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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Detection of CdSe quantum dot photoluminescence for security label on paper

CdSe quantum dot has great potential in various applications especially for emitting devices. One example potential application of CdSe quantum dot is security label for anti-counterfeiting. In this work, we present a practical approach of security label on paper using one and two colors of colloidal CdSe quantum dot, which is used as stamping ink on various types of paper. Under ambient condition, quantum dot is almost invisible. The quantum dot security label can be revealed by detecting emission of quantum dot using photoluminescence and cnc machine. The recorded quantum dot emission intensity is then analyzed using home-made program to reveal quantum dot pattern stamp having the word ’RAHASIA’. We found that security label using quantum dot works well on several types of paper. The quantum dot patterns can survive several days and further treatment is required to protect the quantum dot. Oxidation of quantum dot that occurred during this experiment reduced the emission intensity of quantum dot patterns.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Associations of Leaf Spectra with Genetic and Phylogenetic Variation in Oaks: Prospects for Remote Detection of Biodiversity

Species and phylogenetic lineages have evolved to differ in the way that they acquire and deploy resources, with consequences for their physiological, chemical and structural attributes, many of which can be detected using spectral reflectance form leaves. Recent technological advances for assessing optical properties of plants offer opportunities to detect functional traits of organisms and differentiate levels of biological organization across the tree of life. We connect leaf-level full range spectral data (400–2400 nm) of leaves to the hierarchical organization of plant diversity within the oak genus (Quercus) using field and greenhouse experiments in which environmental factors and plant age are controlled. We show that spectral data significantly differentiate populations within a species and that spectral similarity is significantly associated with phylogenetic similarity among species. Furthermore, we show that hyperspectral information allows more accurate classification of taxa than spectrally-derived traits, which by definition are of lower dimensionality. Finally, model accuracy increases at higher levels in the hierarchical organization of plant diversity, such that we are able to better distinguish clades than species or populations. This pattern supports an evolutionary explanation for the degree of optical differentiation among plants and demonstrates potential for remote detection of genetic and phylogenetic diversity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Utilizing Genetic Programming to Identify Failures in ICS Networks

Previously, researchers have attempted to apply machine learning techniques to network anomaly detection problems. Due to the staggering amount of variety that can occur in normal networks, the results have often been underwhelming. These challenges are far less pronounced when considering industrial control system (ICS) networks. The recurrent nature of these networks results in less noise and more consistent patterns for a machine learning algorithm to recognize. Here, we propose a method of evolving decision trees through genetic programming (GP) in order to detect network anomalies, such as device outages. Our approach extracts over a dozen features from network packet captures and netflows, normalizes them, and relates them in decision trees using fuzzy logic operators. Furthermore, the trees were used to detect three specific network events from three different points on the network across a statistically significant number of runs and achieved 100% accuracy on five of the nine experiments. When the trees attempted to detect more challenging events at points of presence further from the occurrence, the accuracy averaged to above 98%. Finally, using our method, all of the evolutionary cycles of the GP algorithm are computed a-priori, allowing the best resultant trees to be deployed as semi-real-time sensors with little overhead.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Single-crystalline Bi{sub 2}Sr{sub 2}CaCu{sub 2}O{sub 8+x} detectors for direct detection of microwave radiation

We test radiation detectors made from single-crystalline Bi{sub 2}Sr{sub 2}CaCu{sub 2}O{sub 8+x} flakes put on oxidized Si substrates. The 100-nm-thick flakes are lithographically patterned into 4×12 μm{sup 2} large rectangles embedded in thin-film log-spiral antennas. The SiO{sub 2} layer weakens the thermal link between the flakes and the bath. Two modes of radiation detection have been observed. For a bolometric type of sensors a responsivity of ∼300 V/W and a noise equivalent power of 30 nW/√(Hz) has been deduced at 70 K. Much more sensitive is the non-bolometric device showing characteristics similar to a Golay-type detector while being at least a thousand times faster. Making smaller (sub-μm) structures is expected to significantly improve the performance of these devices and makes them very competitive among other microwave and terahertz detectors.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Extracellular DNA Alters Detection of Subtle Bacterial Responses to Soil Rewetting

Microbial communities are often characterized using DNA-based sequencing, but these approaches also capture extracellular DNA (exDNA) released from dead cells, potentially altering inference about microbial responses to environmental change. This may be especially important during pulse disturbances, such as soil drying–rewetting, which can increase microbial mortality and transient necromass pools. We assessed whether exDNA altered inference about bacterial responses to drying–rewetting (an 80 mm simulated rainfall event following a 28-day drought) in conventionally tilled corn and perennial switchgrass soils. We quantified bacterial abundance (16 S rRNA gene copies), alpha diversity, and community composition in paired soil samples with exDNA included (+ exDNA) and in samples treated with propidium monoazide (PMAxx) to reduce amplification of exDNA (− exDNA). At our level of replication (n = 4), PMAxx treatment did not significantly alter overall temporal response patterns (i.e., no significant main effect of DNA treatment or DNA × time interaction). However, PMAxx treatment increased sensitivity to detect some pairwise temporal changes in bacterial abundance and community composition in corn soils following rewetting. exDNA pools were proportionally highest immediately after rewetting in corn soils, suggesting transient extracellular DNA may contribute to masking during disturbance recovery. In contrast, PMAxx treatment had comparatively small effects in switchgrass soils, which exhibited weaker temporal responses overall. Inclusion of exDNA also changed which taxa appeared most responsive to rewetting. Together, our results suggest that exDNA does not uniformly bias soil microbial inference, but may reduce detectability of subtle disturbance-driven shifts in certain soils. Future studies should advance knowledge of microbial turnover and necromass dynamics, particularly using multiple complementary methods, to help predict when exDNA is most likely to influence ecological inference.

drying-rewetting↗
DOE OSTI2014

Thermal stability of hexagonal OsB{sub 2}

The synthesis of novel hexagonal ReB{sub 2}-type OsB{sub 2} ceramic powder was performed by high energy ball milling of elemental Os and B powders. Two different sources of B powder have been used for this mechanochemical synthesis. One B powder consisted of a mixture of amorphous and crystalline phases and a mixture of {sup 10}B and {sup 11}B isotopes with a fine particle size, while another B powder was a purely crystalline (rhombohedral) material consisting of enriched {sup 11}B isotope with coarse particle size. The same Os powder was used for the synthesis in both cases. It was established that, in the first case, the hexagonal OsB{sub 2} phase was the main product of synthesis with a small quantity of Os{sub 2}B{sub 3} phase present after synthesis as an intermediate product. In the second case, where coarse crystalline {sup 11}B powder was used as a raw material, only Os{sub 2}B{sub 3} boride was synthesized mechanochemically. The thermal stability of hexagonal OsB{sub 2} powder was studied by heating under argon up to 876 °C and cooling in vacuo down to −225 °C. During the heating, the sacrificial reaction 2OsB{sub 2}+3O{sub 2}→2Os+2B{sub 2}O{sub 3} took place due to presence of O{sub 2}/water vapor molecules in the heating chamber, resulting in the oxidation of B atoms and formation of B{sub 2}O{sub 3} and precipitation of Os metal out of the OsB{sub 2} lattice. As a result of such phase changes during heating, the lattice parameters of hexagonal OsB{sub 2} changed significantly. The shrinkage of the a lattice parameter was recorded in 276–426 °C temperature range upon heating, which was attributed to the removal of B atoms from the OsB{sub 2} lattice due to oxidation followed by the precipitation of Os atoms and formation of Os metal. While significant structural changes occurred upon heating due to presence of O{sub 2}, the hexagonal OsB{sub 2} ceramic demonstrated good phase stability upon cooling in vacuo with linear shrinkage of the lattice parameters and no phase changes detected during cooling. - Graphical abstract: The in situ high temperature XRD contour plot (A) and XRD patterns (B) of h-OsB{sub 2} upon heating and cooling under an argon atmosphere. - Highlights: • Different boron sources were compared for the synthesis of h-OsB{sub 2}. • The phase stability and thermal behavior of h-OsB{sub 2} were studied by in situ XRD. • Shrinkage of the a lattice parameter was observed from 276 °C to 426 °C upon heating. • Oxidation of OsB{sub 2} produced B vacancies led to the shrinkage of a lattice parameter.

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

A Statistical Framework for Evaluating Rain Microphysics in Model Simulations and Disdrometer Observations

Abstract Statistical analyses of a large disdrometer data set and a diverse set of model simulations for convection using the Regional Atmospheric Modeling System were conducted, with the mutual goal of providing insights into precipitation formation and microphysical processes. We demonstrate that a two‐moment bulk microphysical model successfully captures the dominant observed modes of variability in rainfall related to rainfall intensity and raindrop size distributions. The model reproduced the general distribution of observed precipitation groups (PGs) derived from Principal Component Analysis. The multi‐variable analysis also uncovered some shortcomings in the model as well as limitations of the disdrometer data. The model solutions were constrained in their predicted drop size distributions (DSDs) due to the fixed DSD parameters assumed in a two‐moment microphysics scheme. A case study from the Mid‐latitude Continental Clouds and Convection Experiment field project demonstrated how model results can be used to contextualize the disdrometer observations which are limited in sample size, spatial coherence, and detection of small drops and low drop concentrations. The case study also showed that the spatial patterns of the statistically derived PGs revealed by the model are consistent with the hypothesized microphysical processes that determine surface rain DSDs. This work demonstrates how leveraging the strengths of observations and models together can improve our understanding and representation of rain microphysical processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Si/SiGe QuBus for single electron information-processing devices with memory and micron-scale connectivity function

The connectivity within single carrier information-processing devices requires transport and storage of single charge quanta. Single electrons have been adiabatically transported while confined to a moving quantum dot in short, all-electrical Si/SiGe shuttle device, called quantum bus (QuBus). Here we show a QuBus spanning a length of 10 μm and operated by only six simply-tunable voltage pulses. We introduce a characterization method, called shuttle-tomography, to benchmark the potential imperfections and local shuttle-fidelity of the QuBus. The fidelity of the single-electron shuttle across the full device and back (a total distance of 19 μm) is (99.7 ± 0.3) %. Using the QuBus, we position and detect up to 34 electrons and initialize a register of 34 quantum dots with arbitrarily chosen patterns of zero and single-electrons. The simple operation signals, compatibility with industry fabrication and low spin-environment-interaction in 28 Si/SiGe, promises long-range spin-conserving transport of spin qubits for quantum connectivity in quantum computing architectures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Personalized Tucker Decomposition: Modeling Commonality and Peculiarity on Tensor Data

In this paper, we propose a personalized Tucker decomposition (perTucker) to address the limitations of traditional tensor decomposition methods in capturing heterogeneity across different datasets. perTucker decomposes tensor data into shared global components and personalized local components. We introduce an order orthogonality assumption and develop a proximal gradient regularized block coordinate descent algorithm guaranteed to converge to a stationary point. The unique and common representations learned by perTucker reveal intrinsic statistical patterns in data and provide valuable information for a wide range of downstream analytics, including anomaly detection, source classification, and clustering. We demonstrate perTucker’s effectiveness through a simulation study and two case studies on solar flare detection and tonnage signal classification.

14 SOLAR ENERGY↗
DOE OSTI2022

Inferring safety critical events from vehicle kinematics in naturalistic driving environment: Application of deep learning Algorithms

Advances in sensing technology has enabled the collection of countless terabytes of second-by-second kinematics data. Such data provides opportunities for real-time monitoring of driving behavior and identification of safety critical events (SCEs) including crashes and near crashes. The concept of volatility is relevant in this context, which identifies instability and erratic variations in driving behavior prior to involvement in SCEs. This study utilized vehicle kinematics from a large-scale naturalistic driving data to develop a deep learning approach based on 1D convolutional neural networks (CNN) for inferring SCEs. The data are unique in the sense that such accurate pre-crash data at high fidelity are not available in traditional crash repositories. This study contributes to the literature by providing a first attempt at predicting responses to SCEs by developing deep learning-based CNN architectures using novel driving volatility based kinematic thresholds for a sample of 9553 events. The key contribution lies in developing a volatility-based CNN input layout that is acceptable to CNN schemes and represents the motion kinematics such as speed, acceleration and volatility measures. Several 1D-CNN architectures were developed using layers, numbers of convolutions, layer patterns, and kernels. Shallow and deep architectures were tested, revealing higher accuracy of shallow architectures in detecting SCEs. The optimal number of epochs were identified using an early stopping method while the CNN performance was improved by increasing the number of epochs. The ensemble CNN had the highest predictive accuracy of 95.6% for detection of crashes and near crashes, which was 2.5% higher than the optimal CNN using 20% hold out test data. The ensemble CNN also outperformed classical machine learning models and model performance reported in past studies on detection of SCEs. Finally, these results have implications for identification of safety hotspots and providing real-time alerts and warnings in connected and highly automated vehicle environment including society of automotive engineers levels 3–5.

42 ENGINEERING↗
DOE OSTI2013

An inflationary model with small scalar and large tensor nongaussianities

We study a model of inflation where the scalar perturbations are almost gaussian while there is sizable (equilateral) nongaussianity in the tensor sector. In this model, a rolling pseudoscalar gravitationally coupled to the inflaton amplifies the vacuum fluctuations of a vector field. The vector sources both scalar and tensor metric perturbations. Both kinds of perturbations are nongaussian, but, due to helicity conservation, the tensors have a larger amplitude, so that nongaussianity in the scalar perturbations is negligible. Moreover, the tensors produced this way are chiral. We study, in the flat sky approximation, how constraints on tensor nongaussianities affect the detectability of parity violation in the Cosmic Microwave Background. We expect the model to feature interesting patterns on nongaussianities in the polarization spectra of the CMB.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Short-Term Energy and Meteorological Impacts on Thanksgiving CO2 in Salt Lake City

Abstract Long-term, high-frequency atmospheric CO2 measurements at multiple sites in the Salt Lake City (SLC), Utah, reveal that annual and monthly CO2 variability aligns with a priori estimates of emissions from anthropogenic and biological sources. In this study, we investigate whether short-term fluctuations in anthropogenic emissions, as captured in the Vulcan3 dataset for the United States, can be detected in atmospheric CO2 observations. Specifically, we focus on Thanksgiving holidays, when traffic and energy usage patterns differ from the rest of November. Onroad CO2 emissions exhibit a double peak during weekday morning and evening rush hours but remain relatively low on weekends and Thanksgiving. Interestingly, CO2 mole fractions during Thanksgiving were higher than the rest of November at all SLC monitoring sites, particularly from 2008 to 2013. This increase is partially attributed to elevated energy-related emissions — especially residential sources — and meteorological factors such as weak wind speeds, cold temperature, and a low planetary boundary layer height (PBLH).

 While CO₂ emissions and mole fraction patterns align over time, notable spatial differences exist. For instance, the near-highway site in Murray shows the highest CO₂ mole fractions despite low local emissions, suggesting pollution transport via highways and wind advection. Random Forest model-based SHapley Additive exPlanations (SHAP) analysis reveals that onroad emissions dominate CO2 contributions on weekdays and weekends, while energy-related emissions play a larger role during Thanksgiving, alongside meteorological drivers such as wind speed and PBLH. Across six urban cities, CO2 emissions display a consistent pattern: residential and commercial (onroad) emissions peak during Thanksgiving (weekday) with substantial (minimal) year-to-year variability. These findings highlight that urban CO₂ variability is driven by the combined influence of emissions and meteorology, underscoring the need for integrated mitigation strategies. Additionally, multi-site measurements are essential for accurate source attribution and the development of effective policy interventions. 

Ryoo, Ju-Mee (ORCID:0000000234256296)↗
DOE OSTI2026

Spontaneously Broken Noninvertible Symmetries in Transverse-Field Ising Qudit Chains

Recent developments have revealed that symmetries need not form a group, but instead can be noninvertible. Here we use analytical arguments and numerical evidence to illuminate how spontaneous symmetry breaking of a noninvertible symmetry is similar yet distinct from ordinary, invertible, symmetry breaking. We consider one-dimensional chains of group-valued qudits, whose local Hilbert space is spanned by elements of a finite group 𝐺 (reducing to ordinary qubits when 𝐺=ℤ 2 ). We construct Ising-type transverse-field Hamiltonians with Rep⁡(𝐺) symmetry whose generators multiply according to the tensor product of irreducible representations (irreps) of the group 𝐺 . For non-Abelian 𝐺 , the symmetry is noninvertible. In the symmetry broken phase there is one ground state per irrep on a closed chain. The symmetry breaking can be detected by local order parameters but, unlike the invertible case, different ground states have distinct entanglement patterns. We show that for each irrep of dimension greater than one the corresponding ground state exhibits string order, entanglement spectrum degeneracies, and has gapless edge modes on an open chain—features usually associated with symmetry-protected topological order. Consequently, domain wall excitations behave as one-dimensional non-Abelian anyons with nontrivial internal Hilbert spaces and fusion rules. Our Letter identifies properties of noninvertible symmetry breaking that existing quantum hardware can probe.

1-dimensional spin chains↗
DOE OSTI2025

Tracing the impacts of Mount Pinatubo eruption on regional climate using spatially-varying changepoint detection

Significant events, such as volcanic eruptions, can have global and long-lasting impacts on climate. These global impacts, however, are not uniform across space and time. Understanding how the Mt. Pinatubo eruption affects global and regional climate is of great interest for predicting the impact on climate due to similar events as well as understanding the possible effect of the stratospheric aerosol injections proposed to combat climate change. While many studies illustrated the impact of the Pinatubo eruption on a global scale, studies at a fine regional scale are scarce. Here, we propose a Bayesian spatially-varying changepoint detection and estimation method to trace the impact of Mt. Pinatubo eruption on regional climate. Our approach takes into account the diffusing nature and spatial correlation of the climate changes attributed to the volcanic eruption. We illustrate our method and demonstrate its advantages over an existing changepoint detection method through simulations. Finally, we apply our method to monthly stratospheric aerosol optical depth and surface temperature data from 1985 to 1995 to detect and estimate changepoints following the 1991 Mt. Pinatubo eruption. Our results quantitatively characterize the spatial pattern of the eruption’s impact on regional climate, complementing the previous studies on the global impact of the Pinatubo eruption.

Aerosol optical depth↗
DOE OSTI2013

Devices useful for vacuum ultraviolet beam characterization including a movable stage with a transmission grating and image detector

The invention provides for a device comprising an apparatus comprising (a) a transmission grating capable of diffracting a photon beam into a diffracted photon output, and (b) an image detector capable of detecting the diffracted photon output. The device is useful for measuring the spatial profile and diffraction pattern of a photon beam, such as a vacuum ultraviolet (VUV) beam.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

Both RIG-I and MDA5 detect alphavirus replication in concentration-dependent mode

Alphaviruses are a family of positive-strand RNA viruses that circulate on all continents between mosquito vectors and vertebrate hosts. Despite a significant public health threat, their biology is not sufficiently investigated, and the mechanisms of alphavirus replication and virus–host interaction are insufficiently understood. In this study, we have applied a variety of experimental systems to further understand the mechanism by which infected cells detect replicating alphaviruses. Our new data strongly suggest that activation of the antiviral response by alphavirus-infected cells is determined by the integrity of viral genes encoding proteins with nuclear functions, and by the presence of two cellular pattern recognition receptors (PRRs), RIG-I and MDA5. No type I IFN response is induced in their absence. The presence of either of these PRRs is sufficient for detecting virus replication. However, type I IFN activation in response to pathogenic alphaviruses depends on the basal levels of RIG-I or MDA5. - Highlights: • Both RIG-I and MDA5 detect alphavirus replication. • Alphavirus-induced transcriptional shutoff affects type I IFN induction. • Sensing of alphavirus replication by RIG-I and MDA5 depends on their concentrations. • High basal level of RIG-I and MDA5 allows IFN induction by pathogenic alphaviruses. • This dependence determines the discrepancy between the in vivo and in vitro data.

60 APPLIED LIFE SCIENCES↗