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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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Large Thermo-Spin Effects in Heusler Alloy-Based Spin Gapless Semiconductor Thin Films
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Synergistic Effects of Inexpensive Mixed Metal Oxides for Catalytic Hydrothermal Liquefaction of Food Wastes
Industrial wastes and natural mixed oxide materials were evaluated as inexpensive heterogeneous catalysts for catalytic hydrothermal liquefaction (CHTL) of food wastes. Red mud and red clay achieved biocrude carbon yields of 47.0 and 39.5% with higher heating values (HHVs) of 40.2 and 37.7 MJ kg –1 , respectively, which were much greater than those without the catalyst (biocrude carbon yield of 19.7% and HHV of 36.1 MJ kg –1 ). Biocrude characterization revealed that similar families of molecules were formed in the presence and absence of catalysts, implying that the main role of the catalyst is to promote rates of thermal reactions, leading to biocrude production without opening new pathways. The crystalline structures of inexpensive mixed oxides were stable under hydrothermal conditions, with modest calcium leaching (7.5%) and trace leaching of other metals. Using red clay or red mud resulted in >40% recovery of the energy in food waste as biocrude, greater than that obtained under noncatalytic conditions (18%) or from any individual constituent oxide (19–27%). The improved CHTL performance of the mixed metal oxides compared with single-metal oxides was attributed to the synergistic effects of base and acid sites present on catalyst surfaces; mixed oxides presented balanced densities of acids and bases, whereas the constituent oxides were either primarily acidic or primarily basic. Lastly, the percent of energy recovered as biocrude oil was strongly correlated with the base-to-acid site density ratio, providing an important performance predictor for CHTL conversion of food waste to bioenergy.
Solution and Active Site Speciation Drive Selectivity for Electrocatalytic Reactive Carbon Capture in Diethanolamine over Ni–N–C Catalysts
Direct conversion of captured forms of carbon, or reactive carbon capture (RCC), presents an opportunity to reduce the energy intensity and cost of direct CO 2 utilization from dilute sources. While amine-based sorbents effectively capture CO 2 , their use for RCC presents numerous challenges with typical pure metal catalysts used for electrochemical CO 2 reduction (CO 2 R). Here, using both theory and experiments, we find that Ni–N–C single atom catalysts are effective for RCC conversion to CO using a diethanolamine sorbent, in contrast to pure metal catalysts. Computational analysis reveals that RCC can proceed directly through direct reduction of the sorbent-CO 2 adduct or indirectly by C–N bond breaking facilitating CO 2 adsorption and subsequent reduction. We find that the latter mechanism is most prevalent at low overpotentials where we experimentally observe RCC selectivity. We also find experimentally that the rate of CO production for RCC with Ni–N–C catalysts can exceed pure bicarbonate solutions at intermediate sorbent concentration (0.1–0.5 M DEA) under dilute (10–25%) streams of CO 2 at low overpotentials. The coordination environment of Ni sites and the solution speciation influence their RCC activity, with changes in protonation to coordinating N/C atoms resulting in changing the RCC mechanism and consequent activity. In situ X-ray absorption spectroscopy and computational analysis reveal restructuring under RCC conditions due to hydrogen coadsorption with DEA that limits the stability of Ni–N–C catalysts. This work highlights the importance of carefully controlling the catalyst and solution environment to achieve active and stable RCC electrocatalysis.
DC Hall coefficient of the strongly correlated Hubbard model
The Hall coefficient is related to the effective carrier density and Fermi surface topology in non-interacting and weakly interacting systems. In strongly correlated systems, the relation between the Hall coefficient and single-particle properties is less clear. Clarifying this relation would give insight into the nature of transport in strongly correlated materials that lack well-formed quasiparticles. In this work, we investigate the DC Hall coefficient of the Hubbard model using determinant quantum Monte Carlo in conjunction with a recently developed expansion of magneto-transport coefficients in terms of thermodynamic susceptibilities. At leading order in the expansion, we observe a change of sign in the Hall coefficient as a function of temperature and interaction strength, which we relate to a change in the topology of the apparent Fermi surface. We also combine our Hall coefficient results with optical conductivity values to evaluate the Hall angle, as well as effective mobility and effective mass based on Drude theory of metals.
Radiative impact of record-breaking wildfires from integrated ground-based data
The radiative effects of wildfires have been traditionally estimated by models using radiative transfer calculations. Assessment of model-predicted radiative effects commonly involves information on observation-based aerosol optical properties. However, lack or incompleteness of this information for dense plumes generated by intense wildfires reduces substantially the applicability of this assessment. Here we introduce a novel method that provides additional observational constraints for such assessments using widely available ground-based measurements of shortwave and spectrally resolved irradiances and aerosol optical depth (AOD) in the visible and near-infrared spectral ranges. We apply our method to quantify the radiative impact of the record-breaking wildfires that occurred in the Western US in September 2020. For our quantification we use integrated ground-based data collected at the Atmospheric Measurements Laboratory in Richland, Washington, USA with a location frequently downwind of wildfires in the Western US. We demonstrate that remarkably dense plumes generated by these wildfires strongly reduced the solar surface irradiance (up to 70% or 450 Wm -2 for total shortwave flux) and almost completely masked the sun from view due to extremely large AOD (above 10 at 500 nm wavelength). We also demonstrate that the plume-induced radiative impact is comparable in magnitude with those produced by a violent volcano eruption occurred in the Western US in 1980 and continental cumuli.
The solution structures and relative stability constants of lanthanide–EDTA complexes predicted from computation
Ligand selectivity to specific lanthanide (Ln) ions is key to the separation of rare earth elements from each other. Ligand selectivity can be quantified with relative stability constants (measured experimentally) or relative binding energies (calculated computationally). The relative stability constants of EDTA (ethylenediaminetetraacetic acid) with La 3+ , Eu 3+ , Gd 3+ , and Lu 3+ were predicted from relative binding energies, which were quantified using electronic structure calculations with relativistic effects and based on the molecular structures of Ln–EDTA complexes in solution from density functional theory molecular dynamics simulations. The protonation state of an EDTA amine group was varied to study pH ~7 and ~11 conditions. Further, simulations at 25 °C and 90 °C were performed to elucidate how structures of Ln–EDTA complexes varying with temperature are related to complex stabilities at different pH conditions. Relative stability trends are predicted from computation for varying Ln 3+ ions (La, Eu, Gd, Lu) with a single ligand (EDTA at pH ~11), as well as for a single Ln 3+ ion (La) with varying ligands (EDTA at pH ~7 and ~11). Changing the protonation state of an EDTA amine site significantly changes the solution structure of the Ln–EDTA complex resulting in a reduction of the complex stability. As a result, increased Ln–ligand complex stability is correlated to reduced structural variations in solution upon an increase in temperature.
Local structure heterogeneity in unique tetragonal BaTiO 3 -based relaxor featuring ultrahigh electrostrictive effect
The BT-15BLT relaxor ferroelectric exhibits local T distortions within 100 K to 500 K. Through RMC fitting, it was revealed that T distortions originate from Bi/Li clusters and relaxor phase transition is induced by localized polarization rotations.
Effect of reversible dislocation-based deformation on nanoparticle strain at failure
Molecular dynamics simulations are used to isolate and quantify the reversible and irreversible mechanisms that contribute to deformation in platinum nanoparticles under compression. Quantitative analysis reveals how the nucleation and entanglement of dislocations can lead to reversible dislocation-based deformation. Simulations run at different temperatures and loading conditions show that the formation of entangled dislocations is more likely at higher temperatures and is facilitated by loading orientations where dislocations nucleate on intersecting slip planes. The presence of entangled dislocations increases the strain at failure due to the ability of those dislocations to accommodate strain reversibly. The results are corroborated by the observation of similar entangled dislocation loops during in situ compression experiments on nanoparticles of the same material. Altogether, these findings provide insight into the role of dislocations in both reversible and irreversible deformation and their implications for nanoparticle stability and properties.
Cosmological analysis of three-dimensional BOSS galaxy clustering and Planck CMB lensing cross correlations via Lagrangian perturbation theory
In this work, we present a formalism for jointly fitting pre- and post-reconstruction redshift-space clustering (RSD) and baryon acoustic oscillations (BAO) plus gravitational lensing (of the CMB) that works directly with the observed 2-point statistics. The formalism is based upon (effective) Lagrangian perturbation theory and a Lagrangian bias expansion, which models RSD, BAO and galaxy-lensing cross correlations within a consistent dynamical framework. As an example we present an analysis of clustering measured by the Baryon Oscillation Spectroscopic Survey in combination with CMB lensing measured by Planck. The post-reconstruction BAO strongly constrains the distance-redshift relation, the full-shape redshift-space clustering constrains the matter density and growth rate, and CMB lensing constrains the clustering amplitude. Using only the redshift space data we obtain Ω m = 0.303 ± 0.008, $H_0$ = 69.21 ± 0.78 and $σ_8$ = 0.743 ± 0.043. The addition of lensing information, even when restricted to the Northern Galactic Cap, improves constraints to Ω m = 0.303 ± 0.008, $H_0$ = 69.21 ± 0.77 and $σ_8$ = 0.707 ± 0.035, in tension with CMB and cosmic shear constraints. The combination of Ω m and $H_0$ are consistent with Planck, though their constraints derive mostly from redshift-space clustering. The low $σ_8$ value are driven by cross correlations with CMB lensing in the low redshift bin ($\textit{z}$ ≃ 0.38) and at large angular scales, which show a 20% deficit compared to expectations from galaxy clustering alone. We conduct several systematics tests on the data and find none that could fully explain these tensions.
Controlling optical-cavity locking using reinforcement learning
Abstract This study applies an effective methodology based on Reinforcement Learning to a control system. Using the Pound–Drever–Hall locking scheme, we match the wavelength of a controlled laser to the length of a Fabry-Pérot cavity such that the cavity length is an exact integer multiple of the laser wavelength. Typically, long-term drift of the cavity length and laser wavelength exceeds the dynamic range of this control if only the laser’s piezoelectric transducer is actuated, so the same error signal also controls the temperature of the laser crystal. In this work, we instead implement this feedback control grounded on Q-Learning. Our system learns in real-time, eschewing reliance on historical data, and exhibits adaptability to system variations post-training. This adaptive quality ensures continuous updates to the learning agent. This innovative approach maintains lock for eight days on average.
Two-Neutron Halo is Unveiled in F 29
Here, we report the measurement of reaction cross sections ( σ R ex ) of F 27 , 29 with a carbon target at RIKEN. The unexpectedly large σ R ex and derived matter radius identify F 29 as the heaviest two-neutron Borromean halo to date. The halo is attributed to neutrons occupying the 2 p 3 / 2 orbital, thereby vanishing the shell closure associated with the neutron number N = 20 . The findings are explained by state-of-the-art shell model calculations. Coupled-cluster computations based on effective field theories of the strong nuclear force describe the matter radius of F 27 but are challenged for F 29 .
A Sensorless Coil Detection Scheme based on Dead-Time Effect in Dynamic Wireless Power Transfer Systems
The detection of electric vehicles in dynamic wireless power transfer (DWPT) systems is important to reduce the standby losses and comply with the electromagnetic-field emission guidelines recommended by the International Commission for Non-Ionizing Radiation Protection. This paper discusses a novel sensorless coil detection scheme, which exploits the phenomenon of voltage-polarity reversal/notches caused by the dead-time effect in the full-bridge inverter. The variations in the system impedance and dead-time effects are collectively exploited to detect the receiver coil in the DWPT system. The proposed coil detection scheme is accomplished at low excitation voltage, which reduces the inverter standby losses. The theoretical analysis of the notch occurrence and open-loop simulation results are presented using a DWPT model developed in the piecewise linear electrical circuit simulation software.
Requirements and Conceptual Design of Off-gas Systems for the Reprocessing of Metallic Fuels
An assessment has been conducted to determine how key regulations regarding volatile radionuclide emissions to the atmosphere may apply to the off-gas streams associated with electrochemical reprocessing. The scope of this assessment was based upon a generic electrochemical reprocessing scheme with a throughput rate of 200 MTIHM/y applied to metallic fuel discharged from a sodium fast reactor (SFR), but the findings are able to be translated to other advanced nuclear scenarios as merited. Air dispersion modeling was performed using the EPA CAP-88 model and evaluated the uncontrolled decontamination factors (DFs) that would be required to achieve regulatory compliance with the dose-based limits set forth by EPA regulation 40 CFR 190.10(a). These DFs were compared to those required by fuel cycle–based limits set forth by EPA regulation 40 CFR 190.10(b). Two theoretical sites with disparate climatological conditions were selected for air dispersion modeling (Idaho and Tennessee). The radionuclides modeled included 3 H, 85 Kr, 129 I, and selected alpha-emitting transuranic isotopes (referred to here as 239 Pu-TRU <1y ). It was found that the fuel cycle-based limits in 40 CFR 190.10(b) are most restrictive for 85 Kr and 239 Pu-TRU <1y , with DFs of 3 and 6.1E+09, respectively. The dose-based limit as derived from 40 CFR 190.10(a) could require mitigation of tritium in some scenarios, with an estimated DF of about 3 for the reference scenarios. The fuel cycle-based limit for 129 I resulted in a DF of about 240 for the reference scenario. The need for iodine mitigation based on dose to the public depended upon the physical form of iodine as either particulate or vapor-phase species. Emission of iodine from the facility as a vapor necessitated DFs of about 2 but emission as a particulate would require DFs >6,000 to meet thyroid dose-based limits. Effects of physical form on needed iodine mitigation are significant, but the understanding of speciation of iodine both during electrochemical reprocessing and after release to the atmosphere is limited. The electrochemical processing unit operations were evaluated to identify potential release points for the volatile radionuclides and to assess the potential for retention of the radionuclides within the process (thus decreasing the need for mitigation). Mitigation strategies for 3 H, 85 Kr, 129 I, and 239 Pu-TRU <1y were identified. In all cases, there are reasonably achievable pathways to regulatory compliance, although in some cases additional R&D is merited to verify the chemical speciation of these isotopes and to develop and demonstrate potential treatment technologies for this application. Whether or not additional off-gas controls (beyond common operations such as HEPA filtration and oxygen and moisture control) are needed for any of these regulated or volatile radionuclides depends on the (a) type of facility (NRC-regulated or DOE), (b) used fuel process rate, (c) used fuel burnup and composition, (d) speciation and retention of volatile radionuclides in the process and in the cell gas cleanup system, (e) site-specific parameters such as location, meteorology, stack height, and site boundaries, and (f) levels of conservatism and safety factors used in assessing compliance to air emissions regulations. Performance of this assessment revealed several areas where information is lacking or additional research is required in order to better determine if or what kinds of off-gas control might be needed. First, and most significantly, the understanding of the chemical speciation and physical form and partitioning of iodine during electrochemical processing operations is lacking and prevents the ability to accurately assess the potential iodine mitigation requirements. Future research in this area should be multifaceted and include thermodynamic modeling of iodine speciation in different process steps, experiments to quantify the kinetics of vapor-phase and melt-phase transitions, bench-scale experiments to determine the potential chemical and physical form of iodine emissions from the electrorefining process, and verification of iodine behavior with experiments utilizing operational facilities. Similarly, an improved understanding of iodine behavior in the environment after release from the facility stack will be required to refine dose estimations, as particulate and vapor-phase emissions result in significantly different doses to the MEI.
Dynamic population balance in molecular-level simulations of hypersonic flows
This report summarizes the work towards developing stochastic weighted particle methods (SWPM) for future application in hypersonic flows. Extensive changes to Sandia’s direct simulation Monte Carlo (DSMC) solver, SPARTA (Stochastic Particle Real Time Analyzer), were made to enable the necessary particle splitting and reduction capabilities for SWPM. The results from one-dimensional Couette and Fourier flows suggest that SWPM can reproduce the correct transport for a large range of Knudsen numbers with adequate accuracy. The associated velocity and temperature profiles are in good agreement with DSMC. An issue with particle placement during particle number reduction, is identified, to which, a simple but effective solution based on minimizing the center of mass error is proposed. High Mach wheel flows are simulated using the SWPM and DSMC methods. SWPM is capable of providing nearly an order of magnitude increase in efficiency over DSMC while retaining high accuracy.
Solvent Infiltration in ZIF-based Type 3 Porous Liquids: Effects on Pore Accessibility and CO2 adsorption
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Scalable Data Center Capacity for DOE's AI Prototype: A Rapidly Available Gigawatt Data Center for DOE
The multilaboratory Gigawatt Data Center working group was commissioned to identify approaches to rapidly establish federal data centers with scalable capacities up to 1,000 MW. These state-of-the-art facilities will serve as hubs for interdisciplinary collaboration, industry partnerships, and transformative applications of artificial intelligence. The proposed strategic shift includes facilitating multilaboratory collaboration, prioritizing operational efficiency, expanding public–private partnerships, optimizing investments, ensuring long-term contractual flexibility, supporting open science and secure data enclaves, and exploiting high-speed national networks. Owing to their extensive experience and best practices, the US Department of Energy national laboratories are uniquely positioned to lead this initiative. We recommend conducting a feasibility analysis to rapidly identify the optimal sites for this initiative, and the effort will likely involve private industry for design, construction, financing, and operational integration. We also propose establishing multiple geographically diverse sites to ensure energy resilience, high operational reliability, and a diverse user base, thereby effectively addressing the nation’s critical needs.