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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 1,369 records · Page 76
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Spatial variability in Arctic–boreal fire regimes influenced by environmental and human factors

Abstract Wildfire activity in Arctic and boreal regions is rapidly increasing, with severe consequences for climate and human health. Regional long-term variations in fire frequency and intensity characterize fire regimes. The spatial variability in Arctic–boreal fire regimes and their environmental and anthropogenic drivers, however, remain poorly understood. Here we present a fire tracking system to map the sub-daily evolution of all circumpolar Arctic–boreal fires between 2012 and 2023 using 375 m Visible Infrared Imaging Radiometer Suite active fire detections and the resulting dataset of the ignition time, location, size, duration, spread and intensity of individual fires. We use this dataset to classify the Arctic–boreal biomes into seven distinct ‘pyroregions’ with unique climatic and geographic environments. We find that these pyroregions exhibit varying responses to environmental drivers, with boreal North America, eastern Siberia and northern tundra regions showing the highest sensitivity to climate and lightning density. In addition, anthropogenic factors play an important role in influencing fire number and size, interacting with other factors. Understanding the spatial variability of fire regimes and its interconnected drivers in the Arctic–boreal domain is important for improving future predictions of fire activity and identifying areas at risk for extreme events.

Geology↗
DOE OSTI2020

Novel genetic risk factors influence progression of islet autoimmunity to type 1 diabetes

Type 1 diabetes arises from the autoimmune destruction of insulin-producing beta-cells of the pancreas, resulting in dependence on exogenously administered insulin to maintain glucose homeostasis. In this study, our aim was to identify genetic risk factors that contribute to progression from islet autoimmunity to clinical type 1 diabetes. We analyzed 6.8 million variants derived from whole genome sequencing of 160 islet autoantibody positive subjects, including 87 who had progressed to type 1 diabetes. The Cox proportional-hazard model for survival analysis was used to identify genetic variants associated with progression. We identified one novel region, 20p12.1 (TASP1; genome-wide P < 5 × 10 –8 ) and three regions, 1q21.3 (MRPS21–PRPF3), 2p25.2 (NRIR), 3q22.1 (COL6A6), with suggestive evidence of association (P < 8.5 × 10 –8 ) with progression from islet autoimmunity to type 1 diabetes. Once islet autoimmunity is initiated, functional mapping identified two critical pathways, response to viral infections and interferon signaling, as contributing to disease progression. These results provide evidence that genetic pathways involved in progression from islet autoimmunity differ from those pathways identified once disease has been established. These results support the need for further investigation of genetic risk factors that modulate initiation and progression of subclinical disease to inform efforts in development of novel strategies for prediction and intervention of type 1 diabetes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Evaluating the factors influencing accuracy, interpretability, and reproducibility in the use of machine learning classifiers in biology to enable standardization

The complexity and variability of biological data has promoted the increased use of machine learning methods to understand processes and predict outcomes. These same features complicate reliable, reproducible, interpretable, and responsible use of such methods, resulting in questionable relevance of the derived. outcomes. Here we systematically explore challenges associated with applying machine learning to predict and understand biological processes using a well- characterized in vitro experimental system. We evaluated factors that vary while applying machine learning classifers: (1) type of biochemical signature (transcripts vs. proteins), (2) data curation methods (pre- and post-processing), and (3) choice of machine learning classifier. Using accuracy, generalizability, interpretability, and reproducibility as metrics, we found that the above factors significantly mod- ulate outcomes even within a simple model system. Our results caution against the unregulated use of machine learning methods in the biological sciences, and strongly advocate the need for data standards and validation tool-kits for such studies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Electrically tunable effective g-factor of a single hole in a lateral GaAs/AlGaAs quantum dot

Electrical tunability of the $g$-factor of a confined spin is a long-time goal of the spin qubit field. Here we utilize the electric dipole spin resonance (EDSR) to demonstrate it in a gated GaAs double-dot device confining a hole. This tunability is a consequence of the strong spin-orbit interaction (SOI) in the GaAs valence band. The SOI enables a spin-flip interdot tunneling, which, in combination with the simple spin-conserving charge transport leads to the formation of tunable hybrid spin-orbit molecular states. EDSR is used to demonstrate that the gap separating the two lowest energy states changes its character from a charge-like to a spin-like excitation as a function of interdot detuning or magnetic field. In the spin-like regime, the gap can be characterized by the effective $g$-factor, which differs from the bulk value owing to spin-charge hybridization, and can be tuned smoothly and sensitively by gate voltages.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Targeting transcription factors through an IMiD independent zinc finger domain

Abstract Immunomodulatory imide drugs (IMiDs) degrade specific C2H2 zinc finger degrons in transcription factors, making them effective against certain cancers. SALL4, a cancer driver, contains seven C2H2 zinc fingers in three clusters, including an IMiD degron in zinc finger cluster one (ZFC1). Surprisingly, IMiDs do not inhibit the growth of SALL4-expressing cancer cells. To overcome this limit, we focused on a non-IMiD domain, SALL4 zinc finger cluster four (ZFC4). By combining ZFC4-DNA crystal structure and an in silico docking algorithm, in conjunction with cell viability assays, we screened several chemical libraries against a potentially druggable binding pocket, leading to the discovery of SH6, a compound that selectively targets SALL4-expressing cancer cells. Mechanistic studies revealed that SH6 degrades SALL4 protein through the CUL4A/CRBN pathway, while deletion of ZFC4 abolished this activity. Moreover, SH6 treatment led to a significant 87% tumor growth inhibition of SALL4+ patient-derived xenografts and demonstrated good bioavailability in pharmacokinetic studies. In summary, these studies represent a new approach for IMiD independent drug discovery targeting C2H2 transcription factors such as SALL4 in cancer.

Liu, Bee Hui↗
DOE OSTI2015

Functional integration of Ni–Mo electrocatalysts with Si microwire array photocathodes to simultaneously achieve high fill factors and light-limited photocurrent densities for solar-driven hydrogen evolution

An n + p-Si microwire array coupled with a two-layer catalyst film consisting of Ni–Mo nanopowder and TiO 2 light-scattering nanoparticles has been used to simultaneously achieve high fill factors and light-limited photocurrent densities from photocathodes that produce H 2 (g) directly from sunlight and water. The TiO 2 layer scattered light back into the Si microwire array, while optically obscuring the underlying Ni–Mo catalyst film. In turn, the Ni–Mo film had a mass loading sufficient to produce high catalytic activity, on a geometric area basis, for the hydrogen-evolution reaction. The best-performing microwire array devices prepared in this work exhibited short-circuit photocurrent densities of -14.3 mA cm -2 , photovoltages of 420 mV, and a fill factor of 0.48 under 1 Sun of simulated solar illumination, whereas the equivalent planar Ni–Mo-coated Si device, without TiO 2 scatterers, exhibited negligible photocurrent due to complete light blocking by the Ni–Mo catalyst layer.

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

Large n- and p-type thermoelectric power factors from doped semiconducting single-walled carbon nanotube thin films

Lightweight, robust, and flexible single-walled carbon nanotube (SWCNT) materials can be processed inexpensively using solution-based techniques, similar to other organic semiconductors. In contrast to many semiconducting polymers, semiconducting SWCNTs (s-SWCNTs) represent unique one-dimensional organic semiconductors with chemical and physical properties that facilitate equivalent transport of electrons and holes. These factors have driven increasing attention to employing s-SWCNTs for electronic and energy harvesting applications, including thermoelectric (TE) generators. Here we demonstrate a combination of ink chemistry, solid-state polymer removal, and charge-transfer doping strategies that enable unprecedented n-type and p-type TE power factors, in the range of 700 μW m –1 K –2 at 298 K for the same solution-processed highly enriched thin films containing 100% s-SWCNTs. We also demonstrate that the thermal conductivity appears to decrease with decreasing s-SWCNT diameter, leading to a peak material zT ≈ 0.12 for s-SWCNTs with diameters in the range of 1.0 nm. Here, our results indicate that the TE performance of s-SWCNT-only material systems is approaching that of traditional inorganic semiconductors, paving the way for these materials to be used as the primary components for efficient, all-organic TE generators.

14 SOLAR ENERGY↗
DOE OSTI2023

Halogenated PETN derivatives: interplay between physical and chemical factors in explosive sensitivity

Determining the factors that influence and can help predict energetic material sensitivity has long been a challenge in the explosives community. Decades of literature reports identify a multitude of factors both chemical and physical that influence explosive sensitivity; however no unifying theory has been observed. Recent work by our team has demonstrated that the kinetics of “trigger linkages” (i.e., the weakest bonds in the energetic material) showed strong correlations with experimental drop hammer impact sensitivity. These correlations suggest that the simple kinetics of the first bonds to break are good indicators for the reactivity observed in simple handling sensitivity tests. Herein we report the synthesis of derivatives of the explosive pentaerythritol tetranitrate (PETN) in which one, two or three of the nitrate ester functional groups are substituted with an inert group. Experimental and computational studies show that explosive sensitivity correlates well with Q (heat of explosion), due to the change in the number of trigger linkages removed from the starting material. In addition, this correlation appears more significant than other observed chemical or physical effects imparted on the material by different inert functional groups, such as heat of formation, heat of explosion, heat capacity, oxygen balance, and the crystal structure of the material.

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

Decoding substrate specificity determining factors in glycosyltransferase-B enzymes – insights from machine learning models

Substrate specificity is an essential characteristic of any enzyme's function and an understanding of the factors that determine this specificity is crucial for enzyme engineering. Unlike the structure of an enzyme which is directly impacted by its sequence, substrate specificity as an enzyme attribute involves a rather indirect relationship with sequence as it also depends on structural aspects that dictate substrate accessibility and active site dynamics. In this study, we explore the performance of classifier-based machine learning models trained on curated sequence and structural data for a class of glycosyltransferases (GTs), namely GT-Bs, to understand their substrate specificity determining factors. GTs enable the transfer of sugar moieties to other biomolecules such as oligosaccharides or proteins and are found in all kingdoms of life. In plants, GTs participate in the biosynthesis of plant cell wall biopolymers (e.g.: hemicelluloses and pectins) and are an integral part of the enzymatic machinery that enables the storage of carbon and energy as plant biomass. To elucidate the substrate specificity of uncharacterized GT-Bs, we constructed multi-label machine learning models (Support Vector Classifier, K-Nearest Neighbors, Gaussian Naïve-Bayes, Random Forest) that incorporate both sequence and structural features. These models achieve good predictive accuracies on test datasets. However, despite our use of structural information, we highlight that there is further scope for improvement in training these models to draw interpretable relationships between sequence, structure and substrate specificity determining motifs in GT-Bs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Photon impact factor in the NLO

The photon impact factor for the BFKL pomeron is calculated in the next-to-leading order (NLO) approximation using the operator expansion in Wilson lines. The result is represented as a NLO k{sub T}-factorization formula for the structure functions of small-x deep inelastic scattering.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2013

Communication: A Jastrow factor coupled cluster theory for weak and strong electron correlation

We present a Jastrow-factor-inspired variant of coupled cluster theory that accurately describes both weak and strong electron correlation. Compatibility with quantum Monte Carlo allows for variational energy evaluations and an antisymmetric geminal power reference, two features not present in traditional coupled cluster that facilitate a nearly exact description of the strong electron correlations in minimal-basis N{sub 2} bond breaking. In double-ζ treatments of the HF and H{sub 2}O bond dissociations, where both weak and strong correlations are important, this polynomial cost method proves more accurate than either traditional coupled cluster or complete active space perturbation theory. These preliminary successes suggest a deep connection between the ways in which cluster operators and Jastrow factors encode correlation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

Relationship between orientation factor of lead zirconate titanate nanowires and dielectric permittivity of nanocomposites

The relationship between the orientation of lead zirconate titanate (PZT) nanowires dispersed in nanocomposites and the resulting dielectric constants are quantified. The orientation of the PZT nanowires embedded in a polymer matrix is controlled by varying the draw ratio and subsequently quantified using Herman's Orientation Factor. Consequently, it is demonstrated that the dielectric constants of nanocomposites are improved by increasing the orientation factor of the PZT nanowires. This technique is proposed to improve the dielectric constant of the nanocomposites without the need for additional filler volume fraction since the nanocomposites are utilized in a wide range of high dielectric permittivity electronic components.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2013

Experimental setup for the determination of the correction factors of the neutron doseratemeters in fast neutron fields

The use of the U-120 Cyclotron of the IFIN-HH allowed to perform a testing bench with fast neutrons in order to determine the correction factors of the doseratemeters dedicated to neutron measurement. This paper deals with researchers performed in order to develop the irradiation facility testing the fast neutrons flux generated at the Cyclotron. This facility is presented, together with the results obtain in determining the correction factor for a doseratemeter dedicated to the neutron dose equivalent rate measurement.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2014

High sensitivity and high Q-factor nanoslotted parallel quadrabeam photonic crystal cavity for real-time and label-free sensing

We experimentally demonstrate a label-free sensor based on nanoslotted parallel quadrabeam photonic crystal cavity (NPQC). The NPQC possesses both high sensitivity and high Q-factor. We achieved sensitivity (S) of 451 nm/refractive index unit and Q-factor >7000 in water at telecom wavelength range, featuring a sensor figure of merit >2000, an order of magnitude improvement over the previous photonic crystal sensors. In addition, we measured the streptavidin-biotin binding affinity and detected 10 ag/mL concentrated streptavidin in the phosphate buffered saline solution.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Influence of germanium nano-inclusions on the thermoelectric power factor of bulk bismuth telluride alloy

Nanocomposite thermoelectric compound of bismuth telluride (Bi{sub 2}Te{sub 3}) with 5 at. % germanium nano-inclusions was prepared via mechanically alloying and sintering techniques. The influence of Ge nano-inclusions and long duration annealing on the thermoelectric properties of nanostructured Bi{sub 2}Te{sub 3} were investigated. It was found that annealing has significant effect on the carrier concentration, Seebeck coefficient, and the power factor of the thermoelectric compound. The systematic heat treatment also reduced the density of donor type defects thereby decreasing the electron concentration. While the as-pressed nanocomposite materials showed n-type properties, it was observed that with the increase of annealing time, the nanocomposite gradually transformed to an abundantly hole-dominated (p-type) sample. The long duration annealing (∼500 h) resulted in a significantly enhanced electrical conductivity pertaining to the augmentation in the density and the structural properties of the sample. Therefore, a simultaneous enhancement in both electrical and Seebeck coefficient characteristics resulted in a remarkable increase in the thermoelectric power factor.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2014

Form factor of pNIPAM microgels in overpacked states

We study the form factor of thermoresponsive microgels based on poly(N-isopropylacrylamide) at high generalized volume fractions, ζ, where the particles must shrink or interpenetrate to fit into the available space. Small-angle neutron scattering with contrast matching techniques is used to determine the particle form factor. We find that the particle size is constant up to a volume fraction roughly between random close packing and space filling. Beyond this point, the particle size decreases with increasing particle concentration; this decrease is found to occur with little interpenetration. Noteworthily, the suspensions remain liquid-like for ζ larger than 1, emphasizing the importance of particle softness in determining suspension behavior.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

The critical compressibility factor value: Associative fluids and liquid alkali metals

We show how to obtain the critical compressibility factor Z{sub c} for simple and associative Lennard-Jones fluids using the critical characteristics of the Ising model on different lattices. The results show that low values of critical compressibility factor are correlated with the associative properties of fluids in critical region and can be obtained on the basis of the results for the Ising model on lattices with more than one atom per cell. An explanation for the results on the critical point line of the Lennard-Jones fluids and liquid metals is proposed within the global isomorphism approach.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Experimental investigation of factors limiting slow axis beam quality in 9xx nm high power broad area diode lasers

GaAs-based broad-area diode lasers are needed with improved lateral beam parameter product (BPP{sub lat}) at high power. An experimental study of the factors limiting BPP{sub lat} is therefore presented, using extreme double-asymmetric (EDAS) vertical structures emitting at 910 nm. Continuous wave, pulsed and polarization-resolved measurements are presented and compared to thermal simulation. The importance of thermal and packaging-induced effects is determined by comparing junction -up and -down devices. Process factors are clarified by comparing diodes with and without index-guiding trenches. We show that in all cases studied, BPP{sub lat} is limited by a non-thermal BPP ground-level and a thermal BPP, which depends linearly on self-heating. Measurements as a function of pulse width confirm that self-heating rather than bias-level dominates. Diodes without trenches show low BPP ground-level, and a thermal BPP which depends strongly on mounting, due to changes in the temperature profile. The additional lateral guiding in diodes with trenches strongly increases the BPP ground-level, but optically isolates the stripe from the device edges, suppressing the influence of the thermal profile, leading to a BPP-slope that is low and independent of mounting. Trenches are also shown to initiate strain fields that cause parasitic TM-polarized emission with large BPP{sub lat}, whose influence on total BPP{sub lat} remains small, provided the overall polarization purity is >95%.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗