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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Higher Energy-Content Jet Blending Components Derived from Ethanol (CRADA 467)

This project aims to develop a new sustainable aviation fuel (SAF) that comprises favorable properties, such as high energy density, excellent thermal stability, and favorable cold fold properties. Through catalyst development, this work will provide a route to control the cycloalkane/n-alkane/iso alkane content of a next-generation fuel with minimal or no aromatic content. Combining n-alkane and iso-alkane streams (high specific energy, MJ/kg) with cycloalkanes (higher energy density, MJ/L), is expected to enable at least a 4% net increase in combined (specific (MJ/kg) and volumetric (MJ/L)) energy content without impacting ‘drop-in’ fuel requirements, such as seal swelling. PNNL and LanzaTech have already demonstrated a sustainable, non-petroleum, route to isoalkanes. However, economically attractive cycloalkane production from waste and biomass is challenged by large hydrogen requirements, preferential selectivity to aromatic compounds and low yields to jet fuel range components. Many gaps in understanding cycloalkane properties and performance in complex jet fuel mixtures remain. The close tie and integration of Purdue’s fuel property analysis, with PNNL’s process development, can lead to an economically attractive process. The fuel analysis and testing by Purdue will enable a robust understanding of the properties and behavior of the cycloalkanes produced to inform process development. Additionally, seal-swelling analysis will quantify the ability of fuel blends with zero or minimal aromatics content to satisfy the seal swell requirement of O rings. Lastly, Purdue’s system-level analysis will lead to the development of a roadmap for deployment in key regions that considers system pressures such as hydrogen, water, energy efficiency, and ease of infrastructure access.

10 SYNTHETIC FUELS↗
DOE OSTI2020

Surface oxidation and crystallization of FeNi-Based soft magnetic nanocrystalline and amorphous nanocomposite alloys

In this work, we present characterization of surface oxidation and crystallization behavior of Metal Amorphous Nanocomposite (MANC) (Fe 70 Ni 30 ) 80 Nb 4 Si 2 B 14 alloys via complementary x-ray diffraction, electron microscopy, and x-ray photoelectron spectroscopy techniques. An adherent amorphous oxide of roughly 15–20 nm in thickness is observed on the wheel side of the ribbon, enriched in Fe relative to Ni and with significant content of Si and Nb as would be expected based upon a comparison of the Gibbs free energy of formation of the stable oxide phases. The amorphous character of the oxide is likely to result from the significant Si-content coupled with the amorphous and nanocrystalline character of the underlying metallic layer. Higher density of FeNi-enriched nanocrystals is also observed within ~100 nm of the wheel-side surface, presumably due to reduction in local glass former concentration. A rough, crystalline copper oxide layer is also present and forms through contact between the copper wheel and the solidifying melt during the rapid solidification process. On the air side of the ribbon, a crystalline oxide layer of ~15–20 nm is formed as well as intergranular oxidation that penetrates along the grain boundaries between highly textured surface crystallites of ~50–100 nm in size. The crystalline nature of the oxide on these surfaces is asserted to result from the lack of significant Si-content and the pre-existing surface crystallites that form during the rapid solidification process which promote a crystalline oxide surface layer. Furthermore, these results shed new insights into the details of surface oxidation and can help to inform processing and alloy composition adjustments which seek to tailor surface properties.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Impact of dynamic Jahn-Teller effect on magnetic excitations, lattice vibration, and thermal conductivity in U 𝑥 ⁢T⁢h 1−𝑥 ⁡O 2 system

Vibrational and magnetic properties of single-crystal uranium-thorium dioxide (U 𝑥 ⁢T⁢h 1−𝑥⁡ O 2 ) with a full range of 0 < 𝑥 < 1 are investigated. Thorium dioxide is a diamagnet whose thermal properties are governed by lattice vibration. The addition of paramagnetic uranium ions leads to the emergence of magnetic effects that alter the thermophysical properties noticeably even at room temperature. The interaction of phonons with magnetic moments of uranium 5⁢𝑓 electrons mediated by magnetoelastic coupling results in an anomalous low-temperature thermal conductivity profile. Analysis of the magnetic susceptibility measurements indicates a departure from the Curie-Weiss relationship characteristic of noninteracting paramagnetic ions, previously associated with the dynamic Jahn-Teller (DJT) effect characterized by coupling between spin and the oxygen sublattice. The T 2⁢g Raman peak position follows a nonlinear trend as a function of uranium concentration and hints that these Raman active optical modes play a role in either DJT or in mediating quadrupole-quadrupole interactions. A first-principle-based thermal transport model is implemented to explain the low-temperature transport measurements, where the anomalous reduction is attributed to phonon-spin resonant scattering. The interplay between spins and phonons is also captured using high-resolution inelastic x-ray scattering (IXS) measurements of phonon linewidths. Our results provide insights into the phonon interactions with the magnetic excitations governing DJT effect and impacting the low-temperature thermal transport processes in this material system. Furthermore, these findings have implications for understanding low-temperature thermal transport and magnetic properties in advanced materials for information processing and energy applications.

36 - MATERIALS SCIENCE↗
DOE OSTI2025

Hidden domain boundary dynamics toward crystalline perfection

A central paradigm of nonequilibrium physics concerns the dynamics of heterogeneity and disorder, impacting processes ranging from the behavior of glasses to the emergent functionality of active matter. Understanding these complex mesoscopic systems requires probing the microscopic trajectories associated with irreversible processes, the role of fluctuations and entropy growth, and the timescales on which nonequilibrium responses are ultimately maintained. Approaches that illuminate these processes in model systems may enable a more general understanding of other heterogeneous nonequilibrium phenomena, and potentially define ultimate speed and energy cost limits for information processing technologies. Here, we apply ultrafast single-shot X-ray photon correlation spectroscopy to resolve the nonequilibrium, heterogeneous, and irreversible mesoscale dynamics during a light-induced phase transition in a (PbTiO 3 ) 16 /(SrTiO 3 ) 16 superlattice. Such ferroelectric superlattice systems are a useful platform to study phase transitions and topological dynamics due to their high degree of tunability. This provides an approach for capturing the nucleation of the light-induced phase, the formation of transient mesoscale defects at the boundaries of the nuclei, and the eventual annihilation of these defects, even in systems with complex polarization topologies. We identify a nonequilibrium correlation response spanning >10 orders of magnitude in timescales, with multistep behavior similar to the plateaus observed in supercooled liquids and glasses. We further show how the observed time-dependent long-time correlations can be understood in terms of stochastic and non-Markovian dynamics of domain walls, encoded in waiting-time distributions with power-law tails. This work defines possibilities for probing the nonequilibrium and correlated dynamics of disordered and heterogeneous media.

36 MATERIALS SCIENCE↗
DOE OSTI2026

In-situ synchrotron X-ray investigation of phase evolution in gas atomized powder enabling manufacturing of nanoscale oxide-dispersion strengthened ferritic steels

Here, we present an investigation of Fe-14Cr-3W-0.4Y-0.4Zr-0.18Ti (wt.%) as a reduced-activation oxide-dispersion strengthened (ODS) ferritic steel, an alternative to the “14YWT” structural alloys designed for nuclear energy applications. Gas atomization reaction synthesis (GARS) was used to produce these Zr-modified powders with a non-equilibrium (metastable) phase that enable a heat treatment (delayed) route for producing nanoscale oxide-dispersion strengthening. In situ synchrotron X-ray diffraction and transmission electron microscopy were used to analyze phase evolution as a function of temperature and time, revealing formation of highly dispersed oxide nanoprecipitate phases at temperatures above those needed for powder consolidation and shaping of components. This would allow fabrication of net-shape parts using conventional powder-processing methods prior to thermal activation of a reaction producing nanocrystalline Y-(Ti, Zr)-O particles, with a size of 20 ± 7 nm. These results can inform processing of tubes, cladding, sheets, and plates for use in advanced fission and fusion reactors.

In-situ synchrotron X-ray diffraction↗
DOE OSTI2020

Methods for Explainable Artificial Intelligence

We explored ways of quantifying information in a neural network. This can be used to determine the right size of a network or to infer the way in which a network is processing information. The first year and a half was somewhat exploratory while the last half of the project focused on approaches that seemed to show the most promise. The introduce a new way of computing explainable artificial intelligence (XAI) saliency maps that is several orders of magnitude faster than methods with similar fidelity We call it FastCAM. The method works be combining a Class Activation Map (CAM) method such as GradCAM with a forward activation map computed with a statistic we call SMOE Scale. The addition of the forward activation maps to CAM methods seems to always improve their fidelity. At the same time, computational overhead is not increased by very much. While Gradients with SmoothGrad scores better on some fidelity measures, it is overall not as good and requires more than 1500 times to compute. We demonstrate two completed applications of FastCAM on tasks outside of the LDRD at LLNL. The source code for FastCAM is currently being implanted into Captum, the official XAI toolkit for the popular deep learning toolkit PyTorch. The LDRD currently has 13 publications released to the public. 10 of them are journal length.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Monitoring Radiochemical Processing Streams for the 238 Pu Supply Program with Process Pulse II

Oak Ridge National Laboratory (ORNL) is developing advanced spectroscopic and real-time monitoring capabilities to improve the timeliness of analytical measurements and process decisions for the 238Pu Supply Program. Reducing the time, resources, and costs associated with each production campaign is critical because overlapping campaigns will be required to meet the production goals of the National Aeronautics and Space Administration. Real-time, in situ analytical measurements in the heavily shielded hot cells at the Radiochemical Engineering Development Center (REDC) will allow for rapid process information feedback and operational benefits that help the 238Pu supply program scale-up production efforts. Noteworthy steps were taken during Campaign 5 to establish the ability to monitor processing streams in real time with spectrophotometry and a commercially available online monitoring software called The Unscrambler X Process Pulse II (PP) multivariate statistical process monitoring system by Camo Analytics (version 5.60). PP automates univariate-type calculations within the software itself and executes multivariate models built using The Unscrambler X (version 10.4 or newer). The Unscrambler is a commercially available data analysis software made by the same company. PP is composed of easy-to-use-tools for all personnel, including data scientists and technicians. The software can be used to plot analyte concentration profiles, spectral data, and other process variables in real time. All process data are represented in a single view with interactive charts useful for viewing how a process evolves over time.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2020

Quasiparticle Couplings in Transport of Heat, Charge, and Spin for Novel Energy Materials. Final report

Understanding the microscopic processes involved in the transport and conversion of energy from the atomic-scale to the meso-scale is critical for the development of next-generation materials for energy conversion and information processing. The goal of this program was to elucidate the couplings between microscopic degrees-of-freedom of atomic vibrations, spins, and electrons, which underpin heat, charge, and spin transport. This project systematically investigated these quasi-particle interactions, using state-of-the-art neutron scattering techniques, combined with first-principles computer simulations. This research program uncovered new information and understanding, which helps to rationalize materials properties based on the interplay of their atomistic degrees of freedom.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Smart Pixels: In-pixel AI for on-sensor data filtering

We present a smart pixel prototype readout integrated circuit (ROIC) designed in CMOS 28 nm bulk process, with in-pixel implementation of an artificial intelligence (AI) / machine learning (ML) based data filtering algorithm designed as proof-of-principle for a Phase III upgrade at the Large Hadron Collider (LHC) pixel detector. The first version of the ROIC consists of two matrices of 256 smart pixels, each 25$\times$25 µm\textsuperscript{2} in size. Each pixel consists of a charge-sensitive preamplifier with leakage current compensation and three auto-zero comparators for a 2-bit flash-type ADC. The frontend is capable of synchronously digitizing the sensor charge within 25 ns. Measurement results show an equivalent noise charge (ENC) of $\sim$30e\textsuperscript{-} and a total dispersion of $\sim$100e\textsuperscript{-} The second version of the ROIC uses a fully connected two-layer neural network (NN) to process information from a cluster of 256 pixels to determine if the pattern corresponds to highly desirable high-momentum particle tracks for selection and readout. The digital NN is embedded in-between analog signal processing regions of the 256 pixels without increasing the pixel size and is implemented as fully combinatorial digital logic to minimize power consumption and eliminate clock distribution, and is active only in the presence of an input signal. The total power consumption of the neural network is $\sim$ 300 $\mu$W. The NN performs momentum classification based on the generated cluster patterns and even with a modest momentum threshold, it is capable of 54.4\% – 75.4\% total data rejection, opening the possibility of using the pixel information at 40MHz for the trigger. The total power consumption of analog and digital functions per pixel is $\sim$ 6 $\mu$W per pixel, which corresponds to $\sim$ 1 W/cm\textsuperscript{2} staying within the experimental constraints.

Parpillon, Benjamin↗
DOE OSTI2024

Smart Pixels: In-pixel AI for on-sensor data filtering

We present a smart pixel prototype readout integrated circuit (ROIC) designed in CMOS 28 nm bulk process, with in-pixel implementation of an artificial intelligence (AI) / machine learning (ML) based data filtering algorithm designed as proof-of-principle for a Phase III upgrade at the Large Hadron Collider (LHC) pixel detector. The first version of the ROIC consists of two matrices of 256 smart pixels, each 25$\times$25 $\mu$m$^2$ in size. Each pixel consists of a charge-sensitive preamplifier with leakage current compensation and three auto-zero comparators for a 2-bit flash-type ADC. The frontend is capable of synchronously digitizing the sensor charge within 25 ns. Measurement results show an equivalent noise charge (ENC) of $\sim$30e$^-$ and a total dispersion of $\sim$100e$^-$ The second version of the ROIC uses a fully connected two-layer neural network (NN) to process information from a cluster of 256 pixels to determine if the pattern corresponds to highly desirable high-momentum particle tracks for selection and readout. The digital NN is embedded in-between analog signal processing regions of the 256 pixels without increasing the pixel size and is implemented as fully combinatorial digital logic to minimize power consumption and eliminate clock distribution, and is active only in the presence of an input signal. The total power consumption of the neural network is $\sim$ 300 $\mu$W. The NN performs momentum classification based on the generated cluster patterns and even with a modest momentum threshold, it is capable of 54.4% - 75.4% total data rejection, opening the possibility of using the pixel information at 40MHz for the trigger. The total power consumption of analog and digital functions per pixel is $\sim$ 6 $\mu$W per pixel, which corresponds to $\sim$ 1 W/cm$^2$ staying within the experimental constraints.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Technoeconomic Analysis of High-Value, Crystalline Silicon Photovoltaic Module Recycling Processes

Recycling is an important circular economy strategy, and for photovoltaics (PV), the one that has received the greatest research attention. Recycling of PV modules is required in Europe; everywhere else it competes in the market of end-of-life options, where cost is a primary decision factor. The vast majority of PV modules sold globally are crystalline-silicon (c-Si); most of the rest of the market are cadmium telluride thin film modules whose primary manufacturer runs its own commercial-scale recycling program. While many different c-Si recycling approaches and technologies have been proposed, they generally lack accompanying cost estimates or enough process information to model costs. Herein we develop detailed estimates of seven categories of capital and operating costs along with estimates of revenue from recovered materials for each step in two proposed recycling processes for c-Si PV modules. Using these results, we develop a hypothetical third recycling process merging process steps from the original two, estimate surcharges required to achieve minimum sustainable prices for each recycling process, as well as consider how economies of scale could reduce costs. Increasing the purity of and identifying higher-value markets for recovered materials are approaches to reducing costs and increasing recycling rates in voluntary markets.

crystalline silicon↗
DOE OSTI2021

Physiological Characterization of Language Comprehension

In this project, our goal was to develop methods that would allow us to make accurate predictions about individual differences in human cognition. Understanding such differences is important for maximizing human and human-system performance. There is a large body of research on individual differences in the academic literature. Unfortunately, it is often difficult to connect this literature to applied problems, where we must predict how specific people will perform or process information. In an effort to bridge this gap, we set out to answer the question: can we train a model to make predictions about which people understand which languages? We chose language processing as our domain of interest because of the well- characterized differences in neural processing that occur when people are presented with linguistic stimuli that they do or do not understand. Although our original plan to conduct several electroencephalography (EEG) studies was disrupted by the COVID-19 pandemic, we were able to collect data from one EEG study and a series of behavioral experiments in which data were collected online. The results of this project indicate that machine learning tools can make reasonably accurate predictions about an individual?s proficiency in different languages, using EEG data or behavioral data alone.

42 ENGINEERING↗
DOE OSTI2023

Dynamics of skyrmion contraction and expansion in a magnetic film

Contraction and expansion of skyrmions in ferromagnetic films are investigated. In centrosymmetric systems, the dynamics of a collapsing skyrmion is driven by dissipation. The collapse time has a minimum on the damping constant. In systems with broken inversion symmetry, the evolution of skyrmions toward equilibrium size is driven by the Dzyaloshinskii–Moriya interaction. As a result, expressions describing the time dependence of the skyrmion size are derived and their implications for skyrmion-based information processing are discussed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

The Novel Charfuel® Coal Refining Process 18 TPD Pilot Plant Project for Co- Producing an Upgraded Coal Product, and Commercially Valuable Co- Products: Area of Interest #3 – Coal Beneficiation Pilot Plant Testing (Final Report)

Operation of Carbon Fuels, LLC’s (“CF”) existing, permitted 18 TPD pilot plant located in Golden, Colorado using two individually ranked (ASTM D 388) coal types (two campaigns), employing the novel Charfuel® coal refining process to produce an upgraded coal product and a number of high-valued organic and inorganic coproducts (for which there presently exists large commercial markets) in order to produce engineering and product data which will then be utilized toward the design of a commercial scale integrated facility (pre-feed document). Carbon Fuels, LLC has developed the Charfuel® Coal Refining Process which refines domestically abundant, raw coal (in the same manner as crude oil is refined) to produce the identical, high value co-products that are refined from crude oil. Thus, gasoline, jet fuel, “green diesel”, fuel oil, and marine fuels, as well as petrochemicals such as benzene, toluene, xylene, and methanol are refined from raw coal using this process. The Charfuel® Coal Refining Process is not a coal conversion process, like pyrolysis, or indirect liquefaction. Nor is it an alternative energy system. Rather it is a coal refining process that has the ability to economically produce products traditionally associated with the refining of crude oil but using only abundant, raw coal as the refinery feed stock. The Charfuel® Coal Refining Process is more economical than crude oil refining and is environmentally benign. Therefore, this value added process yields a return on investment well above 50% for a commercial facility. Furthermore, the Charfuel® process, unlike alternatives such as ethanol and hydrogen, can utilize the existing transportation, delivery, and other petroleum based systems. Hence, there is no need for new engines, pipelines, tankers, or product acceptance. As a result, the profitability of the process is increased. Objectives: (1) Operation of the integrated 18 tpd pilot plant, using two coal types (ranks); (2) Demonstration of process flexibility in being able to produce different products (gas, liquid, and char), as well as determination of operating parameters for identifying scale up criteria for two coal types (ranks); (3) Generation of engineering and design information (process specifications) for use in designing a commercial scale plant (scale-up); (4) Determination of important environmental issues surrounding the process and the products such as fate of trace elements (mercury and other heavy metals) and distributions of SO2, NOx, and CO 2 by analysis of effluent streams; (5) Production of sufficient product to allow reliable commercial economic evaluation of both the refined coal product and the coproducts; and, (6) Assessment of longer-term reliability of unit operations. Period 1: reconfiguration of the 18 TPD plant to meet specific FOA requirements and to qualify the facility for operation; and, Period 2: operation of the 18 TPD plant for two campaigns using two coals types (ranks) which are widely commercially used and abundant - the first being a subbituminous (Powder River Basin (“PRB”)) coal, and the second a bituminous (Illinois #6) coal.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2021

Ultrafast valley polarization in bilayer graphene

We study theoretically the interaction of a bilayer graphene with a circularly polarized ultrafast optical pulse of a single oscillation at an oblique incidence. The normal component of the pulse breaks the inversion symmetry of the system and opens up a dynamical bandgap due to which a valley-selective population of the conduction band becomes sensitive to the angle of incident of the pulse. We show that the magnitude of the valley polarization can be controlled by the angle of incidence, the amplitude, and the angle of in-plane polarization of the chiral optical pulse. Subsequently, a sequence of a circularly polarized pulse followed by a linearly polarized femtosecond-long pulse can be used to control and probe the valley polarization created by the preceding pulse. Our protocol provides a favorable platform to design ultrafast all-optical valleytronic information processing.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Multi-scale organization in communicating active matter

The emergence of collective motion among interacting, self-propelled agents is a central paradigm in non-equilibrium physics. Examples of such active matter range from swimming bacteria and cytoskeletal motility assays to synthetic self-propelled colloids and swarming microrobots. Remarkably, the aggregation capabilities of many of these systems rely on a theme as fundamental as it is ubiquitous in nature: communication. Despite its eminent importance, the role of communication in the collective organization of active systems is not yet fully understood. Here we report on the multi-scale self-organization of interacting self-propelled agents that locally process information transmitted by chemical signals. We show that this communication capacity dramatically expands their ability to form complex structures, allowing them to self-organize through a series of collective dynamical states at multiple hierarchical levels. Our findings provide insights into the role of self-sustained signal processing for self-organization in biological systems and open routes to applications using chemically driven colloids or microrobots.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Classical and quantum compression for edge computing: the ubiquitous data dimensionality reduction

Edge computing aims to address the challenges associated with communicating and transferring large amounts of data generated remotely to a data center in a timely and efficient manner. A central pillar of edge computing is local (i.e., at- or near-source) data processing capability so that data transfer to a data center for processing can be minimized. Data compression at the edge is therefore a natural component of edge workflows. Here we present a survey of data compression algorithms with a focus on edge computing. Not all compression algorithms can accommodate the data type heterogeneity, tight processing and communication time constraints, or energy efficiency requirement characteristics of edge computing. We discuss specific examples of compression algorithms that are being explored in the context of edge computing. We end our review with a brief survey of emerging quantum compression techniques that are of importance in quantum information processing, including the proposed concept of quantum edge computing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Density Functional Theory Study of Controllable Optical Absorptions and Magneto-Optical Properties of Magnetic CrI 3 Nanoribbons: Implications for Compact 2D Magnetic Devices

A chromium triiodide (CrI 3 ) monolayer has an interesting ferromagnetic ground-state. In this work, we calculate band structures and magnetic moments of tensile-strained and bent zigzag CrI 3 nanoribbons with density functional theory. The edge iodine atoms form flat low-lying conduction bands and couple with chromium atoms ferromagnetically, while the non-edge iodine atoms weakly couple antiferromagnetically. Narrow CrI 3 nanoribbons have two locally stable magnetic moment orientations, namely out-of-plane and in-plane (along the nanoribbon periodic direction) configurations. This enables four magnetization states in CrI 3 nanoribbons, including two out-of-plane ones (up and down) and two in-plane ones (forward and backward along the nanoribbon periodical direction), increasing the operating controllability. Based on the one-dimensional Ising spin chain model, the spin correlation length of the narrow CrI 3 nanoribbon is estimated as about 10 Å at its estimated Curie temperature of 27 Kelvin, which is lower than the measured 45 Kelvin of the monolayer CrI 3 . The optical absorption and magneto-optical properties of CrI 3 nanoribbons are investigated with many-body perturbation GW-BSE (Bethe-Salpeter equation), including magnetic dichroism, Faraday and magneto-optical Kerr effects. Here, the low-energy dark excitons are mainly from transitions between electrons and holes with unlike spins and are non-Frenkel-like, while the bright excitons have mixed spin configurations. The intrinsic lifetime of excitons can be over one nanosecond, suitable for quantum information processes. Tensile strains and bending manifestly modulate the absorption spectra and magneto-optical properties of CrI 3 nanoribbons within a technologically important photon energy-range of ~1.0-2.0 eV. The CrI 3 nanoribbons can be used in 1D or 2D magnetic storage nanodevices, tunable magnetic optoelectronics, and spin-based quantum information controls.

36 MATERIALS SCIENCE↗