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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 1,171 records · Page 65
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Rashba exciton in a 2D perovskite quantum dot

The Rashba effect has been proposed to give rise to a bright exciton ground state in halide perovskite nanocrystals (NCs), resulting in very fast radiative recombination at room temperature and extremely fast radiative recombination at low temperature. In this paper we find the dispersion of the “Rashba exciton”, i.e., the exciton whose bulk dispersion reflects large spin–orbit Rashba terms in the conduction and valence bands and thus has minima at non-zero quasi-momenta. Placing Rashba excitonsin quasi-2D cylindrical quantum dots, we calculate size-dependent levels of confined excitons and their oscillator transition strengths. Here, we consider the implications of this model for two-dimensional hybrid organic–inorganic perovskites, discuss generalizations of this model to 3D NCs, and establish criteria under which a bright ground exciton state could be realized.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Elucidating the role of reactive nitrogen intermediates in hetero-cyclization during hydrothermal liquefaction of food waste

Hydrothermal liquefaction (HTL) has emerged as a promising strategy for converting abundant, water-rich organic streams into an energy-dense, sustainable, biocrude. Despite major strides in improving oil yields and process intensification, a key underlying challenge persists in relating the composition of the feedstock to the ultimate fate of nitrogen, which is especially important for biocrude quality. To elucidate how nitrogen partitions into the respective gas, aqueous, oil and solid hydrothermal products, food waste was treated under HTL conditions (15 wt% solids, 575 K reaction temperature, and 1 hour reaction time) and elemental, chromatographic and mass spectroscopy analyses were performed on the products to establish dominant product classes and to close mass, carbon, and nitrogen balances. Liquid products (aqueous and biocrude) were found to contain nearly 60% of the nitrogen, with a majority of the biocrude-phase nitrogen in the form of amides. Ab initio thermodynamic and kinetic simulations on model reactants were used to evaluate potential reaction pathways involving reactive nitrogen intermediates. A subsequent kinetic model was evaluated at reaction temperatures ranging 300–1000 K and for a range of feedstock compositions to identify primary reaction pathways. The Maillard reaction is revealed to be the dominant pathway for converting reactive nitrogen intermediates into observed products, especially those in which nitrogen is present as a heterocyclic aromatic. Subsequent product analysis by Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FT-ICR MS) confirms strong agreement among the experimental data, kinetic model and proposed Maillard pathways.

09 BIOMASS FUELS↗
DOE OSTI2024

Structure of RADX and mechanism for regulation of RAD51 nucleofilaments

Replication fork reversal is a fundamental process required for resolution of encounters with DNA damage. A key step in the stabilization and eventual resolution of reversed forks is formation of RAD51 nucleoprotein filaments on exposed single strand DNA (ssDNA). To avoid genome instability, RAD51 filaments are tightly controlled by a variety of positive and negative regulators. RADX (RPA-related RAD51-antagonist on the X chromosome) is a recently discovered negative regulator that binds tightly to ssDNA, directly interacts with RAD51, and regulates replication fork reversal and stabilization in a context-dependent manner. Here, we present a structure-based investigation of RADX’s mechanism of action. Mass photometry experiments showed that RADX forms multiple oligomeric states in a concentration-dependent manner, with a predominance of trimers in the presence of ssDNA. The structure of RADX, which has no structurally characterized orthologs, was determined ab initio by cryo-electron microscopy (cryo-EM) from maps in the 2 to 4 Å range. The structure reveals the molecular basis for RADX oligomerization and the coupled multi-valent binding of ssDNA binding. The interaction of RADX with RAD51 filaments was imaged by negative stain EM, which showed a RADX oligomer at the end of filaments. Based on these results, we propose a model in which RADX functions by capping and restricting the end of RAD51 filaments.

Science & Technology - Other Topics↗
DOE OSTI2023

Recipes for when physics fails: recovering robust learning of physics informed neural networks

Abstract Physics-informed neural networks (PINNs) have been shown to be effective in solving partial differential equations by capturing the physics induced constraints as a part of the training loss function. This paper shows that a PINN can be sensitive to errors in training data and overfit itself in dynamically propagating these errors over the domain of the solution of the PDE. It also shows how physical regularizations based on continuity criteria and conservation laws fail to address this issue and rather introduce problems of their own causing the deep network to converge to a physics-obeying local minimum instead of the global minimum. We introduce Gaussian process (GP) based smoothing that recovers the performance of a PINN and promises a robust architecture against noise/errors in measurements. Additionally, we illustrate an inexpensive method of quantifying the evolution of uncertainty based on the variance estimation of GPs on boundary data. Robust PINN performance is also shown to be achievable by choice of sparse sets of inducing points based on sparsely induced GPs. We demonstrate the performance of our proposed methods and compare the results from existing benchmark models in literature for time-dependent Schrödinger and Burgers’ equations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

A detailed study of interpretability of deep neural network based top taggers

Abstract Recent developments in the methods of explainable artificial intelligence (XAI) allow researchers to explore the inner workings of deep neural networks (DNNs), revealing crucial information about input–output relationships and realizing how data connects with machine learning models. In this paper we explore interpretability of DNN models designed to identify jets coming from top quark decay in high energy proton–proton collisions at the Large Hadron Collider. We review a subset of existing top tagger models and explore different quantitative methods to identify which features play the most important roles in identifying the top jets. We also investigate how and why feature importance varies across different XAI metrics, how correlations among features impact their explainability, and how latent space representations encode information as well as correlate with physically meaningful quantities. Our studies uncover some major pitfalls of existing XAI methods and illustrate how they can be overcome to obtain consistent and meaningful interpretation of these models. We additionally illustrate the activity of hidden layers as neural activation pattern diagrams and demonstrate how they can be used to understand how DNNs relay information across the layers and how this understanding can help to make such models significantly simpler by allowing effective model reoptimization and hyperparameter tuning. These studies not only facilitate a methodological approach to interpreting models but also unveil new insights about what these models learn. Incorporating these observations into augmented model design, we propose the particle flow interaction network model and demonstrate how interpretability-inspired model augmentation can improve top tagging performance.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

On the role of α-alumina in the origin of life: Surface-driven assembly of amino acids

We investigate the hypothesis that mineral/water interfaces played a crucial catalytic role in peptide formation by promoting the self-assembly of amino acids. Using classical molecular dynamics simulations, we demonstrate that the α-alumina(0001) surface exhibits an affinity of 4k B Tfor individual glycine or GG dipeptide molecules due to hydrogen bonds. In simulations with multiple glycine molecules, surface-bound glycine enhances further adsorption, leading to the formation of long chains connected by hydrogen bonds between the carboxyl and amine groups of glycine molecules. We find that the likelihood of observing chains longer than 10 glycine units increases by at least five orders of magnitude at the surface compared to the bulk. This surface-driven assembly is primarily due to local high density and alignment with the alumina surface pattern. Together, these results propose a model for how mineral surfaces can induce configuration-specific assembly of amino acids, thereby promoting condensation reactions.

Science & Technology - Other Topics↗
DOE OSTI2019

Aerosol-driven droplet concentrations dominate coverage and water of oceanic low-level clouds

A lack of reliable estimates of cloud condensation nuclei (CCN) aerosols over oceans has severely limited our ability to quantify their effects on cloud properties and extent of cooling by reflecting solar radiation—a key uncertainty in anthropogenic climate forcing. We introduce a methodology for ascribing cloud properties to CCN and isolating the aerosol effects from meteorological effects. Its application showed that for a given meteorology, CCN explains three-fourths of the variability in the radiative cooling effect of clouds, mainly through affecting shallow cloud cover and water path. This reveals a much greater sensitivity of cloud radiative forcing to CCN than previously reported, which means too much cooling if incorporated into present climate models. This suggests the existence of compensating aerosol warming effects yet to be discovered, possibly through deep clouds.

Science & Technology - Other Topics↗
DOE OSTI2025

Wind and solar energy droughts: Potential impacts on energy system dynamics and research needs

This Perspective article provides a brief overview of the topic of wind and solar energy droughts (henceforth WSDs). It does not attempt to provide a complete literature review of the subject but rather highlights some of the main concepts associated with WSDs. These include wind and solar energy drought definitions and metrics; meteorological conditions producing WSDs; a comparison of their characteristics with hydrologic droughts and hydropower droughts; model-based and observational datasets useful for WSD analyses; the linkage of WSDs to transmission, storage, and demand response; the potential impacts of WSDs vs energy demand variations; wind and solar flood events; WSD predictability; WSD dependency on climate modes of variability; climate change impacts on WSDs; and the special challenge of evaluating the characteristics of WSDs in developing countries that have limited historical data available. Finally, the manuscript identifies research areas that the authors believe would provide immediate benefit to energy system planners.

14 SOLAR ENERGY↗
DOE OSTI2023

Concordance

Dimension reduction techniques have long been an important topic in statistics, and active subspaces (AS) have received much attention this past decade in the computer experiments literature. The most common approach towards estimating the AS is to use Monte Carlo with numerical gradient evaluation. This software takes a new approach towards estimating the active subspace, in which Multivariate Adaptive Regression Splines (MARS) is used as a surrogate model, and relevant calculation are obtained analytically. Using a MARS surrogate has many advantages including improved scaling, better estimation of active subspaces in high dimensions and the ability to handle a large number of prior distributions in closed form. This software is also capable of conducting a so-called "concordance analysis", using a generalization of ASs which we refer to as "Co-Active" subspaces.

Rumsey, Kelin↗
DOE OSTI2024

Seismic Tomography 2024

Seismic tomography is the most abundant source of information about the internal structure of the Earth at scales ranging from a few meters to thousands of kilometers. It constrains the properties of active volcanoes, earthquake fault zones, deep reservoirs and storage sites, glaciers and ice sheets, or the entire globe. It contributes to outstanding societal problems related to natural hazards, resource exploration, underground storage, and many more. The recent advances in seismic tomography are being translated to nondestructive testing, medical ultrasound, and helioseismology. Nearly 50 yr after its first successful applications, this article offers a snapshot of modern seismic tomography. Focused on major challenges and particularly promising research directions, it is intended to guide both Earth science professionals and early-career scientists. The individual contributions by the coauthors provide diverse perspectives on topics that may at first seem disconnected but are closely tied together by a few coherent threads: multiparameter inversion for properties related to dynamic processes, data quality, and geographic coverage, uncertainty quantification that is useful for geologic interpretation, new formulations of tomographic inverse problems that address concrete geologic questions more directly, and the presentation and quantitative comparison of tomographic models. Finally, it remains to be seen which of these problems will be considered solved, solved to some extent, or practically unsolvable over the next decade.

58 GEOSCIENCES↗
DOE OSTI2024

Disentangling the Black Hole Mass Spectrum with Photometric Microlensing Surveys

Abstract From the formation mechanisms of stars and compact objects to nuclear physics, modern astronomy frequently leverages surveys to understand populations of objects to answer fundamental questions. The population of dark and isolated compact objects in the Galaxy contains critical information related to many of these topics, but is only practically accessible via gravitational microlensing. However, photometric microlensing observables are degenerate for different types of lenses, and one can seldom classify an event as involving either a compact object or stellar lens on its own. To address this difficulty, we apply a Bayesian framework that treats lens type probabilistically and jointly with a lens population model. This method allows lens population characteristics to be inferred despite intrinsic uncertainty in the lens class of any single event. We investigate this method’s effectiveness on a simulated ground-based photometric survey in the context of characterizing a hypothetical population of primordial black holes (PBHs) with an average mass of 30 M ⊙ . On simulated data, our method outperforms current black hole (BH) lens identification pipelines and characterizes different subpopulations of lenses while jointly constraining the PBH contribution to dark matter to ≈25%. Key to robust inference, our method can marginalize over population model uncertainty. We find the lower mass cutoff for stellar origin BHs, a key observable in understanding the BH mass gap, particularly difficult to infer in our simulations. This work lays the foundation for cutting-edge PBH abundance constraints to be extracted from current photometric microlensing surveys.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

TRISO-form HALEU-fueled Experiment for Transport Applications (THETA) Serpent 2 Benchmarking

A number of new advanced reactor designs use TRI-structural ISO-topic (TRISO) fuel. The uranium enrichment for the TRISO fuel is in the 5- to 19.75-weight percent range, which is considered High-Assay Low Enriched Uranium (HALEU). The Nuclear Regulatory Commission and vendors both have a strong interest in benchmarking these advanced reactor designs and having confidence in the predictive capabilities of the computer codes used to model them. In the recent years, Serpent 2 gained several capabilities focused on the reactor applications making it attractive for many reactor vendors.

Critical Experiment↗
DOE OSTI2013

Marine and Hydrokinetic Technology (MHK) Instrumentation, Measurement, and Computer Modeling Workshop

The Marine and Hydrokinetic Technology (MHK) Instrumentation, Measurement, and Computer Modeling Workshop was hosted by the National Renewable Energy Laboratory (NREL) in Broomfield, Colorado, July 9-10, 2012. The workshop brought together over 60 experts in marine energy technologies to disseminate technical information to the marine energy community and collect information to help identify ways in which the development of a commercially viable marine energy industry can be accelerated. The workshop was comprised of plenary sessions that reviewed the state of the marine energy industry and technical sessions that covered specific topics of relevance. Each session consisted of presentations, followed by facilitated discussions. During the facilitated discussions, the session chairs posed several prepared questions to the presenters and audience to encourage communication and the exchange of ideas between technical experts. Following the workshop, attendees were asked to provide written feedback on their takeaways and their best ideas on how to accelerate the pace of marine energy technology development. The first four sections of this document give a general overview of the workshop format, provide presentation abstracts and discussion session notes, and list responses to the post-workshop questions. The final section presents key findings and conclusions from the workshop that suggest how the U.S. Department of Energy and national laboratory resources can be utilized to most effectively assist the marine energy industry.

16 TIDAL AND WAVE POWER↗
DOE OSTI2021

Optical and Electronic Losses Arising from Physically Mixed Interfacial Layers in Perovskite Solar Cells

Perovskite solar cell device performance is affected by optical and electronic losses. To minimize these losses in solar cells, it is important to identify their sources. Here, we report the optical and electronic losses arising from physically mixed interfacial layers between the adjacent component materials in highly efficient two terminal (2T) all-perovskite tandem, single junction wide-bandgap, and single junction narrow-bandgap perovskite-based solar cells. Physically mixed interfacial layers as the sources of optical and electronic losses are identified from spectroscopic ellipsometry measurements and data analysis followed by comparisons of simulated and measured external quantum efficiency spectra. Parasitic absorbance in the physically mixed regions between silver metal electrical contacts and electron transport layers (ETLs) near the back contact and a physical mixture of commercial indium tin oxide and hole transport layers (HTL) near the front electrical contact lead to substantial optical loss. Here, a lower-density void + perovskite nucleation layer formed during perovskite deposition at the interface between the perovskite absorber layer and the HTL causes electronic losses due to incomplete collection of photogenerated carriers likely originating from poor coverage and passivation of the initially nucleating grains.

14 SOLAR ENERGY↗
DOE OSTI2017

Design of Non-Deterministic Quasi-random Nanophotonic Structures Using Fourier Space Representations

Despite their seemingly random appearances in the real space, quasi-random nanophotonic structures exhibit distinct structural correlations and have been widely utilized for effective photon management. However, current design approaches mainly rely on the deterministic representations consisting two-dimensional (2D) discretized patterns in the real space. They fail to capture the inherent non-deterministic characteristic of the quasi-random structures and inevitably result in a large design dimensionality. Here, we report a new design approach that employs the one-dimensional (1D) spectral density function (SDF) as the unique representation of non-deterministic quasi-random structures in the Fourier space with greatly reduced design dimensionality. One 1D SDF representation can be used to generate infinite sets of real space structures in 2D with equally optimized performance, which was further validated experimentally using light-trapping structures in a thin film absorber as a model system. The optimized non-deterministic quasi-random nanostructures improve the broadband absorption by 225% over the unpatterned cell.

Science & Technology - Other Topics↗
DOE OSTI2013

Crystal Structure of KLHL3 in Complex with Cullin3

KLHL3 is a BTB-BACK-Kelch family protein that serves as a substrate adapter in Cullin3 (Cul3) E3 ubiquitin ligase complexes. KLHL3 is highly expressed in distal nephron tubules where it is involved in the regulation of electrolyte homeostasis and blood pressure. Mutations in KLHL3 have been identified in patients with inherited hypertension disorders, and several of the disease-associated mutations are located in the presumed Cul3 binding region. Here, we report the crystal structure of a complex between the KLHL3 BTB-BACK domain dimer and two copies of an N terminal fragment of Cul3. We use isothermal titration calorimetry to directly demonstrate that several of the disease mutations in the KLHL3 BTB-BACK domains disrupt the association with Cul3. Both the BTB and BACK domains contribute to the Cul3 interaction surface, and an extended model of the dimeric CRL3 complex places the two E2 binding sites in a suprafacial arrangement with respect to the presumed substrate-binding sites.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

The quinic acid derivative KZ-41 prevents glucose-induced caspase-3 activation in retinal endothelial cells through an IGF-1 receptor dependent mechanism

Retinal microaneurysms, an early disease manifestation of diabetic retinopathy, are associated with retinal endothelial cell (REC) death and macular edema. We previously demonstrated that a quinic acid (QA) analog, KZ-41, promoted REC survival by blunting stress-induced p38 MAPK activation. Herein, we sought to expand our understanding of the prosurvival signal transduction pathways actuated by KZ-41. Using human RECs exposed to high glucose (25 mM, 72 hours), we demonstrated that KZ-41 blocks caspase-3 activation by triggering phosphorylation of the PI3K regulatory subunit (p85; Tyr458) and its downstream target Akt (Ser473). Akt signal transduction was accompanied by autophosphorylation of the receptor tyrosine kinase, insulin growth factor-1 receptor (IGF-1R). IGF-1R knockdown using either the tyrosine kinase inhibitor AG1024 or silencing RNA abolished KZ-41’s pro-survival effect. Under high glucose stress, caspase-3 activation correlated with elevated ERK1/2 phosphorylation and decreased insulin receptor substrate-1 (IRS-1) levels. KZ-41 decreased ERK1/2 phosphorylation and reversed the glucose-dependent reduction in IRS-1. To gain insight into the mechanistic basis for IGF-1R activation by KZ-41, we used molecular modeling and docking simulations to explore a possible protein:ligand interaction between the IGF-1R kinase domain and KZ-41. Computational investigations suggest two possible KZ-41 binding sites within the kinase domain: a region with high homology to the insulin receptor contains one potential allosteric binding site, and another potential site on the other side of the kinase domain, near the hinge domain. These data, together with previous proof-of-concept efficacy studies demonstrating KZ-41 mitigates pathologic retinal neovascularization in the murine oxygen-induced retinopathy model, suggests that QA derivatives may offer therapeutic benefit in ischemic retinopathies.

59 BASIC BIOLOGICAL SCIENCES↗