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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Mechanism-Informed Breakdown: Understanding Degradation by Controlling Voltage-Hold Patterns in Proton Exchange Membrane Water Electrolyzers

Low catalyst loadings pose challenges to performance stability in proton exchange membrane (PEM) water electrolysis over extended operation. To study the impact of degradation mechanisms and voltage loss rates, different stress tests are applied to membrane electrode assemblies. Potential cycling conditions were observed to induce higher degrees of iridium (Ir) oxide crystallization, ionomer degradation, and catalyst layer (CL) thinning, which likely contributed to higher kinetic loss rates. On the other hand, while Ir migrating into the PEM (Ir band) generally impairs performance, the interconnected and more uniform Ir band formed under a constant 2 V hold may allow for Ir at the catalyst/membrane interface to remain electronically connected and kinetically accessible, as well as indicate greater Ir site access during the applied stressor. The 2 V hold also demonstrates improved kinetic durability through a lower Tafel slope, faster polarization kinetics, and reduced charge transfer resistance. In contrast, potential cycling caused the migration of disconnected Ir agglomerates into the membrane bulk and created a steady increase in charge transfer resistance, a more dramatic decrease in capacitance (46.7% loss), and significant damage to the surrounding ionomer, indicating a decline in both the quality and quantity of active sites in the anode CL. This work underscores the distinct degradation pathways associated with load holds versus cycling, highlighting the role of catalyst-ionomer interactions in kinetic performance and long-term stability. These insights can inform operational strategies for PEM electrolyzers powered by intermittent energy sources, aiming to minimize efficiency losses over extended operation.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Exploratory analysis and performance prediction of big data transfer in High-performance Networks

Big data transfer in large-scale scientific and business applications is increasingly carried out over connections with guaranteed bandwidth provisioned in High-performance Networks (HPNs) via advance bandwidth reservation. Provisioning agents need to carefully schedule data transfer requests, compute network paths, and allocate appropriate bandwidths. Such reserved bandwidths, if not fully utilized, could be simply wasted due to the exclusive access during the approved time window, and cause extra overhead and complexity for resource management. This calls for accurate performance prediction to reserve bandwidths that match actual needs and avoid over-provisioning. We employ machine learning algorithms to predict big data transfer performance based on extensive performance measurements collected in the past several years from data transfer tests using different protocols and toolkits between various end sites on several real-life physical or emulated testbeds. We first analyze the performance patterns in response to a comprehensive list of parameters in end-host systems, network connections, and data transfer applications, which motivate the use of machine learning and also help us identify the effects of latent factors. We then propose threshold- and clustering-based methods to eliminate negative effects of latent factors in data preprocessing and build a robust performance predictor based on customized domain-oriented loss functions. The performance of the proposed methods is verified by extensive experiments using SVR and RFR as well as theoretical analysis of the general performance bound.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

The cytochrome P450 2AA gene cluster in zebrafish (Danio rerio): Expression of CYP2AA1 and CYP2AA2 and response to phenobarbital-type inducers

The cytochrome P450 (CYP) 2 gene family is the largest and most diverse CYP gene family in vertebrates. In zebrafish, we have identified 10 genes in a new subfamily, CYP2AA, which does not show orthology to any human or other mammalian CYP genes. Here we report evolutionary and structural relationships of the 10 CYP2AA genes and expression of the first two genes, CYP2AA1 and CYP2AA2. Parsimony reconstruction of the tandem duplication pattern for the CYP2AA cluster suggests that CYP2AA1, CYP2AA2 and CYP2AA3 likely arose in the earlier duplication events and thus are most diverged in function from the other CYP2AAs. On the other hand, CYP2AA8 and CYP2AA9 are genes that arose in the latest duplication event, implying functional similarity between these two CYPs. A molecular model of CYP2AA1 showing the sequence conservation across the CYP2AA cluster reveals that the regions with the highest variability within the cluster map onto CYP2AA1 near the substrate access channels, suggesting differing substrate specificities. Zebrafish CYP2AA1 transcript was expressed predominantly in the intestine, while CYP2AA2 was most highly expressed in the kidney, suggesting differing roles in physiology. In the liver CYP2AA2 expression but not that of CYP2AA1, was increased by 1,4-bis [2-(3,5-dichloropyridyloxy)] benzene (TCPOBOP) and, to a lesser extent, by phenobarbital (PB). In contrast, pregnenolone 16α-carbonitrile (PCN) increased CYP2AA1 expression, but not CYP2AA2 in the liver. The results identify a CYP2 subfamily in zebrafish that includes genes apparently induced by PB-type chemicals and PXR agonists, the first concrete in vivo evidence for a PB-type response in fish. - Highlights: • A tandemly duplicated cluster of ten CYP2AA genes was described in zebrafish. • Parsimony and duplication analyses suggest pathways to CYP2AA diversity. • Homology models reveal amino acid positions possibly related to functional diversity. • The CYP2AA locus does not share synteny with any CYP2 subfamily in mammals. • Induction of CYP2AA1 and CYP2AA2 indicates a phenobarbital-type response in fish.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

A primer on artificial intelligence in plant digital phenomics: embarking on the data to insights journey

Artificial intelligence (AI) has emerged as a fundamental component of global agricultural research that is poised to impact on many aspects of plant science. In digital phenomics, AI is capable of learning intricate structure and patterns in large datasets. We provide a perspective and primer on AI applications to phenome research. We propose a novel human-centric explainable AI (X-AI) system architecture consisting of data architecture, technology infrastructure, and AI architecture design. We clarify the difference between post hoc models and 'interpretable by design' models. We include guidance for effectively using an interpretable by design model in phenomic analysis. We also provide directions to sources of tools and resources for making data analytics increasingly accessible. In conclusion, this primer is accompanied by an interactive online tutorial.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Directing Charge Carriers and Ferroelectric Domains at Lateral Interfaces in van der Waals Heterostructures

Emergent phenomena in traditional ferroelectrics are frequently observed at heterointerfaces. Accessing such functionalities in van der Waals ferroelectrics requires the formation of layered heterostructures, either vertically stacked (similar to oxide ferroelectrics) or laterally stitched (without equivalent in 3D-crystals). Here, we investigate lateral heterostructures of the ferroelectric van der Waals semiconductors SnSe and SnS. A two-step process produces ultrathin crystals comprising an SnSe core laterally joined to an SnS edge-band, as confirmed by Raman spectroscopy, transmission electron microscopy (TEM) imaging, and electron diffraction. TEM shows a moiré pattern across the SnSe core due to coverage by an ultrathin SnS layer. The ability of the lateral interface (IF) to direct excited carriers, probed by cathodoluminescence, shows electron transfer over 560 nm diffusion length from the SnS edge-band. Large, thin flakes supporting ferroelectricity allow investigating domains and domain wall interactions in uniform crystals and lateral heterostructures. Polarized optical microscopy of sub-20 nm flakes consistently shows ⟨110⟩ oriented stripe domains with mirror-twin domain walls. Heterostructures adopt two domain configurations, with domains either constrained to the SnSe core or propagating across the entire SnSe–SnS flakes. Furthermore, the combined results demonstrate multifunctional van der Waals heterostructures with high-quality IFs presenting extraordinary opportunities for manipulating carrier flows and ferroelectric domain patterns.

2D ferroelectrics↗
DOE OSTI2024

2024 roadmap on magnetic microscopy techniques and their applications in materials science

Considering the growing interest in magnetic materials for unconventional computing, data storage, and sensor applications, there is active research not only on material synthesis but also characterisation of their properties. In addition to structural and integral magnetic characterisations, imaging of magnetisation patterns, current distributions and magnetic fields at nano- and microscale is of major importance to understand the material responses and qualify them for specific applications. In this roadmap, we aim to cover a broad portfolio of techniques to perform nano- and microscale magnetic imaging using superconducting quantum interference devices, spin centre and Hall effect magnetometries, scanning probe microscopies, x-ray- and electron-based methods as well as magnetooptics and nanoscale magnetic resonance imaging. The roadmap is aimed as a single access point of information for experts in the field as well as the young generation of students outlining prospects of the development of magnetic imaging technologies for the upcoming decade with a focus on physics, materials science, and chemistry of planar, three-dimensional and geometrically curved objects of different material classes including two-dimensional materials, complex oxides, semi-metals, multiferroics, skyrmions, antiferromagnets, frustrated magnets, magnetic molecules/nanoparticles, ionic conductors, superconductors, spintronic and spinorbitronic materials.

2D materials↗
DOE OSTI2014

Application of small-angle neutron scattering to the study of forces between magnetically chained monodisperse ferrofluid emulsion droplets

The optical magnetic chaining technique (MCT) developed by Leal-Calderon, Bibette and co-workers in the 1990 s allows precise measurements of force profiles between droplets in monodisperse ferrofluid emulsions. However, the method lacks an in-situ determination of droplet size and therefore requires the combination of separately acquired measurements of droplet chain periodicity versus an applied magnetic field from optical Bragg scattering and droplet diameter inferred from dynamic light scattering (DLS) to recover surface force-distance profiles between the colloidal particles. Compound refractive lens (CRL) focussed small-angle scattering (SANS) MCT should result in more consistent measurements of droplet size (form factor measurements in the absence of field) and droplet chaining period (from structure factor peaks when the magnetic field is applied); and, with access to shorter length scales, extend force measurements to closer approaches than possible by optical measurements. We report on CRL-SANS measurements of monodisperse ferrofluid emulsion droplets aligned in straight chains by an applied field perpendicular to the incident beam direction. Analysis of the scattering from the closely spaced droplets required algorithms that carefully treated resolution and its effect on mean scattering vector magnitudes in order to determine droplet size and chain periods to sufficient accuracy. At lower applied fields scattering patterns indicate structural correlations transverse to the magnetic field direction due to the formation of intermediate structures in early chain growth.

Colloid↗
DOE OSTI2018

Microscale-Resolution Thermal Mapping Using a Flexible Platform of Patterned Quantum Sensors

Here, temperature sensors with micro- and nanoscale spatial resolution have long been explored for their potential to investigate the details of physical systems at an unprecedented scale. In particular, the rapid miniaturization of transistor technology, with its associated steep boost in power density, calls for sensors that accurately monitor heating distributions. Here, we report on a simple and scalable fabrication approach, based on directed self-assembly and transfer-printing techniques, to constructing arrays of nanodiamonds containing temperature-sensitive fluorescent spin defects. The nano-particles are embedded within a low-thermal-conductivity matrix that allows for repeated use on a wide range of systems with minimal spurious effects. Additionally, we demonstrate access to a wide spectrum of array parameters ranging from sparser single-particle arrays, with the potential for quantum computing applications, to denser devices with 98 ± 0.8% yield and stronger photoluminescence signals, ideal for temperature measurements. With these, we experimentally reconstruct the temperature map of an operating coplanar waveguide to confirm the accuracy of these platforms.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Redox cycling-based detection of phenazine metabolites secreted from Pseudomonas aeruginosa in nanopore electrode arrays

The opportunistic pathogen Pseudomonas aeruginosa (P. aeruginosa) produces several redox-active phenazine metabolites, including pyocyanin (PYO) and phenazine-1-carboxamide (PCN), which are electron carrier molecules that also aid in virulence. In particular, PYO is an exclusive metabolite produced by P. aeruginosa, which acts as a virulence factor in hospital-acquired infections and is therefore a good biomarker for identifying early stage colonization by this pathogen. Here, we describe the use of nanopore electrode arrays (NEAs) exhibiting metal–insulator–metal ring electrode architectures for enhanced detection of these phenazine metabolites. The size of the nanopores allows phenazine metabolites to freely diffuse into the interior and access the working electrodes, while the bacteria are excluded. Consequently, highly efficient redox cycling reactions in the NEAs can be accessed by free diffusion unhindered by the presence of bacteria. This strategy yields low limits of detection, i.e. 10.5 and 20.7 nM for PYO and PCN, respectively, values far below single molecule pore occupancy, e.g. at 10.5 nM < n pore > ~ 0.082 per nanopore – a limit which reflects the extraordinary signal amplification in the NEAs. Furthermore, experiments that compared results from minimal medium and rich medium show that P. aeruginosa produces the same types of phenazine metabolites even though growth rates and phenazine production patterns differ in these two media. Here, the NEA measurement strategy developed here should be useful as a diagnostic for pathogens generally and for understanding metabolism in clinically important microbial communities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Large Angle Rocking Beam Electron Diffraction Utilizing Electron Direct Detector

Electron diffraction of a crystal is fundamentally a function of the potential of that crystal. The intensity of electron diffraction patterns is, as a result, sensitive to the charge density of atoms and bonding inside crystals. Experimentally, the traditional method to probe this information is quantitative Convergent Beam Electron Diffraction (CBED). Quantitative CBED or QCEBD is a method which uses dynamic diffraction theory to quantify CBED intensities and to extract information about crystal structure and bonding. The sensitivity of dynamical scattering is leveraged to measure crystal symmetry and crystal structure factors. At its limit, electron structure factors are measured at high accuracy allowing access to chemical bonding information, which corroborate theoretical calculations through multipole model refinements of the experimental charge density. The primary limit to QCBED is the requirement of a non-overlapping convergent beam. This subsequently limits QCBED to crystals with small unit cells which are stable under the focused probe.

Busch, Robert↗
DOE OSTI2025

Technical Background and Validation Report on the Residential Water Inhalation Risk Calculator Presented in the Risk Assessment Information System

Indoor air quality (IAQ) is critical for human health. Poor IAQ is linked to respiratory issues, cardiovascular diseases, and cancer. Indoor pollutants are emitted by typical household items such as cleaning products, personal care items, building materials, and tap water - an understudied volatile organic compound (VOC) source. This document presents the Residential Water Inhalation Risk Calculator (RWIRC), which estimates daily VOC exposure concentrations from various household water uses, such as showering and dishwashing, to assess exposure risks for the most vulnerable occupant. Integrated into the Risk Assessment Information System (RAIS) and sponsored by the US Department of Energy (DOE), the calculator divides a house into three compartments: shower, bathroom, and other spaces, accounting for daily water usage patterns and calculating VOC concentrations. Exposure data generated using the calculator can assist health assessors in estimating excess lifetime cancer risk (ELCR) and hazard index (HI) from VOC inhalation. Unlike traditional exposure models that utilize Andelman’s constant, the RWIRC continuously assesses variability in VOC concentrations and environmental conditions using differential equations to track VOC concentrations and air exchange between compartments. The calculator also provides unique volatilization fractions for each chemical and appliance, enhancing accuracy of the exposure concentration estimation. The RWIRC is accessible online and allows users to customize parameters (i.e., number of bathrooms, water temperature, and exhaust fan conditions) and input VOC characteristics (i.e., tap water and ambient air concentrations). This document provides a step-by-step guide on implementing the calculator. It also provides comparisons with the ATSDR-SHOWER calculator, using eight VOCs with varying physicochemical properties to reveal differences in algorithms and output concentrations. Simulations also assess how bathroom door positions and exhaust fan usage affect VOC exposure. The calculator results can enhance EPA risk screening levels for inhalation exposure to VOCs from tap water, offering a sophisticated tool for assessing inhalation risks and improving public health protection.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

OBSERVATIONAL SELECTION EFFECTS WITH GROUND-BASED GRAVITATIONAL WAVE DETECTORS

Ground-based interferometers are not perfect all-sky instruments, and it is important to account for their behavior when considering the distribution of detected events. In particular, the LIGO detectors are most sensitive to sources above North America and the Indian Ocean, and as the Earth rotates, the sensitive regions are swept across the sky. However, because the detectors do not acquire data uniformly over time, there is a net bias on detectable sources’ right ascensions. Both LIGO detectors preferentially collect data during their local night; it is more than twice as likely to be local midnight than noon when both detectors are operating. We discuss these selection effects and how they impact LIGO’s observations and electromagnetic (EM) follow-up. Beyond galactic foregrounds associated with seasonal variations, we find that equatorial observatories can access over 80% of the localization probability, while mid-latitudes will access closer to 70%. Facilities located near the two LIGO sites can observe sources closer to their zenith than their analogs in the south, but the average observation will still be no closer than 44° from zenith. We also find that observatories in Africa or the South Atlantic will wait systematically longer before they can begin observing compared to the rest of the world; though, there is a preference for longitudes near the LIGOs. These effects, along with knowledge of the LIGO antenna pattern, can inform EM follow-up activities and optimization, including the possibility of directing observations even before gravitational-wave events occur.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Insights Into Seismicity Associated With Flexibly Operating Enhanced Geothermal System From Real‐Time Distributed Acoustic Sensing

Enhanced Geothermal Systems (EGS) have the capacity to broaden the accessible resource pool for geothermal power generation. Traditionally viewed as a “baseload” resource, their flexible operation might also enable dispatchable load‐following generation and long‐term energy storage, aligning them with the evolving landscape of decarbonized electricity systems. However, increasing permeability and extracting energy during EGS operations can induce microseismic events; for many prior EGS efforts, some associated seismicity has been observed. While energetically beneficial, the flexibility of EGS operations prompts our inquiry into whether new types of operations will yield previously unseen seismicity patterns. We demonstrate the use of distributed acoustic sensing (DAS) with real‐time edge computing to monitor seismicity during a pilot test of a cyclically operated EGS facility at the Blue Mountain geothermal field. Our focus lies in uncovering seismicity insights from the real‐time microseismic catalog, particularly during load‐following dispatchability tests simulating flexible EGS operation. Here, we find that variations in pore pressure consistently correlate with seismicity, and that controlling pressure cycles during flexible operations appears to constrain microseismic activity during subsequent cycles. The spatio‐temporal evolution of microseismic clouds recorded during cyclic injection cycles fits diffusive models over our available observation period. Additionally, seismicity elevation lags behind pore pressure increases, likely due to pressure diffusion to the fracture system boundary. Through real‐time monitoring, we offer novel insights into seismicity associated with flexibly operating EGS. Our findings suggest that leveraging DAS and edge computing can inform EGS operations and help mitigate induced seismicity.

Chamarczuk, Michal [Rice Univ., Houston, TX (Unite↗
DOE OSTI2022

Direct observation of the dead-cone effect in quantum chromodynamics

In particle collider experiments, elementary particle interactions with large momentum transfer produce quarks and gluons (known as partons) whose evolution is governed by the strong force, as described by the theory of quantum chromodynamics (QCD). These partons subsequently emit further partons in a process that can be described as a parton shower, which culminates in the formation of detectable hadrons. Studying the pattern of the parton shower is one of the key experimental tools for testing QCD. This pattern is expected to depend on the mass of the initiating parton, through a phenomenon known as the dead-cone effect, which predicts a suppression of the gluon spectrum emitted by a heavy quark of mass m Q and energy E, within a cone of angular size m Q /E around the emitter. Previously, a direct observation of the dead-cone effect in QCD had not been possible, owing to the challenge of reconstructing the cascading quarks and gluons from the experimentally accessible hadrons. We report the direct observation of the QCD dead cone by using new iterative declustering techniques to reconstruct the parton shower of charm quarks. This result confirms a fundamental feature of QCD. Furthermore, the measurement of a dead-cone angle constitutes a direct experimental observation of the non-zero mass of the charm quark, which is a fundamental constant in the standard model of particle physics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Factors Affecting Override Behavior during Demand Flexibility from High-Resolution Smart Thermostat Data

In this study, we delineate key weather and demographic predictors of override behavior in residential buildings during connected thermostats demand response events. Anticipating and reducing overrides is critical to demand flexibility (DF) program success. We use high- dimensional fixed effects linear regression techniques on a large ecobee dataset for about 5,000 enrolled households in the United States. We identify critical weather (indoor and outdoor temperature), building (housing type), and occupant (previous DF overrides and previous DF event exposure) factors influencing the override patterns of customers during thermostat demand response. We also differentiate DF events by season to understand the different indoor and outdoor conditions that might influence seasonal override rates. We found significant differences in override rates between building types, with single-family semi-detached homes generally having the highest overrides. Having a history of overrides was additionally a critical factor in predicting occupant response to future DF events. Understanding these override differences is necessary for rural electric cooperatives and emerging DF programs without access to large DR historical data. Overall, we provide critical information on technical and local demographic characteristics that may be correlated to building type to influence strategies to reduce overrides and improve the adoption of DF technologies.

connected thermostats (CTs)↗
DOE OSTI2022

Constraining the release of Sn to the ambient melting point following shock loading using time-resolved x-ray diffraction

The formation of liquid following release from a shocked state governs the transition from spall to cavitation and the formation of ejecta in metals. In order to build physics-based models of these processes, it is necessary to critically evaluate the relative importance of kinetics and entropy generation during the release along with the accuracy of multiphase equations of state. Tin (Sn) has served as a testbed for a variety of experiments examining strength and ejecta due to its accessible melt boundary and solid–solid phase transitions. This work presents experiments examining the phase evolution of high purity Sn following the shock and release to ambient stress near the melting point. Sn is found to release to states between its ambient solidus and liquidus from approximately 19 to 33 GPa under uniaxial loading, with the two-phase region being characterized by a reduction in the intensity of the (220), (211) β -Sn doublet. Jetting experiments performed at 27–28 GPa exhibit comparable diffraction patterns with what is observed following the uniaxial release. The solid fractions of β-Sn in the ambient mixed phase region are found to decrease linearly with increasing shock stress as increasing liquid Sn is formed. Here, the results provide much needed information for interpreting measurements of dynamic strength at a high strain rate and experiments examining cavitation and shallow bubble collapse in Sn.

, spall↗
DOE OSTI2020

Improving qubit readout with hidden Markov models

We demonstrate the application of pattern recognition algorithms via hidden Markov models (HMM) for qubit readout. This scheme provides a state-path trajectory approach capable of detecting qubit-state transitions and makes for a robust classification scheme with higher starting-state assignment fidelity than when compared to a multivariate Gaussian or a support vector machine scheme. Therefore, the method also eliminates the qubit-dependent readout time optimization requirement in current schemes. Using a HMM state discriminator we estimate fidelities reaching the ideal limit. Unsupervised learning gives access to transition matrix, priors, and IQ distributions, providing a toolbox for studying qubit-state dynamics during strong projective readout.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Emulating 2D Materials with Magnons

Spin waves (magnons) in two-dimensional (2D) materials have received increasing interest due to their unique states and potential for tunability. However, many interesting features of these systems, including Dirac points and topological states, occur at high frequencies, where experimental probes are limited. Here, we study a crystal formed by patterning a hexagonal array of holes in a perpendicularly magnetized thin film. Through simulation, we find that the magnonic band structure imitates that of graphene, but additionally has some kagomelike character and includes a few flat bands. Surprisingly, its nature can be understood using a nine-band tight-binding Hamiltonian. This clear analogy to 2D materials enables band-gap engineering in 2D, topological magnons along 1D phase boundaries, and spectrally isolated modes at 0D point defects. Interestingly, the 1D phase boundaries allow access to the valley degree of freedom through a magnonic analog of the quantum valley Hall insulator. These approaches can be extended to other magnonic systems, but are potentially more general due to the simplicity of the model, which resembles existing results from electron, phonon, photon, and cold-atom systems. This finding brings the physics of spin waves in 2D materials to more experimentally accessible scales, augments it, and outlines a few principles for controlling magnonic states.

Ferrimagnets↗