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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A detection of the sea level fingerprint of Greenland Ice Sheet melt

Rapid melting of ice sheets and glaciers drives a unique geometry, or fingerprint, of sea level change. However, the detection of individual fingerprints has been challenging because of sparse observations at high latitudes and the difficulty of disentangling ocean dynamic variability from the signal. Here we predict the fingerprint of Greenland Ice Sheet (GrIS) melt using recent ice mass loss estimates from radar altimetry data and model reconstructions of nearby glaciers and compare this prediction to an independent, altimetry-derived sea surface height trend corrected for ocean dynamic variability in the region adjacent to the ice sheet. A statistically significant correlation between the two fields (P < 0.001) provides an unambiguous observational detection of the near-field sea level fingerprint of recent GrIS melting in our warming world.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

The Fingerprints of Stratospheric Aerosol Injection in E3SM

The June 15, 1991 Mt. Pinatubo eruption is simulated in E3SM by injecting 10 Tg of SO 2 gas in the stratosphere, turning off prescribed volcanic aerosols, and enabling E3SM to treat stratospheric volcanic aerosols prognostically. This experimental prognostic treatment of volcanic aerosols in the stratosphere results in some realistic behaviors (SO 2 evolves into H 2 SO 4 which heats the lower stratosphere), and some expected biases (H 2 SO 4 aerosols sediment out of the stratosphere too quickly). Climate fingerprinting techniques are used to establish a Mt. Pinatubo fingerprint based on the vertical profile of temperature from the E3SMv1 DECK ensemble. By projecting reanalysis data and preindustrial simulations onto the fingerprint, the Mt. Pinatubo stratospheric heating anomaly is detected. Projecting the experimental prognostic aerosol simulation onto the fingerprint also results in a detectable heating anomaly, but, as expected, the duration is too short relative to reanalysis data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Preparation of Waste Fingerprints for the Miscellaneous Beta Gamma Waste Feeds to the Box Encapsulation Plant at Sellafield - 16080

There are a number of legacy pond and silo storage facilities on Sellafield Site that contain a broad range of ILW arising from the early Windscale Pile and Magnox Fuel Reprocessing Programmes. The waste comprises of solid Miscellaneous Beta Gamma Waste (MBGW) from operations (including filters, containerised waste, thermocouple wire, support struts, pumps, soft wastes) and associated sludges that have arisen from the corrosion of the fuel, Magnox Swarf cladding and the MBGW. It is intended to retrieve and package this waste to meet the requirements of interim storage and final disposal in the Box Encapsulation Plant (BEP) at Sellafield. As part of this process each package must be assigned a realistic and justifiable radionuclide and material inventory. These inventories can either be assigned by radiometric measurements including the associated errors or developed by fundamental data underpinning these assessments and a 'chain of custody' approach of knowing where the waste has been and how it has evolved. The subject of this paper is concerned with the development of the waste fingerprints for these legacy waste streams. As the wastes have arisen over a ∼70 year period there have been an assortment of different working practices and developments in equipment design that have led to significant variations in the waste condition and its composition. During storage the waste items have become mixed, corroded and sludge deposits have arisen. Because of this, and that early consignment records are either incomplete or missing, the task of assigning material and radionuclide fingerprints has been very challenging. In addition, to comply with regulatory requirements the inventory assignment has to be sufficiently robust to meet the processing envelope of the encapsulation process i.e. to allow controls to be made on the amounts of reactive materials (e.g. aluminium, Magnox and uranium) that can be processed within each product and allow identification of excluded items from being consigned from the donor plants. Also, as the waste comprises actinides, fission and activation products it was noted that whilst the UK standard inventory code FISPIN10 predicts the actinides and fission products well, there was a significant discrepancy in the prediction of activation products when compared with those predicted by the specialised fusion code FISPACT. It should be noted that the use of FISPACT to predict actinides and fission products is not recommended. To address these issues, - position statements were produced for each of the waste streams that would be consigned to BEP; - gaps within the data were assessed and where possible inactive trial work was identified to address it; - material and radionuclide fingerprint justification documents were developed from the position statements based upon available data, the experimental work and justified assumptions; - where FISPIN runs were required, these were run with a modified activation data library based on the European Activation File 2010 (EAF2010) to model the activation products. This paper summarises the BEP process, discusses examples of how the material and radionuclide waste stream fingerprints have been justified by revisiting the sample data, original consignment records, engineering drawings and recent remotely operated vehicle (ROV) pond surveys and making reasoned assumptions based on operational practices and non-active experimental work. Incorporation of the EAF2010 library within the FISPIN code has offered significant benefits to BEP and indeed other plants processing mixed fission and activated wastes as it allows comparable predictions of activation products compared with that made by FISPACT and for the plant to maintain one data processing stream rather than two if it had to utilise both modelling codes. This work will underpin the inventory submission in support of the Interim Letter of Compliance (ILoC) to Radioactive Waste Management Limited (RWM). The process of examining the original records, plant operation schedules and engineering drawings has enabled removal of some of the pessimisms that have been made in previous assessments. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

High Throughput Ambient Mass Spectrometric Approach to Species Identification and Classification from Chemical Fingerprint Signatures

A high throughput method for species identification and classification through chemometric processing of direct analysis in real time (DART) mass spectrometry-derived fingerprint signatures has been developed. The method entails introduction of samples to the open air space between the DART ion source and the mass spectrometer inlet, with the entire observed mass spectral fingerprint subjected to unsupervised hierarchical clustering processing. Moreover, a range of both polar and non-polar chemotypes are instantaneously detected. The result is identification and species level classification based on the entire DART-MS spectrum. In this paper, we illustrate how the method can be used to: (1) distinguish between endangered woods regulated by the Convention for the International Trade of Endangered Flora and Fauna (CITES) treaty; (2) assess the origin and by extension the properties of biodiesel feedstocks; (3) determine insect species from analysis of puparial casings; (4) distinguish between psychoactive plants products; and (5) differentiate between Eucalyptus species. An advantage of the hierarchical clustering approach to processing of the DART-MS derived fingerprint is that it shows both similarities and differences between species based on their chemotypes. Furthermore, full knowledge of the identities of the constituents contained within the small molecule profile of analyzed samples is not required.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Rapid metabolic analysis of Rhodococcus opacus PD630 via parallel 13 C‐metabolite fingerprinting

ABSTRACT For rapid analysis of microbial metabolisms, 13 C‐fingerprinting employs a set of tracers to generate unique labeling patterns in key amino acids that can highlight active pathways. In contrast to rigorous 13 C‐metabolic flux analysis ( 13 C‐MFA), this method aims to provide metabolic insights without expensive flux measurements. Using 13 C‐fingerprinting, we investigated the metabolic pathways in Rhodococcus opacus PD630, a promising biocatalyst for the conversion of lignocellulosic feedstocks into value‐added chemicals. Specifically, seven metabolic insights were gathered as follows: (1) glucose metabolism mainly via the Entner–Doudoroff (ED) pathway; (2) lack of glucose catabolite repression during phenol co‐utilization; (3) simultaneous operation of gluconeogenesis and the ED pathway for the co‐metabolism of glucose and phenol; (4) an active glyoxylate shunt in acetate‐fed culture; (5) high flux through anaplerotic pathways (e.g., malic enzyme and phosphoenolpyruvate carboxylase); (6) presence of alternative glycine synthesis pathway via glycine dehydrogenase; and (7) utilization of preferred exogenous amino acids (e.g., phenylalanine). Additionally, a 13 C‐fingerprinting kit was developed for studying the central metabolism of non‐model microbial species. This low‐cost kit can be used to characterize microbial metabolisms and facilitate the design‐build‐test‐learn cycle during the development of microbial cell factories. Biotechnol. Bioeng. 2016;113: 91–100. © 2015 Wiley Periodicals, Inc.

Hollinshead, Whitney D.↗
DOE OSTI2015

Fourier series of atomic radial distribution functions: A molecular fingerprint for machine learning models of quantum chemical properties

Here we introduce a fingerprint representation of molecules based on a Fourier series of atomic radial distribution functions. This fingerprint is unique (except for chirality), continuous, and differentiable with respect to atomic coordinates and nuclear charges. It is invariant with respect to translation, rotation, and nuclear permutation, and requires no preconceived knowledge about chemical bonding, topology, or electronic orbitals. As such, it meets many important criteria for a good molecular representation, suggesting its usefulness for machine learning models of molecular properties trained across chemical compound space. To assess the performance of this new descriptor, we have trained machine learning models of molecular enthalpies of atomization for training sets with up to 10 k organic molecules, drawn at random from a published set of 134 k organic molecules with an average atomization enthalpy of over 1770 kcal/mol. We validate the descriptor on all remaining molecules of the 134 k set. For a training set of 10 k molecules, the fingerprint descriptor achieves a mean absolute error of 8.0 kcal/mol. This is slightly worse than the performance attained using the Coulomb matrix, another popular alternative, reaching 6.2 kcal/mol for the same training and test sets.

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 OSTI2026

Position-Specific Carbon Isotope Fingerprinting of Fluorinated Organics and Degradation Products

Fluorinated organic compounds are of growing environmental and forensic relevance due to their widespread use in pharmaceuticals, agrochemicals, and consumer products, their environmental persistence, and potential ecological and human health impacts. Elucidating their sources and transformation pathways is therefore a major focus of current research. Stable carbon isotope analysis provides a powerful approach for tracing molecular origins and linking parent compounds to degradation products. Recent isotope measurements have largely relied on mass-spectrometry techniques, which provide only an average isotope ratio across a compound. In this work, we employ a novel nuclear magnetic resonance (NMR) spectroscopy tool to determine position-specific carbon isotope ratios ( 13 C/ 12 C) in organofluorine compounds and their degradation products. This approach enables isotope measurements without combustion or extensive purification and, crucially, resolves ratios at individual carbon positions rather than bulk averages. The resulting intramolecular isotope fingerprints are unique to a molecule’s source. Applied to selected pharmaceuticals and pesticides, these fingerprints allow discrimination of chemically identical compounds. Moreover, we show that the 13 C/ 12 C signature at the fluorinated carbon persists through degradation, demonstrated for lansoprazole and fipronil. The 19 F NMR data produced for the 13 C/ 12 C analyses are also well suited for impurity profiling, providing an additional dimension for fingerprinting fluorinated organics. These findings suggest that position-specific isotope analysis can serve as part of a broader suite of tools for source characterization of organofluorine compounds and their breakdown derivatives, with potential applications in product validation, forensics, and linking these compounds to their breakdown products.

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

Microsecond fingerprint stimulated Raman spectroscopic imaging by ultrafast tuning and spatial-spectral learning

Label-free vibrational imaging by stimulated Raman scattering (SRS) provides unprecedented insight into real-time chemical distributions. Specifically, SRS in the fingerprint region (400–1800 cm -1 ) can resolve multiple chemicals in a complex bio-environment. However, due to the intrinsic weak Raman cross-sections and the lack of ultrafast spectral acquisition schemes with high spectral fidelity, SRS in the fingerprint region is not viable for studying living cells or large-scale tissue samples. Here, we report a fingerprint spectroscopic SRS platform that acquires a distortion-free SRS spectrum at 10 cm -1 spectral resolution within 20 µs using a polygon scanner. Meanwhile, we significantly improve the signal-to-noise ratio by employing a spatial-spectral residual learning network, reaching a level comparable to that with 100 times integration. Collectively, our system enables high-speed vibrational spectroscopic imaging of multiple biomolecules in samples ranging from a single live microbe to a tissue slice.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Likely accelerated weakening of Atlantic overturning circulation emerges in optimal salinity fingerprint

The long-term response of the Atlantic meridional overturning circulation (AMOC) to anthropogenic forcing has been difficult to detect from the short direct measurements available due to strong interdecadal variability. Here, we present observational and modeling evidence for a likely accelerated weakening of the AMOC since the 1980s under the combined forcing of anthropogenic greenhouse gases and aerosols. This likely accelerated AMOC weakening signal can be detected in the AMOC fingerprint of salinity pileup remotely in the South Atlantic, but not in the classic warming hole fingerprint locally in the North Atlantic, because the latter is contaminated by the “noise” of interdecadal variability. Our optimal salinity fingerprint retains much of the signal of the long-term AMOC trend response to anthropogenic forcing, while dynamically filtering out shorter climate variability. Given the ongoing anthropogenic forcing, our study indicates a potential further acceleration of AMOC weakening with associated climate impacts in the coming decades.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Gyrokinetic analysis and simulation of pedestals to identify the culprits for energy losses using ‘fingerprints’

Fusion performance in tokamaks hinges critically on the efficacy of the edge transport barrier (ETB) in suppressing energy losses. The new concept of 'fingerprints' is introduced to identify the instabilities that cause transport losses in the ETBs of many of today's experiments, from among widely posited candidates. Analysis of the gyrokinetic-Maxwell equations and gyrokinetic simulations of experiments reveals that each mode type produces characteristic ratios of transport in the various channels: density, heat, and impurities. This, together with experimental observations of transport in some channel or of the relative size of the driving sources of channels, can identify or determine the dominant modes causing energy transport. In multiple H-mode cases with edge-localized modes that are examined, these fingerprints indicate that magnetohydrodynamic (MHD)-like modes are apparently not the dominant agent of energy transport; rather, this role is played by micro-tearing modes (MTMs) and electron temperature gradient (ETG) modes, and furthermore, possibly by ion temperature gradient/trapped electron modes (ITG/TEM) on JET (Joint European Torus). MHD-like modes may dominate the electron particle losses. Fluctuation frequency can also be a vital means of identification, and is often closely related to the transport fingerprint. The analytical arguments unify and explain previously disparate experimental observations on multiple devices, including DIII-D, JET, and ASDEX-U. Detailed simulations of two DIII-D ETBs also demonstrate and corroborate this.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Genomic fingerprints of the world’s soil ecosystems

Despite the explosion of soil metagenomic data, we lack a synthesized understanding of patterns in the distribution and functions of soil microorganisms. These patterns are critical to predictions of soil microbiome responses to climate change and resulting feedbacks that regulate greenhouse gas release from soils. To address this gap, we assay 1,512 manually curated soil metagenomes using complementary annotation databases, read-based taxonomy, and machine learning to extract multidimensional genomic fingerprints of global soil microbiomes. Our objective is to uncover novel biogeographical patterns of soil microbiomes across environmental factors and ecological biomes with high molecular resolution. We reveal shifts in the potential for (i) microbial nutrient acquisition across pH gradients; (ii) stress-, transport-, and redox-based processes across changes in soil bulk density; and (iii) greenhouse gas emissions across biomes. We also use an unsupervised approach to reveal a collection of soils with distinct genomic signatures, characterized by coordinated changes in soil organic carbon, nitrogen, and cation exchange capacity and in bulk density and clay content that may ultimately reflect soil environments with high microbial activity. Genomic fingerprints for these soils highlight the importance of resource scavenging, plant-microbe interactions, fungi, and heterotrophic metabolisms. Across all analyses, we observed phylogenetic coherence in soil microbiomes—more closely related microorganisms tended to move congruently in response to soil factors. Collectively, the genomic fingerprints uncovered here present a basis for global patterns in the microbial mechanisms underlying soil biogeochemistry and help beget tractable microbial reaction networks for incorporation into process-based models of soil carbon and nutrient cycling.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Frequency Emitter Geolocation Using Signal Strength Fingerprinting Informed By 3D Propagation Modeling

This work focuses on the problem of RF geolocation in complex multipath environments. Using 3D electromagnetic propagation modeling to characterize environments of interest will enable more accurate RF geolocation. Specifically, a path-loss radio map can be generated in simulation for use in received signal strength indicators (RSSI) fingerprinting, or pattern matching. RSSI fingerprinting is an example of data-based method that takes site specific information into account which should allow for better performance than other model-based methods that use a generalized model of electromagnetic propagation. This modeling capability will also be used to evaluate the relative performance of RSSI fingerprinting, pathloss model based RSSI methods such as differential received signal strength circles (DRSS), RSSI joint gaussian estimation, and time-difference of arrival (TDOA). New methods using this simulation derived electromagnetic characterization could improve the efficacy of currently deployed and future RF spectral monitoring solutions. Wireless InSite developed by Remcom is used as the simulation tool of choice in this work. An indoor location is simulated with a grid of fixed receivers and a grid of transmit locations. Using the output of the Wireless InSite simulation the response from a given transmit location to a given receive location can be generated. During the first year of the project various geolocation methods evaluated on purely synthetic, but realistic, data. The second year focused on testing and validating the efficacy of simulation informed RF geolocation using two physical testbeds. This work has shown that data-based approaches are more accurate than model-based ones at the expensive of requiring measured or simulated site-specific training data.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Dual-Polarization Radar Fingerprints of Precipitation Physics: A Review

This article reviews how precipitation microphysics processes are observed in dual-polarization radar observations. These so-called “fingerprints” of precipitation processes are observed as vertical gradients in radar observables. Fingerprints of rain processes are first reviewed, followed by processes involving snow and ice. Then, emerging research is introduced, which includes more quantitative analysis of these dual-polarization radar fingerprints to obtain microphysics model parameters and microphysical process rates. New results based on a detailed rain shaft bin microphysical model are presented, and we conclude with an outlook of potentially fruitful future research directions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Decoding THz‐Driven Dynamic Fingerprints of Ferroelectric Nanotwin Networks

Ultrafast polarization dynamics in ferroelectrics are of considerable interest for high-speed tunable dielectrics and electro-optics. Extended domain wall networks formed in ferroelectric twin nanodomains can support collective dynamics in the terahertz regime but require techniques that track polarization and strain evolution driven by ultrafast stimulus. Here, we use multi-modal probing of THz-pulse-driven excitations in PbTiO 3 /SrTiO 3 superlattices by combining X-ray free electron laser measurements that directly tracks lattice changes, with optical second harmonic generation that tracks the electronic potential coupled with the lattice potential. Dynamical phase-field modeling enables fingerprinting of these collective modes as superpositions of domain “breathing” through wall oscillations and polarization “rotations” with still walls. Ultrafast domain wall motion at 0.1–0.5 THz is observed at practical fields of 100 kV/cm with wall velocities of >4000 m/s, approaching typical speed of sound in PbTiO 3 . A unique “charging” mode is discovered that can electrically charge and discharge domain walls on ∼4 ps time scale thus dynamically tuning wall conductivity. Integrated experimental and theoretical fingerprinting of the dynamical landscape presented here enables ultrafast control of ferroics for high-speed microelectronics and optical applications.

THz dynamics↗
DOE OSTI2016

Multiple Decay Mechanisms and 2D-UV Spectroscopic Fingerprints of Singlet Excited Solvated Adenine-Uracil Monophosphate

The decay channels of singlet excited adenine uracil monophosphate (ApU) in water are studied with CASPT2//CASSCF:MM potential energy calculations and simulation of the 2D-UV spectroscopic fingerprints with the aim of elucidating the role of the different electronic states of the stacked conformer in the excited state dynamics. The adenine 1 L a state can decay without a barrier to a conical intersection with the ground state. In contrast, the adenine 1 L b and uracil S(U) states have minima that are separated from the intersections by sizeable barriers. Depending on the backbone conformation, the CT state can undergo inter-base hydrogen transfer and decay to the ground state through a conical intersection, or it can yield a long-lived minimum stabilized by a hydrogen bond between the two ribose rings. This suggests that the 1 L b , S(U) and CT states of the stacked conformer may all contribute to the experimental lifetimes of 18 and 240 ps. We have also simulated the time evolution of the 2D-UV spectra and provide the specific fingerprint of each species in a recommended probe window between 25 000 and 38 000 cm -1 in which decongested, clearly distinguishable spectra can be obtained. This is expected to allow the mechanistic scenarios to be discerned in the near future with the help of the corresponding experiments. Our results reveal the complexity of the photophysics of the relatively small ApU system, and the potential of 2D-UV spectroscopy to disentangle the photophysics of multichromophoric systems.

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

Cryogenic Vibrational Spectroscopy Provides Unique Fingerprints for Glycan Identification

The structural characterization of glycans by mass spectrometry is particularly challenging. This is because of the high degree of isomerism in which glycans of the same mass can differ in their stereochemistry, attachment points, and degree of branching. Here we show that the addition of cryogenic vibrational spectroscopy to mass and mobility measurements allows one to uniquely identify and characterize these complex biopolymers. We investigate six disaccharide isomers that differ in their stereochemistry, attachment point of the glycosidic bond, and monosaccharide content, and demonstrate that we can identify each one unambiguously. Even disaccharides that differ by a single stereogenic center or in the monosaccharide sequence order show distinct vibrational fingerprints that would clearly allow their identification in a mixture, which is not possible by ion mobility spectrometry/mass spectrometry alone. Moreover, this technique can be applied to larger glycans, which we demonstrate by distinguishing isomeric branched and linear pentasaccharides. The creation of a database containing mass, collision cross section, and vibrational fingerprint measurements for glycan standards should allow unambiguous identification and characterization of these biopolymers in mixtures, providing an enabling technology for all fields of glycoscience. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Cluster-Graph Fingerprinting: A Framework for Quantitative Analysis of Machine-Learned Interatomic Model Training and Simulation Data

Machine-learned interatomic models represent a significant advancement in simulation methods, extending the predictive ability of first-principles methods to previously inaccessible length and time scales. However, the data-driven nature of these models can lead to difficult-to-detect errors that can compromise prediction accuracy. To address this challenge, we introduce a novel fingerprinting approach based on the Chebyshev Interaction Model for Efficient Simulation (ChIMES) ML-IAM graph-based descriptor. Our strategy enables efficient and statistically rigorous analysis of system configurations used in ML-IAM training and those generated by their application, e.g., in molecular dynamics simulations. We demonstrate that these fingerprints can effectively assess novelty of a configuration relative to an existing data set and determine dissimilarity among individual configurations, which are two key tasks in workflows for active learning-based ML-IAM training, data set curation, and on-the-fly uncertainty quantification.

36 MATERIALS SCIENCE↗