR attributes and both C content and moisture levels were detected. The accuracy of two predictive models using a Naïve Bayes classifier for C content was trivial but the accuracy for C structure was 56%. The analyses confirmed the ability of GPR to identify differences in both C content and C structure. Beneficial future applications could focus on applying GPR across more diverse soil conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Tracking single-particle rotation during macrophage uptake

We investigated the rotational dynamics of single microparticles during their internalization by macrophage cells. The microparticles used were triblock patchy particles that display two fluorescent patches on their two poles. The optical anisotropy made it possible to directly visualize and quantify the orientation and rotation of the particles. We show that particles exhibit a mixture of fast and slow rotation as they are uptaken by macrophages and transiently undergo directional rotation during their entry into the cell. As a result, the size of the particles and the surface presentation of ligands exerted a negligible influence on this heterogeneity of particle rotation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

The corrosion behavior of technetium metal exposed to aqueous sulfate and chloride solutions

Here, metal waste forms are being studied as possible disposal forms for technetium and other fission products from spent nuclear fuel. As an initial step in assessing the viability of waste forms, technetium corrosion and passivity behavior was assessed across a broad pH spectrum (pH –1 to pH 13). Measurements indicate that the open circuit potential falls into the region of Tc +7 stability, more noble than the region of presumed passivity. Potentiodynamic polarization tests indicate that the Tc samples are not passive. Both electrochemical results and visual inspection suggest the presence of a nonprotective film. The corrosion rate is relatively independent of pH and low, as measured by linear polarization resistance. No evidence of passivity was observed in the Tc +4 region of the potential-pH diagram following in-situ abrasion, suggesting that Tc does not passivate, regardless of potential.

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

Influence of Concentration Gradients on Electroconvection at a Cation-Exchange Membrane Surface

Membrane-based systems, such as electrodialysis, play an important role in desalination and industrial separation processes. Electrodialysis uses alternating anion- and cation-exchange membranes with a perpendicular electric field to generate concentrated and diluate streams from a feed solution. It is known that under overlimiting current conditions, reduced charge and mass transfer at the membrane interface leads to regions of high ion depletion generating instability and vortices termed electroconvection. While electroconvective mixing is known to directly impact the separation efficiency of electrodialysis, the influence of ion concentration gradients across the membrane experienced in a functional electrodialysis system is not known. Here, we report the influence of ion concentration gradients across a cation exchange membrane (Nafion) that is both aligned with and opposed to the applied electric field. Experiments were conducted by coflowing NaCl solutions of different concentrations (0.1–100 mM) on each side of the membrane, and electroconvection was visualized with a fluorescence dye (Rhodamine 6G). Here, we obtained concentration profiles from fluorescence image data and systematically measured the thickness of the depletion boundary layer d BL under different conditions. We found smaller d BL values at a higher flow rate both with and without concentration gradients. Our results show that electroconvection is enhanced when the electric field is opposite to the direction of the concentration gradient.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Assigning the absolute configuration of single aliphatic molecules by visual inspection

Deciphering absolute configuration of a single molecule by direct visual inspection is the next step in compound identification, with far-reaching implications for medicinal chemistry, pharmacology, and natural product synthesis. We demonstrate the feasibility of this approach utilizing low temperature atomic force microscopy (AFM) with a CO-functionalized tip to determine the absolute configuration and orientation of a single, adsorbed [123]tetramantane molecule, the smallest chiral diamondoid. We differentiate between single enantiomers on Cu(111) by direct visual inspection, and furthermore identify molecular dimers and molecular clusters. The experimental results are confirmed by a computational study that allowed quantification of the corresponding intermolecular interactions. The unique toolset of absolute configuration determination combined with AFM tip manipulation opens a route for studying molecular nucleation, including chirality-driven assembly or reaction mechanisms.

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

MultiTaskDeltaNet: change detection-based image segmentation for operando ETEM with application to carbon gasification kinetics

Transforming in situ transmission electron microscopy (TEM) imaging into a tool for spatially-resolved operando characterization of solid-state reactions requires automated, high-precision semantic segmentation of dynamically evolving features. However, traditional deep learning methods for semantic segmentation often face limitations due to the scarcity of labeled data, visually ambiguous features of interest, and scenarios involving small objects. To tackle these challenges, we introduce MultiTaskDeltaNet (MTDN), a novel deep learning architecture that creatively reconceptualizes the segmentation task as a change detection problem. By implementing a unique Siamese network with a U-Net backbone and using paired images to capture feature changes, MTDN effectively leverages minimal data to produce high-quality segmentations. Furthermore, MTDN utilizes a multi-task learning strategy to exploit correlations between physical features of interest. In an evaluation using data from in situ environmental TEM (ETEM) videos of filamentous carbon gasification, MTDN demonstrated a significant advantage over conventional segmentation models, particularly in accurately delineating fine structural features. Notably, MTDN achieved a 10.22% performance improvement over conventional segmentation models in predicting small and visually ambiguous physical features. This work bridges key gaps between deep learning and practical TEM image analysis, advancing automated characterization of nanomaterials in complex experimental settings.

08 HYDROGEN↗
DOE OSTI2017

Low-Temperature Combustion of High Octane Fuels in a Gasoline Compression Ignition Engine

Gasoline Compression Ignition (GCI) has been shown as one of the advanced combustion concepts that could potentially provide a pathway to achieve cleaner and more efficient combustion engines. Fuel and air in GCI are not fully premixed as compared to homogeneous charge compression ignition (HCCI) which is a completely kinetic-controlled combustion system. Therefore, the combustion phasing can be controlled by the time of injection, usually post injection in a multiple-injection scheme, to mitigate combustion noise. Gasoline fuels ignite more difficult than Diesel. The autoignition quality of gasoline can be indicated by research octane number (RON). Fuels with high octane tend to have more resistance to auto-ignition, hence more time for fuel-air mixing. In this study, three fuels, namely, Aromatic, Alkylate, and E30, with similar RON value of 98 but different hydrocarbon compositions were tested in a multi-cylinder engine under GCI combustion mode. Considerations of EGR, start of injection (SOI), and boost were investigated to study the sensitivity of dilution, local stratification, and reactivity of the charge, respectively, for each fuel. Combustion phasing was kept constant during the experiments to the changes in ignition and combustion process before and after 50% of the fuel mass is burned. Emission characteristics at different levels of EGR and lambda were revealed for all fuels with E30 having the lowest filter smoke number (FSN) and was also most sensitive to the change in dilution. Reasonably low combustion noise (< 90 dB) and stable combustion (COVIMEP < 3%) were maintained during the experiments. The second part of this paper contains visualization of the combustion process obtained from endoscope imaging for each fuel at selected conditions. Soot radiation signal from GCI combustion were strong during late injection, and also more intense at low EGR conditions. Furthermore, soot/temperature profiles indicated only the high-temperature combustion period, while cylinder pressure-based heat release rate (HRR) showed a two-stage combustion phenomenon.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Cryo-electron Microscopy of Adeno-associated Virus

Adeno-associated virus (AAV) has a single-stranded DNA genome encapsidated in a small icosahedrally symmetric protein shell with 60 subunits. AAV is the leading delivery vector in emerging gene therapy treatments for inherited disorders, so its structure and molecular interactions with human hosts are of intense interest. A wide array of electron microscopic approaches have been used to visualize the virus and its complexes, depending on the scientific question, technology available, and amenability of the sample. Approaches range from subvolume tomographic analyses of complexes with large and flexible host proteins to detailed analysis of atomic interactions within the virus and with small ligands at resolutions as high as 1.6 Å. Analyses have led to the reclassification of glycan receptors as attachment factors, to structures with a new-found receptor protein, to identification of the epitopes of antibodies, and a new understanding of possible neutralization mechanisms. AAV is now well-enough characterized that it has also become a model system for EM methods development. Heralding a new era, cryo-EM is now also being deployed as an analytic tool in the process development and production quality control of high value pharmaceutical biologics, namely AAV vectors.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

An approach for broad molecular imaging of the root-soil interface via indirect matrix-assisted laser desorption/ionization mass spectrometry

Understanding of rhizospheric processes is limited by the need for imaging complex molecular transformations at relevant spatial scales within the root soil continuum. In this work, we demonstrate a method to enable this analysis by first extracting organic compounds from the rhizosphere onto a PVDF membrane while maintaining their 2D distribution. We then image the distribution of chemical compounds using matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS). This approach permitted us to visualize and identify compounds on the root surface and presumed root exudates in the rhizosphere. Within a 1.8 cm x 0.6 cm sampling area of a switchgrass rhizosphere, we could observe at least four chemically distinct zones. Using high performance Fourier transform ion cyclotron MS, we were able to accurately annotate numerous molecules co-localized to each of these zones.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Thermally driven phase transition of halide perovskites revealed by big data-powered in situ electron microscopy

Halide perovskites are promising light-absorbing materials for high-efficiency solar cells, while the crystalline phase of halide perovskites may influence the device’s efficiency and stability. In this work, we investigated the thermally driven phase transition of perovskite (CsPbIxBr3—x), which was confirmed by electron diffraction and high-resolution transmission electron microscopy results. CsPbIxBr3—x transitioned from δ phase to α phase when heated, and the γ phase was obtained when the sample was cooled down. The γ phase was stable as long as it was isolated from humidity and air. A template matching-based data analysis method enabled visualization of the thermally driven phase evolution of perovskite during heating. Here, we also proposed a possible atomic movement in the process of phase transition based on our in situ heating experimental data. The results presented here may improve our understanding of the thermally driven phase transition of perovskite as well as provide a protocol for big-data analysis of in situ experiments.

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

The early-stage growth and reversibility of Li electrodeposition in Br-rich electrolytes

Significance Spatial variations in chemical composition and transport properties of the material phases (interphases) formed on reactive metals in liquid electrolytes are thought to be responsible for the propensity of metal battery electrodes to electrodeposit in irregular, nonplanar morphologies. Equilibrium theoretical calculations using joint density functional analysis in vacuum and generic liquid media indicate that in-plane transport at such interphases is enhanced substantially if LiX (X = Br > Cl > F) species predominate. This study employs optical visualization experiments and nucleation theory to experimentally investigate nucleation and early-stage growth dynamics of metallic lithium in electrolytes enriched with LiBr. It is shown that the Li-Br–rich interphases formed profoundly alter the morphology of Li electrodeposits by enhancing Li-ion surface diffusion.

25 ENERGY STORAGE↗
DOE OSTI2023

Fast Semi-automated Filtration Method for Non-targeted LC-QTOF Data of Aged Nitroplasticizer Samples

A full dataset of aged nitroplasticizer (NP) is composed of more than 2000 unique mass-to-charges (m/z) when combining the non-targeted data obtained from both positive and negative electrospray ionization modes in time-of-flight mass spectrometry. Therefore, manual processing of these data often takes days, weeks, or even months to scrutinize for mechanistic insights. To effectively extract meaningful signals that represent vital degradation intermediates in the early NP degradation mechanism, a semi-automated postprocessing workflow for data filtering, tailored to the aging experiment of NP, has been developed. The automated portion of this workflow is written in a Python code (using pandas, numpy, and matplotlib libraries), which removes more than 65% of potential false signals within seconds via four threshold-based adjustable filters: signal sensitivity, coefficient of variation, number of measurements, and retention time variability. As for the manual portion, a pattern-based inspection method is employed to reduce another 23% or more false positives, which greatly simplifies data visualization and results in less than 3% of potential candidate m/z needing in-depth data interpretation. As a positive control, known compounds are verified. Using this semi-automated data reduction method, the amount of time required is reduced to a matter of hours for data filtering in the non-targeted datasets of aged NP, which saves more time and effort for compound identification.

36 MATERIALS SCIENCE↗