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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Thermo-mechanical behavior of hypoeutectic Ni-Y-Zr alloys

Microstructure refinement and optimized alloying can improve metallic alloy performance: stable nanocrystalline (NC) alloys with immiscible second phases, e.g., Cu-Ta, are stronger than unstable NC alloys and their coarse-grained (CG) counterparts, but higher melting point matrices are needed. Hypoeutectic, CG Ni-Y-Zr alloys were produced via arc-melting to explore their potential as high-performance materials. Microstructures were studied to determine phases present, local composition and length scales, while heat treatments allowed investigating microstructural stability. Alloys had a stable, hierarchical microstructure with ~250 nm ultrafine eutectic, ~10 µm dendritic arm spacing and ~1 mm grain size. Hardness and uniaxial compression tests revealed that mechanical properties of Ni-0.5Y-1.8Zr (in wt%) were comparable to Inconel 617 despite the small alloying additions, due to its hierarchical microstructure. Here, uniaxial compression at 600 °C showed that ternary alloys outperformed Ni-Zr and Ni-Y binary alloys in flow stress and hardening rates, which indicates that the Ni 17 Y 2 phase was an effective reinforcement for the eutectic, which supplemented the matrix hardening due to increased solubility of Zr. Results suggest that ternary Ni-Y-Zr alloys hold significant promise for high temperature applications.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Stability, metallicity, and magnetism in niobium silicide nanofilms

Modern superconducting qubits based on two-dimensional (2D) transmons typically involve the growth of Nb thin films on high-resistivity Si substrates. Since imperfections at the Nb-Si heterointerface have been implicated as a source of two-level systems that limit quantum coherence times, detailed characterization and understanding of niobium silicide interfacial layers are critical to improving superconducting qubit technology. While bulk binary intermetallic niobium silicide phases are well understood, the thermodynamic phase stability and properties of ultrathin niobium silicides, such as those found at the Nb-Si heterointerface in 2D transmons, have not yet been explored. Here, we report finite-sized effects for ultrathin niobium silicide films using density functional theory calculations and predict nanoscale stabilization of Nb 6 Si 5 over the bulk α-Nb 5 Si 3 phase. This result is consistent with our experimental observations of a niobium silicide interfacial layer between a sputtered Nb thin film and the underlying Si substrate. Furthermore, our calculations show that Nb 6 Si 5 nanofilms are nonmagnetic, making them superior to nanofilms of α-Nb 5 Si 3 that exhibit antiferromagnetic correlations detrimental to long coherence times in superconducting qubits. Furthermore, by providing atomic-scale insight into niobium silicide nanofilms, this paper can help guide ongoing efforts to optimize Nb-Si heterointerfaces for long coherence times in superconducting qubits.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Neural architecture search via similarity adaptive guidance

Evolutionary neural network architecture search (ENAS) has attracted the attention of many experts due to its global optimization capabilities to automatically search for convolutional neural network architectures based on the target task. The current search space for ENAS is not to design a fully structured network, but to search for smaller cell architectures to reduce search costs. However, blind search strategies do not effectively utilize the potential experience of the population. In order to utilize the potential experience learned by the current population to guide the evolutionary search of the population, we propose a similarity guided neural network architecture search algorithm based on cell architecture, which utilizes the similarity between pairwise architectures in the population as empirical knowledge learned by the population. Our proposed algorithm provides a novel method for calculating architecture similarity, which calculates architecture similarity separately from the cell and macro-structure. Then we decouple the connections and operations in the cell and calculate connection and operation similarity separately. In addition, we propose adaptive similarity selection and binary tournament selection strategies to enhance the algorithm’s global and local search capabilities and effectively explore the search space. Finally, we design an improved single-point crossover operator to enhance the local search ability of the evolutionary operator. The experimental results show that SAGNAS is a competitive algorithm that achieves 97.44% and 81.60% in CIFAR10 and CIFAR100 with only 1.9 GPU-days spent.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Fast Fourier transform evaluation of the Fresnel integral for gravitational-wave lensing

Gravitational waves (GWs) exhibit wave-optics effects when their wavelength is comparable to the scale of the gravitational lens. This may occur in lensing from galactic subhalos in GWs emitted by binary black-hole mergers and is gaining interest as a novel probe of dark matter. Predictions for observables in these cases ultimately rely on evaluating a Fresnel integral that quantifies the effect of lensing on the amplitude of a GW at a given frequency. However, numerical evaluation of this Fresnel integral is tricky, and several algorithms and publicly available codes that implement it have been developed. Here, we show that the dependence of this integral on the lens position can be written as a two-dimensional Fourier transform. Modern FFT techniques then enable rapid evaluation at all-sky positions simultaneously for general lenses without symmetry. Vectorization of FFT routines allows for derivatives with respect to model parameters to be obtained with only incremental additional computational cost. If the lens is axisymmetric, further speedups can be achieved with recently developed techniques for nonuniform fast Hankel transforms. To demonstrate, we make available Fresnel Integral Optimization with Nonuniform Transforms (fiona), an efficient and accurate code that is significantly faster than current methods for dense source grids, reaching 2 orders of magnitude speedups for ∼10 6 GW-emitting points. As part of FIONA , we developed code that provides vectorized nonuniform fast Hankel transforms that may have other uses (e.g., calculation of cosmological two-point correlation functions) beyond those considered here.

dark matter↗
DOE OSTI2021

Phase effects from strong gravitational lensing of gravitational waves

Assessing the probability that two or more gravitational wave (GW) events are lensed images of the same source requires an understanding of the properties of the lensed images. For short enough wavelengths where wave effects can be neglected, lensed images will generically have a fixed relative phase shift that needs to be taken into account in the lensing hypothesis. For non-precessing, circular binaries dominated by quadrupole radiation these lensing phase shifts are degenerate with either a shift in the coalescence phase or a detector and inclination dependent shift in the orientation angle. This degeneracy is broken by the presence of higher harmonic modes with |m| ≠ 2 in the former and |m| ≠ l in the latter. The presence of precession or eccentricity will also break this degeneracy. This implies that a lensed GW image will not necessarily be consistent with (unlensed) predictions from general relativity (GR). Therefore, unlike the conventional scenario of electromagnetic waves, strong lensing of GWs can lead to images with a modified phase evolution that can be observed. However, we find that templates with a shifted orientation angle remain a good approximation, with signal-to-noise ratio differences of less than 1% for mass ratios up to 1/18, and less than 5% for precession parameters up to 0.5 and eccentricities up to 0.4. We conclude that an optimal strong lensing search strategy would incorporate phase information in all stages of the identification of strong-lensing, with an exact treatment in the final assessment of the probability of multiple lensed events. Here, this work clarifies the role that strong lensing plays in the phase evolution of GWs: how it can lead to apparent deviations from GR, how it can affect the detectability of GW events, and how it can be exploited to help identify cases of strong gravitational lensing of gravitational wave sources.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2015

Python-Based Scientific Analysis and Visualization of Precipitation Systems at NASA Marshall Space Flight Center

At NASA Marshall Space Flight Center (MSFC), Python is used several different ways to analyze and visualize precipitating weather systems. A number of different Python‐based software packages have been developed, which are available to the larger scientific community. The approach in all these packages is to utilize pre‐existing Python modules as well as to be object‐oriented and scalable. The first package that will be described and demonstrated is the Python Advanced Microwave Precipitation Radiometer (AMPR) Data Toolkit, or PyAMPR for short. PyAMPR reads geolocated brightness temperature data from any flight of the AMPR airborne instrument over its 25‐year history into a common data structure suitable for user‐defined analyses. It features rapid, simplified (i.e., one line of code) production of quick‐look imagery, including Google Earth overlays, swath plots of individual channels, and strip charts showing multiple channels at once. These plotting routines are also capable of significant customization for detailed, publication‐ready figures. Deconvolution of the polarization‐varying channels to static horizontally and vertically polarized scenes is also available. Examples will be given of PyAMPR's contribution toward real‐time AMPR data display during the Integrated Precipitation and Hydrology Experiment (IPHEx), which took place in the Carolinas during May‐June 2014. The second software package is the Marshall Multi‐Radar/Multi‐Sensor (MRMS) Mosaic Python Toolkit, or MMM‐Py for short. MMM‐Py was designed to read, analyze, and display three‐dimensional national mosaicked reflectivity data produced by the NOAA National Severe Storms Laboratory (NSSL). MMM‐Py can read MRMS mosaics from either their unique binary format or their converted NetCDF format. It can also read and properly interpret the current mosaic design (4 regional tiles) as well as mosaics produced prior to late July 2013 (8 tiles). MMM‐Py can easily stitch multiple tiles together to provide a larger regional or national picture of precipitating weather systems. Composites, horizontal and vertical crosssections, and combinations thereof are easily displayed using as little as one line of code. MMM‐Py can also write to the native MRMS binary format, and sub‐sectioning of tiles (or multiple stitched tiles) is anticipated to be in place by the time of this meeting. Thus, MMM‐Py also can be used to power the creation of custom mosaics for targeted regional studies. Overlays of other data (e.g., lightning observations) are easily accomplished. Demonstrations of MMM‐Py, including the creation of animations, will be shown. Finally, Marshall has done significant work to interface Python‐based analysis routines with the U.S. Department of Energy's Py‐ART software package for radar data ingest, processing, and analysis. One example of this is the Python Turbulence Detection Algorithm (PyTDA), an MSFC‐based implementation of the National Center for Atmospheric Research (NCAR) Turbulence Detection Algorithm (NTDA) for the purposes of convective‐scale analysis, situational awareness, and forensic meteorology. PyTDA exploits Py‐ART's radar data ingest routines and data model to rapidly produce aviation‐relevant turbulence estimates from Doppler radar data. Work toward processing speed optimization and better integration within the Py‐ART framework will be highlighted. Python‐based analysis within the Py‐ART framework is also being done for new research related to intercomparison of ground‐based radar data with satellite estimates of ocean winds, as well as research on the electrification of pyrocumulus clouds.

Lang, Timothy J.↗
DOE OSTI2022

Machine Learning Models for Binary Molecular Classification using VUV Absorption Spectra

Machine learning methods were combined with differential absorption spectroscopy measurements in the vacuum-ultraviolet region (5.167 – 9.920 eV) in order to develop predictive capabilities for inferring molecular structure from the spectra. Several types of species were analyzed and, for modeling purposes, were defined using a single classification: (1) alkane, (2) conjugation with oxygen (e.g. diacetyl, ethyl vinyl ether), (3) non-conjugated alkene (e.g. 1-butene, 1,4-cyclohexadiene), (4) oxygen-containing (e.g. 1-butanol, tetrahydrofuran), or (5) cyclic (e.g. cyclopentane, cyclohexanone). The latter molecular classification excluded cyclic ethers. Several modeling methods were employed in the analysis of 102 absorption spectra, 24 of which were measured for the first time. The primary objective was to identify suitable methods that enable accurate predictions of molecular structure classifications with minimized statistical uncertainties. Rather than identifying a single, unifying method to reliably predict molecular structure contributions to VUV absorption spectra, coordination is required among a particular method, the type of molecular structure detail (e.g. conjugation), and absorption region of interest. The latter is accomplished using a binning approach, wherein absorption regions of ~0.5 eV were utilized rather than the entire ~4.8 eV range. Photon energy binning enabled analysis of region-specific predictions of accuracy, precision, and recall. The outcome from the binning approach is that, rather than utilizing the entire spectrum, optimal determination of molecular structure using machine learning methods depends on the absorption region. Furthermore, the present work provides separate machine learning models for each molecular classification, which enables the identification of multi-functional species relevant to atmospheric chemistry and combustion chemistry, where isomer-resolved speciation is critical to understanding complex reaction networks.

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

Efficient Control of Atom Arrangement in Ternary Metal Chalcogenide Nanoparticles Using Precursor Oxidation State

Controlling both the concentration and the distribution of elements in a given material is often crucial to extracting and optimizing synergistic properties of the various constituents. An interesting class of such multielement materials is metal chalcogenide nanoparticles, which exhibit a wide range of composition-dependent optoelectronic properties including both bandgap-mediated processes and localized surface plasmon resonance properties, each of which is useful in applications ranging from energy conversion to sensing. Because metal chalcogenide nanoparticles can support several different metal elements in a variety of chalcogen lattices, this material class has particularly benefited from the ability to control both atom concentration and atom arrangement to tailor final particle properties. The primary method to access complex, multimetallic chalcogenide particles is via a postsynthetic cation exchange strategy. One-pot syntheses have been less explored to access these complex particles, although this route is desirable for economy and scalability. In this work, we compare the composition and morphology outcomes from cation exchange and one-pot preparation approaches using a Cu/Ag/Se system, which is already known to exhibit both binary and ternary metal chalcogenide phases. We show that at similar concentrations of the two metal cations, initial reaction conditions for the one-pot method yield multicomponent nanoparticles, whereas cation exchange yields homogeneous ternary metal chalcogenide structures. We then show that by tuning the precursor oxidation state for the one-pot method, this approach can be used to access homogeneous ternary metal chalcogenide particles that are similar in atom arrangement to the particles obtained using cation exchange. Taken together, our results demonstrate reliable synthetic methods that yield a variety of controlled compositions and composition morphologies in the Cu/Ag/Se system. Importantly, we demonstrate that this entire collection of architectures can all be accessed via a one-pot method simply by modifying metal precursor chemistry. The mechanistic insights gained and the resulting streamlined syntheses outlined indicate pathways to easily scaled, highly tailorable syntheses for rapid translation into downstream technologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Reimagining Disassembly Interfaces With Visualization: Combining Instruction Tracing and Control Flow With DisViz

In applications where efficiency is critical, developers may examine their compiled binaries, seeking to understand how the compiler transformed their source code and what performance implications that transformation may have. This analysis is challenging due to the vast number of disassembled binary instructions and the many-to-many mappings between them and the source code. These problems are exacerbated as source code size increases, giving the compiler more freedom to map and disperse binary instructions across the disassembly space. Interfaces for disassembly typically display instructions as an unstructured listing or sacrifice the order of execution. Here, we design a new visual interface for disassembly code that combines execution order with control flow structure, enabling analysts to both trace through code and identify familiar aspects of the computation. Central to our approach is a novel layout of instructions grouped into basic blocks that displays a looping structure in an intuitive way. We add to this disassembly representation a unique block-based mini-map that leverages our layout and shows context across thousands of disassembly instructions. Finally, we embed our disassembly visualization in a web-based tool, DisViz, which adds dynamic linking with source code across the entire application. DizViz was developed in collaboration with program analysis experts following design study methodology and was validated through evaluation sessions with ten participants from four institutions. Participants successfully completed the evaluation tasks, hypothesized about compiler optimizations, and noted the utility of our new disassembly view. Our evaluation suggests that our new integrated view helps application developers in understanding and navigating disassembly code.

Computer science↗
DOE OSTI2025

Kinetics of amorphous defect phases measured through ultrafast nanocalorimetry

Recognition of the role of extended defects on local phase transitions has led to the conceptualization of the defect phase, localized thermodynamically stable interfacial states that have since been applied in a myriad of material systems to realize significant enhancements in material properties. Here, we explore the kinetics of grain boundary confined amorphous defect phases, utilizing the high temperature and scanning rates afforded by ultrafast differential scanning calorimetry to apply targeted annealing/quenching treatments at high rates capable of capturing the kinetic behavior. Four Al-based nanocrystalline alloys, including two binary systems, Al–Ni and Al–Y, and two ternary systems, Al–Mg–Y and Al–Ni–Y, are selected to probe the materials design space (enthalpy of mixing, enthalpy of segregation, chemical complexity) for amorphous defect phase formation and stability, with correlative transmission electron microscopy applied to link phase evolution and grain stability to nanocalorimetry signatures. A series of targeted isothermal annealing heat treatments is utilized to construct a Time–Temperature-Transformation curve for the Al–Ni system, from which a critical cooling rate of 2400 °C/s was determined for the grain boundary confined disordered-to-ordered transition. Finally, a thermal profile consisting of 1000 repeated annealing sequences was created to quantify the recovery of the amorphous defect phase following sequential annealing treatments, with results indicating remarkable microstructural stability after annealing at temperatures above 90% of the melting temperature. This work contributes to a deeper understanding of grain boundary localized thermodynamics and kinetics, with potential implications for the design and optimization of advanced materials with enhanced stability and performance.

Amorphous defect phases↗
DOE OSTI2024

Atomistic Simulations for Thermophysical Properties of Uranium-Containing Halide Molten Salts

Characterizing the thermophysical properties in both fuel and coolant salts are critical in modeling, developing, process optimizing and utilizing molten salt reactors (MSRs), as these properties directly relate to operation metrics and can inform on the selection of candidate salts. The demand for consistent, accurate and publicly available thermophysical property data has become more apparent in recent years as interests have increased from molten salt reactor developers. There are a number of challenges in experimentally measuring properties such as thermal conductivity, viscosity, density and heat capacity , which have led to sparse and often times conflicting data points or molten salts in general. Additionally, there are a number of hazards to consider when synthesizing, storing, using, treating and disposing of molten salts. With the advances in computational capabilities over the last 10 years, the use of atomistic simulations can be implemented to support these efforts. The primary objective of this work is characterize the thermophysical transport properties in a number of molten chloride salts, and in particular NaCl-UCl 3 using ab-initio molecular dynamic (AIMD) simulations. In this binary salt the UCl 3 acts as the primary fissile material and NaCl acts as a carrier salt due with its’ high solubility for actinides A number of studies on the thermophysical properties of NaCl-UCl 3 have been published but there is not a vast amount of viscosity data for this system. In 1975, Desyatnik, et al published a study reporting dynamic viscosities that were calculated from kinematic viscosity measurements, and using the coefficients provided the viscosity in a 70:30 NaCl:UCl 3 mixture is 2.29 cP and 2.88 for a 60:40 mixture. Termini et al. recently reported viscosities in the range of 2.75 – 3 cP for the 63:37 NaCl-UCl 3 mixture in the same temperature range using rolling ball viscosity measurements. Computational viscosity of a similar mixture (64:36) can be obtained from the work Andersson et al. using the reported diffusion coefficients, and the hydrodynamic radius from the pair-radial distribution functions (RDFs). Using Eq (1) (vida infra), the viscosity would be 2.50 cP at 1100K. This is not to say that these values are incorrect due to the varying reported values, but aims to highlight the necessity of this work. The data reported in this ongoing work are computations on a 64:36 mixture of NaCl-UCl 3 at 987K. This work is likely to be expanded into varying concentrations of this mixture along with the inclusion of other salt candidate mixtures.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2026

Chasing Gamma-Ray Signals from Binary Neutron Star Coalescences with the Cherenkov Telescope Array: Prospects and Observing Strategies

The detection of gravitational waves (GWs) from a binary neutron star (BNS) merger by Advanced LIGO and Advanced Virgo (GW170817), together with its electromagnetic counterpart, the short gamma-ray burst GRB 170817A, heralded the birth of multimessenger astronomy. The detection of TeV emission from GRBs motivates follow-up observations with the Cherenkov Telescope Array Observatory (CTAO), which is ideal for detecting such signals due to its unprecedented sensitivity, rapid response, and wide-field survey capabilities. The aim of this work is to evaluate GeV–TeV GW follow-up strategies for CTAO using a multistep simulation pipeline and to estimate the expected rate of joint GW–GRB detections during observing run O5. Using a simulated sample of BNS systems with corresponding GW detections, gamma-ray emission is simulated through phenomenological prescriptions based on the observed population of short GRBs, including off-axis jet scenarios. CTAO observations are simulated to account for instrument response, sky tiling strategies, integration times, and varying observing conditions. Strategies with variable and constant integration times are investigated. We find that, via an optimized follow-up strategy, about 5% of simulated GW-associated short GRBs produce GeV–TeV radiation detectable by CTAO. Detectability is strongly influenced by the jet opening angle and viewing angle, suggesting that even rough estimates of the viewing angle in GW alerts could enhance targeting. This framework motivates future follow-ups of GW-detectable events, including neutron star–black hole mergers, and further supports the development of advanced strategies incorporating galaxy distributions and synergies with future detectors such as the Einstein Telescope.

Abe, S. [University of Tokyo] (ORCID:0000000172503↗
NASA NTRS2017

NASA Double Asteroid Redirection Test (DART) Trajectory Validation and Robutness

The Double Asteroid Redirection Test (DART) mission will be the first to test the concept of a kinetic impactor. Several studies have been made on asteroid redirection and impact mitigation, however, to this date no mission tested the proposed concepts. An impact study on a representative body allows the measurement of the effects on the target's orbit and physical structure. With this goal, DART's objective is to verify the effectiveness of the kinetic impact concept for planetary defense. The spacecraft uses solar electric propulsion to escape Earth, fly by (138971) 2001 CB21 for impact rehearsal, and impact Didymos-B, the secondary body of the binary (65803) Didymos system. This work focuses on the heliocentric transfer design part of the mission with the validation of the baseline trajectory, performance comparison to other mission objectives, and assessment of the baseline robustness to missed thrust events. Results show a good performance of the selected trajectory for different mission objectives: latest possible escape date, maximum kinetic energy on impact, shortest possible time of flight, and use of an Earth swing-by. The baseline trajectory was shown to be robust to a missed thrust with 1% of fuel margin being enough to recover the mission for failures of more than 14 days.

optimization↗
DOE OSTI2020

The Binary–Host Connection: Astrophysics of Gravitational-Wave Binaries from Host Galaxy Properties

Gravitational waves from the merger of binary neutron stars (BNSs) are accompanied by electromagnetic counterparts, making it possible to identify the associated host galaxy. In this work, we explore how properties of the hosts relate to the astrophysical processes leading to the mergers. It is thought that the BNS merger rate within a galaxy at a given epoch depends primarily on the galaxy's star formation history, as well as the underlying merger time-delay distribution of the binary systems. The stellar history of a galaxy, meanwhile, depends on the cosmological evolution of the galaxy through time, and is tied to the growth of structure in the universe. We study the hosts of BNS mergers in the context of structure formation by populating the UniverseMachine simulations with gravitational wave (GW) events, based on a simple time-delay model. We find that different time-delay distributions predict different properties of the associated host galaxies, including the distributions of stellar mass, star formation rate, halo mass, and local and large-scale clustering of hosts. Moreover, BNSs merging today with short delay times occur preferentially in hosts with high star formation rates, while those with long delay times live in dense regions within massive halos that have low star formation. Here, we show that with ${ \mathcal O }(10)$ events from current GW detector networks, it is possible to make preliminary distinctions between formation channels which trace stellar mass, halo mass, or star formation rate. We also find that strategies to follow-up GW events with electromagnetic telescopes can be significantly optimized using the clustering properties of their hosts.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

A DESGW Search for the Electromagnetic Counterpart to the LIGO/Virgo Gravitational-wave Binary Neutron Star Merger Candidate S190510g

In this work, we present the results from a search for the electromagnetic counterpart of the LIGO/Virgo event S190510g using the Dark Energy Camera (DECam). S190510g is a binary neutron star (BNS) merger candidate of moderate significance detected at a distance of 227 ± 92 Mpc and localized within an area of 31 (1166) square degrees at 50% (90%) confidence. While this event was later classified as likely nonastrophysical in nature within 30 hours of the event, our short latency search and discovery pipeline identified 11 counterpart candidates, all of which appear consistent with supernovae following offline analysis and spectroscopy by other instruments. Later reprocessing of the images enabled the recovery of six more candidates. Additionally, we implement our candidate selection procedure on simulated kilonovae and supernovae under DECam observing conditions (e.g., seeing and exposure time) with the intent of quantifying our search efficiency and making informed decisions on observing strategy for future similar events. This is the first BNS counterpart search to employ a comprehensive simulation-based efficiency study. We find that using the current follow-up strategy, there would need to be 19 events similar to S190510g for us to have a 99% chance of detecting an optical counterpart, assuming a GW170817-like kilonova. We further conclude that optimization of observing plans, which should include preference for deeper images over multiple color information, could result in up to a factor of 1.5 reduction in the total number of follow-ups needed for discovery.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Ferroelectricity in hafnia controlled via surface electrochemical state

Ferroelectricity in binary oxides including hafnia and zirconia has riveted the attention of the scientific community due to the highly unconventional physical mechanisms and the potential for the integration of these materials into semiconductor workflows. Over the last decade, it has been argued that behaviours such as wake-up phenomena and an extreme sensitivity to electrode and processing conditions suggest that ferroelectricity in these materials is strongly influenced by other factors, including electrochemical boundary conditions and strain. Here we argue that the properties of these materials emerge due to the interplay between the bulk competition between ferroelectric and structural instabilities, similar to that in classical antiferroelectrics, coupled with non-local screening mediated by the finite density of states at surfaces and internal interfaces. Via the decoupling of electrochemical and electrostatic controls, realized via environmental and ultra-high vacuum piezoresponse force microscopy, we show that these materials demonstrate a rich spectrum of ferroic behaviours including partial-pressure-induced and temperature-induced transitions between ferroelectric and antiferroelectric behaviours. In conclusion, these behaviours are consistent with an antiferroionic model and suggest strategies for hafnia-based device optimization.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Hardware-accelerated inference for real-time gravitational-wave astronomy

The field of transient astronomy has seen a revolution with the first gravitational-wave detections and the arrival of multi-messenger observations they enabled. Transformed by the first detection of binary black hole and binary neutron star mergers, computational demands in gravitational-wave astronomy are expected to grow by at least a factor of two over the next five years as the global network of kilometer-scale interferometers are brought to design sensitivity. With the increase in detector sensitivity, real-time delivery of gravitational-wave alerts will become increasingly important as an enabler of multi-messenger followup. In this work, we report a novel implementation and deployment of deep learning inference for real-time gravitational-wave data denoising and astrophysical source identification. This is accomplished using a generic Inference-as-a-Service model that is capable of adapting to the future needs of gravitational-wave data analysis. Overall, our implementation allows seamless incorporation of hardware accelerators and also enables the use of commercial or private (dedicated) as-a-service computing. Based on our results, we propose a paradigm shift in low-latency and offline computing in gravitational-wave astronomy. Such a shift can address key challenges in peak-usage, scalability and reliability, and provide a data analysis platform particularly optimized for deep learning applications. The achieved sub-millisecond scale latency will also be relevant for any machine learning-based real-time control systems that may be invoked in the operation of near-future and next generation ground-based laser interferometers, as well as the front-end collection, distribution and processing of data from such instruments.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Numerical Analysis of Fuel Effects on Advanced Compression Ignition Using a Cooperative Fuel Research Engine Computational Fluid Dynamics Model

Growing environmental concerns and demand for a better fuel economy are driving forces that motivate the research for more advanced engines. Multi-mode combustion strategies have gained attention for their potential to provide high thermal efficiency and low emissions for light-duty applications. These strategies target optimizing the engine performance by correlating different combustion modes to load operating conditions. The extension from boosted spark ignition (SI) mode at high loads to advanced compression ignition (ACI) mode at low loads can be achieved by increasing the compression ratio and utilizing intake air heating. Further, in order to enable an accurate control of intake charge condition for ACI mode and rapid mode-switches, it is essential to gain fundamental insights into the autoignition process. Within the scope of ACI, homogeneous charge compression ignition (HCCI) mode is of significant interest. It is known for its potential benefits, operation at low fuel consumption, low NOx, and particulate matter (PM) emissions. In the present work, a virtual Cooperative Fuel Research (CFR) engine model is used to analyze fuel effects on ACI combustion. In particular, the effect of fuel octane sensitivity (S) (at constant Research Octane Number (RON)) on autoignition propensity is assessed under beyond-RON (BRON) and beyond-MON (BMON) ACI conditions. The three-dimensional CFR engine computational fluid dynamics (CFD) model employs a finite-rate chemistry approach with a multi-zone binning strategy to capture autoignition. Two binary blends with Research Octane Number (RON) of 90 are chosen for this study: primary reference fuel (PRF) with S = 0 and toluene–heptane (TH) blend with S = 10.8, representing paraffinic and aromatic gasoline surrogates. Reduced mechanisms for these blends are generated from a detailed gasoline surrogate kinetic mechanism. Simulation results with the reduced mechanisms are validated against experimental data from an in-house CFR engine, with respect to in-cylinder pressure, heat release rate, and combustion phasing. Thereafter, the sensitivity of combustion behavior to ACI operating condition (BRON versus BMON), air-fuel ratio (λ = 2 and 3), and engine speed (600 and 900 rpm) is analyzed for both fuels. It is shown that the sensitivity of a fuel’s autoignition characteristics to λ and engine speed significantly differs at BRON and BMON conditions. Moreover, this sensitivity is found to vary among fuels, despite the same RON. It is also observed that the presence of low-temperature heat release (LTHR) under BRON condition leads to more sequential autoignition and longer combustion duration than BMON condition. Finally, the study indicates that the octane index (OI) fails to capture the trend in the variation of autoignition propensity with S under the BMON condition.

33 ADVANCED PROPULSION SYSTEMS↗