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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 127 records · Page 7

Design principles for energy transfer in the photosystem II supercomplex from kinetic transition networks

Photosystem II (PSII) has the unique ability to perform water-splitting. With light-harvesting complexes, it forms the PSII supercomplex (PSII-SC) which is a functional unit that can perform efficient energy conversion, as well as photoprotection, allowing photosynthetic organisms to adapt to the naturally fluctuating sunlight intensity. Achieving these functions requires a collaborative energy transfer network between all subunits of the PSII-SC. In this work, we perform kinetic analyses and characterise the energy landscape of the PSII-SC with a structure-based energy transfer model. With first passage time analyses and kinetic Monte Carlo simulations, we are able to map out the overall energy transfer network. We also investigate how energy transfer pathways are affected when individual protein complexes are removed from the network, revealing the functional roles of the subunits of the PSII-SC. In addition, we provide a quantitative description of the flat energy landscape of the PSII-SC. We show that it is a unique landscape that produces multiple kinetically relevant pathways, corresponding to a high pathway entropy. These design principles are crucial for balancing efficient energy conversion and photoprotection.

59 BASIC BIOLOGICAL SCIENCES↗

Q -score as a reliability measure for protein, nucleic acid and small-molecule atomic coordinate models derived from 3DEM maps

Atomic coordinate models are important for the interpretation of 3D maps produced with cryoEM and cryoET (3D electron microscopy; 3DEM). In addition to visual inspection of such maps and models, quantitative metrics can inform about the reliability of the atomic coordinates, in particular how well the model is supported by the experimentally determined 3DEM map. A recently introduced metric, Q-score, was shown to correlate well with the reported resolution of the map for well fitted models. Here, we present new statistical analyses of Q-score based on its application to ∼10 000 maps and models archived in the EMDB (Electron Microscopy Data Bank) and PDB (Protein Data Bank). Further, we introduce two new metrics based on Q-score to represent each map and model relative to all entries in the EMDB and those with similar resolution. We explore through illustrative examples of proteins, nucleic acids and small molecules how Q-scores can indicate whether the atomic coordinates are well fitted to 3DEM maps and also whether some parts of a map may be poorly resolved due to factors such as molecular flexibility, radiation damage and/or conformational heterogeneity. These examples and statistical analyses provide a basis for how Q-scores can be interpreted effectively in order to evaluate 3DEM maps and atomic coordinate models prior to publication and archiving.

B factors↗

STREAM: A technology planning and capacity expansion model for the industrial sector

The Strategic Technology Roadmapping and Energy, Environmental, and Economic Analysis Model—STREAM—is an optimization-based modeling tool and analysis framework to assist with strategic planning and technology investments of the industrial sector. This open-source framework is written in Julia using the JuMP package, which enables users to model future “pathways” for incumbent and future production technologies, costs, fuels and energy carriers, and energy and non-energy environmental impacts from industries as they transform in pursuit of a robust and competitive manufacturing sector. The model starts with an initial stock of industrial production technologies and assets at a facility level and then determines pathways that minimize cost, subject to an array of possible constraints on demand, market shares, environmental flows, and other exogenously specified operational considerations such as capacity utilization rates or regional energy costs. Key features of the framework include flexibility to model a wide range of industries and industrial technologies/processes at varying levels of granularity, ability to perform parametric sensitivity analyses, and ability to visualize model results using visualization objects.

capacity expansion↗

Experimental and fuel-surrogates modeling study of the high-pressure pyrolysis of specialty cetane number fuels: implications for fall-off in ethylene unimolecular dissociation

Single pulse shock tube experiments were conducted at 50 atm nominal pressure and 4 ms nominal reaction time over a temperature range of 900–1800 K, to study the pyrolysis speciation of a multi-component jet fuel, F-24, and six cetane number (CN) specialty fuels - CN30, CN35, CN40, CN45, CN50, and CN55. Gas chromatography (GC) was used to qualitatively and quantitatively analyze the post shock gases. The relationship between the formation of key pyrolysis species and the chemically controlled combustion propensity as reflected by the cetane number of each fuel was examined. A surrogate-based mechanism from the CRECK Modelling Group and chemical-functional group based optimized surrogates (CFGO) were used to simulate the pyrolysis speciation results. The model was able to capture the chemistry of most species except two important pyrolysis intermediates – ethylene and acetylene. Chemical kinetic analyses were performed to identify the important reactions which affect the chemistry of these species; however, the rate parameters of critical reactions were found to be unsuitable for simulating the present high-pressure studies. Here, to address this unsuitability, a theory-based fall-off analysis for three reactions representing the decomposition of ethylene and subsequent formation of acetylene was performed, and these are included in an updated version of the CRECK mechanism. This update resolves discrepancies between the experimental results and simulations for ethylene and acetylene. Reaction flux analyses using the updated surrogate model were also performed to identify the important reaction pathways responsible for the formation of crucial species and to provide an analysis of the chemistry of complex multi-component fuel systems. The fundamental reactions responsible for driving pyrolysis chemistry were greatly influenced by the chemical functional groups present in these fuels. In addition to updating the rate parameters of specific reactions to improve modeling, this study also emphasizes the effectiveness of the fuel-surrogate approach, where surrogates representing the chemical functional group composition of the parent fuel serve as a valuable tool for predicting the combustion chemistry of novel fuels.

Chemical Kinetics↗

Hot droughts in the Amazon provide a window to a future hypertropical climate

Tropical forests represent the warmest and wettest of Earth’s biomes, but with continued anthropogenic warming, they will be pushed to climate states with no current analogue. Droughts in the tropics are already becoming more intense as they occur at successively higher temperatures. Here, in this study, we synthesize multiple datasets to assess the effects of hot droughts on a central Amazon forest. First, a more than 30-year record of annually resolved forest demographic data from a selective logging experiment showed higher tree mortality during intense droughts, particularly among fast-growing pioneer species with low wood density. Second, analysis of ecophysiological field measurements from the 2015 and 2023 El Niño droughts identified a soil moisture threshold beyond which transpiration rates rapidly declined. As rainless days beyond this threshold continued, drought conditions intensified, increasing the potential for tree mortality from hydraulic failure and carbon starvation. Third, analyses from the Coupled Model Intercomparison Project Phase 6 demonstrated that under high-emission scenarios, a large area of tropical forest will shift to a hotter ‘hypertropical’ climate by 2100. Last, under a hypertropical climate, temperature and moisture conditions during typical dry season months will more frequently exceed identified drought mortality thresholds, elevating the risk of forest dieback. Present-day hot droughts are harbingers of this emerging climate, offering a window for studying tropical forests under expected extreme future conditions.

drought↗

Catalytic reduction of carbon dioxide to methanol over defect-laden hexagonal boron nitride: insights into reaction mechanisms

Abstract We present a density functional theory-based mechanistic understanding of CO 2 hydrogenation to value-added products on a nitrogen-vacancy (V N ) defect in hexagonal boron nitride ( dh -BN). Activation occurs through back-donation to the π * orbitals of CO 2 from the frontier orbitals (defect state) of the h- BN sheet that are localized near a nitrogen-vacancy. Subsequent hydrogenation to methanol (CH 3 OH) and formic acid (HCOOH) proceed through vacancy-facilitated co-adsorption of hydrogen and CO 2 . More importantly, our reaction pathway analyses complimented by microkinetic modeling indicate that dh -BN is potentially a low-temperature, selective catalyst for CO 2 reduction to methanol. Our findings are in agreement with experiments conducted in a mechanical reactor that show high selectivity towards methanol formation for CO 2 hydrogenation on defect induced h- BN.

Jiang, Tao (ORCID:0000000304197288)↗

HOD-dependent systematics in Emission Line Galaxies for the DESI 2024 BAO analysis

The Dark Energy Spectroscopic Instrument (DESI) will provide precise measurements of Baryon Acoustic Oscillations (BAO) to constrain the expansion history of the Universe and set stringent constraints on dark energy. Therefore, precise control of the global error budget due to various systematic effects is required for the DESI 2024 BAO analysis. In this work, we estimate the level of systematics induced in the DESI BAO analysis due the assumed Halo Occupation Distribution (HOD) model for the Emission Line Galaxy (ELG) tracer. We make use of mock galaxy catalogs constructed by fitting various HOD models to early DESI data, namely the One-Percent survey data. Our analysis includes typical HOD models for the ELG tracer used in the literature as well as extensions to the baseline models. Among the extensions, we consider various recipes for galactic conformity and assembly bias. We use 25 AbacusSummit simulations under the ΛCDM cosmology for each HOD model and perform independent analyses in Fourier space and in configuration space. To recover the BAO signal from our mocks we perform BAO reconstruction and apply the control variates technique to reduce sample variance noise. Our BAO analyses can recover the isotropic BAO parameter α iso within 0.1% and the Alcock Paczynski parameter α AP within 0.3%. Overall, we find that the systematic error due to the HOD dependence is below 0.17%, with the Fourier space analysis being more robust against the HOD systematics. We conclude that our analysis pipeline is robust enough against the HOD systematics for the ELG tracer in the DESI 2024 BAO analysis, for the assumptions made.

79 ASTRONOMY AND ASTROPHYSICS↗

The three-dimensional structure of black hole accretion flows within the plunging region

ABSTRACT We analyse, using new analytical models and numerical general relativistic magnetohydrodynamic simulations, the three-dimensional properties of accretion flows inside the plunging region of black hole spacetimes (i.e. at radii smaller than the innermost stable circular orbit). These simulations are of thick discs, with aspect ratios of order unity $h/r \sim 1$, and with a magnetic field geometry given by the standard low-magnetization ‘SANE’ configuration. This work represents the first step in a wider analysis of this highly relativistic region. We show that analytical expressions derived in the ‘thin disc’ limit describe the numerical results remarkably well, despite the large aspect ratio of the flow. We further demonstrate that accretion within this region is typically mediated via spiral arms, and that the geometric properties of these spiral structures can be understood with a simple analytical model. These results highlight how accretion within the plunging region is fundamentally two-dimensional in character, which may have a number of observational implications. We derive a modified theoretical description of the pressure within the plunging region which accounts for turbulent heating and may be of use to black hole image modelling.

Astronomy & Astrophysics↗

Improving missing transverse momentum estimation with a deep neural network

At hadron colliders, the net transverse momentum of particles that do not interact with the detector (missing transverse momentum, $^→_𝑝$$^{miss}_{T}$) is a crucial observable in many analyses. In the standard model, $^→_𝑝$$^{miss}_{T}$ originates from neutrinos. Many beyond-the-standard-model particles, such as dark matter candidates, are also expected to leave the experimental apparatus undetected. This paper presents a novel deep neural network based $^→_𝑝$$^{miss}_{T}$ estimator, DeepMET, developed by the CMS Collaboration at the LHC. The DeepMET algorithm produces a weight for each reconstructed particle based on its properties. The estimator is based on the negative vector sum of the weighted transverse momenta of all reconstructed particles in an event. Compared with other estimators currently employed by CMS, DeepMET improves the $^→_𝑝$$^{miss}_{T}$ resolution by 10%–30%, shows improvement for a wide range of final states, is easier to train, and is more resilient against the effects of additional proton-proton interactions accompanying the collision of interest.

artificial neural networks↗

Toward UV models of kinetic mixing and portal matter. VI. A more complex dark matter sector?

Portal matter (PM), having both Standard Model (SM) and dark sector charges, can induce kinetic mixing between the 𝑈⁢(1) 𝐷 dark photon and the SM gauge fields at the 1-loop level offering an attractive mechanism by which light (≲1 GeV) thermal dark matter (DM) can interact with visible matter and obtain its observed relic density. In doing so, if the DM is fermionic, the CMB and other astrophysical observations inform us that it must be Majorana/pseudo-Dirac in nature to avoid velocity/temperature-independent 𝑠-wave annihilation to SM final states. How does this idea fit into a more UV-complete picture also including the SM interactions? There are some reasons to believe that at least a first step along this path may not lie too far away in energy due to the renormalization group equations running of the dark gauge coupling, which for a significant range of parameters, becomes nonperturbative at/before the ∼10’s of TeV energy range. This implies that 𝑈⁢(1) 𝐷 must become embedded in an asymptotically free, non-Abelian group, 𝐺 𝐷 , before this can occur. The breaking of this larger group then produces the masses for the PM and the additional gauge fields associated with 𝐺 𝐷 then can lead to new interactions between the SM and the dark sector. Following several bottom-up approaches, we have examined a set of distinctive and testable phenomenological features associated with this general setup, based upon a number of simplifying assumptions. Clearly, it behooves us to explore the impact of these specific assumptions on these predictions for the array of possible experimental tests of this class of models. In most past analyses it has been assumed that DM is a vectorlike, complex singlet under the group 𝐺 𝐷 . If this assumption is relaxed, the dark sector must be augmented by additional fermion(s) and the associated scalar fields needed to break the gauge symmetries while generating the needed Majorana-like mass terms for the DM. In this paper, we analyze the simplest extension of this kind wherein the DM lies in a vectorlike doublet of 𝐺 𝐷 , which we take to have the structure 𝑆⁢𝑈⁢(2) 𝐼 ×𝑈⁢(1) 𝑌 𝐼 as in earlier work, leading to new phenomenological implications. We find, for example, that given the current LHC search constraints on the masses of heavy gauge bosons, the production of these new dark states with large rates is unlikely to occur at colliders unless they are produced singly in 𝑔⁡𝑔 fusion or their pair production cross sections are resonantly enhanced. Here, we also find that an additional mechanism arises to generate hierarchal neutrino masses in such a setup.

Extensions of Higgs sector↗

Discovery of GuaB inhibitors with efficacy against Acinetobacter baumannii infection

ABSTRACT Guanine nucleotides are required for growth and viability of cells due to their structural role in DNA and RNA, and their regulatory roles in translation, signal transduction, and cell division. The natural antibiotic mycophenolic acid (MPA) targets the rate-limiting step inde novoguanine nucleotide biosynthesis executed by inosine-5´-monophosphate dehydrogenase (IMPDH). MPA is used clinically as an immunosuppressant, but whetherin vivoinhibition of bacterial IMPDH (GuaB) is a valid antibacterial strategy is controversial. Here, we describe the discovery of extremely potent small molecule GuaB inhibitors (GuaBi) specific to pathogenic bacteria with a low frequency of on-target spontaneous resistance and bactericidal efficacyin vivoagainstAcinetobacter baumanniimouse models of infection. The spectrum of GuaBi activity includes multidrug-resistant pathogens that are a critical priority of new antibiotic development. Co-crystal structures ofA. baumannii, Staphylococcus aureus, andEscherichia coliGuaB proteins bound to inhibitors show comparable binding modes of GuaBi across species and identifies key binding site residues that are predictive of whole-cell activity across both Gram-positive and Gram-negative clades of Bacteria. The clearin vivoefficacy of these small molecule GuaB inhibitors in a model ofA. baumanniiinfection validates GuaB as an essential antibiotic target. IMPORTANCE The emergence of multidrug-resistant bacteria worldwide has renewed interest in discovering antibiotics with novel mechanism of action. For the first time ever, we demonstrate that pharmacological inhibition ofde novoguanine biosynthesis is bactericidal in a mouse model ofAcinetobacter baumanniiinfection. Structural analyses of novel inhibitors explain differences in biochemical and whole-cell activity across bacterial clades and underscore why this discovery may have broad translational impact on treatment of the most recalcitrant bacterial infections.

Microbiology↗

New approaches to Bayesian uncertainty quantification for Nuclear Science (Final Technical Report)

Inverse problems play a central role in experimentation and theory/data comparisons for many areas of modern Nuclear Physics (NP) and High-Energy Physics (HEP). Bayes’s Theorem is a powerful tool for solving Inverse Problems, providing conceptually transparent and unbiased constraints on theoretical parameters and their uncertainties (“Bayesian Inference”) and enabling the quantification of agreement or tension between models and data. However, analyses based on Bayesian Inference are often challenging for NP and HEP applications, either because of the large number of parameters in the problem, the high computational cost, or both. We propose a multi-institutional collaboration to develop and deploy novel Bayesian analysis tools that advance the scientific scope of a broad range of current and future NP experiments. This project brings together NP domain scientists working on several high-profile NP projects for which new, high-performance Bayesian Uncertainty Quantification (“Bayesian UQ”) methods are essential to carry out the science, and data scientists who are developing state-of-the-art methods applicable to these problems. The NP projects in this proposal comprise measurements of the mass and fundamental nature of the neutrino; study of the Quark-Gluon Plasma that filled the early universe; and mapping of natural and anthropogenic radiation environments. While these NP projects have very different scientific goals, with datasets and analysis approaches that differ significantly, they share common requirements for improving computationally intensive Bayesian analyses using advanced Machine Learning algorithms and will benefit strongly from a coherent effort to develop general solutions. This proposal brings together these projects and forefront ML-based data science algorithms to develop such general solutions. The methods developed in this project will also be more widely applicable, thereby advancing science in the larger Nuclear Physics portfolio.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

A Curated Dataset of Regional Meteor Events with Simultaneous Optical and Infrasound Observations (2006–2011)

We present a curated, openly accessible dataset of 71 regional meteor events simultaneously recorded by optical and infrasound instrumentation between 2006 and 2011. These events were captured during an observational campaign using the all-sky cameras of the Southern Ontario Meteor Network and the co-located Elginfield Infrasound Array. Each entry provides optical trajectory measurements, infrasound waveforms, and atmospheric specification profiles. The integration of optical and acoustic data enables robust linkage between observed acoustic signals and specific points along meteor trajectories, offering new opportunities to examine shock wave generation, propagation, and energy deposition processes. This release fills a critical observational gap by providing the first validated, openly accessible archive of simultaneous optical–infrasound meteor observations that supports trajectory reconstruction, acoustic propagation modeling, and energy deposition analyses. By making these data openly available in a structured format, this work establishes a durable reference resource that advances reproducibility, fosters cross-disciplinary research, and underpins future developments in meteor physics, atmospheric acoustics, and planetary defense.

astrometry↗

The Capacity Expansion Regional Feasibility (CERF) Model: High-Resolution Power Plant Siting

Abstract This presentation gives an overview of the geospatial power plant siting model CERF. CERF (Capacity Expansion Regional Feasibility) is an open source Python package developed under the Integrated Multisector Multiscale Modeling (IM3) Project at PNNL. This presentation covers an overview of how the CERF model works, walks through various power plant siting analyses, and discusses future research opportunities for the model. The CERF model can be accessed at https://github.com/IMMM-SFA/cerf. PNNL Information Release Number: PNNL-SA-207336 Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program.

Mongird, Kendall [Pacific Northwest National Labor↗

First search for sterile neutrino oscillation leading to $ν_μ$ disappearance in the Booster Neutrino Beam at ICARUS

We present a search for muon neutrino disappearance in the Booster Neutrino Beam (BNB) at Fermilab using the ICARUS detector. Neutrino interactions identified as muon neutrinos interacting with argon nuclei via the charged current interaction and having only a muon and at least one proton in the final state (1$μ$Np) have been selected from data collected in 2022-2023 (ICARUS Run 2) and compared with a simulation-based expectation. In the context of a fit to a two-neutrino approximation of the sterile 3+1 model, including the impact of systematic uncertainty from the flux, neutrino interaction, and detector models, we find no statistically significant muon neutrino disappearance at the ICARUS baseline of 600 meters from the BNB target. Corresponding 90% C.L. exclusion contours in $Δm^2_{41}$ - sin$^22θ_{μμ}$ space are presented. This is the first oscillation analysis produced by ICARUS exposed to the BNB. We note that the analysis is systematics limited due to large unconstrained uncertainties from the flux and interaction models. In future joint analyses, data from ICARUS and the SBND detector, exposed to the BNB at 110 meters from target, will be combined to provide significant constraint of these uncertainties, enabling a robust, world-leading two-detector analysis.

Alrahman, F. Abd [Houston U.]↗

Using Parameter Sweep in WaterTAP to Analyze New Water Treatment Technologies

We describe a powerful and generalized parameter sweep tool in this report that was originally developed to analyze the performance of existing and novel water treatment models being developed in WaterTAP. Since WaterTAP is built upon IDAES and Pyomo, the parameter sweep tool can be used to systematically explore and debug the behavior of most Pyomo and IDAES numerical models. In order to enable meaningful analyses, the parameter sweep tool has been designed with the following features: 1) Model flexibility: The parameter sweep tool does not enforce any restrictions on the types of models that can be used with it. As long as a Pyomo model can be solved and the parameter is active and mutable, the tool only needs functions that describe how to run the model, the sweep parameters, and the output quantities of interest. 2) Flexible sampling: The parameter sweep tool has inbuilt functions to generate samples from a random distribution or a multidimensional Euclidean space. Furthermore, the users have to ability to supply samples generated from a tool of their choice. 3) Multiple sweep types: A user can choose from one of 3 types of parameter sweeps depending on their needs. 4) Detailed outputs: Outputs generated by the parameter sweep tool can be stored in detailed H5 file or user-friendly CSV files for post processing. 5) Parallel computing: The parameter sweep supports shared and distributed memory parallel computing to enable the use of high performance computers (HPC) for large-scale analyses. 6) Modular: The parameter sweep tool is self-contained and can easily be integrated within an outer-loop analysis or as desired by the user. 7) Ease of use: The tool is well documented and a simple sweep can be easily executed by following the online documentation in a few lines of code. We demonstrate the use of the parameter sweep tool on a simple water treatment system from the WaterTAP repository and show its parallel scaling performance on an Apple laptop and NREL's Eagle HPC. The parameter sweep tool is actively being used with models currently being developed within WaterTAP and we expect its use to grow beyond it to other IDAES and Pyomo models.

97 MATHEMATICS AND COMPUTING↗

Model-based economic analysis under uncertainty for PFAS treatment by granular activated carbon and ion exchange technologies

Recent drinking water regulations have imposed the need for per- and polyfluoroalkyl substances (PFAS) remediation. In response, treatment facilities may be required to retrofit existing treatment schemes to treat PFAS below maximum contaminant levels (MCLs). Adsorption technologies such as granular activated carbon (GAC) and ion exchange (IX) have been demonstrated to be effective; however, there are limited techno-economic metrics available which provide guidance on technology selection and design for diverse PFAS-containing source water conditions. Process systems engineering (PSE) tools which can traditionally perform these analyses are hindered by the data availability, model validity, and understanding of treatment phenomena for emerging contaminants. This work employs published data regressions, statistical models, process models, techno-economic analyses, and other process systems tools in a model-based uncertainty framework to consider the limitations of emerging contaminant research. Through this analysis framework, economic results are provided as probabilistic distributions based on the uncertainty of the models and diverse conditions that treatment facilities experience.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗