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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Vibronic fingerprint of singlet fission in hexacene

Singlet fission has the great potential to overcome the Shockley–Queisser thermodynamic limit and thus promotes solar power conversion efficiency. However, the current limited understandings of detailed singlet fission mechanisms hinder a further improved design of versatile singlet fission materials. In the present study, we combined ultrafast transient infrared spectroscopy with ab initio calculations to elucidate the roles played by the vibrational normal modes in the process of singlet fission for hexacene. Our transient infrared experiments revealed three groups of vibrational modes that are prominent in vibronic coupling upon photoexcitation. Through our computational study, those normal modes with notable Franck-Condon shifts have been classified as ring-twisting modes near 1300.0 cm−1, ring-stretching modes near 1600.0 cm−1, and ring-scissoring modes near 1700.0 cm−1. Experimentally, a ring-stretching mode near 1620.0 cm−1 exhibits a significant blue-shift of 4.0 cm−1 during singlet fission, which reaction rate turns out to be 0.59 ± 0.07 ps. More interestingly, the blue-shifted mode was also identified by our functional mode singlet fission theory as the primary driving mode for singlet fission, suggesting the importance of vibronic coupling when a correlated triplet pair of hexacene is directly converted from its first excited state singlet exciton. Our findings indicate that the ultrafast transient infrared spectroscopy, in conjunction with the nonadiabatic transition theory, is a powerful tool to probe the vibronic fingerprint of singlet fission.

Deng, Gang-Hua↗
DOE OSTI2020

Molecular polarizabilities as fingerprints of perturbations to water by ions and confinement

Perturbations to water, both by ions and confining media, have been the focus of numerous experimental and theoretical studies. Yet, several open questions remain, including the extent to which such perturbations modify the structural and dielectric properties of the liquid. Here, we present a first-principles molecular dynamics study of alkali cations in water (Li + , Na + , and K + ) as well as of water and LiCl and KCl solutions under confinement within carbon nanotubes (CNTs) of small diameter (1.1-1.5 nm). Our simulations support the view that the water structure is only modified locally in the presence of cations. We found that molecular polarizabilities are fingerprints of hydrogen bonding modifications, which occur at most up to the second solvation shell for all cations in bulk water. Under confinement, we found that the overall value of the molecular polarizability of water molecules near the surface is determined by the balance of two effects, which are quantitatively different in CNTs of different radii: the presence of broken hydrogen bonds at the surface leads to a decrease in the polarizabilities of water molecules, while the interaction with the CNT enhances polarizabilities. Interestingly, the reduction in dipole moments of interfacial water molecules under confinement is instead driven only by changes in the water structure and not by interfacial interactions. As expected, confinement effects on water molecular polarizabilities and dipole moments are more pronounced in the case of the 1.1 nm CNT.

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

Elucidating the photodissociation fingerprint and quantifying the determination of organic hydroperoxides in gas-phase autoxidation

Hydroperoxides are formed in the atmospheric oxidation of volatile organic compounds, in the combustion autoxidation of fuel, in the cold environment of the interstellar medium, and also in some catalytic reactions. They play crucial roles in the formation and aging of secondary organic aerosols and in fuel autoignition. However, the concentration of organic hydroperoxides is seldom measured, and typical estimates have large uncertainties. In this work, we developed a mild and environmental-friendly method for the synthesis of alkyl hydroperoxides (ROOH) with various structures, and we systematically measured the absolute photoionization cross-sections (PICSs) of the ROOHs using synchrotron vacuum ultraviolet-photoionization mass spectrometry (SVUV-PIMS). A chemical titration method was combined with an SVUV-PIMS measurement to obtain the PICS of 4-hydroperoxy-2-pentanone, a typical molecule for combustion and atmospheric autoxidation ketohydroperoxides (KHPs). We found that organic hydroperoxide cations are largely dissociated by loss of OOH. This fingerprint was used for the identification and accurate quantification of the organic peroxides, and it can therefore be used to improve models for autoxidation chemistry. The synthesis method and photoionization dataset for organic hydroperoxides are useful for studying the chemistry of hydroperoxides and the reaction kinetics of the hydroperoxy radicals and for developing and evaluating kinetic models for the atmospheric autoxidation and combustion autoxidation of the organic compounds.

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

Barkhausen noise as an intrinsic fingerprint for ferromagnetic components

Here in this work, the suitability of magnetic Barkhausen noise as an intrinsic fingerprint of ferromagnetic components is determined. This technique has potential for this application because it is based inherently on the near surface microstructural features of ferromagnetic materials. All materials typically display some variation in their microstructure simply as a result of the manufacturing process (rolling, heat treating, welding, grinding), thus providing the potential that Barkhausen noise measurements between nominally similar components will be unique. In this work, we demonstrate that Barkhausen noise measurements are both repeatable in time for a single sample made from a ferromagnetic material, and unique across a number of instances of nominally similar samples. The results of this work have profound implications in a variety of applications in forensics and physical security. For example, consider the fabrication of the next generation of tamper-evident containers and devices using conventional processes for steel. In addition, since Barkhausen noise is sensitive to changes in microstructures due to grinding and welding, these measurements can be used to detect clandestine repairs and tampering. Finally, because the method inherently results in a time series measurement at each point on a sample, it is expected to have far higher dimensionality than physically similar eddy current measurement. However, the higher dimensionality of Barkhausen measurements suggest that they should be harder to counterfeit than eddy current measurements.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Fingerprints of external forcings on Sahel rainfall: aerosols, greenhouse gases, and model-observation discrepancies

Over the 20th and 21st centuries, both anthropogenic greenhouse gas increases and changes in anthropogenic aerosols have affected rainfall in the Sahel. Using multiple characteristics of Sahel precipitation, we construct a multivariate fingerprint that allows us to distinguish between the model-predicted responses to greenhouse gases and anthropogenic aerosols. Models project the emergence of a detectable signal of aerosol forcing in the middle of the 20th century and a detectable signal of greenhouse gas forcing at the beginning of the 21st. However, the signals of both aerosol and greenhouse gas forcing in observations emerge earlier and are stronger than in the models, far stronger in the case of aerosols. The similarity between the response to aerosol forcing and the leading mode of internal variability makes it difficult to attribute this model-observation discrepancy to errors in the forcing, errors in the forced response, model inability to capture the amplitude of internal variability, or some combination of these. For greenhouse gases, however, the forced response is distinct from internal variability as estimated by models, and the observations are largely commensurate with the model projections.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Ecosystem and soil respiration radiocarbon detects old carbon release as a fingerprint of warming and permafrost destabilization with climate change

The permafrost region has accumulated organic carbon in cold and waterlogged soils over thousands of years and now contains three times as much carbon as the atmosphere. Global warming is degrading permafrost with the potential to accelerate climate change as increased microbial decomposition releases soil carbon as greenhouse gases. A 19-year time series of soil and ecosystem respiration radiocarbon from Alaska provides long-term insight into changing permafrost soil carbon dynamics in a warmer world. Nine per cent of ecosystem respiration and 23% of soil respiration observations had radiocarbon values more than 50‰ lower than the atmospheric value. Furthermore, the overall trend of ecosystem and soil respiration radiocarbon values through time decreased more than atmospheric radiocarbon values did, indicating that old carbon degradation was enhanced. Boosted regression tree analyses showed that temperature and moisture environmental variables had the largest relative influence on lower radiocarbon values. This suggested that old carbon degradation was controlled by warming/permafrost thaw and soil drying together, as waterlogged soil conditions could protect soil carbon from microbial decomposition even when thawed. Overall, changing conditions increasingly favoured the release of old carbon, which is a definitive fingerprint of an accelerating feedback to climate change as a consequence of warming and permafrost destabilization.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Magnetization dynamics fingerprints of an excitonic condensate t 2 g 4 magnet

The competition between spin-orbit coupling (SOC) λ and electron-electron interaction U leads to a plethora of novel states of matter, extensively studied in the context of t 2 g 4 and t 2 g 5 materials, such as ruthenates and iridates. Excitonic magnets—the antiferromagnetic state of bounded electron-hole pairs-are prominent examples of phenomena driven by those competing energy scales. Interestingly, recent theoretical studies predicted that excitonic magnets can be found in the ground state of SOC t 2 g 4 Hubbard models. Here we present a detailed computational study of the magnetic excitations in that excitonic magnet, employing one-dimensional chains (via density matrix renormalization group) and small two-dimensional clusters (via Lanczos). Specifically, first we show that the low-energy spectrum is dominated by a dispersive (acoustic) magnonic mode, with extra features arising from the λ = 0 state in the phase diagram. Second, and more importantly, we found a novel magnetic excitation forming a high-energy optical mode with the highest intensity at wave-vector q → 0 . In the excitonic condensation regime at large U , we also have found a novel high-energy π mode composed solely of orbital excitations. Overall, these features do not appear all together in any of the neighboring states in the phase diagram and thus constitute unique fingerprints of the t 2 g 4 excitonic magnet, of importance in the analysis of neutron and resonant inelastic x-ray scattering experiments.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Electronic fingerprints of Cr and V dopants in the topological insulator Sb 2 Te 3

By combining scanning tunneling microscopy/spectroscopy and first-principles calculations, we systematically study the local electronic states of magnetic dopants V and Cr in the topological insulator (TI) Sb 2 Te 3 . Spectroscopic imaging shows diverse local defect states between Cr and V, which agree with our first-principle calculations. The unique spectroscopic features of V and Cr dopants provide electronic fingerprints for the codoped magnetic TI samples with the enhanced quantum anomalous Hall effect. Here our results also facilitate the exploration of the underlying mechanism of the enhanced quantum anomalous Hall temperature in Cr/V codoped TIs.

36 MATERIALS SCIENCE↗
DOE OSTI2020

solar-fingerprinting

An algorithm for creating a low-dimensional representation (fingerprint) of daily photovoltaic solar power generation signals.

Meyers, Bennet↗
DOE OSTI2025

Vedizar Fingerprinter

SAND2025-03289O Vedizar Fingerprinter simplifies the process of identifying devices on a network by analyzing traffic data. It uses a unique library to recognize different devices, making it easier for users to understand what is happening on their networks. This software is ideal for IT and operational technology environments, helping organizations monitor their networks effectively. By saving results in a database, it allows for easy access and review of device information. Users can enhance their network security and optimize performance without needing specialized hardware or technical expertise. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Jacobellis, John [Sandia National Lab. (SNL-CA), L↗
DOE OSTI2024

Beyond PCA: Additional Dimension Reduction Techniques to Consider in the Development of Climate Fingerprints

Abstract Dimension reduction techniques are an essential part of the climate analyst’s toolkit. Due to the enormous scale of climate data, dimension reduction methods are used to identify major patterns of variability within climate dynamics, to create compelling and informative visualizations, and to quantify major named modes such as El Niño–Southern Oscillation. Principal components analysis (PCA), also known as the method of empirical orthogonal functions (EOFs), is the most commonly used form of dimension reduction, characterized by a remarkable confluence of attractive mathematical, statistical, and computational properties. Despite its ubiquity, PCA suffers from several difficulties relevant to climate science: high computational burden with large datasets, decreased statistical accuracy in high dimensions, and difficulties comparing across multiple datasets. In this paper, we introduce several variants of PCA that are likely to be of use in climate sciences and address these problems. Specifically, we introduce non-negative , sparse , and tensor PCA and demonstrate how each approach provides superior pattern recognition in climate data. We also discuss approaches to comparing PCA-family results within and across datasets in a domain-relevant manner. We demonstrate these approaches through an analysis of several runs of the E3SM climate model from 1991 to 1995, focusing on the simulated response to the Mt. Pinatubo eruption; our findings are consistent with a recently identified stratospheric warming fingerprint associated with this type of stratospheric aerosol injection.

Weylandt, Michael↗
DOE OSTI2020

Comprehensive Chemical Fingerprinting by Multidimensional GC and Supervised Machine Learning

This project leverages advances in machine learning based data analysis techniques and untargeted omic analytical methods to progress nuclear nonproliferation technologies beyond current capabilities. The developed approaches can be used to identify and detect complex chemical fingerprints of facilities of interest. These techniques have been developed for fields such as metabolomics and genomics but have not been applied to nuclear nonproliferation applications. Adaptation of these techniques for volatile organic compound analysis has far reaching application within the scientific community including environmental chemistry, atmospheric physics, and climate sciences.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Rheo-Structural Spectroscopy: Fingerprinting the In Situ Response of Fluids to Arbitrary Flow Fields

The objectives of this project were to develop new sample environments, measurement methodologies and associated modeling tools for characterizing the structural response to arbitrarily complex processing flows using small angle scattering, and to apply these new tools for understanding the fundamental physics governing the structuring of anisotropic particulate and polymeric materials under flow histories and conditions relevant to industrial processing flows. The research resulted in the development and implementation of a new sample environment, the fluidic four roll mill (FFoRM), for in situ small angle neutron and X-ray scattering (SANS/SAXS) measurements. These measurements are capable of generating large data sets that “fingerprint” how a complex fluid responds to a wide range of flow histories involving time variations in deformation type and rate. New modeling tools were developed to extract detailed microstructural information from such data sets, including orientation distribution functions and interparticle correlation functions, as well as reduced-order parametric descriptors of these high-dimensional functions that can be used to readily map, visualize and interpret a fluid’s structural response to its flow history. These new tools were applied to a range of model materials involving elongated particle suspensions in order to provide new insights into the physics of how flow couples with orientational and structural order in complex flows, particularly under non-dilute conditions for which no accurate theories currently exist. Using these investigations, we elucidated a number of new insights into the fundamental phenomena driving such process-structure-property relationships. These findings provide guidance for the further development of rheological models, and ultimately can inform the rational and model-based design of flow processes to achieve optimized orientational ordering that is key to the properties and function of a wide range of energy-relevant materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Comprehensive Chemical Fingerprinting by Multidimensional GC and Supervised Machine Learning

This project leveraged advances in machine learning based data analysis techniques and untargeted analytical methods for organic analysis to progress nuclear nonproliferation technologies beyond current capabilities. The developed approaches can be used to detect and identify complex chemical fingerprints of facilities of interest. These techniques have been developed for fields such as metabolomics and genomics but have not been applied to nuclear nonproliferation applications. Adaptation of these techniques for volatile organic compound analysis has far reaching application within the scientific community including environmental chemistry, atmospheric physics, and climate sciences.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2025

Tabletop soft x-ray absorption spectroscopy for molecular fingerprinting

For applications related to nuclear security, safeguards, and nonproliferation, it is often critical to know the molecular compositions of lanthanide- and actinide-containing samples. Spectroscopy is a widely used tool that looks at the interaction between light and matter: Different species absorb or emit light at unique wavelengths which act as signatures. However, there is a limited number of tools that can achieve high-sensitivity, accurate measurements of lanthanide and actinide molecular compositions. Candidate methods include mass spectrometry, which usually destroys at least part of the sample and requires complicated stoichiometry to guess the original sample’s molecular compositions; optical spectroscopies, which have great atomic but limited molecular sensitivities or other drawbacks which make sensing molecules difficult like limited light sources or strong absorption in the atmosphere; and nuclear spectroscopies (gamma, neutron) which also have limited sources and long (>minute) collection times. As such, the purpose of our research is to develop a new tool to better distinguish between subtle differences in molecules containing lanthanides and actinides. Soft x-ray spectroscopy is sensitive to molecular form and is minimally intrusive/nondestructive to the sample. However, soft x-ray light with sufficient brightness for spectroscopy is typically limited to user-facilities like synchrotrons or free electron lasers, where beamtimes are competitive, and work with radiological materials may be difficult or entirely prohibited. To overcome this issue, our Team has developed a custom tabletop laser-driven, soft x-ray light source which employs high harmonic generation (HHG). Soft x-ray spectroscopy can distinguish between subtly different molecules, in the spectral range which we need to study these heavy elements. A tabletop system provides an effective and affordable tool to find both the elemental and chemical specificity of lanthanide and samples. Creating a light source in the soft x-ray spectrum is difficult because these wavelengths in the range 5-20 nm (20-350 eV photon energies) only penetrate several 100s of nm in most solid materials and only reflect well in shallow, grazing incident angles. The results are applicable to nuclear forensics, because molecular fingerprinting of lanthanide and actinide samples can be used to back out the origin and processing method of nuclear materials (Skrodzki, et al.).

36 MATERIALS SCIENCE↗
DOE OSTI2025

Bioindicator “fingerprints” of methane-emitting thermokarst features in Alaskan soils

Permafrost thaw increases the bioavailability of ancient organic matter, facilitating microbial metabolism of volatile organic compounds (VOCs), carbon dioxide, and methane (CH 4 ). The formation of thermokarst (thaw) lakes in icy, organic-rich Yedoma permafrost leads to high CH 4 emissions, and subsurface microbes that have the potential to be biogeochemical drivers of organic carbon turnover in these systems. However, to better characterize and quantify rates of permafrost changes, methods that further clarify the relationship between subsurface biogeochemical processes and microbial dynamics are needed. In this study, we investigated four sites (two well-drained thermokarst mounds, a drained thermokarst lake, and the terrestrial margin of a recently formed thermokarst lake) to determine whether biogenic VOCs (1) can be effectively collected during winter, and (2) whether winter sampling provides more biologically significant VOCs correlated with subsurface microbial metabolic potential. During the cold season (March 2023), we drilled boreholes at the four sites and collected cores to simultaneously characterize microbial populations and captured VOCs. VOC analysis of these sites revealed “fingerprints” that were distinct and unique to each site. Total VOCs from the boreholes included > 400 unique VOC features, including > 40 potentially biogenic VOCs related to microbial metabolism. Subsurface microbial community composition was distinct across sites; for example, methanogenic archaea were far more abundant at the thermokarst site characterized by high annual CH 4 emissions. The results obtained from this method strongly suggest that ∼10% of VOCs are potentially biogenic, and that biogenic VOCs can be mapped to subsurface microbial metabolisms. By better revealing the relationship between subsurface biogeochemical processes and microbial dynamics, this work advances our ability to monitor and predict subsurface carbon turnover in Arctic soils.

anaerobic degradation↗
NASA NTRS1980

FBI fingerprint identification automation study. AIDS 3 evaluation report. Volume 1: Compendium

The primary features of the overall study are encompassed and an evaluation of an automation system is presented. Objectives of the study are described, methods of evaluation are summarized and conclusions about the system's feasibility are presented. Also included is a brief history of fingerprint automation activities within the FBI, the organization of the FBI, a bibliography of documents and records, a data dictionary and a reference set of all of the transparencies presented throughout the study.

Mulhall, B. D. L.↗
NASA NTRS1980

FBI fingerprint identification automation study. AIDS 3 evaluation report. Volume 4: Economic feasibility

The results of the economic analysis of the AIDS 3 system design are presented. AIDS 3 evaluated a set of economic feasibility measures including life cycle cost, implementation cost, annual operating expenditures and annual capital expenditures. The economic feasibility of AIDS 3 was determined by comparing the evaluated measures with the same measures, where applicable, evaluated for the current system. A set of future work load scenarios was constructed using JPL's environmental evaluation study of the fingerprint identification system. AIDS 3 and the current system were evaluated for each of the economic feasibility measures for each of the work load scenarios. They were compared for a set of performance measures, including response time and accuracy, and for a set of cost/benefit ratios, including cost per transaction and cost per technical search. Benefit measures related to the economic feasibility of the system are also presented, including the required number of employees and the required employee skill mix.

Mulhall, B. D. L.↗