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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 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Comparative life cycle analysis on ethylene production from electrocatalytic reduction of carbon dioxide

Ethylene is one of the largest greenhouse gas emitters and the most diversly used commodity chemicals globally. Electrocatalytic reduction of CO 2 to ethylene received great attention from the research society to decarbonize the ethylene production. Here, in this study, a life-cycle analysis is conducted using the Greenhouse Gases, Regulated Emissions, and Energy use in Technologies (GREET) model on the three electrocatalytic CO 2 -reduction pathways (or “e-ethylene” pathways): i) cascade conversion via carbon monoxide intermediate; ii) single-step conversion in membrane electrode assembly (MEA); and iii) single-step conversion in alkaline flow cell. The results showed that the electricity consumption is the lowest for the cascade pathway (164 MJ/kg), thus resulting in the lowest cradle-to-gate carbon intensity [18 kgCO 2 e/kg with United States (US) average grid)] among the three pathways followed by the single-step MEA (32 kgCO 2 e/kg) and then by the single-step alkaline (56 kgCO 2 e/kg). However, all three e-ethylene pathways were significantly more carbon-intensive than their fossil-based counterpart (1.1 kgCO 2 e/kg) due to their excessive energy consumption with the current state of technology. With renewable electricity, all three pathways yielded negative carbon intensity: from -3.1 kgCO 2 e/kg to -1.6 kgCO 2 e/kg depending on the source of CO 2 . The threshold carbon intensity of electricity (TCIE), defined as the upper bound of the carbon intensity of electricity to achieve lower carbon intensity for e-ethylene compared to fossil-based ethylene, is calculated for both current and future state of e-ethylene technologies. The cascade pathway had the highest TCIE out of the three e-ethylene pathways for both current (92 gCO 2 e/kWh) and future (124 gCO 2 e/kWh) state of technologies. However, the carbon intensity of average US grid (i.e., 467 and 303 gCO 2 e/kWh for current and future projections) were higher than the TCIEs of the corresponding timeline. Thus, reducing electricity requirement for e-ethylene pathways and bringing low-carbon generation mix in the United States (US) grid faster than the current projection are both essential to decarbonize ethylene and its downstream chemicals/polymers.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Surface chemical trapping of optical cycling centers

Quantum information processors based on trapped atoms utilize laser-induced optical cycling transitions for state preparation and measurement. These transitions consist of an electronic excitation from the ground to an excited state and a decay back to the initial ground state, associated with a photon emission. While this technique has been used primarily with atoms, it has also recently been shown to work for some divalent metal hydroxides ( e.g. SrOH) and alkoxides ( e.g. SrOCH 3 ). Additionally, this extension to molecules is possible because these molecules feature nearly isolated, atomic-like ground and first-excited electronic states centered on the radical metal atom. We theoretically investigate the extension of this idea to a larger scale by growing the alkyl group, R, beyond the initial methyl group, CH 3 , while preserving the isolated and highly vertical character of the electronic excitation on the radical metal atom, M. Theory suggests that in the limit as the size of the ligand carbon chain increases, it can be considered a functionalized diamond (or cubic boron nitride) surface. Several requirements must be observed for the cycling centers to function when bound to the surface. First, the surface must have a significant band gap that fully encapsulates both the ground and excited states of the cycling center. Second, while the surface lattice imposes strict limits on the achievable spacing between the SrO– groups, at high coverage, SrO– centers can interact, and show geometric changes and/or electronic state mixing. We show that the coverage of the diamond surface with SrO– cycling centers needs to be significantly sub-monolayer for the functionality of the cycling center to be preserved. Having the lattice-imposed spatial control of SrO– placements will allow nanometer-scale proximity between qubits and will eliminate the need for atom traps for localized cycling emitters. Our results also imply that a functionalization could be done on a scanning microscope tip for local quantum sensing or on photonic structures for optically-mediated quantum information processing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Soil organic carbon is not just for soil scientists: measurement recommendations for diverse practitioners

Soil organic carbon (SOC) regulates terrestrial ecosystem functioning, provides diverse energy sources for soil microorganisms, governs soil structure, and regulates the availability of organically bound nutrients. Investigators in increasingly diverse disciplines recognize how quantifying SOC attributes can provide insight about ecological states and processes. Today, multiple research networks collect and provide SOC data, and robust, new technologies are available for managing, sharing, and analyzing large data sets. Here, we advocate that the scientific community capitalize on these developments to augment SOC data sets via standardized protocols. We describe why such efforts are important and the breadth of disciplines for which it will be helpful, and outline a tiered approach for standardized sampling of SOC and ancillary variables that ranges from simple to more complex. We target scientists ranging from those with little to no background in soil science to those with more soil-related expertise, and offer examples of the ways in which the resulting data can be organized, shared, and discoverable.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Signaling snapshots of a serotonin receptor activated by the prototypical psychedelic LSD

Serotonin (5-hydroxytryptamine [5-HT]) 5-HT2-family receptors represent essential targets for lysergic acid diethylamide (LSD) and all other psychedelic drugs. Although the primary psychedelic drug effects are mediated by the 5-HT 2A serotonin receptor (HTR2A), the 5-HT 2B serotonin receptor (HTR2B) has been used as a model receptor to study the activation mechanisms of psychedelic drugs due to its high expression and similarity to HTR2A. Here, in this study, we determined the cryo-EM structures of LSD-bound HTR2B in the transducer-free, Gq-protein-coupled, and β-arrestin-1-coupled states. These structures provide distinct signaling snapshots of LSD’s action, ranging from the transducer-free, partially active state to the transducer-coupled, fully active states. Insights from this study will both provide comprehensive molecular insights into the signaling mechanisms of the prototypical psychedelic LSD and accelerate the discovery of novel psychedelic drugs.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Molecular mechanism of biased signaling at the kappa opioid receptor

The κ-opioid receptor (KOR) has emerged as an attractive drug target for pain management without addiction, and biased signaling through particular pathways of KOR may be key to maintaining this benefit while minimizing side-effect liabilities. As for most G protein-coupled receptors (GPCRs), however, the molecular mechanisms of ligand-specific signaling at KOR have remained unclear. To better understand the molecular determinants of KOR signaling bias, we apply structure determination, atomic-level molecular dynamics (MD) simulations, and functional assays. We determine a crystal structure of KOR bound to the G protein-biased agonist nalfurafine, the first approved KOR-targeting drug. We also identify an arrestin-biased KOR agonist, WMS-X600. Using MD simulations of KOR bound to nalfurafine, WMS-X600, and a balanced agonist U50,488, we identify three active-state receptor conformations, including one that appears to favor arrestin signaling over G protein signaling and another that appears to favor G protein signaling over arrestin signaling. These results, combined with mutagenesis validation, provide a molecular explanation of how agonists achieve biased signaling at KOR.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Complexity-calibrated benchmarks for machine learning reveal when prediction algorithms succeed and mislead

Abstract Recurrent neural networks are used to forecast time series in finance, climate, language, and from many other domains. Reservoir computers are a particularly easily trainable form of recurrent neural network. Recently, a “next-generation” reservoir computer was introduced in which the memory trace involves only a finite number of previous symbols. We explore the inherent limitations of finite-past memory traces in this intriguing proposal. A lower bound from Fano’s inequality shows that, on highly non-Markovian processes generated by large probabilistic state machines, next-generation reservoir computers with reasonably long memory traces have an error probability that is at least $$\sim 60\%$$ ∼ 60 % higher than the minimal attainable error probability in predicting the next observation. More generally, it appears that popular recurrent neural networks fall far short of optimally predicting such complex processes. These results highlight the need for a new generation of optimized recurrent neural network architectures. Alongside this finding, we present concentration-of-measure results for randomly-generated but complex processes. One conclusion is that large probabilistic state machines—specifically, large $$\epsilon$$ ϵ -machines—are key to generating challenging and structurally-unbiased stimuli for ground-truthing recurrent neural network architectures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Cryo-EM structure determination of small therapeutic protein targets at 3 Å-resolution using a rigid imaging scaffold

Cryoelectron microscopy (Cryo-EM) has enabled structural determination of proteins larger than about 50 kDa, including many intractable by any other method, but it has largely failed for smaller proteins. Here, we obtain structures of small proteins by binding them to a rigid molecular scaffold based on a designed protein cage, revealing atomic details at resolutions reaching 2.9 Å. We apply this system to the key cancer signaling protein KRAS (19 kDa in size), obtaining four structures of oncogenic mutational variants by cryo-EM. Importantly, a structure for the key G12C mutant bound to an inhibitor drug (AMG510) reveals significant conformational differences compared to prior data in the crystalline state. The findings highlight the promise of cryo-EM scaffolds for advancing the design of drug molecules against small therapeutic protein targets in cancer and other human diseases.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Particle-in-cell modeling of electron beam generated plasma

Plasmas generated using energetic electron beams are well known for their low electron temperature (T e ) and plasma potential, which makes them attractive for atomic-precision plasma processing applications such as atomic layer etch and deposition. A 2-dimensional particle-in-cell model for an electron beam-generated plasma in argon confined by a constant applied magnetic field is described here in this article. Plasma production primarily occurs in the path of the beam electrons in the center of the chamber. The resulting plasma spreads out in the chamber through non-ambipolar diffusion with a short-circuiting effect allowing unequal electron and ion fluxes to different regions of the bounding conductive chamber walls. The cross-field transport of the electrons (and thus the steady-state characteristics of the plasma) are strongly impacted by the magnetic field. T e is anisotropic in the electron beam region, but low and isotropic away from the plasma production zone. The plasma density increases and the plasma becomes more confined near the region of production when the magnetic field strengthens. The magnetic field reduces both electron physical and energy transport perpendicular to the magnetic field. T e is uniform along the magnetic field lines and slowly decreases perpendicular to it. Electrons are less energetic in the sheath regions where the sheath electric field repels and confines the low-energy electrons from the bulk plasma. Even though electron and ion densities are similar in the bulk plasma due to quasi-neutrality, electron and ion fluxes on the grounded chamber walls are unequal at most locations. Electron confinement by the magnetic field weakens with increasing pressure, and the plasma spread out farther from the electron beam region.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Learning to classify quantum phases of matter with a few measurements

We study the identification of quantum phases of matter, at zero temperature, when only part of the phase diagram is known in advance. Following a supervised learning approach, we show how to use our previous knowledge to construct an observable capable of classifying the phase even in the unknown region. By using a combination of classical and quantum techniques, such as tensor networks, kernel methods, generalization bounds, quantum algorithms, and shadow estimators, we show that, in some cases, the certification of new ground states can be obtained with a polynomial number of measurements. An important application of our findings is the classification of the phases of matter obtained in quantum simulators, e.g. cold atom experiments, capable of efficiently preparing ground states of complex many-particle systems and applying simple measurements, e.g. single qubit measurements, but unable to perform a universal set of gates.

quantum machine learning↗
DOE OSTI2026

Mesogenesis through the ephemeral dark decay of Beauty

Mesogenesis provides a path for generating the baryon asymmetry of the Universe, using only the CP violation furnished by the Standard Model in the decay of B mesons. While this is an intriguing possibility, it is largely constrained by the data on B meson branching fractions into baryons and missing energy carried into the dark sector. We point out that it is possible to make this branching fraction dominant only in the early Universe, through an ultralight scalar coupled to the dark sector and the Standard Model leptons. A scenario is examined where the thermal density of muons in the early Universe temporarily lowers the mass of a dark fermion, allowing for efficient B meson decays. This `dark’ decay channel is shut off later when the muon number density falls, making the scenario compatible with flavor data. Our model can be consistent with the LHC constraints on color-charged heavy bosons required to implement Mesogenesis; such states may be discovered in the future runs as their masses cannot be far above the current bounds. We also outline other possible signals, which can arise in future displaced vertex searches, long range force searches, and observations of neutron star binary mergers.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Past-completeness of inflationary spacetimes

Here, we discuss the question of whether or not inflationary spacetimes can be geodesically complete in the infinite past. Geodesic completeness is a necessary condition for averting an initial singularity during eternal inflation. It is frequently argued that cosmological models which are expanding sufficiently fast (having average Hubble expansion rate H avg > 0) must be incomplete in null and timelike past directions. This well-known conjecture relies on specific bounds on the integral of the Hubble parameter over a past- directed timelike or null geodesic. As stated, we show this claim is an open issue. We show that the calculation of H avg yields a continuum of results for a given spacetime predicated upon the underlying topological assumptions. We present an improved definition for H avg and introduce an uncountably infinite cohort of cosmological solutions which are geodesically complete despite having H avg > 0. We discuss a standardized definition for inflationary spacetimes as well as quantum (semiclassical) cosmological concerns over physically reasonable scale factors.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Photovoltaic Inverter Failure Mechanism Estimation Using Unsupervised Machine Learning and Reliability Assessment

This article introduces a data-driven approach to assessing failure mechanisms and reliability degradation in outdoor photovoltaic (PV) string inverters. The manufacturer's stated PV inverter lifetime can vary due to the impact of operating site conditions. To address limitations in degradation estimation through accelerated testing, condition monitoring, or degradation modeling, we propose a machine learning (ML) oriented approach. Utilizing data from a 1.4 MW PV power plant operational since 2016, with 46 string PV inverters tied to the grid, we employ the unsupervised one-class support vector machine ML technique to analyze inverter and sensor data, capable of classifying humidity cycling and temperature fluctuations as dominant failure mechanisms. Utilizing the anomaly alert relationship and alert details specific to the inverter, the level of PV inverter output is considered as its availability or available reliability. Subsequently, a continuous Markov model is applied to six-month alert data, revealing an average stated reliability of 20% after 20 years of continuous operation. These results support recommendations for time-bound preventive measures to enhance PV inverter reliability under diverse outdoor conditions. Furthermore, the approach provides a nondestructive, top–down, and generalized method for analyzing any commercial PV inverter exposed to outdoor conditions, contingent on the availability of relevant data.

14 SOLAR ENERGY↗
DOE OSTI2025

A membrane-based approach to medical isotope purification (Final Report)

This is the final technical report from the grant "A membrane-based approach to medical isotope purification" which was awarded by the Isotope Research and Development Program through the early career research program to Christine Duval at Case Western Reserve University. The project developed adsoprtive membranes with covalently bound diglycolamide-derived ligands for the purification of Ac-225 and benchmarked them against the current state of the art adsorbent materials.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2023

Iodide uptake by forest soils is principally related to the activity of extracellular oxidases

129 I is a nuclear fission decay product of concern because of its long half-life (16 Ma) and propensity to bioaccumulate. Microorganisms impact iodine mobility in soil systems by promoting iodination (covalent binding) of soil organic matter through processes that are not fully understood. Here, we examined iodide uptake by soils collected at two depths (0–10 and 10–20 cm) from 5 deciduous and coniferous forests in Japan and the United States. Autoclaved soils, and soils amended with an enzyme inhibitor (sodium azide) or an antibacterial agent (bronopol), bound significantly less 125 I tracer (93%, 81%, 61% decrease, respectively) than the untreated control soils, confirming a microbial role in soil iodide uptake. Correlation analyses identified the strongest significant correlation between 125 I uptake and three explanatory variables, actinobacteria soil biomass ( p = 6.04E-04, 1.35E-02 for Kendall-Tau and regression analysis, respectively), soil nitrogen content ( p = 4.86E-04, 4.24E-03), and soil oxidase enzyme activity at pH 7.0 using the substrate L-DOPA ( p = 2.83E-03, 4.33E-04) and at pH 5.5 using the ABTS ( p = 5.09E-03, 3.14E-03). Together, the results suggest that extracellular oxidases, primarily of bacterial origin, are the primary catalyst for soil iodination in aerobic, surface soils of deciduous and coniferous forests, and that soil N content may be indicative of the availability of binding sites for reactive iodine species.

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

A General Framework for Error-controlled Unstructured Scientific Data Compression

Data compression plays a key role in reducing storage and I/O costs. Traditional lossy methods primarily target data on rectilinear grids and cannot leverage the spatial coherence in unstructured mesh data, leading to suboptimal compression ratios. We present a multi-component, error-bounded compression framework designed to enhance the compression of floating-point unstructured mesh data, which is common in scientific applications. Our approach involves interpolating mesh data onto a rectilinear grid and then separately compressing the grid interpolation and the interpolation residuals. This method is general, independent of mesh types and typologies, and can be seamlessly integrated with existing lossy compressors for improved performance. We evaluated our framework across twelve variables from two synthetic datasets and two real-world simulation datasets. The results indicate that the multi-component framework consistently outperforms state-of-the-art lossy compressors on unstructured data, achieving, on average, a 2.3 − 3.5× improvement in compression ratios, with error bounds ranging from 1 × 10 the −6 to 1×10−2. We further investigate impact of hyperparameters, such as grid spacing and error allocation, to deliver optimal compression ratios in diverse datasets.

Gong, Qian↗
DOE OSTI2023

Converging towards atomic and nuclear pressures (Final Report)

his report details the development of transformational tools and techniques, allowing the accurate characterization of matter at the most extreme conditions yet studied in the high energy density (HED) domain. Before this work, most experiments quantitatively mapping the nature of matter in the HED realm were performed using planar geometry, which allows for the isolation and measurement of variables in a single thermodynamic state. Such measurements include equation of state variables, optical conductivity, heat transport and more. However, due to a variety of plasma processes, such experiments are limited to below ~10 TPa (100 Mbar) pressures. To achieve higher pressures, convergent experiments are needed. Historically, convergent experiments have not been used for benchmark data because they are integral measurements. That is each part of a convergent target undergoes a time dependent wide range of states, making it difficult to accurately isolate any particular quantity for a given thermodynamic state. This effort developed innovative convergent HED platforms and techniques enabling the exploration of matter from atomic to nuclear scale pressures. This effort also performed pioneering experiments that yielded the first rigorous benchmark data at these extreme conditions. This funding award began with the overarching goal to understand the behavior of matter at extreme (atomic-to-nuclear scale) pressures. The motivation for these goals lie in the fact that every time scientists explore matter beyond the threshold of an atomic unit, there is a fundamental shift in science. The atomic unit for energy, mass, charge, length, and time have each been explored, and each time such a threshold was crossed, a new sequence of discoveries was made resulting in significant awards such as the Nobel Prize. The only unexplored atomic unit is pressure, and this effort set the course for exploring matter at and beyond such pressures. That most of the recently discovered extrasolar planets and stars, as well as matter in the late implosion stages of inertial fusion targets, have deep internal pressures at and beyond atomic pressures amplifies the importance of this effort. Much of the initial work in developing techniques to create these atomic-to-nuclear pressures already existed within the HED community, predominantly at large scale laser facilities such as the National Ignition Facility (NIF) and the Omega60 laser the University of Rochester and although these experiments were routinely performed the ability to extract information about the underlying physical states and processes remained elusive due to the complexity of the experiments, extreme scales in both time and space, and the integrated nature of all the measurements. This work built a rigorous framework so such measurements can routinely be made. This was done in part through the introduction of Bayesian inference techniques into the field of HED science. These techniques allow for the self-consistent extraction of the relevant variables and their explicit and implicit correlations, so as to make use of integrated experimental data to constrain physical models and provide accurate uncertainty bounds for the data. The techniques developed here are fully transparent and proved immediately useful providing quantitative rigorous benchmarks for physical states and processes at some of the most extreme conditions yet explored on Earth. This funding is directly or partly responsible for 7 publications in major peer-reviewed scientific journals, a doctoral thesis, 3 invited talks at major conferences, and the training of a post-doc, 2 graduate students, and 1 undergraduate student. Beyond the effort supported by this award launched the introduction of Bayesian inference into the HED physics community and helped push the usage if modern data-science techniques within the physics community at large.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Tetraquark Production by Intrinsic Charm

A number of new four-quark states containing from one to four c or ̅c quarks have been observed recently. Many of these new states have been discovered at the LHC. The production of these states via intrinsic charm in the proton is investigated. The tetraquark masses obtained in this approach, agree well with the measured masses. These calculations can provide some insight into the nature of the tetraquark candidates, whether as a bound meson pair or as a looser configuration of four individual partons which can influence their interactions in nuclear medium, such as in heavy-ion collisions. The kinematic distributions of these states as a function of y and pT are also studied. The possible cross sections for these states are also considered.

Vogt, Ramona [Lawrence Livermore National Laborato↗
DOE OSTI2021

Fragile Topology and Flat-Band Superconductivity in the Strong-Coupling Regime

In flat bands, superconductivity can lead to surprising transport effects. The superfluid “mobility”, in the form of the superfluid weight D s , does not draw from the curvature of the band but has a purely band-geometric origin. In a mean-field description, a nonzero Chern number or fragile topology sets a lower bound for D s , which, via the Berezinskii-Kosterlitz-Thouless mechanism, might explain the relatively high superconducting transition temperature measured in magic-angle twisted bilayer graphene (MATBG). For fragile topology, relevant for the bilayer system, the fate of this bound for finite temperature and beyond the mean-field approximation remained, however, unclear. Here, we numerically use exact Monte Carlo simulations to study an attractive Hubbard model in flat bands with topological properties akin to those of MATBG. We find a superconducting phase transition with a critical temperature that scales linearly with the interaction strength. Then, we investigate the robustness of the superconducting state to the addition of trivial bands that may or may not trivialize the fragile topology. Our results substantiate the validity of the topological bound beyond the mean-field regime and further stress the importance of fragile topology for flat-band superconductivity.

2-dimensional systems↗