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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 1,387 records · Page 77
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Understanding Charge Storage in Hydrated Layered Solids MOPO 4 (M = V, Nb) with Tunable Interlayer Chemistry

Hydrated layered solids are interesting charge storage hosts with potentially high electrochemical activity and interlayer tunability. Although it is often possible to tune their interlayer distance by a pillaring strategy, the poor electrochemical stability of such artificial structures remains a major issue in device operation. Here we investigate the charge storage properties of MOPO 4 (M = V, Nb) hydrates with a nanosheet morphology to understand the influence of the interlayer environment on cycling stability, as well as ion selectivity. While in hydrated VOPO 4 interlayer H 2 O molecules act as compressible springs to enable fast Li-/Na-ion transport kinetics and reasonable structural reversibility, NbOPO 4 layers with bridging PO 4 groups serving as permanent linkers exhibit highly stable cyclability for Li-ions, owing to a zero-volume-change ion transport process. However, the latter suffers from a much larger migration energy barrier for Na-ions. Lastly, our findings not only highlight a structurally intriguing material system, but also provide insights into reviving materials with an originally unstable interlayer chemical environment, and shed light on the design principles for creating electrochemically stable charge storage hosts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Development and Validation of Predictive Models for In-Cylinder Radiation and Wall Heat Transfer

The lack of accurate submodels for in-cylinder radiation and heat transfer has been identified as a key shortcoming in developing truly predictive, physics-based computational fluid dynamics (CFD) models that can be used to develop and design combustion systems for advanced high-efficiency, low-emissions engines. Measurements of wall boundary layers in engines show discrepancies of up to 100% with respect to standard CFD boundary layer models. And analysis of in-cylinder radiation based on the most recent spectral property databases and high-fidelity radiative transfer equation solvers has shown that at operating pressures and exhaust-gas recirculation levels typical of modern compression-ignition truck engines, molecular gas radiation (mainly carbon dioxide and water vapor) can be more important than soot particle radiation, and that a significant fraction of the emitted radiation (50% or more) can be reabsorbed before reaching the walls, thereby acting to redistribute energy in the combustion chamber. In this project, an integrated experimental and simulation approach has been used to generate new physical insight into in-cylinder heat-transfer processes in engines, and to develop computationally practicable CFD-based models that accurately represent the physics. New experimental data have been taken in an optically accessible single-cylinder research engine, and in a multi-cylinder production engine. Those data have provided new insight into the radiative environment in engines. New CFD models have been developed and validated for in-cylinder heat transfer, focusing mainly on radiative heat transfer and coupling between turbulent boundary layer wall heat transfer and radiative heat transfer. The CFD models have been developed and implemented in an open-source software framework that can be shared with other researchers. The models are compatible both with unsteady Reynolds-averaged Navier Stokes (URANS) formulations and with large-eddy simulations (LES) of in-cylinder processes in engines.

02 PETROLEUM↗
DOE OSTI2022

Scan strategies in EBM-printed IN718 and the physics of bulk 3D microstructure development

Three-dimensional (3D) characterization provides opportunities for understanding processing-structure relationships in additively manufactured (AM) materials. Bulk samples of Inconel 718 were fabricated via electron beam melting (EBM) in order to study microstructural development as a function of energy input and beam scan strategy. TriBeam tomography of bulk Inconel 718 microstructures built under steady-state growth conditions reveals the sensitivity of microstructure formation and evolution to machine process parameters. Here, samples manufactured using a narrow range of energy input per unit build area result in varied grain morphologies and crystallographic textures. Using TRUCHAS, a thermal simulation software, the thermal history of bulk scan strategies was predicted, and combined with a calibrated microstructure-processing map to accurately predict bulk grain morphologies. The solidification parameters and the 3D measured nucleation density are used to predict the transition between columnar and equiaxed grain morphologies, providing a process map to guide AM parameter choices to locally control as-printed microstructure. A two-dimensional metric for characterizing bulk grain morphology was also found to agree well with predictions from the process map calibrated by 3D data. Combined with 3D tomography and thermal modelling, the physics of structure development were understood at a new level of detail with respect to the competing processes of grain nucleation and epitaxial growth.

36 MATERIALS SCIENCE↗
DOE OSTI2023

LHC hadronic jet generation using convolutional variational autoencoders with normalizing flows

Abstract In high energy physics, one of the most important processes for collider data analysis is the comparison of collected and simulated data. Nowadays the state-of-the-art for data generation is in the form of Monte Carlo (MC) generators. However, because of the upcoming high-luminosity upgrade of the Large Hadron Collider (LHC), there will not be enough computational power or time to match the amount of needed simulated data using MC methods. An alternative approach under study is the usage of machine learning generative methods to fulfill that task. Since the most common final-state objects of high-energy proton collisions are hadronic jets, which are collections of particles collimated in a given region of space, this work aims to develop a convolutional variational autoencoder (ConVAE) for the generation of particle-based LHC hadronic jets. Given the ConVAE’s limitations, a normalizing flow (NF) network is coupled to it in a two-step training process, which shows improvements on the results for the generated jets. The ConVAE+NF network is capable of generating a jet in 18.30 ± 0.04 μ s , making it one of the fastest methods for this task up to now.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Neutrino-Nucleus Interactions in the Precision Era

Current and future accelerator-based neutrino facilities, leveraging intense neutrino beams and advanced detectors, aim to precisely determine neutrino properties and probe signals of weakly interacting beyond the Standard Model physics. Achieving discovery-level precision and fully exploring the physics potential of these experiments critically depends on the accuracy of our understanding of fundamental underlying neutrino-nucleus interaction processes. This talk will focus on neutrino interactions spanning energies from tens of MeV to a few GeV—a complex, multi-scale and multi-process domain spanning from low-energy nuclear physics to perturbative QCD, with no unified underlying framework currently known. In this seminar, I will provide an overview of the field, discuss recent advancements, and share examples of ongoing cross-community efforts addressing these challenges.

Pandey, Vishvas [Fermilab]↗
DOE OSTI2025

Neutrino-Nucleus Interactions in the Precision Era

Current and future accelerator-based neutrino facilities, leveraging intense neutrino beams and advanced detectors, aim to precisely determine neutrino properties and probe signals of weakly interacting beyond the Standard Model physics. Achieving discovery-level precision and fully exploring the physics potential of these experiments critically depends on the accuracy of our understanding of fundamental underlying neutrino-nucleus interaction processes. This talk will focus on neutrino interactions spanning energies from tens of MeV to a few GeV a complex, multi-scale and multi-process domain spanning from low-energy nuclear physics to perturbative QCD, with no unified underlying framework currently known. In this talk, I will provide an overview of the field, discuss recent advancements, and share examples of ongoing cross-community efforts addressing these challenges.

Pandey, Vishvas [Fermilab] (ORCID:0000000230827987↗
DOE OSTI2022

Efficient Source of Shaped Single Photons Based on an Integrated Diamond Nanophotonic System

An efficient, scalable source of shaped single photons that can be directly integrated with optical fiber networks and quantum memories is at the heart of many protocols in quantum information science. We demonstrate a deterministic source of arbitrarily temporally shaped single-photon pulses with high efficiency [detection efficiency = 14.9 %] and purity [g (2) (0) = 0.0168] and streams of up to 11 consecutively detected single photons using a silicon-vacancy center in a highly directional fiber-integrated diamond nanophotonic cavity. Finally, combined with previously demonstrated spin-photon entangling gates, this system enables on-demand generation of streams of correlated photons such as cluster states and could be used as a resource for robust transmission and processing of quantum information.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

The role of supernova convection for the lower mass gap in the isolated binary formation of gravitational wave sources

ABSTRACT Understanding the astrophysical phenomena involving compact objects requires an insight about the engine behind the core-collapse supernovae (SNe) and the fate of the stellar collapse of massive stars. In particular, this insight is crucial in developing an understanding of the origin and formation channels of the growing populations of the detected black hole–black hole, black hole–neutron star, and neutron star–neutron star mergers. The time-scale of convection growth may have a large effect on the strength of SN explosion and therefore also on the mass distribution of stellar remnants. We adopt new formulas for the relation between the pre-SN star properties and their remnants and check how they impact the population of double compact object (DCO) mergers formed via the isolated binary evolution. The new formulas give one the ability to test a wide spectrum of assumptions on the convection growth time. In particular, the different variants allow for a smooth transition between having a deep mass gap and a remnant mass distribution filled by massive neutron stars and low-mass black holes. We present the distribution of masses, mass ratios, and the local merger rate densities of DCO for the different variants of new formulas and test them together with different approaches to other highly uncertain processes. We find that the mass distribution of DCO mergers is sensitive to the adopted assumption on the SN convection growth time-scale up to $m_1+m_2 \lesssim 35 \, \mathrm{M}_{\odot }$. Between the two extreme tested variants the probability of compact object formation within the mass gap may differ by up to approximately two orders of magnitude.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Impact of in situ nuclear networks and atomic opacities on neutron star merger ejecta dynamics, nucleosynthesis, and kilonovae

Context. Binary neutron star merger (BNSM) ejecta are key sites of rapid neutron capture (r-process) nucleosynthesis and they produce kilonovae powered by the radioactive decay of freshly synthesized nuclei. Modeling their evolution requires multi-physics simulations involving hydrodynamics, nuclear reactions, and radiative processes. The impact of nuclear burning and atomic opacity is poorly understood and often treated with simplified prescriptions. Aims. We systematically investigate different treatments of nuclear heating, particle thermalization, and atomic opacities in radiation-hydrodynamics simulations of BNSM ejecta and kilonova light curves. Methods. Ejecta profiles from long-term numerical-relativity simulations of asymmetric neutron star binaries with a massive neutron star remnant were evolved to ∼30 days using a 2D ray-by-ray approach. We compared simplified heating-rate and thermalization prescriptions with in situ Nuclear reaction Network (NN) calculations that track nuclear energy deposition and include a composition-dependent thermalization scheme. We also contrasted various gray opacity models with a frequency-dependent treatment based on atomic calculations. Results. Coupling NN and hydrodynamics significantly affects nucleosynthesis and kilonova emission. Assuming homologous expansion alters abundance evolution and produces a narrower, less populated second r-process peak and a third peak shifted to higher mass numbers. The back-reaction of nuclear heating affects the temperature evolution enough to delay and redden the early (t∼ hours) kilonova peaks. A constant thermalization efficiency underestimates and reddens the early emission while overestimating the late-time luminosity compared to the composition-dependent treatment. Analytical opacity prescriptions yield a more extended, colder photosphere, resulting in dimmer, redder kilonovae at early times (t≲ hour), while the delayed recession of the photosphere prolongs the red emission at t ≳ 5 days. Conclusions. Coupling hydrodynamics to an in situ NN is crucial for reliable nucleosynthesis and kilonova predictions. Resolving the first several hundred milliseconds of the hydrodynamics is essential for robust nucleosynthesis calculations. Composition-dependent thermalization and frequency-dependent, atomic-physics-based opacities are needed to accurately capture the temperature evolution of the ejecta and the brightness and color evolution of the kilonova. Calibrated analytic nuclear-power fits with simplified thermalization and opacity prescriptions can still reproduce the density and temperature evolution of the ejecta.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Imaging the Phase Transformation in Single Particles of Lithium Titanate Anode for Lithium-ion Batteries

Lithium uptake and release in lithium titanate (LTO) anode materials during a discharge and charge cycle is one of the fundamental processes of a Lithium-ion battery (LIB), still not fully understood at the microscopic level.During discharge cycle, LTO undergoes a phase transformation between Li 4 Ti 5 O 12 and Li 7 Ti 5 O 12 states within a cubic crystal lattice. To reveal the details of the microscopic mechanism,it is necessary to track the sequence of phase transformation sat different discharge/charge states under operating conditions.Here we use in-situ Bragg Coherent Diffraction Imaging (BCDI) and in-situ X-ray diffraction (XRD) experiments to examine the lithium insertion-induced materials phase transformation within a single LTO particle anda bulk battery analogue,respectively. BCDI analysis from (111) Bragg peak, shows the two-phase transformation manifesting as a distinct image phase modulation within a single LTO nanoparticle occurring in the middle of the discharge region then subsiding towards the end of the discharge cycle. We observe the biggest phase variation at the two-phase stage,indicating the formation of phase domains of 200 nm in size during the discharge process. Additionally, we also observe a lattice contraction of >0.2% in a single LTO nanoparticle at the (400) Bragg peak measurement, larger than that in the corresponding bulk material. Our observation of this phase transformation at a single particle level has implications for the understanding of the microscopic/mesoscale picture of the phase transformation in anode and cathode LIBs materials.

25 ENERGY STORAGE↗
DOE OSTI2022

Carbon dioxide-enhanced metal release from kerogen

Heavy metals released from kerogen to produced water during oil/gas extraction have caused major environmental concerns. To curtail water usage and production in an operation and to use the same process for carbon sequestration, supercritical CO 2 (scCO 2 ) has been suggested as a fracking fluid or an oil/gas recovery agent. It has been shown previously that injection of scCO 2 into a reservoir may cause several chemical and physical changes to the reservoir properties including pore surface wettability, gas sorption capacity, and transport properties. Using molecular dynamics simulations, we here demonstrate that injection of scCO 2 might lead to desorption of physically adsorbed metals from kerogen structures. This process on one hand may impact the quality of produced water. On the other hand, it may enhance metal recovery if this process is used for in-situ extraction of critical metals from shale or other organic carbon-rich formations such as coal.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Measurement of isolated-photon plus two-jet production in p p collisions at s = 13 TeV with the ATLAS detector

The dynamics of isolated-photon plus two-jet production in pp collisions at a centre-of-mass energy of 13 TeV are studied with the ATLAS detector at the LHC using a dataset corresponding to an integrated luminosity of 36.1 fb−1. Cross sections are measured as functions of a variety of observables, including angular correlations and invariant masses of the objects in the final state, γ+jet+jet. Measurements are also performed in phase-space regions enriched in each of the two underlying physical mechanisms, namely direct and fragmentation processes. The measurements cover the range of photon (jet) transverse momenta from 150 GeV (100 GeV) to 2 TeV. The tree-level plus parton-shower predictions from SHERPA and PYTHIA as well as the next-to-leading-order QCD predictions from SHERPA are compared with the measurements. The next-to-leading-order QCD predictions describe the data adequately in shape and normalisation except for regions of phase space such as those with high values of the invariant mass or rapidity separation of the two jets, where the predictions overestimate the data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Quantum advantage for differential equation analysis

Quantum algorithms for differential equation solving, data processing, and machine learning potentially offer an exponential speedup over all known classical algorithms. However, there also exist obstacles to obtaining this potential speedup in useful problem instances. The essential obstacle for quantum differential equation solving is that outputting useful information may require difficult postprocessing, and the essential obstacle for quantum data processing and machine learning is that inputting the data is a difficult task just by itself. In this study, we demonstrate that, when combined, these difficulties solve one another. We show how the output of quantum differential equation solving can serve as the input for quantum data processing and machine learning, allowing dynamical analysis in terms of principal components, power spectra, and wavelet decompositions. To illustrate this, we consider continuous-time Markov processes on epidemiological and social networks. These quantum algorithms provide an exponential advantage over existing classical Monte Carlo methods.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

A survey of software implementations used by application codes in the Exascale Computing Project

The US Department of Energy Office of Science and the National Nuclear Security Administration initiated the Exascale Computing Project (ECP) in 2016 to prepare mission-relevant applications and scientific software for the delivery of the exascale computers starting in 2023. The ECP currently supports 24 efforts directed at specific applications and six supporting co-design projects. These 24 application projects contain 62 application codes that are implemented in three high-level languages—C, C++, and Fortran—and use 22 combinations of graphical processing unit programming models. The most common implementation language is C++, which is used in 53 different application codes. The most common programming models across ECP applications are CUDA and Kokkos, which are employed in 15 and 14 applications, respectively. This article provides a survey of the programming languages and models used in the ECP applications codebase that will be used to achieve performance on the future exascale hardware platforms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Cyber-Physical Smart Light Control System Integration with Smart Grid using Zigbee

This paper presents a hardware-in-the-loop cyber-physical system architecture design to monitor and control smart lights connected to the active distribution grid. The architecture uses Zigbee-based (IEEE 802.15.4) wireless sensor networks and publish-subscribe architecture to exchange monitoring and control signals between smart-light actuators (SLAs) and a smart-light central controller (SLCC). Each SLA integrated into a smart light consists of a Zigbee-based endpoint module to send and receive signals to and from the SLCC. The SLCC consists of a Zigbee-based coordinator module, which further exchanges the monitoring and control signals with the active distribution management system over the TCP/IP communication network. The monitoring signals from the SLAs include light status, brightness level, voltage, current, and power data, whereas, the control signals to the SLAs include light intensity, turn ON, turn OFF, standby, and default settings. We have used our existing hardware-in-the-loop (HIL) cyber-physical system (CPS) security SCADA testbed to process signals received from the SLCC and respond suitable control signals based on the smart light schedule requirements, system operation, and active distribution grid dynamic characteristics. We have integrated the proposed cyber-physical smart light control system (CPSLCS) testbed to our existing HIL CPS SCADA testbed. We use the integrated testbed to demonstrate the efficacy of the proposed algorithm by real-time performance and latency between the SLCC and SLAs. The experiments demonstrated significant results by 100% realtime performance and low latency while exchanging data between the SLCC and SLAs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Surface-Activated Corrosion in Tin–Lead Halide Perovskite Solar Cells

Mixed tin–lead halide perovskite solar cells have promising power conversion efficiencies, but long-term stability is still a challenge. Here, we examine the stability of a 60:40 tin–lead perovskite to better understand diminished device performance upon thermal treatment, both in ambient and inert atmosphere. Operando X-ray diffraction shows a stable bulk structure of the perovskite absorber, leading to the hypothesis that surface chemistry dominates the degradation mechanism. X-ray photoelectron spectroscopy reveals two new observations post-thermal annealing that accompany previously reported Sn 4+ evolution: (i) the formation of I 3 – intermediates preceding I 2 loss at the surface and (ii) evidence of under-coordinated tin and lead surface sites (Sn δ<2+ and Pb δ<2+ , respectively) in inert and ambient conditions. These two species indicate an activated corrosion (i.e., both oxidation and reduction) process at the surface as a possible chemical pathway for degradation, which is expected to be accelerated under operando voltage and light biases.

14 SOLAR ENERGY↗
DOE OSTI2021

Tuning Electrogenerated Chemiluminescence Intensity Enhancement Using Hexagonal Lattice Arrays of Gold Nanodisks

Electrogenerated chemiluminescence (ECL) microscopy shows promise as a technique for mapping chemical reactions on single nanoparticles. The technique’s spatial resolution is limited by the quantum yield of the emission and the diffusive nature of the ECL process. To improve signal intensity, ECL dyes have been coupled with plasmonic nanoparticles, which act as nanoantennas. Here, we characterize the optical properties of hexagonal arrays of gold nanodisks and how they impact the enhancement of ECL from the coreaction of tris(2,2'-bipyridyl)dichlororuthenium(II) hexahydrate and tripropylamine. Here, we find that varying the lattice spacing results in a 23-fold enhancement of ECL intensity because of increased dye-array near-field coupling as modeled using finite element method simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗