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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 1,225 records · Page 68
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Extracting scattering amplitudes for arbitrary two-particle systems with one-particle left-hand cuts via lattice QCD

We derive a general formalism that relates the spectrum of two-particle systems in a finite volume to physical scattering amplitudes, taking into account the presence of any left-hand branch cuts due to single-particle exchanges. The method first relates the finite-volume spectrum to an infinite-volume short-range quantity, denoted ${\mathcal{M}}_0$, and then relates the latter to the physical scattering amplitudes via known integral equations. The derivation of both relations is performed using all-orders perturbation theory and is exact up to neglected exponentially suppressed volume dependence. The relations hold for arbitrary two-particle systems with any number of coupled channels, non-identical and non-degenerate particles, and any intrinsic spin.

algorithms↗
DOE OSTI2024

Synchrotron-based diffraction-enhanced imaging and diffraction-enhanced imaging combined with CT X-ray imaging systems to image seeds at 30 keV

Utilized the upgraded Synchrotron-based non-destructive Diffraction-enhanced imaging and Diffraction-enhanced imaging coupled with CT X-ray imaging systems to image the chickpea seeds, to enhance the contrast in plant root architecture, visibility of fine structures of root architecture growth and some aspects of physiology at acceptable level. DEI-CT images were acquired with 30 keV synchrotron X-rays. A series of DEI-CT slices were assembled together, to form a 3D data set. DEI-CT images explored more structural information and morphology. Noticed detailed anatomical, physiological observations, and contrast mechanisms. Furthermore, with these systems, some of the complex plant traits, root morphology, growth of laterals and subsequent laterals can be visualized directly.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Inferring Stochastic Rates from Heterogeneous Snapshots of Particle Positions

Many imaging techniques for biological systems—like fixation of cells coupled with fluorescence microscopy—provide sharp spatial resolution in reporting locations of individuals at a single moment in time but also destroy the dynamics they intend to capture. In this study, these snapshot observations contain no information about individual trajectories, but still encode information about movement and demographic dynamics, especially when combined with a well-motivated biophysical model. The relationship between spatially evolving populations and single-moment representations of their collective locations is well-established with partial differential equations (PDEs) and their inverse problems. However, experimental data is commonly a set of locations whose number is insufficient to approximate a continuous-in-space PDE solution. Here, motivated by popular subcellular imaging data of gene expression, we embrace the stochastic nature of the data and investigate the mathematical foundations of parametrically inferring demographic rates from snapshots of particles undergoing birth, diffusion, and death in a nuclear or cellular domain. Toward inference, we rigorously derive a connection between individual particle paths and their presentation as a Poisson spatial process. Using this framework, we investigate the properties of the resulting inverse problem and study factors that affect quality of inference. One pervasive feature of this experimental regime is the presence of cell-to-cell heterogeneity. Rather than being a hindrance, we show that cell-to-cell geometric heterogeneity can increase the quality of inference on dynamics for certain parameter regimes. Altogether, the results serve as a basis for more detailed investigations of subcellular spatial patterns of RNA molecules and other stochastically evolving populations that can only be observed for single instants in their time evolution.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Breaking the passivation barrier via d-p orbital optimization for stable hydrogen production and sulfion upgrading

The development of energy-efficient hydrogen production technologies represents a critical pathway toward achieving global carbon neutrality objectives. This work provides fundamental insights into overcoming catalyst passivation challenges in sulfide oxidation reaction (SOR)-coupled hydrogen evolution reaction (HER) systems through precise orbital hybridization engineering. Our theoretical simulations reveal that sulfur-passivated ruthenium surfaces can effectively modulate d-p orbital hybridization, significantly reduce d-electron activity while stabilizing long-chain S 8 species and decreasing intermediate adsorption energies. Furthermore, metal carbides/ruthenium heterostructure (MC/Ru, M = V, Mo, W) was designed to achieve simultaneous optimization of both HER (∆G H* = −0.11 eV) and SOR (∆G RDS = 1.51 eV) via work-function-mediated interfacial electron transfer, which effectively tailors surface electronic states. Guided by theoretical predictions, we successfully synthesized a series of metal carbides/ruthenium/nitrogen-doped carbon catalysts based on a solid-phase reaction and designated as MC/Ru@NC (M = V, Mo, W). The optimized VC/Ru@NC catalyst exhibits exceptional performance in a membrane-free two-electrode system, achieving an ultralow cell voltage of 0.76 V at 200 mA cm −2 with outstanding stability over 1600 h, while maintaining 97.5 % Faradaic efficiency for hydrogen production and 73.8 % sulfur recovery efficiency.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Feedstock and Catalyst Impact on Bio-Oil Production and FCC Co-Processing to Fuels

NREL's thermochemical biomass conversion research is focused on ex-situ upgrading of biomass fast-pyrolysis (FP) vapors as an efficient route to completely biogenic pyrolysis-based fuel precursors, fuels, and value-added chemicals depending on catalyst and process conditions. A near term pathway being developed uses these liquids for co-processing with petroleum feedstocks to assess biogenic carbon incorporation in hydrocarbon fuel feedstocks for potential refinery use. In this work, the impact of feedstock and catalyst on catalytic fast pyrolysis oil (CFPO) composition was determined with the oils then assessed for biogenic fuel production via FCC (fluidized catalytic cracking) co-processing. Biomass vapors were generated via fast pyrolysis with destabilizing vapor components (char, inorganics, tar aerosols) removed by hot gas filtration to produce clean vapors more responsive to catalytic upgrading. A Davison Circulating Riser (DCR), a petroleum industry standard for fluidized catalytic cracking (FCC) catalyst evaluation, was coupled to a custom pyrolyzer system designed to produce consistent-composition pyrolysis vapors as feed to the DCR. Pyrolysis vapors, derived from pure hardwood and softwood, were upgraded using commercially available modified zeolite-based catalysts to produce CFPOs. These upgraded oils were analyzed via 31P and 13C NMR spectroscopy, GCxGC-TOF/MS, carbonyl and ultimate analysis (CHNO), and simulated distillation (SIMDIS) to assess both oil chemistry and distillation behavior as they relate to catalyst and feedstock type for producing fungible hydrocarbon product liquids. These exploratory vapor-phase-upgrading results demonstrated the feasibility of producing refinery-compatible hydrocarbon fuel intermediates entirely from biomass-derived fast-pyrolysis vapors using an industry-accepted DCR system for catalytic upgrading. The FCC co-processing results demonstrated the feasibility of using CFPOs with VGO feeds in FCC refinery operations to produce biogenic carbon containing fuels.

biogenic carbon↗
DOE OSTI2025

Steric effects of central dogma processes on the compaction and segregation of bacterial nucleoids

The bacterial cytoplasm is characterized by a distinctive membrane-less organelle, the nucleoid, which harbors the chromosomal DNA. Here, we investigate the steric effects of dynamic processes associated with transcription and translation on the structure of this organelle using coarse-grained molecular dynamics simulations that incorporate out-of-equilibrium reactions. Our model captures the scale of the entire cell and incorporates a reaction-diffusion system for ribosomes and polyribosomes, coupling their nonequilibrium kinetics to DNA excluded volume interactions. Our findings demonstrate that out-of-equilibrium reactions increase the size of the nucleoid and the number of ribosomes in this subcellular region. In addition, we show that nucleoid size is proportional to transcriptional activity. Our model reproduces the time-dependent change in nucleoid size observed in rifampicin treatment experiments, where the pool of polyribosomes is depleted. Furthermore, we find that these active processes are essential for complete sister chromosome separation and correct nucleoid positioning within the cell. Overall, our study reveals the effects of the central dogma processes on the internal organization and localization of bacterial nucleoids.

Chang, Mu-Hung [Univ. of Tennessee, Knoxville, TN ↗
DOE OSTI2022

Modeling gas release from a Bingham plastic slurry and deconvoluting measured data

Physics-based models for predicting the off-gassing characteristics of agitated slurries are presented. This approach decomposes the system into two separate but coupled slurry and headspace models. The physics driving bubble transport through the slurry and gas mixing within the headspace are discussed. An analytical expression for predicting the time evolution of the headspace concentration using first principles theory is also presented. Predictions from the numerical models, as well as expectations from the analytical solution, both agree with measured off gassing data for two different experimental operating conditions. After benchmarking the numerical model predictions against experimental data, the model was used to make predictions for gas release from a full-scale vessel and to perform sensitivity analyses to examine the sensitivity of gas release to parameters such as yield stress, consistency index, slurry density, bubble size, bubble concentration, and impeller speed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

A simple and fast algorithm for estimating the capacity credit of solar and storage

Energy storage is a leading option to enhance the resource adequacy contribution of solar energy. Detailed analysis of the capacity credit of solar energy and energy storage is limited in part due to the data intensive and computationally complex nature of probabilistic resource adequacy assessments. This paper presents a simple algorithm for calculating the capacity credit of energy-limited resources that, due to the low computational and data needs, is well suited to exploratory analysis. Validation against benchmarks based on probabilistic techniques shows that it can yield similar insights. The method is used to evaluate the impact of different solar and storage configurations, particularly with respect to the strategy for coupling storage and solar photovoltaic systems. Furthermore, application of the method to a case study of utilities in Florida, where solar is rapidly growing and demand peaks in the winter and summer, demonstrates that it can improve on rules of thumb used in practice by some utilities. If storage is required to charge only from solar, periods of high demand driven by cold weather events accompanied by lower solar production can result in a capacity credit of solar and storage that is less than the capacity credit of storage alone.

14 SOLAR ENERGY↗
DOE OSTI2025

A fully-integrated lattice Boltzmann method for fluid–structure interaction

Here we present a fully-integrated lattice Boltzmann (LB) method for fluid–structure interaction (FSI) simulations that efficiently models deformable solids in complex suspensions and active systems. Our Eulerian method (LBRMT) couples finite-strain solids to the LB fluid on the same fixed computational grid with the reference map technique (RMT). An integral part of the LBRMT is a new LB boundary condition for moving deformable interfaces across different densities. With this fully Eulerian solid–fluid coupling, the LBRMT is well-suited for parallelization and simulating multi-body contact without remeshing or extra meshes. We validate its accuracy via a benchmark of a deformable solid in a lid-driven cavity, then showcase its versatility through examples of soft solids rotating and settling. The LBRMT achieves a spatial convergence rate between first-order and second-order for FSI simulations and is designed for low to intermediate Reynolds number flows with finite inertia at small Mach numbers. With simulations of complex suspensions mixing, we highlight the potential of the LBRMT for studying collective behavior in soft matter and biofluid dynamics.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Toward DMC Accuracy Across Chemical Space with Scalable Δ-QML

In the past decade, quantum diffusion Monte Carlo (DMC) has been demonstrated to successfully predict the energetics and properties of a wide range of molecules and solids by numerically solving the electronic many-body Schrödinger equation. With O(N 3 ) scaling with the number of electrons N, DMC has the potential to be a reference method for larger systems that are not accessible to more traditional methods such as CCSD(T). Assessing the accuracy of DMC for smaller molecules becomes the stepping stone in making the method a reference for larger systems. We show that when coupled with quantum machine learning (QML)-based surrogate methods, the computational burden can be alleviated such that quantum Monte Carlo (QMC) shows clear potential to undergird the formation of high-quality descriptions across chemical space. We discuss three crucial approximations necessary to accomplish this: the fixed-node approximation, universal and accurate references for chemical bond dissociation energies, and scalable minimal amons-set-based QML (AQML) models. Numerical evidence presented includes converged DMC results for over 1000 small organic molecules with up to five heavy atoms used as amons and 50 medium-sized organic molecules with nine heavy atoms to validate the AQML predictions. Finally, numerical evidence collected for Δ-AQML models suggests that already modestly sized QMC training data sets of amons suffice to predict total energies with near chemical accuracy throughout chemical space.

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

Future sea level change under CMIP5 and CMIP6 scenarios from the Greenland and Antarctic ice sheets

Projections of the sea level contribution from the Greenland and Antarctic ice sheets rely on atmospheric and oceanic drivers obtained from climate models. The Earth System Models participating in the Coupled Model Intercomparison Project phase 6 (CMIP6) generally project greater future warming compared with the previous CMIP5 effort. Here we use four CMIP6 models and a selection of CMIP5 models to force multiple ice sheet models as part of the Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6). We find that the projected sea level contribution at 2100 from the ice sheet model ensemble under the CMIP6 scenarios falls within the CMIP5 range for the Antarctic ice sheet but is significantly increased for Greenland. Warmer atmosphere in CMIP6 models results in higher Greenland mass loss due to surface melt. For Antarctica, CMIP6 forcing is similar to CMIP5 and mass gain from increased snowfall counteracts increased loss due to ocean warming.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Wetter California Projected by CMIP6 Models With Observational Constraints Under a High GHG Emission Scenario

As the world's fifth-largest economy entity, California (CA) is vulnerable to climate changes especially the magnitude of winter (wet season) precipitation that is closely linked to regional drought severity, vegetation growth, and wildfire activities. However, the fate of CA precipitation in the future remains highly uncertain, for example, the state-of-the-art Earth system models (ESMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) projected –3% to +42% and –27% to +63% precipitation changes in northern and central-southern CA, respectively, under the high greenhouse gas (GHG) emission scenario (SSP585). In this work, we applied the Pareto optimality concept and used observed teleconnection patterns (causal relationships between ocean regions and CA precipitation) to mechanistically constrain CMIP6 projected CA precipitations. We estimated that precipitation will robustly increase by 0.4–1.3 mm d –1 (10–34%) over northern CA and increase by 0.1–0.5 mm d –1 (7–32%) over central-southern CA by the end of the 21st century compared with present-day. Up to 71% of ESM projection uncertainties were reduced mainly due to the strong and consistent causal relationship between North American west coast sea level pressure and CA precipitation in both observations and CMIP6 models. Our results suggest that teleconnection patterns are powerful mechanistic constraints that can help explain and reduce uncertainties in ESM projections.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Abundant Nitrate and Nitric Acid Aerosol in the Upper Troposphere and Lower Stratosphere

The tropospheric and stratospheric nitrate aerosol is simulated by a sectional aerosol model coupled to the Community Earth System Model. The simulated nitrate mass fractional contribution to aerosols is significantly higher in the upper troposphere and lower stratosphere (UTLS) than that at the surface. Both in situ measurements and simulations show that nitrate aerosol accounts for about 30%–40% of the aerosol mass at the tropopause of the Asian summer monsoon (ASM) region. Furthermore, simulated condensed nitric acid particles account for ~20% of the annual mean aerosol mass at the tropical tropopause, and over 95% in the UTLS at the South Pole in June-July-August. Here, our study suggests that the extremely cold ambient conditions in the UTLS of the tropics, ASM and polar regions thermodynamically favor the condensation of ammonia and nitric acid. The widely distributed nitrate aerosol in the global UTLS may be overlooked by climate models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

How Could Future Climate Conditions Reshape a Devastating Lake‐Effect Snow Storm?

Abstract Lake‐effect snow (LES) storms, characterized by heavy convective precipitation downwind of large lakes, pose significant coastal hazards with severe socioeconomic consequences in vulnerable areas. In this study, we investigate how devastating LES storms could evolve in the future by employing a storyline approach, using the LES storm that occurred over Buffalo, New York, in November 2022 as an example. Using a Pseudo‐Global Warming method with a fully three‐dimensional two‐way coupled lake‐land‐atmosphere modeling system at a cloud‐resolving 4 km resolution, we show a 14% increase in storm precipitation under the end‐century warming. This increase in precipitation is accompanied by a transition in the precipitation form from predominantly snowfall to nearly equal parts snowfall and rainfall. Through additional simulations with isolated atmospheric and lake warming, we discerned that the warmer lake contributes to increased storm precipitation through enhanced evaporation while the warmer atmosphere contributes to the increase in the storm's rainfall, at the expense of snowfall. More importantly, this shift from snowfall to rainfall was found to nearly double the area experiencing another winter hazard, Rain‐on‐Snow. Our study provides a plausible future storyline for the Buffalo LES storm, focusing on understanding the intricate interplay between atmospheric and lake warming in shaping the future dynamics of LES storms. It emphasizes the importance of accurately capturing the changing lake‐atmosphere dynamics during LES storms under future warming.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

An Integrated Modeling Framework for Sediment Dynamics During Urban Flooding: Application to Hurricane Harvey in Houston

Floodwater can mobilize and redistribute large volumes of sediment from upland to downstream urban areas, threatening infrastructure, water quality, and ecosystem health. However, existing modeling approaches often fail to capture sediment dynamics in urban floodplains due to the lack of integration between upland hydrological processes and riverine sediment transport. This study presents the first integrated modeling framework that couples the Energy Exascale Earth System Model (E3SM) land component, which simulates runoff and hillslope erosion, with TELEMAC-GAIA, a two-dimensional hydrodynamic and sediment transport model. This framework enables the fully distributed, process-based simulation of high-resolution (as fine as 30 m) sediment dynamics from hillslopes to floodplains. Applied to a highly urbanized watershed in Houston during Hurricane Harvey, this framework reproduced observed water levels at 16 USGS gauges (median R 2 = 0.83 and KGE = 0.78), key sediment dynamics such as sediment transport and deposition processes, and reproduced spatial deposition patterns consistent with LiDAR-derived data. Based on the simulation, we estimate 8.0 million m 3 of event-scale sediment deposition, including 5.7 million m 3 trapped in the flood-control reservoirs and 2.3 million m 3 deposited along major channels and floodplains. Using a representative unit removal cost, this corresponds to an estimated dredging cost of $581 million for total deposition. These results provide a first-order, physically based quantification of Harvey-scale sediment impacts. This study provides a valuable tool for the holistic analysis of sediment dynamics triggered by extreme urban flooding, supporting flood-resilience planning. More broadly, it highlights the importance of integrating physically based hydrological processes for urban flooding and sediment research.

Hurricane Harvey↗
DOE OSTI2020

Feedback regulation of crystal growth by buffering monomer concentration

Abstract Crystallization is a ubiquitous means of self-assembly that can organize matter over length scales orders of magnitude larger than those of the monomer units. Yet crystallization is notoriously difficult to control because it is exquisitely sensitive to monomer concentration, which changes as monomers are depleted during growth. Living cells control crystallization using chemical reaction networks that offset depletion by synthesizing or activating monomers to regulate monomer concentration, stabilizing growth conditions even as depletion rates change, and thus reliably yielding desired products. Using DNA nanotubes as a model system, here we show that coupling a generic reversible bimolecular monomer buffering reaction to a crystallization process leads to reliable growth of large, uniformly sized crystals even when crystal growth rates change over time. Buffering could be applied broadly as a simple means to regulate and sustain batch crystallization and could facilitate the self-assembly of complex, hierarchical synthetic structures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Study of the doubly charmed tetraquark $\mathrm{T}$ $^+_{cc}$

Quantum chromodynamics, the theory of the strong force, describes interactions of coloured quarks and gluons and the formation of hadronic matter. Conventional hadronic matter consists of baryons and mesons made of three quarks and quark-antiquark pairs, respectively. Particles with an alternative quark content are known as exotic states. Here a study is reported of an exotic narrow state in the D 0 D 0 π + mass spectrum just below the D *+ D 0 mass threshold produced in proton-proton collisions collected with the LHCb detector at the Large Hadron Collider. The state is consistent with the ground isoscalar T$^{+}_{cc}$ tetraquark with a quark content of cc$\bar{u}\bar{d}$ and spin-parity quantum numbers J P = 1 + . Study of the DD mass spectra disfavours interpretation of the resonance as the isovector state. The decay structure via intermediate off-shell D *+ mesons is consistent with the observed D 0 π+ mass distribution. To analyse the mass of the resonance and its coupling to the D*D system, a dedicated model is developed under the assumption of an isoscalar axial-vector T$^{+}_{cc}$ state decaying to the D*D channel. Using this model, resonance parameters including the pole position, scattering length, effective range and compositeness are determined to reveal important information about the nature of the T$^{+}_{cc}$ state. In addition, an unexpected dependence of the production rate on track multiplicity is observed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Stability of Kuramoto networks subject to large and small fluctuations from heterogeneous and spatially correlated noise

Oscillatory networks subjected to noise are broadly used to model physical and technological systems. Due to their nonlinear coupling, such networks typically have multiple stable and unstable states that a network might visit due to noise. In this article, we focus on the assessment of fluctuations resulting from heterogeneous and spatially correlated noise inputs on Kuramoto model networks. We evaluate the typical, small fluctuations near synchronized states and connect the network variance to the overlap between stable modes of synchronization and the input noise covariance. Going beyond small to large fluctuations, we introduce the indicator mode approximation that projects the dynamics onto a single amplitude dimension. Such an approximation allows for estimating rates of fluctuations to saddle instabilities, resulting in phase slips between connected oscillators. Statistics for both regimes are quantified in terms of effective noise amplitudes that are compared and contrasted for several noise models. In conclusion, bridging the gap between small and large fluctuations, we show that a larger network variance does not necessarily lead to higher rates of large fluctuations.

42 ENGINEERING↗