Chemical vapour deposition of Fe-N-C oxygen reduction catalysts with full utilization of dense Fe-N4 sites
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99 GENERAL AND MISCELLANEOUS↗
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Results for “phase current limiter”
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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Cosmic structure strikes back: The elimination of vector-mediated nonstandard interaction models as a mechanism for sterile neutrino dark matter production
We revisit sterile neutrino production enabled by nonstandard interactions (NSIs) among active neutrinos mediated by new bosons. We focus on vector mediators, including neutrinophilic, gauged 𝐿 𝜇 −𝐿 𝜏 , and 𝐵−𝐿 realizations, that modify in-medium dispersion and scattering, thereby altering the active-sterile conversion history. Building on a novel production framework with NSI thermal potentials and collision integrals, we compute nonthermal phase-space distributions across sterile neutrino mixing and NSI parameters and map each point to an equivalent thermal warm dark matter particle mass 𝑚 th via linear theory transfer function fitting with the cosmological structure formation Boltzmann solver. This enables a direct reinterpretation of state-of-the-art structure formation limits from Milky Way satellites, strong lensing, and the Lyman-𝛼 forest. These limits, in conjunction with x-ray decay searches, as well as results from a wide variety of particle physics experiments allow for a more complete examination of these models. We find that these vector-mediated models are ruled out when the full combination of current constraints, listed above, are taken into account. NSI scalar-mediated models and models with low reheating temperatures remain viable.
cosmology↗
Harmonic Modeling, Data Generation and Analysis of Power Electronics-Interfaced Residential Loads
The share of electronics-based residential load is expected to rise as devices such as variable frequency drives (VFDs), electric vehicle chargers, and inverter-based distributed energy resources (DERs), e.g., photovoltaic (PV) systems become more common. These loads may introduce significant harmonics into power networks that need to be closely studied in order to perform accurate load modeling and forecasting. However, it can be difficult to obtain harmonic-rich voltage and current data - necessary for identifying accurate load models - for residential electrical loads. Recognizing this need, we identify and model a set of electronics-based end-use loads and DERs in an electromagnetic transients program (EMTP) tool for a residence with a single- phase split-phase supply. Further, a procedure is developed to model harmonic interactions between end-use loads connected to the same non-ideal supply voltage in a residential setting. Finally, a harmonic-rich dataset produced via the proposed procedure is utilized to identify frequency coupling matrix (FCM) based load model. Numerical results demonstrate the accuracy of the model, and explore model identifiability with limited data points.
harmonics, power quality, load modeling↗
Electrochemically driven carbon dioxide separation
This project explored the viability of a Ni(OH) 2 based hydroxide exchange membrane carbon capture (HEMCC) device for direct air capture. It is built off an H 2 fuel cell based HEMCC previously developed in the Yushan Yan group at University of Delaware. Taking the same membrane-based, electrochemically driven pH gradient concept, similar flux performance was able to be seen in the Ni(OH) 2 system as the H 2 system when using comparable current densities. The project produced two types of membrane electrode assemblies (MEA). The first was a traditional MEA with two electrodes and a membrane, the second was a flow-through membrane MEA. Consistent performance was achieved with the traditional MEA with an energy cost of 1.1 MWh∙ton -1 and flux of 82 kg∙m -2 ∙yr -1 . This was the most stable of the two designs. This project investigated strategies to improve performance with a flow-through membrane design. Two designs were made, one with a cast phase inversion membrane, and one with powdered membrane layer. The template phase inversion membrane achieved low pressure drop but had performance limitations due to a skin layer of membrane limiting CO 2 gas transport. The powdered membrane layer had better performance but higher pressure drop. Finally, using the powdered membrane, commercial battery materials were able to be used in order to achieve higher flux. This showed that the flow through membrane design does have the capability to overcome flux inefficiencies in the traditional MEA. Moreover, the process design of the system is proposed and given in this project. The process mass and energy balances were calculated for a reference plant of 1000 t/yr CO 2 capture, which contains several subsystems, e.g. air processing subsystem, electrical subsystem, and CO 2 purification and compression subsystem is designed and evaluated. Based on our calculation, When the power consumption for stack is 1 MWh t -1 CO 2 , Additional 382 kWh t -1 CO 2 will be consumed by other subsystem of the plant, i.e. The total power consumption of 1.38 MWh t -1 CO 2 , lower than the final milestone of 1.5 MWh t -1 CO 2 in this project.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Quasi‐Binary Transition Metal Dichalcogenide Alloys: Thermodynamic Stability Prediction, Scalable Synthesis, and Application
Abstract Transition metal dichalcogenide (TMDCs) alloys could have a wide range of physical and chemical properties, ranging from charge density waves to superconductivity and electrochemical activities. While many exciting behaviors of unary TMDCs have been demonstrated, the vast compositional space of TMDC alloys has remained largely unexplored due to the lack of understanding regarding their stability when accommodating different cations or chalcogens in a single‐phase. Here, a theory‐guided synthesis approach is reported to achieve unexplored quasi‐binary TMDC alloys through computationally predicted stability maps. Equilibrium temperature–composition phase diagrams using first‐principles calculations are generated to identify the stability of 25 quasi‐binary TMDC alloys, including some involving non‐isovalent cations and are verified experimentally through the synthesis of a subset of 12 predicted alloys using a scalable chemical vapor transport method. It is demonstrated that the synthesized alloys can be exfoliated into 2D structures, and some of them exhibit: i) outstanding thermal stability tested up to 1230 K, ii) exceptionally high electrochemical activity for the CO 2 reduction reaction in a kinetically limited regime with near zero overpotential for CO formation, iii) excellent energy efficiency in a high rate Li–air battery, and iv) high break‐down current density for interconnect applications. This framework can be extended to accelerate the discovery of other TMDC alloys for various applications.
Hemmat, Zahra↗
VQE method: a short survey and recent developments
Abstract The variational quantum eigensolver (VQE) is a method that uses a hybrid quantum-classical computational approach to find eigenvalues of a Hamiltonian. VQE has been proposed as an alternative to fully quantum algorithms such as quantum phase estimation (QPE) because fully quantum algorithms require quantum hardware that will not be accessible in the near future. VQE has been successfully applied to solve the electronic Schrödinger equation for a variety of small molecules. However, the scalability of this method is limited by two factors: the complexity of the quantum circuits and the complexity of the classical optimization problem. Both of these factors are affected by the choice of the variational ansatz used to represent the trial wave function. Hence, the construction of an efficient ansatz is an active area of research. Put another way, modern quantum computers are not capable of executing deep quantum circuits produced by using currently available ansatzes for problems that map onto more than several qubits. In this review, we present recent developments in the field of designing efficient ansatzes that fall into two categories—chemistry–inspired and hardware–efficient—that produce quantum circuits that are easier to run on modern hardware. We discuss the shortfalls of ansatzes originally formulated for VQE simulations, how they are addressed in more sophisticated methods, and the potential ways for further improvements.
Fedorov, Dmitry A. (ORCID:0000000316598580)↗
Search for an Anomalous Production of Charged-Current 𝜈 𝑒 Interactions without Visible Pions across Multiple Kinematic Observables in MicroBooNE
This Letter presents an investigation of low-energy electron-neutrino interactions in the Fermilab Booster Neutrino Beam by the MicroBooNE experiment, motivated by the excess of electron-neutrino-like events observed by the MiniBooNE experiment. This is the first measurement to use data from all five years of operation of the MicroBooNE experiment, corresponding to an exposure of 1.11 × 10 21 protons on target, a 70% increase on past results. Two samples of electron neutrino interactions without visible pions are used, one with visible protons and one without any visible protons. The MicroBooNE data show reasonable agreement with the nominal prediction, with 𝑝 values ≥26.7% when the two 𝜈 𝑒 samples are combined, though the prediction exceeds the data in limited regions of phase space. The data are further compared to two empirical models that modify the predicted rate of electron-neutrino interactions in different variables in the simulation to match the unfolded MiniBooNE low energy excess. In the first model, this unfolding is performed as a function of electron neutrino energy, while the second model aims to match the observed shower energy and angle distributions of the MiniBooNE excess. This measurement excludes an electronlike interpretation of the MiniBooNE excess based on these models at >99% CLs in all kinematic variables.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Solid Phase Processing of Lead-Free Brass with Carbon Additives
Currently, “lead-free” brass alloys (like C27450/C27451/C6930), used extensively in drinking water fixtures and automotive, electrical, and electronic applications contain maximum 0.25% lead to maintain mechanical performance and machinability. Adding graphite to brass as an alternative to lead, using casting, powder metallurgy, and extrusion methods, has been explored previously. However, all these methods have proven to be energy-, time-, and resource-intensive, while not enabling performance equivalent to that of C36000 brass. In this project, we developed a one-step approach using friction extrusion and ShAPE to make lead-free brass/graphite components such as wires, rods and tubes with mechanical performance equivalent to commercial lead-free brass alloys. Manufacturing temperatures were maintained ~550-730 °C with feed rates ranging between 4 – 25 mm/min. Results show larger grains at the center of the rods and wires with smaller grains developing at the edges. Graphite particles were sheared in the direction of extrusion with higher strains observed towards the edges. Hardness of the brass/graphite samples was over 25% higher than that of the corresponding brass-only samples (rods and wires), also friction extruded. Our results show that the sub-micron graphite plays an important role in limiting process temperature and restraining grain growth during friction extrusion, thus reducing grain size in composites.
36 MATERIALS SCIENCE↗
Fighting the climate crisis with caloric heat pumping: Innovations to enable widespread adoption
Caloric heat pumping is a cross-cutting thermal energy technology that can cover a wide range of applications and temperatures, from millikelvins to hundreds of kelvins, with a working medium that has zero global warming potential. The technology promises cost savings and high efficiency, having 60% Carnot efficiency demonstrated to date. The Energy Earthshots™ Initiative, launched by the U.S. Department of Energy, aims to fight the climate crisis and overcome technological barriers to a decarbonized economy. The initiative focuses on the development of energy solutions that increase efficiency, reduce greenhouse gas emissions, and ensure affordability. Three out of eight Energy Earthshots™ look for alternative thermal energy technologies for extensive temperature ranges, from hydrogen liquefaction to metal-treating temperatures. Caloric heat pumping can fulfill all these requirements; however, at the current stage, caloric systems have limited presence in real-world applications. Further, this perspective discusses key efforts to address barriers hindering the widespread adoption of caloric technology. We focus on essential breakthroughs in and effective approaches to material discovery and draw a path to high-power-density, grid-interactive caloric systems to support achieving the ambitious net-zero carbon economy goal.
42 ENGINEERING↗
Revisit the VEC rule in high entropy alloys (HEAs) with high-throughput CALPHAD approach and its applications for material design-A case study with Al–Co–Cr–Fe–Ni system
Valence electron concentration (VEC) was treated as a useful parameter to predict solid solution phases, and the VEC rule was proposed for high entropy alloys (HEAs). However, this empirical rule has its limitations, which restricts its applications for phase predictions in HEAs. In this paper, we revisited the empirical VEC rule with the HT-CALPHAD approach in the Al–Co–Cr–Fe–Ni system. Our investigation showed that more than 90% compositions are observed to have BCC structures when 5.7≤VEC≤7.2 and we got 100% FCC structures when VEC≥8.4. Meanwhile, we proposed a data screening procedure to classify and discover the new HEAs. The concepts of average density (ρHEA), highest BCC/FCC temperatures ($T$ $^{max}_{BCC/FCC}$), and temperature ranges (ΔT BCC/FCC ) were introduced as useful data screening criteria to down-screen the candidate alloy compositions for specific engineering applications. In the current work, we have identified three HEA categories (refractory BCC HEAs, light-weight BCC HEA and refractory FCC HEAs) in the Al–Co–Cr–Fe–Ni system and proposed the best candidate in each group. Here, our investigation showed the HEA non-equiatomic composition space provides ample opportunities for the discovery of the next-generation HEAs.
36 MATERIALS SCIENCE↗
Real-time damage characterization for GFRCs using high-speed synchrotron X-ray phase contrast imaging
Here, we report the application of high-speed synchrotron X-ray phase contrast imaging (PCI) in real-time damage characterization for glass fiber reinforced composites (GFRCs) subjected to dynamic loading. Dynamic single-edge notched bending (DSENB) experiments on pre-notched S-2 GFRCs were performed on a modified Kolsky compression bar. During loading, the synchrotron X-ray beam penetrated through the composite specimen from the side to detect damage evolution inside the material. Entire dynamic events were recorded by a high-speed camera as image sequences.0° and 90° unidirectional and cross-ply composites were investigated. An optical imaging technique was also employed to capture similar dynamic events in comparison with the radiographic imaging. It is demonstrated that high-speed X-ray PCI had sufficient phase contrast to characterize a crack initiation at a 20-μm spatial resolution within 920 ns and track the crack geometry during propagation, thereby providing reliable data to quantify the dynamic damage resistance of GFRCs. Furthermore, being capable of recognizing microscopic damage-related features at a sub-10-μm resolution, high-speed X-ray PCI provided fundamental material failure mechanisms to reveal the essential of macroscale structural failure of composites. It can also track the damage evolution inside and between individual plies of laminated composites. However, current high-speed X-ray PCI technique only supports in-situ observation and the high timing and spatial resolutions are limited within a field of view of ~2.5 mm in square, preventing its application in the three-dimensional and larger-area damage detection for GFRC structures.
42 ENGINEERING↗
ELM-free H-mode phase and decoupling of peeling–ballooning stability boundary in the MAST Upgrade tokamak
A linear magnetohydrodynamic (MHD) peeling–ballooning stability analysis of the edge-localized mode (ELM)-free phase of a MAST Upgrade (MAST-U) H-mode plasma is presented. In contrast to other similar discharges, #47018 is found to have a significantly higher and wider pedestal during its ELM-free H-mode phase that lasts for approximately 80 ms; this is made possible by the reduced core MHD mode activity on the q = 2 surface. During this period, there is sustained decoupling of peeling and ballooning branches of the stability boundary on J–α space, opening an access channel to the second stability regime with higher peaks in pedestal current density $J_{\mathrm{N,ped}}$ and pressure gradient (α). Such decoupling of the stability boundary has not previously been observed in MAST-U H-modes, and if such a condition can be readily reproduced, it opens a wide range of opportunities for MAST-U to explore low-collisionality peeling-limited pedestal regimes as well as advanced scenarios such as quiescent H-modes that are relevant to future reactors such as STEP and ITER.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Nanoscale Three-Dimensional Imaging of Degradation in Composite Si-Containing Anodes
The use of silicon (Si) in next-generation lithium-ion battery (LIB) anodes has the potential to dramatically improve electrochemical performance over current LIB graphite (Gr) anodes, due to silicon’s higher specific capacity.1 However, widespread implementation of Si-containing anodes is inhibited by issues such as significant Si volume expansion during lithiation and an unstable solid-electrolyte interphase (SEI), resulting in unreliable performance and poor cycle life. Currently, composite anodes with both Si and graphite active materials are used to increase capacity and mitigate some of the limitations associated with Si. In composite electrodes with a heterogeneous distribution of components with varying electrical properties (including Si, Gr, conductive carbon additive, and binder), it is important to understand the local distribution of each component to correlate with electrochemical processes, particularly localized degradation and heterogeneous aging, and to optimize performance. To investigate Si-containing composite anodes in the nanoscale, we use scanning spreading resistance microscopy (SSRM), a form of scanning probe microscopy (SPM) that probes local electronic resistivity. By examining the intrinsic electronic resistivity contrast between the anode components, separate phases can be distinguished and understood within the composite structure.2 This work studies the effect of electrochemical cycling in two different electrolytes on component distribution and aging by comparing the electrical and structural evolution of composite Si-graphite electrodes and SEI before and after charge-discharge cycling. 1. W. J. Zhang. A review of the electrochemical performance of alloy anodes for lithium-ion batteries J. Power Sources 196 13–24 (2011). 2. C. Stetson, Z. Huey, A. Downard, Z. Li, B. To, A. Zakutayev, C.-S. Jiang, M. Al-Jassim, D. Finegan, S.-D. Han and S. DeCaluwe: Three-Dimensional Mapping of Resistivity and Microstructure of Composite Electrodes for Lithium-Ion Batteries. ACS Nano Letters Accepted (2020).
ADVANCED PROPULSION SYSTEMS↗
AI-enabled high-resolution scanning coherent diffraction imaging
Ptychographic imaging is a powerful means of imaging beyond the resolution limits of typical x-ray optics. Capturing recovered images from raw ptychographic data, however, requires the solution of an inverse problem, namely, phase retrieval. Phase retrieval algorithms are computationally expensive, which precludes real-time imaging. In this work, we propose PtychoNN, an approach to solve the ptychography data inversion problem based on a deep convolutional neural network. We demonstrate how the proposed method can be used to predict real-space structure and phase at each scan point solely from the corresponding far-field diffraction data. Our results demonstrate the practical application of machine learning to recover high fidelity amplitude and phase contrast images of a real sample hundreds of times faster than current ptychography reconstruction packages. Furthermore, by overcoming the constraints of iterative model-based methods, we can significantly relax sampling constraints on data acquisition while still producing an excellent image of the sample. Besides drastically accelerating acquisition and analysis, this capability has profound implications for the imaging of dose sensitive, dynamic, and extremely voluminous samples.
47 OTHER INSTRUMENTATION↗
Operational space and performance limiting events in the first physics campaign of MAST-U
Abstract The MAST-U fusion plasma research device, an upgrade to the Mega Amp Spherical Tokamak, has recently completed its first campaign of physics operation. MAST-U operated with Ohmic, or one or two neutral beams for heating, at 400–800 kA plasma current, in conventional or ‘SuperX’ divertor configurations. Equilibrium reconstructions provide key plasma physics parameters vs. time for each discharge, and diagrams are produced which show where the prevalence of operation occurs as well as the limits in various operational spaces. When compared to stability limits, the operation of MAST-U so far has generally stayed out of the low q , low density instability region, and below the high density Greenwald limit, high beta global stability limit, and high elongation vertical stability limit. MAST-U still has the potential to reach higher elongation, which could benefit the plasma performance. Despite the majority of operations happening below established stability limits, disruptions do occur in the flat-top phase of MAST-U plasmas. The reasons for these disruptions are highlighted, and possible strategies to avoid them and to extend the operational space of MAST-U in future campaigns are discussed.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Image-driven discriminative and generative machine learning algorithms for establishing microstructure–processing relationships
We investigate methods of microstructure representation for the purpose of predicting processing condition from microstructure image data. A binary alloy that is currently under development as a nuclear fuel was studied for the purpose of developing an improved machine learning approach to image recognition, characterization, and building predictive capabilities linking microstructure to processing conditions. Here, we test different microstructure representations and evaluate model performance based on classification accuracy. A classification accuracy of 95.8% was achieved fordistinguishing between micrographs corresponding to ten different thermo-mechanical material processing conditions.We find that our newly developed microstructure representation describes image data well, and the traditional approachof utilizing area fractions of different phases is insufficient for distinguishing between multiple classes using a relativelysmall, imbalanced original data set of 272 images. To explore the applicability of generative methods for supplementing such limited data sets, generative adversarial networks were trained to generate artificial microstructure images. Two different generative networks were trained and tested to assess performance. Challenges and best practices associated with applying machine learning to limited microstructure image data sets is also discussed. Our work has implications for quantitative microstructure analysis, and development of microstructure-processing relationships in limited data sets typical of metallurgical process design studies.
36 MATERIALS SCIENCE↗
Determination of impurities in cubic boron nitride (cBN) by inductively coupled plasma mass spectrometry (ICPMS)
The phase stability of cBN is critically dependent on the content and amount of impurities present. While studies have shown qualitatively that the addition of certain impurities can either increase or decrease the cBN-hBN phase transition temperature, studies have yet to show this effect quantitatively. This is because analytical methods to characterize minor and trace impurities in cBN are currently lacking. To this end, we present flux fusion methods capable of fully digesting cBN samples for ICPMS analyses. The materials used in this study are commercially available cBN powders in three different sizes. Two types of fluxes (LiOH and NaOH·H 2 O) are utilized so that both Li and Na impurities can be determined. To ensure the accuracy of Si measurements, a column chromatography method has been developed to purify Si from flux materials in order to increase the amount of dissolved sample sent to the ICP. Detection limits have been determined using procedural blanks and are found to be below 20 μg/g for all 58 elements analyzed except for Si, for which the detection limit is 312 μg/g. Nonetheless, all cBN powders studied are found to have high Si impurity levels that are above detection limit. This study provides a much-needed analytical protocol to enable comprehensive screening of impurities in cBN.
36 MATERIALS SCIENCE↗
Achieving high rate performance in hybrid pristine-recycled cathodes using model-informed electrode designs
Direct recycling lithium-ion battery cathodes, a process that retains the engineered oxide structures from end-of-life materials, presents a cost-effective and energy-efficient alternative to other battery recycling methods. However, while direct-recycled cathodes have demonstrated performance comparable to that of pristine materials at low cycling rates, their high-rate performance remains uncertain. Morphology changes in cathode particles, a main mode of degradation, directly impact rate performance by limiting surface kinetics and solid-phase diffusion. If direct recycling processes do not sufficiently restore pristine-like morphologies, the recycled materials may retain structural defects that hinder high-rate performance. The present work uses a physics-based pseudo-2D model to simulate hybrid electrodes with pristine and artificially “aged/recycled” NMC materials to investigate potential impacts of incorporating performance-limited aged cathode materials into cells. The study highlights how differences in transport and kinetic properties can influence rate capabilities in mixed electrodes — particularly in high-loading cells in high-demand applications. However, model results also reveal a possible mitigation strategy via dual-layer electrode architectures with lower-performing materials positioned near the current collector. Simulations of 4.0 mAh cm −2 cells cycled at 4C using a dual-layer architecture provided approximately 5%–30% more capacity in constant-current protocols compared to homogeneously blended electrode architectures with the same loadings and mixed-material compositions. These findings highlight the importance of strategic electrode design in minimizing potential performance losses and facilitating the integration of recycled materials into high-performance batteries, advancing sustainable and cost-effective battery manufacturing.
25 ENERGY STORAGE↗