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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 343 records · Page 19

Challenges resulting from urban density and climate change for the EU energy transition

Dense urban morphologies further amplify extreme climate events due to the urban heat island phenomenon, rendering cities more vulnerable to extreme climate events. Here we develop a modelling framework using multi-scale climate and energy system models to assess the compound impact of future climate variations and urban densification on renewable energy integration for 18 European cities. We observe a marked change in wind speed and temperature due to the aforementioned compound impact, resulting in a notable increase in both peak and annual energy demand. Therefore, an additional cost of 20–60% will be needed during the energy transition (without technology innovation in building) to guarantee climate resilience. Failure to consider extreme climate events will lower power supply reliability by up to 30%. Here, energy infrastructure in dense urban areas of southern Europe is more vulnerable to the compound impact, necessitating flexibility improvements at the design phase when improving renewable penetration levels.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Photochemistry of Oxygen Compounds in Neptune's Stratosphere

ISO SWS observations of H2O and CO2 on Neptune (Feuchtgruber et al. 1997, Nature 389, 159) coupled with ground based millimeter observations of CO (Marten et al., 1993, Ap. J. 406 285) provide strong constraints on the photochemistry of these compounds in Neptune's stratosphere. Additional constraints on the photochemistry and vertical mixing come from the rich suite of hydrocarbons observed by ISO: CH4, C2H2, C2H6 (Bezard, 1998, Ann. Geophysicae 16, Sup. III C1037), CH3 (Bezard, et al. Ap. J. 515, 868), and C2H4 (Encrenaz et al. this DPS). We will use a one-dimensional global average photochemical model to analyze these compounds. In particular, we will better constrain the estimated external flux of H2O to Neptune's stratosphere given in Feuchtgruber et al., which is important in understanding the source of the observed stratospheric CO2. Kingdoms will come and go, the relentless march of time will continue, all will be explained.

Romani, P. N.↗

Transport Upscaling under Flow Heterogeneity and Matrix-Diffusion in Three-Dimensional Discrete Fracture Networks

For this work, we investigate the combined effects of network scale flow variability and retention due to matrix-diffusion on the scaling behavior of transport through fractured media. Two of the principal mechanisms controlling the transport of solutes through fractured low-permeability media are broad distributions of flow velocities and retention times in the solid matrix. We study the relative impact of these two processes under different initial conditions using a set of three-dimensional discrete fracture network simulations. We use these simulations to develop and calibrate an upscaled continuous time random walk (CTRW) approach for advective transport based on an Ornstein-Uhlenbeck model for the particle velocities that accounts for the fracture-matrix coupling using a compound Poisson process. This CTRW model can be conditioned on the initial solute distribution and allows to observe late-time scaling behavior at distances beyond what is feasible to observe using high-fidelity direct numerical simulations. We determine that the initial distribution of particles leads to marked differences in the persistent long-term scale behavior in the solute travel time distributions, even those undergoing retention due to matrix diffusion through implementation and analysis of the model.

54 ENVIRONMENTAL SCIENCES↗

Modeling Phase Equilibrium of Common Sugars Glucose, Fructose, and Sucrose in Mixed Solvents

The industrial processing of sugars and sugar-containing mixtures is gaining widespread use as a form of renewable manufacturing from biomass. To aid in process modeling for design and optimization, a commonly available thermodynamic model is needed that describes the phase equilibrium of these compounds. This work compiles and compares models for solid–liquid and vapor–liquid phase equilibrium from the available data for the representative sugars glucose, fructose, and sucrose in the representative solvents water, methanol, and ethanol, including data for multisugar, multisolvent systems. Additionally, the nonrandom two-liquid (NRTL) model was chosen for these systems because of its widespread use in industry and the availability of parameters for many solvents and cosolutes. The association-NRTL (aNRTL) model was investigated as an improvement for modeling sugars, which may experience a high degree of association because of their many hydroxy groups. Both models accurately capture the data and are able to predict the behavior of multisugar systems with only solute–solvent interaction parameters. The aNRTL model shows an improvement over the baseline NRTL model that is most significant for sucrose, the component with the highest association strength, and least significant for fructose, which has the lowest association strength.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Coupled dimer and bond-order-wave order in the quarter-filled one-dimensional Kondo lattice model

Motivated by experiments on the organic compound (Per) 2 [Pt(mnt) 2 ], we study the ground state of the onedimensional Kondo lattice model at quarter filling with the density matrix renormalization group method. Here, we show a coupled dimer and bond-order-wave (BOW) state in the weak-coupling regime for the localized spins and itinerant electrons, respectively. The quantum phase transitions for the dimer and the BOW orders occur at the same critical coupling parameter J c , with the opening of a charge gap. The emergence of the combination of dimer and BOW order agrees with the experimental findings of the simultaneous Peierls and spin-Peierls transitions at low temperatures, which provides a theoretical understanding of such a phase transition. We also show that the localized spins in this insulating state have quasi-long-ranged spin correlations with collinear configurations, which resemble the classical dimer order in the absence of a magnetic order.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Kinetic model-based group contribution method for derived cetane number prediction of oxygenated fuel components and blends

A four-step autoignition model was used to derive an expression for the ignition delay (ID) measured in ignition quality testers (IQT) with the derived cetane number (DCN) determined from this ID using the ASTM D6890 standard correlation. The model predicts DCN for individual compounds and blends as a function of each compound's global initiation and net chain branching rate constants. Expressions for these values were determined assuming they could be related to the functional groups present in each compound. Measurement data for 125 compounds and 94 binary and ternary blends (including oxygenates: alcohols, aldehydes, esters, ethers, and ketones), from literature and from measurements performed in our lab, were used to obtain the dependence of the measured ignition delay on each functional group. The new kinetic model-based group contribution method was able to predict the ignition delay of both pure compounds and blends, with an average DCN error of 4.4 (19%) and 2.8 (11%), respectively. Here, the blend model was also used to develop an ID mixing rule by incorporating existing IQT ignition delay data for each compound. Use of the mixing rule gave an average DCN error of 3.6 (16%) for blends. Both the blend model and mixing rule were found to be superior compared to standard linear by volume fraction or mole fraction mixing rules commonly used to estimate the DCN of mixtures.

42 ENGINEERING↗

Floquet engineering of Kitaev quantum magnets

Abstract In recent years, there has been an intense search for materials realizing the Kitaev quantum spin liquid model. A number of edge-shared compounds with strong spin-orbit coupling, such as RuCl 3 and iridates, have been proposed to realize this model. Nevertheless, an effective spin Hamiltonian derived from the microscopic model relevant to these compounds generally contains terms that are antagonistic toward the quantum spin liquid. This is consistent with the fact that the zero magnetic field ground state of these materials is generally magnetically ordered. It is a pressing issue to identify protocols to drive the system to the limit of the Kitaev quantum spin model. In this work, we propose Floquet engineering of these Kitaev quantum magnets by coupling materials to a circularly polarized laser. We demonstrate that all the magnetic interactions can be tuned in situ by the amplitude and frequency of the laser, hence providing a route to stabilize the Kitaev quantum spin liquid phase.

36 MATERIALS SCIENCE↗

A numerical study of the meso-structure variability in the compaction process of prepreg platelet molded composites

Compaction deformations in a thermoplastic composite system molded from chopped prepreg platelets were analyzed to obtain statistical distributions of local distortions that define the final consolidated meso-structure. This study provides an insight into and allows quantification of the intrinsic geometric variability of the composite meso-structure that controls the variability of the effective composite mechanical properties. A two-phase viscoelastic finite element model was utilized to treat the behavior of molten prepreg platelets, which were assumed to be incompressible and inextensible in the fiber direction during processing. A two-step simulation procedure with discretely modeled platelets and platelet-to-platelet contacts is proposed. The analysis begins with a drop simulation of the uncontrolled material deposition followed by a 3D finite element analysis of the preform compaction and bulk material flow. The proposed model provides a method for generating a composite meso-structure ab initio starting from a statistical sampling of the initial conditions for platelet deposition. The predicted platelet thickness distribution, intra-platelet fiber waviness and out-of-plane platelet undulations were found to be in good agreement with experimental measurements. An estimate of the volume of resin pockets was inferred from the compaction simulation.

36 MATERIALS SCIENCE↗

Integrated hydrological, power system and economic modelling of climate impacts on electricity demand and cost

Impacts of climate-related water stress and temperature changes can cascade through energy systems, although models have yet to capture this compounding of effects. Here, we employ a coupled water–power–economy model to capture these important interactions in a study of the exceedance of water temperature thresholds for power generation in the western United States. We find that not all reductions in reserve electricity-generation capacity result in impacts, and that when they occur, intermittent interruptions in electricity supply at critical times of the day, week and year account for much of the economic impacts. Finally, we find that impacts may be in different locations from the original water stress. Herein, we estimate that the consumption loss can be up to 0.3% annually and the drivers identified in coupled modelling can increase the average cost of electricity by up to 3%. Integrated models will be needed to capture the cascading effects of climate change through climatic, water, energy and economic systems. Webster et al. now develop a coupled hydrologic–power-production–economic model to estimate water-stress impacts on electricity cost.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

High-throughput search for magnetic topological materials using spin-orbit spillage, machine learning, and experiments

Magnetic topological insulators and semi-metals have a variety of properties that make them attractive for applications including spintronics and quantum computation. Here, we use systematic high-throughput density functional theory calculations to identify magnetic topological materials from the ≈ 40000 three-dimensional materials in the JARVIS-DFT database. First, we screen materials with net magnetic moment > 0.5 μB and spin-orbit spillage > 0.25, resulting in 25 insulating and 564 metallic candidates. The spillage acts as a signature of spin-orbit induced band-inversion. Then, we carry out calculations of Wannier charge centers, Chern numbers, anomalous Hall conductivities, surface bandstructures, and Fermi-surfaces to determine interesting topological characteristics of the screened compounds. We also train machine learning models for predicting the spillage, bandgaps, and magnetic moments of new compounds, to further accelerate the screening process. We experimentally synthesize and characterize a few candidate materials to support our theoretical predictions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Measurement and modeling of proton-induced reactions on arsenic from 35 to 200 MeV

72 As is a promising positron emitter for diagnostic imaging that can be employed locally using a 72 Se generator. However, current reaction pathways to 72 Se have insufficient nuclear data for efficient production using regional 100–200 MeV high-intensity proton accelerators. In order to address this deficiency, stacked-target irradiations were performed at LBNL, LANL, and BNL to measure the production of the 72 Se/ 72 As positron emission tomography (PET) generator system via 75 As (p, x) between 35 and 200 MeV. This work provides the most well-characterized excitation function for 75 As ( p , 4 n ) 72 Se starting from threshold. Additional focus was given to report the first measurements of 75 As (p, x) 68 Ge and bolster an already robust production capability for the highly valuable 68 Ge/ 68 Ga PET generator. Thick target yield comparisons with prior established formation routes to both generators are made. In total, high-energy proton-induced cross sections are reported for 55 measured residual products from 75 As, nat Cu , and nat Ti targets, where the latter two materials were present as monitor foils. These results were compared with literature data as well as the default theoretical calculations of the nuclear model codes TALYS, COH, EMPIRE, and ALICE. Reaction modeling at these energies is typically unsatisfactory due to few prior published data and many interacting physics models. Therefore, a detailed assessment of the talys code was performed with simultaneous parameter adjustments applied according to a standardized procedure. Particular attention was paid to the formulation of the two-component exciton model in the transition between the compound and preequilibrium regions, with a linked investigation of level density models for nuclei off of stability and their impact on modeling predictive power. This paper merges experimental work and evaluation techniques for high-energy charged-particle isotope production in an extension to an earlier study of this kind.

43 PARTICLE ACCELERATORS↗

Understanding the compound flood risk along the coast of the contiguous United States

Abstract. Compound flooding is a type of flood event caused by multiple flood drivers. The associated risk has usually been assessed using statistics-based analyses or hydrodynamics-based numerical models. This study proposes a compound flood (CF) risk assessment (CFRA) framework for coastal regions in the contiguous United States (CONUS). In this framework, a large-scale river model is coupled with a global ocean reanalysis dataset to (a) evaluate the CF exposure related to the coastal backwater effects on river basins, and (b) generate spatially distributed data for analyzing the CF hazard using a bivariate statistical model of river discharge and storm surge. The two kinds of risk are also combined to achieve a holistic understanding of the continental-scale CF risk. The estimated CF risk shows remarkable inter- and intra-basin variabilities along the CONUS coast with more variabilities in the CF hazard over the US west and Gulf coastal basins. Different risk assessment methods present significantly different patterns in a few key regions such as the San Francisco Bay area, the lower Mississippi River, and Puget Sound. Our results highlight the need to weigh different CF risk measures and avoid using single statistics-based or hydrodynamics-based CFRAs. Uncertainty sources in these CFRAs include the use of gauge observations, which cannot account for the flow physics or resolve the spatial variability of risks, and underestimations of the flood extremes and the dependence of CF drivers in large-scale models, highlighting the importance of understanding the CF risks for developing a more robust CFRA.

54 ENVIRONMENTAL SCIENCES↗

Triggering typical nemaline myopathy with compound heterozygous nebulin mutations reveals myofilament structural changes as pathomechanism

Nebulin is a giant protein that winds around the actin filaments in the skeletal muscle sarcomere. Compound-heterozygous mutations in the nebulin gene (NEB) cause typical nemaline myopathy (NM), a muscle disorder characterized by muscle weakness with limited treatment options. We created a mouse model with a missense mutation p.Ser6366Ile and a deletion of NEB exon 55, the Compound-Het model that resembles typical NM. We show that Compound-Het mice are growth-retarded and have muscle weakness. Muscles have a reduced myofibrillar fractional-area and sarcomeres are disorganized, contain rod bodies, and have longer thin filaments. In contrast to nebulin-based severe NM where haplo-insufficiency is the disease driver, Compound-Het mice express normal amounts of nebulin. X-ray diffraction revealed that the actin filament is twisted with a larger radius, that tropomyosin and troponin behavior is altered, and that the myofilament spacing is increased. The unique disease mechanism of nebulin-based typical NM reveals novel therapeutic targets.

59 BASIC BIOLOGICAL SCIENCES↗

High-Temperature Fe-Based Fischer–Tropsch Synthesis: Experimentally Validated Kinetic Models Implemented at Pellet and Reactor Scales

Pellet- and reactor-scale models for Fischer–Tropsch synthesis (FTS) with a Fe–K/silica catalyst were developed to investigate the sensitivity of the hydrocarbon products and carbon dioxide selectivity to process conditions and feed composition at high temperature (350–400 °C), moderate pressure (1–10 bar), and a range of H 2 /CO ratios (3–1). The major objective of this paper is to develop, validate, and evaluate a high-temperature FTS model that is then used to assess the feasibility of process integration with syngas production. Since there is limited kinetic data available, in literature at these conditions, bench-scale reactor tests were conducted to obtain operational data for parameter fitting of kinetic expressions used in the model. This resulting kinetic model demonstrated agreement with the experimental data with an R 2 of 0.97 to the testing data set and, thus, was feasible to apply at pellet and reactor scales. Here, multiple pellet sizes were modeled to detail the role of transport limitations as the sphere’s diameter approached and exceeded 1 mm. Application of the reactor model indicated that hydrocarbon selectivity depended strongly on temperature, whereas the ratio of olefin to paraffin products decreased with increasing temperature, pressure, and H 2 /CO ratio. Product selectivity was not sensitive to the conversion of carbon monoxide. Furthermore, the roles of the pressure and H 2 /CO ratio were closely coupled. At a H 2 /CO ratio of 3, only slight variations in selectivity occurred over a pressure range of 1–20 bar, whereas at a ratio of 1, selectivity could vary by as much as 30% over the same pressure range. At pressures below 5 bar and temperatures above 350 °C, minimal selectivity to heavy hydrocarbons (C 12+ ) is obtained, and selectivity to midrange products (C 5–11 ) rapidly declined as pressure dropped below 5 bar, which indicated that an operational pressure of at least 5 bar is needed to achieve reasonable yields in this temperature range. These results, while tentative, provide guidelines for further experimentation and evaluation of integrated FTS processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Emission Factors and Evolution of SO2 Measured From Biomass Burning in Wildfires and Agricultural Fires

Fires emit sufficient sulfur to affect local and regional air quality and climate. This study analyzes SO2 emission factors and variability in smoke plumes from US wildfires and agricultural fires, as well as their relationship to sulfate and hydroxymethanesulfonate (HMS) formation. Observed SO2 emission factors for various fuel types show good agreement with the latest reviews of biomass burning emission factors, producing an emission factor range of 0.47–1.2 g SO2 kg^(−1) C. These emission factors vary with geographic location in a way that suggests that deposition of coal burning emissions and application of sulfur-containing fertilizers likely play a role in the larger observed values, which are primarily associated with agricultural burning. A 0-D box model generally reproduces the observed trends of SO2 and total sulfate (inorganic + organic) in aging wildfire plumes. In many cases, modeled HMS is consistent with the observed organosulfur concentrations. However, a comparison of observed organosulfur and modeled HMS suggests that multiple organosulfur compounds are likely responsible for the observations but that the chemistry of these compounds yields similar production and loss rates as that of HMS, resulting in good agreement with the modeled results. We provide suggestions for constraining the organosulfur compounds observed during these flights, and we show that the chemistry of HMS can allow organosulfur to act as an S(IV) reservoir under conditions of pH > 6 and liquid water content >10^(−7) g sm^(−3). This can facilitate long-range transport of sulfur emissions, resulting in increased SO2 and eventually sulfate in transported smoke.

Sulfur↗

ChemoGraph: Interactive Visual Exploration of the Chemical Space

Exploratory analysis of the chemical space is an important task in the field of cheminformatics. For example, in drug discovery research, chemists investigate sets of thousands of chemical compounds in order to identify novel yet structurally similar synthetic compounds to replace natural products. Manually exploring the chemical space inhabited by all possible molecules and chemical compounds is impractical, and therefore presents a challenge. To fill this gap, we present ChemoGraph, a novel visual analytics technique for interactively exploring related chemicals. In ChemoGraph, we formalize a chemical space as a hypergraph and apply novel machine learning models to compute related chemical compounds. It uses a database to find related compounds from a known space and a machine learning model to generate new ones, which helps enlarge the known space. Moreover, ChemoGraph highlights interactive features that support users in viewing, comparing, and organizing computationally identified related chemicals. With a drug discovery usage scenario and initial expert feedback from a case study, we demonstrate the usefulness of ChemoGraph.

chemical space exploration↗

Tropospheric OH and the lifetimes of hydrochlorofluorocarbons

Hydrochlorofluorocarbons (HCFCs) may be used as alternatives for the chlorofluorocarbons (CFCs). Lifetimes for the HCFCs are predicted here in two ways: integrating their loss with a global model and scaling to another compound with a better known lifetime. Both approaches are shown to yield similar results. Three-dimensional fields of modeled tropospheric OH concentrations are used to calculate lifetimes against destruction by OH for the HCFCs and other hydrogenated halocarbons. The lifetimes of various hydro-halocarbons are shown to be insensitive to possible spatial variations and seasonal cycles. It is possible to scale the HCFC lifetimes to that of methyl chloroform or methane by using a ratio of the rate coefficients for reaction with OH at an appropriate temperature, about 277 K.

Prather, Michael↗

Modeling of the Thermoelectric Properties of p-Type IrSb(sub 3)

IrSb(sub 3) is a compound of the skutterudite family of materials now being investigated at JPL. A combination of experimental and theoretical approaches has been recently applied at JPL to evaluate the potential of several thermoelectric materials such as n-type and p-type Si(sub 80) Ge(sub 20) alloys, n-type and p-type Bi(sub 2) Te(sub 3)-based alloys and p-type Ru(sub 2) Ge(sub 3) compound. The use of a comprehensive model for the thermal and electrical transport properties of a given material over its full temperature range of usefulness is a powerful tool for guiding experimental optimization of the composition, temperature and doping level as well as for predicting the maximum ZT value likely to be achieved.

skutterudite thermoelectric material thermoelectri↗