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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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This perspective focuses on electrokinetic methods for separating the smallest microplastics (<10 μm) on the basis of charge. Advantages, limitations, and future research opportunities regarding electrokinetic separation methods are discussed.
X-ray ptychography, a powerful scanning lensless imaging technique, has become attractive for nondestructively imaging internal structures at nanoscale. Stage positioning overhead in conventional step-scan ptychography is one of the limiting factors on the imaging throughput. In this work, we demonstrate the use of advanced fly scan ptychography to achieve high-resolution ptychograms of modern integrated circuits on a large field-of-view at millimeter scale. By completely removing stage overheads between scan points, the imaging time for millimeter-size sample can be significantly reduced. Furthermore, we implement the orthogonal probe relaxation technique to overcome the variation of illumination across the large scan area as well as local vibrations. The capability of x-ray ptychography shown here is broadly applicable for various studies, which requires both high spatial resolution and large scan area.
With X-ray free-electron lasers (XFELs), it is possible to determine the three-dimensional structure of noncrystalline nanoscale particles using X-ray single-particle imaging (SPI) techniques at room temperature. Classifying SPI scattering patterns, or `speckles', to extract single-hits that are needed for real-time vetoing and three-dimensional reconstruction poses a challenge for high-data-rate facilities like the European XFEL and LCLS-II-HE. Here, we introduce SpeckleNN, a unified embedding model for real-time speckle pattern classification with limited labeled examples that can scale linearly with dataset size. Trained with twin neural networks, SpeckleNN maps speckle patterns to a unified embedding vector space, where similarity is measured by Euclidean distance. We highlight its few-shot classification capability on new never-seen samples and its robust performance despite having only tens of labels per classification category even in the presence of substantial missing detector areas. Without the need for excessive manual labeling or even a full detector image, our classification method offers a great solution for real-time high-throughput SPI experiments.
As we push the boundaries of state-of-the-art lithium-ion intercalation materials, such as nickel-rich chemistries, the ability to isolate and understand specific degradation and performance limitations is becoming increasingly important. Half-cells, wherein lithium metal is employed as a dual counter and reference electrode, are commonly used in industry and academia for this purpose. However, the high reactivity of lithium metal drives premature electrolyte degradation and limits cell lifetime, bringing into question the reliability and validity of this cell configuration. Here we explore the limitations of half-cell studies of LiNi 0.8 Mn 0.1 Co 0.1 O 2 (NMC811) electrodes with commercially relevant loading. We identify the failure mechanism of this cell configuration through a combination of electrochemical, chemical, and spectroscopic techniques and show that the Li has a direct detrimental impact on the NMC811 chemistry. Our measurements show that vinylene carbonate is critical for these half-cell studies and underpins the cycle limits. Furthermore, we demonstrate the use of Li 4 Ti 5 O 12 (LTO) as an alternative counter electrode for understanding the performance of NMC positive electrode materials, due to its high coulombic efficiency and low reactivity with the organic carbonates routinely employed in lithium-ion battery cell chemistries. These data confirm that NMC811 electrodes can tolerate high voltages (stressed) conditions and that cell failure is mainly a result of crossover effects.
This report presents the initial development of a data-driven approach for reconstructing the core power distribution in a nuclear reactor (power shape synthesis) using ex-core sensors. Traditional techniques rely on deploying a large number of detectors throughout the reactor core. However, this approach is not feasible for innovative reactor concepts like Advanced Reactors and Microreactors. First, the tight lattice pitch, designed to maximize power density, limits the space available for sensors. Secondly, the harsh operating conditions are not compatible with commercially available detectors. The method proposed in this work integrates high-fidelity modeling with data-driven techniques to accurately reconstruct power distribution across various reactor types, thereby reducing the reliance on in-core sensors. Purdue University Reactor One (PUR-1) was selected as the test case. The CAD model representing the latest configuration of the PUR-1 core was imported into the OpenMC simulation framework, and the model was built. Additionally, the previously developed MCNP6 model was updated. The two models were assessed against the data collected during an experimental campaign conducted in July 2024. Thirty gold foils were placed in three Irradiation Assemblies in PUR-1 core. Using the measured activity of the irradiated foils, the neutron flux at different core locations was estimated.
We present the first calculation of the pion gluon moment from lattice QCD in the continuum-physical limit. The calculation is done using clover fermions for the valence action with three pion masses, 220, 310 and 690 MeV, and three lattice spacings, 0.09, 0.12, and 0.15 fm, using ensembles generated by MILC Collaboration with 2+1+1 flavors of highly improved staggered quarks (HISQ). On the lattice, we nonperturbatively renormalize the gluon operator in RI/MOM scheme using the cluster-decomposition error reduction (CDER) technique to enhance the signal-to-noise ratio of the renormalization constant. We extrapolate the pion gluon moment to the continuum-physical limit and obtain ⟨𝑥⟩ 𝑔 = 0.394(58) stat+NPR (39) mixing in the $\overline{MS}$ scheme at 2 GeV, with first error being the statistical error and uncertainties in nonperturbative renormalization, and the second being a systematic uncertainty estimating the effect of ignoring quark mixing. Our pion gluon momentum fraction has a central value lower than two recent single-ensemble lattice-QCD results near physical pion mass but is consistent with the recent global fits by JAM and xFitter and with most QCD-model estimates.
Band gap is known as an effective parameter for tuning the Landé g factor in semiconductors and can be manipulated in a wide range through the bowing effect in ternary alloys. In this work, using the recently developed virtual substrate technique, high-quality InAsSb alloys throughout the whole Sb composition range are fabricated and a large g factor of g≈-90 at the minimum band gap of ~0.1 eV, which is almost twice that in bulk InSb, is found. Further analysis to the zero gap limit reveals a possible gigantic g factor of g≈-200 with a peculiar relativistic Zeeman effect that disperses as the square root of magnetic field. Such a g-factor enhancement toward the narrow gap limit cannot be quantitatively described by the conventional Roth formula, as the orbital interaction effect between the nearly triply degenerated bands becomes the dominant source for the Zeeman splitting. These results may provide insights into realizing large g factors and spin-polarized states in semiconductors and topological materials.
ABSTRACT We search for the baryon acoustic oscillations in the projected cross-correlation function binned into transverse comoving radius between the SDSS-IV DR16 eBOSS quasars and a dense photometric sample of galaxies selected from the DESI Legacy Imaging Surveys. We estimate the density of the photometric sample of galaxies in this redshift range to be about 2900 deg−2, which is deeper than the official DESI emission line galaxy selection, and the density of the spectroscopic sample is about 20 deg−2. In order to mitigate the systematics related to the use of different imaging surveys close to the detection limit, we use a neural network approach that accounts for complex dependences between the imaging attributes and the observed galaxy density. We find that we are limited by the depth of the imaging surveys that affects the density and purity of the photometric sample and its overlap in redshift with the quasar sample, which thus affects the performance of the method. When cross-correlating the photometric galaxies with quasars in the range 0.6 ≤ z ≤ 1.2, the cross-correlation function can provide better constraints on the comoving angular distance DM (6 per cent precision) compared to the constraint on the spherically averaged distance DV (9 per cent precision) obtained from the autocorrelation. Although not yet competitive, this technique will benefit from the arrival of deeper photometric data from upcoming surveys that will enable it to go beyond the current limitations we have identified in this work.
The net CO 2 assimilation (A) response to intercellular CO 2 concentration (C i ) is a fundamental measurement in photosynthesis and plant physiology research. The conventional A/C i protocols rely on steady-state measurements and take 15–40 min per measurement, limiting data resolution or biological replication. Additionally, there are several CO 2 protocols employed across the literature, without clear consensus as to the optimal protocol or systematic biases in their estimations. We compared the non-steady-state Dynamic Assimilation Technique (DAT) protocol and the three most used CO 2 protocols in steady-state measurements, and tested whether different CO 2 protocols lead to systematic differences in estimations of the biochemical limitations to photosynthesis. The DAT protocol reduced the measurement time by almost half without compromising estimation accuracy or precision. The monotonic protocol was the fastest steady-state method. Estimations of biochemical limitations to photosynthesis were very consistent across all CO 2 protocols, with slight differences in Rubisco carboxylation limitation. The A/C i curves were not affected by the direction of the change of CO 2 concentration but rather the time spent under triose phosphate utilization (TPU)-limited conditions. Our results suggest that the maximum rate of Rubisco carboxylation (V cmax ), linear electron flow for NADPH supply (J), and TPU measured using different protocols within the literature are comparable, or at least not systematically different based on the measurement protocol used.
Microscale mechanical testing has greatly benefited nuclear materials studies in at least two aspects: one is its feasibility to integrate with SEM and TEM microscopes for in situ atomic scale or microscale structural characterization to reveal fundamental details, and the other is its significance in development of accelerator-based ion irradiation technique as a surrogate method to simulate neutron damage. Ion irradiation is able to reach damage creation at a level at least three orders of magnitudes higher than test reactors. However, limited ion penetration depths, which are about a few microns for MeVs heavy ions and 10s microns for MeV light ions, make microscale mechanical tests a necessity. But, there is a great challenge to bridge microscale tests to macroscale tests because a bulk specimen of irradiated nuclear materials for high dose applications cannot be obtained in laboratory.
Microscale mechanical testing has greatly benefited nuclear materials studies in at least two aspects: one is its feasibility to integrate with SEM and TEM microscopes for in situ atomic scale or microscale structural characterization to reveal fundamental details, and the other is its significance in development of accelerator-based ion irradiation technique as a surrogate method to simulate neutron damage. Ion irradiation is able to reach damage creation at a level at least three orders of magnitudes higher than test reactors. However, limited ion penetration depths, which are about a few microns for MeVs heavy ions and 10s microns for MeV light ions, make microscale mechanical tests a necessity. But, there is a great challenge to bridge microscale tests to macroscale tests because a bulk specimen of irradiated nuclear materials for high dose applications cannot be obtained in laboratory.
The inhomogeneous nucleation and growth of Li dendrite combined with the spontaneous side reactions with the electrolytes dramatically challenge the stability and safety of Li metal anode (LMA). Despite tremendous endeavors, current success relies on the use of significant excess of Li to compensate the loss of active Li during cycling. Herein, a near-surface Li + irrigation strategy is developed to regulate the inhomogeneous Li deposition behavior and suppress the consequent side reactions under limited Li excess condition. The conformal polypyrrole (PPy) coating layer on Cu surface via oxidative chemical vapor deposition technique can induce the migration of Li + to the interregional space between PPy and Cu, creating a near-surface Li + -rich region to smooth diffusion of ion flux and uniform the deposition. Moreover, as evidenced by multiscale characterizations including synchrotron high-energy X-ray diffraction scanning, a robust N-rich solid-electrolyte interface (SEI) is formed on the PPy skeleton to effectively suppress the undesired SEI formation/dissolution process. Strikingly, stable Li metal cycling performance under a high areal capacity of 10 mAh cm -2 at 2.0 mA cm -2 with merely 0.5 × Li excess is achieved. The findings not only resolve the long-standing poor LMA stability/safety issues, but also deepen the mechanism understanding of Li deposition process.
Cadmium telluride (CdTe) solar cells represent a commercially successful photovoltaic technology, with an annual production capacity approaching 20 GW. However, improving the open-circuit voltage (V OC ) remains challenging. This study aims to deepen the understanding of charge carrier recombination in CdTe solar cells and to explore alternative dynamical characterization methods that address the limitations found in conventionally used time-resolved photoluminescence for CdTe solar cells. Transient photovoltage and transient photocurrent techniques are utilized to investigate charge carrier dynamics under conditions resembling real-world solar cell operation. The results reveal that an effective nonradiative recombination lifetime of 580 ns dominates the charge dynamics at VOC values below 850 mV. Above this threshold, radiative recombination becomes significant, with a radiative recombination coefficient of 1.1 × 10 −9 cm 3 s −1 . Additionally, the stationary charge carrier density at 1 sun is determined to be around 1 × 10 14 cm −3 . By accurately determining both radiative and nonradiative recombination, this work provides a comprehensive understanding of carrier dynamics in high-performing CdTe devices and paves the way for improving the V OC and performance of CdTe solar cells.
We introduce the concept of random interpenetrating electrode structures, inspired by spinodal decomposition, as a transformative approach for energy storage applications. While ordered architectures, such as double gyroids and Kelvin cell structures, have long been favored for their structural uniformity and surface area utilization, we demonstrate that random structures offer distinct advantages including shorter diffusion pathways, higher packing density, and enhanced reaction kinetics, particularly at low temperatures. Using a combination of computational and electrochemical analysis, we show that random architecture outperforms their ordered counterparts in scenarios where diffusion dominates. This work represents the first systematic exploration of random structures in energy storage, highlighting their potential to overcome limitations of traditional designs. However, challenges such as structural reproducibility and scalability remain, necessitating further investigation into fabrication techniques and material selection. By establishing a framework to optimize random electrode architectures, we provide critical insights into the interplay between geometry, diffusion, and reaction kinetics. This study not only introduces a new design principle for 3D electrodes but also opens pathways for next-generation energy storage systems that demand both high performance and adaptability to a range of operating conditions.
Tantalum is a refractory metal used in a variety of harsh environment applications. Additive manufacturing of tantalum is limited based on its high melting point and affinity for oxygen. Directed Energy Deposition is an additive manufacturing technique with rapid deposition time and compositional flexibility within builds. Additively manufactured tantalum is susceptible to a variety of material and process-based defects. Various lack-of-fusion defects were identified resulting from excessive powder feed rates or insufficient laser power. Oxygen impurities in some samples caused cracking and increased material hardness. Precipitates were identified in the highly oxidized samples which were printed immediately after the build chamber was opened. High-density, low-defect parts were successfully produced. The effects of scan speed, laser power, and powder feed rate on density and defects were analyzed. A processing window was identified for producing high-quality parts which requires adequately high laser power and lower powder feed rate.
As a low-Z material, lithium is widely tested and used in tokamak devices for particle recycling and impurity control to improve plasma performance. Lithium application as plasma-facing materials via different methods, such as coating, injection and flowing liquid limiter, has been investigated more than 10 years on EAST. This study presents the development of the lithium techniques applied on EAST, and reviews the progresses on the investigation of its interaction with plasma and its effects on the improvement on the plasma performances. In addition, this paper further discusses the potential applications of lithium technique in future fusion devices.
Fuel cladding chemical interactions (FCCI) occurred on the interface between the nuclear metal fuel and cladding is the primary cause of cladding wastage, weakening cladding mechanical integrity, and placing fuel and cladding at risk. Although the microstructural and phase information of FCCI has been fairly understood, mechanical properties remain less studied due to limited reaction volume. Here, through a combining of advanced electron microscopy characterizations and small-scale mechanical testing techniques, including indentation and micro-tensile testing, this study investigated the microscale mechanical properties of FCCI between the ferritic/martensitic (F/M) HT9 cladding and an advanced Uranium (U)-based metallic fuel irradiated at the Advanced Test Reactor to 2.2% FIMA with peak inner cladding temperature reached to 650 °C. Mechanical testing results show significant hardening and embrittlement in the FCCI region. The brittle fracture of FCCI specimen is mainly attributed to the formation of nano-crystallized intermetallic σ-FeCr phase. Whereas mechanical softening was revealed in the unreacted HT9 matrix due to irradiation-induced microstructural and microchemical evolution, specifically, the disappearance of martensitic lath structure and the formation of Fe 2 Mo Laves phase precipitation which consumed the solid solution strengthening Mo from the F/M HT9 matrix. Due to the achieved high cladding temperature, this fuel pin is of particular significance for revealing the high-temperature irradiation effect on the mechanical properties of HT9 cladding. Therefore, the outcomes of this study are expected to contribute to the development of multi-scale mechanical behavior modeling of HT9 cladding for Generation IV reactors which requires cladding to run at higher temperature (above 600 ?).
Reconstruction quality in Far-field High-Energy Diffraction Microscopy (FF-HEDM) is limited by the spatial resolution of area detectors and the frequent occurrence of overlapping diffraction spots. To address these challenges, we developed a super-resolution (SR) framework using convolutional neural networks (CNNs) to recreate 2D diffraction peaks at up to ×8 resolution from raw detector data. A specialized simulation tool was created to generate synthetic training datasets with varying degrees of peak overlap. Integrated into the Microstructural Imaging using Diffraction Analysis Software (MIDAS), the SR model improves the spatial accuracy and precision of 3D grain reconstruction by an order of magnitude. This approach provides a robust solution for investigation of complex micromechanical states and material classes where the analysis is limited by the presence of overlapping peaks. Furthermore, the methodology developed here can potentially be extended to other techniques that require sub-pixel accuracy for high-fidelity data analysis.