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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 919 records · Page 51

Complexity Reduction Methods for Large-Scale Spatially Explicit Biofuels Network Design

The size and complexity of energy system optimization models have increased significantly in recent years, driven by the availability of high-resolution spatial data. We present complexity reduction and solution methods that enable us to efficiently represent high-resolution spatial data in the network design of large-scale energy systems. We aim to reduce the size and enhance the computational efficiency of network design models without sacrificing solution accuracy. Specifically, we first present how to aggregate highly granular data into larger resolutions without averaging out their specific properties through a composite-curve-based approach and then develop a method to linearly represent these curves. Second, we utilize a general clustering method to determine groups of geographically proximate biomass fields and establish a single transportation arc for all of them, reducing the number of transportation-related variables while maintaining an accurate representation of the system. Finally, we introduce a two-step algorithm that decomposes large-scale network design problems into two smaller, more manageable subproblems. We demonstrate the application of our methods using a case study of switchgrass-to-biofuels network design in the eight states of the U.S. Midwest, using realistic and highly explicit spatial data.

09 BIOMASS FUELS↗

Folding Coarse-Grained Oligomer Models with PyRosetta

Non-biological foldamers are a promising class of macromolecules that share similarities to classical biopolymers such as proteins and nucleic acids. Currently, designing novel foldamers is a non-trivial process, often involving many iterations of trial synthesis and characterization until folded structures are observed. In this work, we aim to tackle these foldamer design challenges using computational modeling techniques. We developed CG PyRosetta, an extension to the popular protein folding python package, PyRosetta, which introduces coarse-grained (CG) residues into PyRosetta, enabling the folding of toy CG foldamer models. Although these models are simplified, they can help explore overarching physical hypotheses about how oligomers can form. Through systematic variation of CG parameters in these models, we can investigate various folding hypotheses at the CG scale to inform the design process of new foldamer chemistries. In this study, we demonstrate CG PyRosetta’s ability to identify minimum energy structures with a diverse structural search over a range of simple models, as well as two hypothesis-driven parameter scans investigating the effects of side-chain size and internal backbone angle on secondary structures. We are able to identify several types of secondary structures from single- and double-helices to sheet-like and knot-like structures. Here, we show how side-chain size and backbone bond angle both play an important role in the structure and energetics of these toy models. Optimal side-chain sizes promote favorable packing of side chains, while specific backbone bond angles influence the specific helix type found in folded structures.

36 MATERIALS SCIENCE↗

Strain Effects in SrHfO 3 Films Grown by Hybrid Molecular Beam Epitaxy

Perovskite oxide heterostructures host a large number of interesting phenomena such as ferroelectricity, which are often driven by octahedral distortions in the crystal that may induce polarization. SrHfO 3 (SHO) is a perovskite oxide with a pseudocubic lattice parameter of 4.08 Å that previous density functional theory (DFT) calculations suggest can be stabilized in a ferroelectric P4mm phase when stabilized with sufficient compressive strain. Additionally, it is insulating and possesses a large band gap and a high dielectric constant, making it an ideal candidate for oxide electronic devices. Here, to test the viability of epitaxial strain as a driver of ferroic phase transitions, SHO films were grown by hybrid molecular beam epitaxy (hMBE) with a tetrakis(ethylmethylamino)hafnium(IV) source on GdScO 3 and TbScO 3 substrates. Strained SHO phases were characterized using X-ray diffraction, X-ray absorption spectroscopy, and scanning transmission electron microscopy to determine the space group of the strained films, with the results compared to those of DFT-optimized models of phase stability versus strain. Contrary to past reports, we find that compressively strained SrHfO 3 undergoes octahedral tilt distortions without associated ferroelectric polarization and most likely takes on the I4/mcm phase with the a 0 a 0 c – tilt pattern.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Toward Low-Cost 4-Terminal GaAs//Si Tandem Solar Cells

Mechanically stacked III-V-on-Si (III-V//Si) tandem solar cells have demonstrated efficiencies beyond what can theoretically be achieved by single junction Si solar cells, but III-V costs are currently at least an order of magnitude higher than Si costs. Recent techno-economic analysis shows that costs could be substantially reduced by replacing traditional metalorganic vapor phase epitaxy (MOVPE) with a lower-cost III-V deposition technique, such as hydride vapor phase epitaxy (HVPE). This study analyzes the performance of an HVPE-grown GaAs top cell incorporated into a 4-terminal (4T) GaAs//Si tandem cell that achieved an efficiency of 29%, which is the highest solar cell efficiency fabricated without expensive deposition techniques such as MOVPE or MBE. We compare these results to an MOVPE-grown GaAs//Si tandem cell that has the same structure. Finally, we model optimizations to the HVPE-grown GaAs top cell and provide a near-term pathway to 31.4% efficiency with a low-cost III-V deposition technique.

14 SOLAR ENERGY↗

Surface-Plasmon-Mediated Gradient Force Enhancement and Mechanical State Transitions of Graphene Sheets

Graphene, a two-dimensional material possessing extraordinary properties in electronics as well as mechanics, provides a great platform for various optoelectronic and opto-mechanical devices. Here in this article, we theoretically study the optical gradient force arising from the coupling of surface plasmon modes on parallel graphene sheets, which can be several orders stronger than that between regular dielectric waveguides. Furthermore, with an energy functional optimization model, possible force-induced deformation of graphene sheets is calculated. We show that the significantly enhanced optical gradient force may lead to mechanical state transitions of graphene sheets, which are accompanied by abrupt changes in reflection and transmission spectra of the system. Our demonstrations illustrate the potential for a broader graphene-related applications such as force sensors and actuators.

36 MATERIALS SCIENCE↗

Emissions Implications of Future Natural Gas Production and Use in the U.S. and in the Rocky Mountain Region

Enhanced prospects for natural gas production raise questions about the balance of impacts on air quality, as increased emissions from production activities are considered alongside the reductions expected when natural gas is burned in place of other fossil fuels. This study explores how trends in natural gas production over the coming decades might affect emissions of greenhouse gases (GHG), volatile organic compounds (VOCs) and nitrogen oxides (NOx) for the United States and its Rocky Mountain region. The MARKAL (MARKet ALlocation) energy system optimization model is used with the U.S. Environmental Protection Agency's nine-region database to compare scenarios for natural gas supply and demand, constraints on the electricity generation mix, and GHG emissions fees. Through 2050, total energy system GHG emissions show little response to natural gas supply assumptions, due to offsetting changes across sectors. Policy-driven constraints or emissions fees are needed to achieve net reductions. In most scenarios, wind is a less expensive source of new electricity supplies in the Rocky Mountain region than natural gas. U.S. NOx emissions decline in all the scenarios considered. Increased VOC emissions from natural gas production offset part of the anticipated reductions from the transportation sector, especially in the Rocky Mountain region.

emissions↗

Quantum computing for finance

Quantum computers are expected to surpass the computational capabilities of classical computers and have a transformative impact on numerous industry sectors. Here, we present a comprehensive summary of the state of the art of quantum computing for financial applications, with particular emphasis on stochastic modelling, optimization and machine learning. This Review is aimed at physicists, so it outlines the classical techniques used by the financial industry and discusses the potential advantages and limitations of quantum techniques. Finally, we look at the challenges that physicists could help tackle. Quantum computers are expected to surpass classical computers and transform industries. This Review focuses on quantum computing for financial applications and provides a summary for physicists on potential advantages and limitations of quantum techniques, as well as challenges that physicists could help tackle.

97 MATHEMATICS AND COMPUTING↗

Ultrafast flow chemistry for the acid-catalyzed conversion of fructose

Biomass conversion to chemicals and fuels has been epitomized by batch processing and long reaction times that limit the economic viability of future biorefineries and prevent modular manufacturing near the source-production site that is necessary due to the biomass’ large water content. Herein we introduce a continuous flow microreactor to enable process intensification and one thousand-fold device miniaturization for remote chemical processing. We demonstrate the approach in HCl-catalyzed fructose dehydration in water. We characterize and quantify the mixing using laser induced fluorescence (LIF) of fluorescent dyes and particle image velocimetry (PIV) of fluorescent microspheres. The estimated mixing times ranged from 0.03 to 4.8 s for residence times from 1 to 120 s, respectively. Moreover, a curved channel geometry induces secondary (Dean) vortices that produce a three-fold increase in mixing by diffusion through advection along the cross-sectional direction of the channel, creating dissipative chaotic mixing under laminar flow. We then obtain for the first time isothermal kinetics of fructose dehydration at short contact times and high temperatures and compare to a previously published, hybrid ab initio and data-driven kinetic model. Rigorous model optimization is carried out and an optimal HMF yield of 54% is attained in a single aqueous phase. High temperatures and low pH improve the reactor throughput by increasing the HMF space-time yield. We demonstrate the highest ever productivity (HMF yield per unit time). Importantly, this can be achieved at ~100% fructose conversion, eliminating the need for recycling to improve economics. Furthermore, optimization of the reactor dimensions and the specific energy dissipation rate results in ~60% pressure-drop related energy savings. We describe a methodology to scale-up microreactors to millimeter size and increase productivity 16-fold under optimal conditions. The energy efficiency and cost analysis for HMF production from corn stover of a typical corn farm indicate an optimal strategy for numbering-up millimeter size reactors and, importantly, they underscore the potential feasibility of producing bioproducts in a distributed manner.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Calculated covariance matrices for fission product yields using BeoH

Fission product yields (FPY) are important for a variety of applications (reactor neutronics, spent fuel, dosimetry, radiochemistry, etc.) and are currently included in many of the evaluated libraries around the world. The FPYs in the current US evaluation, ENDF/B-VIII.0, are mainly based on the 1994 evaluation of England and Rider and have only had slight updates—such as the inclusion of a 2 MeV point for 239 Pu—since their development. Additionally, only mean values and uncertainties are included in the evaluation, not full correlations. Los Alamos National Laboratory, in collaboration with several other institutes, has been working on an updated evaluation for the FPYs of 239 Pu(n,f), 235 U(n,f), 238 U(n,f), and 252 Cf(sf) using the deterministic, Hauser-Feshbach, fission fragment decay code, BeoH. BeoH calculates the FPYs consistently with many other prompt and delayed fission observables, explicitly taking into account multi-chance fission and ensuring consistency between observables. In addition to providing updated means and uncertainties for the FPYs on a pointwise energy grid from thermal to 20 MeV, we calculate correlations between all FPYs at each incident energy and across incident energies. Here, we discuss the development of these covariance matrices, differences in the correlations between FPYs based on the parameters that are included in the model optimization, and correlations across incident energies for neutron-induced fission.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Spatial Impacts of Electric Vehicle Charging on Power Grid Stability: A Downtown Atlanta Case Study

The rapid increase in electric vehicle (EV) charging demand poses a potential risk to power grid stability, particularly as the spatial distribution of this demand remains underexplored. Existing research often focuses on technical optimization models while overlooking the geographic and human dynamics that affect energy consumption. This study addresses this gap by incorporating mobility data to estimate both building energy use and EV charging demand while also considering geographic factors for a better understanding of grid load. Using agent-based simulations and the Open-Source Distribution System Simulator, the study evaluates the effect of various EV penetration scenarios on grid voltage and unbalance. The results show that, although voltage remains within acceptable limits at lower EV penetration rates, significant voltage drop and unbalance occur as EV penetration exceeds 40%, particularly in residential areas with high charging demand. This study offers a framework for integrating spatial analysis and mobility data in power network simulations, providing insights for future EV infrastructure planning.

Pan, Melrose [ORNL] (ORCID:000000031627448X)↗

An integrated time-of-flight versus residual energy subsystem for a compact dual ion composition experiment for space plasmas

We have developed a novel concept for a Compact Dual Ion Composition Experiment (CoDICE) that simultaneously provides high quality plasma and energetic ion composition measurements over 6 decades in ion energy in a wide variety of space plasma environments. CoDICE measures the two critical ion populations in space plasmas: (1) mass and ionic charge state composition and 3D velocity and angular distributions of ∼10 eV/q–40 keV/q plasma ions—CoDICE-Lo and (2) mass composition, energy spectra, and angular distributions of ∼30 keV–10 MeV energetic ions—CoDICE-Hi. CoDICE uses a common, integrated Time-of-Flight (TOF) versus residual energy (E) subsystem for measuring the two distinct ion populations. This paper describes the CoDICE design concept, and presents results of the laboratory tests of the TOF portion of the TOF vs. E subsystem, focusing specifically on (1) investigation of spill-over and contamination rates on the start and stop microchannel plate (MCP) anodes vs. secondary electron steering and focusing voltages, scanned around their corresponding model-optimized values, (2) TOF measurements and resolution and angular resolution, and (3) cross-contamination of the start and stop MCPs’ singles rates from CoDICE-Lo and -Hi, and (4) energy resolution of avalanche photodiodes near the lower end of the CoDICE-Lo energy range. We also discuss physical effects that could impact the performance of the TOF vs. E subsystem in a flight instrument. Finally, we discuss advantages of the CoDICE design concept by comparing with capabilities and resources of existing flight instruments.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A promising limited angular computed tomography reconstruction via segmentation based regional enhancement and total variation minimization

X-ray computed tomography (CT) is a powerful and common inspection technique used for the industrial non-destructive testing. However, large-sized and heavily absorbing objects cause the formation of artifacts because of either the lack of specimen penetration in specific directions or the acquisition of data from only a limited angular range of views. Although the sparse optimization-based methods, such as the total variation (TV) minimization method, can suppress artifacts to some extent, reconstructing the images such that they converge to accurate values remains difficult because of the deficiency in continuous angular data and inconsistency in the projections. To address this problem, we use the idea of regional enhancement of the true values and suppression of the illusory artifacts outside the region to develop an efficient iterative algorithm. This algorithm is based on the combination of regional enhancement of the true values and TV minimization for the limited angular reconstruction. In this algorithm, the segmentation approach is introduced to distinguish the regions of different image knowledge and generate the support mask of the image. A new regularization term, which contains the support knowledge to enhance the true values of the image, is incorporated into the objective function. Then, the proposed optimization model is solved by variable splitting and the alternating direction method efficiently. A compensation approach is also designed to extract useful information from the initial projections and thus reduce false segmentation result and correct the segmentation support and the segmented image. The results obtained from comparing both simulation studies and real CT data set reconstructions indicate that the proposed algorithm generates a more accurate image than do the other reconstruction methods. The experimental results show that this algorithm can produce high-quality reconstructed images for the limited angular reconstruction and suppress the illusory artifacts caused by the deficiency in valid data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A MACHINE-LEARNING METHOD TO INFER FUNDAMENTAL STELLAR PARAMETERS FROM PHOTOMETRIC LIGHT CURVES

A fundamental challenge for wide-field imaging surveys is obtaining follow-up spectroscopic observations: there are >10{sup 9} photometrically cataloged sources, yet modern spectroscopic surveys are limited to ∼few× 10{sup 6} targets. As we approach the Large Synoptic Survey Telescope era, new algorithmic solutions are required to cope with the data deluge. Here we report the development of a machine-learning framework capable of inferring fundamental stellar parameters (T {sub eff}, log g, and [Fe/H]) using photometric-brightness variations and color alone. A training set is constructed from a systematic spectroscopic survey of variables with Hectospec/Multi-Mirror Telescope. In sum, the training set includes ∼9000 spectra, for which stellar parameters are measured using the SEGUE Stellar Parameters Pipeline (SSPP). We employed the random forest algorithm to perform a non-parametric regression that predicts T {sub eff}, log g, and [Fe/H] from photometric time-domain observations. Our final optimized model produces a cross-validated rms error (RMSE) of 165 K, 0.39 dex, and 0.33 dex for T {sub eff}, log g, and [Fe/H], respectively. Examining the subset of sources for which the SSPP measurements are most reliable, the RMSE reduces to 125 K, 0.37 dex, and 0.27 dex, respectively, comparable to what is achievable via low-resolution spectroscopy. For variable stars this represents a ≈12%-20% improvement in RMSE relative to models trained with single-epoch photometric colors. As an application of our method, we estimate stellar parameters for ∼54,000 known variables. We argue that this method may convert photometric time-domain surveys into pseudo-spectrographic engines, enabling the construction of extremely detailed maps of the Milky Way, its structure, and history.

79 ASTRONOMY AND ASTROPHYSICS↗

Assessing the performance of global thermostat adjustment in commercial buildings for load shifting demand response

Abstract Efficiently leveraging new sources of flexibility is critical to mitigating load balancing challenges posed by variable renewable resources. The thermal inertia of commercial buildings allows us to shift their power consumption on minute to hourly timescales to provide demand response to the grid while maintaining occupant comfort. Global thermostat adjustment (GTA) provides a readily available and scalable approach for implementing load shifting demand response using commercial heating, ventilation, and air conditioning (HVAC) systems, since it leverages the inherent sophistication of modern building automation systems. However, there is an incomplete understanding of GTA’s performance for this purpose and its impact on building systems and occupant comfort. In this paper, we explore the performance of GTA by analyzing results from nearly nine hundred experiments on eight university campus buildings in Michigan and North Carolina. Using GTA, we manipulate each building’s thermostat setpoints causing the building to shift its power consumption with respect to its baseline. We quantify the magnitude of HVAC power response, energy use of HVAC subsystems, and impact on occupant comfort. Finally, we connect our experimental results with power system operation using an optimization model that coordinates GTA actions across a large collection of grid-interactive efficient buildings (GEBs) to reduce high ramp rates on the grid and mitigate renewable energy curtailment. Overall, our work finds that the impacts on HVAC subsystems are often complex, and may result in additional energy being consumed by fans and terminal reheat. These effects must be considered when using GTA for load shifting. Additionally, we demonstrate that occupant comfort, as assessed by indoor temperature and humidity, can be maintained during GTA events. From a societal perspective, our modeling work finds that the additional renewable energy that can be integrated through the use of GTA strategies eclipses any additional energy consumed by buildings.

Keskar, Aditya (ORCID:0000000244617980)↗

Increasing water use efficiency along the C3 to C4 evolutionary pathway: a stomatal optimization perspective

C4 photosynthesis evolved independently numerous times, probably in response to declining atmospheric CO2 concentrations, but also to high temperatures and aridity, which enhance water losses through transpiration. Here, the environmental factors controlling stomatal behaviour of leaf-level carbon and water exchange were examined across the evolutionary continuum from C3 to C4 photosynthesis at current (400 μmol mol–1) and low (280 μmol mol–1) atmospheric CO2 conditions. To this aim, a stomatal optimization model was further developed to describe the evolutionary continuum from C3 to C4 species within a unified framework. Data on C3, three categories of C3–C4 intermediates, and C4 Flaveria species were used to parameterize the stomatal model, including parameters for the marginal water use efficiency and the efficiency of the CO2-concentrating mechanism (or C4 pump); these two parameters are interpreted as traits reflecting the stomatal and photosynthetic adjustments during the C3 to C4 transformation. Neither the marginal water use efficiency nor the C4 pump strength changed significantly from C3 to early C3–C4 intermediate stages, but both traits significantly increased between early C3–C4 intermediates and the C4-like intermediates with an operational C4 cycle. At low CO2, net photosynthetic rates showed continuous increases from a C3 state, across the intermediates and towards C4 photosynthesis, but only C4-like intermediates and C4 species (with an operational C4 cycle) had higher water use efficiencies than C3 Flaveria. The results demonstrate that both the marginal water use efficiency and the C4 pump strength increase in C4 Flaveria to improve their photosynthesis and water use efficiency compared with C3 species. These findings emphasize that the advantage of the early intermediate stages is predominantly carbon based, not water related.

54 ENVIRONMENTAL SCIENCES↗

mBEEF-vdW: Robust fitting of error estimation density functionals

Here, we propose a general-purpose semilocal/nonlocal exchange-correlation functional approximation, named mBEEF-vdW. The exchange is a meta generalized gradient approximation, and the correlation is a semilocal and nonlocal mixture, with the Rutgers-Chalmers approximation for van der Waals (vdW) forces. The functional is fitted within the Bayesian error estimation functional (BEEF) framework. We improve the previously used fitting procedures by introducing a robust MM-estimator based loss function, reducing the sensitivity to outliers in the datasets. To more reliably determine the optimal model complexity, we furthermore introduce a generalization of the bootstrap 0.632 estimator with hierarchical bootstrap sampling and geometric mean estimator over the training datasets. Using this estimator, we show that the robust loss function leads to a 10% improvement in the estimated prediction error over the previously used least-squares loss function. The mBEEF-vdW functional is benchmarked against popular density functional approximations over a wide range of datasets relevant for heterogeneous catalysis, including datasets that were not used for its training. Overall, we find that mBEEF-vdW has a higher general accuracy than competing popular functionals, and it is one of the best performing functionals on chemisorption systems, surface energies, lattice constants, and dispersion. We also show the potential-energy curve of graphene on the nickel(111) surface, where mBEEF-vdW matches the experimental binding length. mBEEF-vdW is currently available in gpaw and other density functional theory codes through Libxc, version 3.0.0.

36 MATERIALS SCIENCE↗