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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Multiscale Cryo Electron Microscopy Reveals Interfacial Degradation and Stabilization in Battery Electrodes

Electrochemical interfaces are dynamic systems, evolving based on their local environment and reactant surface structures. The electrode-electrolyte interface in Li-ion batteries can be protective, limiting parasitic reactions with the electrolyte to passivate the surface [1]. Additionally, this interphase has an impact on the Li-ion transport through that layer based on its composition, bonding environment, and thickness. These parameters are challenging to collect and may vary depending on the electrode surface site investigated relative to its spatial position in a coin cell. This study will detail a multiscale cryogenic electron microscopy approach where millimeter-scale cross-sections through the coin cell batteries were made using a cryogenic stage within a fs-laser plasma focused ion beam (laser PFIB) with complementary energy dispersive X-ray spectroscopy able to detect variations in the composition at electrode interfaces [2]. Microscale cross-sectioning and lamella sample preparation of battery electrodes was conducted at the Center for Integrated Nanotechnologies using a Ga-ion focused ion beam (FIB) with air-free and cryo-transfer [3], followed by nanoscale mapping of composition and bonding within the CEI through cryo-scanning transmission electron microscopy (cryo-STEM) electron energy loss spectroscopy [4]. This multiscale approach enabled identification of millimeter-scale features of a battery stack with visualization of degradation in electrodes such as cracks in cathode particles, gas evolution, and SEI evolution; microscale interfacial characteristics, such as heterogeneity in the SEI or barrier layer and identification of electrolyte networks to the electrode surfaces; and nanoscale measurement of the CEI thickness, mapping of transition metal bonding within the cathode particles to identify loss of active materials, and identification of beneficial electrolyte additives incorporated into the CEI structure. This multiscale approach allows for a statistical understanding of the primary mechanisms and parasitic degradation pathways that impact performance by limiting the ion transport pathways within Li+ batteries.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Track Matching in the DUNE Near Detectors

The Deep Underground Neutrino Experiment (DUNE) is an international particle physics experiment looking answer some of the largest unanswered questions in neutrino physics. DUNE uses a high power neutrino beam produced at Fermi National Accelerator Laboratory (Fermilab), and consists of a near detector (ND) also located at Fermilab and a far detector (FD) 1300 km away at the Sanford Underground Research Facility (SURF) in South Dakota. In the first phase of the experiment, the ND complex will contain a modular liquid argon TPC (ND-LAr) and a solid scintillator-based muon spectrometer (TMS), in addition to a beam monitoring detector (SAND) and systems for moving ND-LAr and TMS away from the neutrino beam axis (PRISM). A prototype of ND-LAr, the 2x2 demonstrator, alongside a solid scintillator muon tagger provided by repurposed MINERvA planes, has been built and taken data at Fermilab. For analyses with the ND, connecting particle tracks (such as muons) that exit the liquid argon active volume into the solid scintillator muon detector can improve particle identification and energy reconstruction, and alleviate pileup due to the intense beam. To match tracks between detectors during reconstruction, we have explored using Graph Neural Networks (GNNs) to connect tracks segments between the liquid argon detector region and the solid scintillator detector planes. We have trained a GNN on reconstructed simulated data from the 2×2 demonstrator and repurposed MINERvA planes. We will evaluate its performance and then train a similar network on reconstructed ND-LAr and TMS simulations.

Xing, Daniel [U. Colorado, Boulder]↗
DOE OSTI2023

Active Colloids as Models, Materials, and Machines

Active colloids use energy input at the particle level to propel persistent motion and direct dynamic assemblies. We consider three types of colloids animated by chemical reactions, time-varying magnetic fields, and electric currents. For each type, we review the basic propulsion mechanisms at the particle level and discuss their consequences for collective behaviors in particle ensembles. These microscopic systems provide useful experimental models of nonequilibrium many-body physics in which dissipative currents break time-reversal symmetry. Freed from the constraints of thermodynamic equilibrium, active colloids assemble to form materials that move, reconfigure, heal, and adapt. Colloidal machines based on engineered particles and their assemblies provide a basis for mobile robots with increasing levels of autonomy. This review provides a conceptual framework for understanding and applying active colloids to create material systems that mimic the functions of living matter. We highlight opportunities for chemical engineers to contribute to this growing field.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Aerosol Activation in Radiation Fog at the Atmospheric Radiation Program Southern Great Plains Site

Environmental supersaturation is a key parameter in the formation of fog and clouds, yet it cannot be measured directly and must be inferred. Calculating the ambient supersaturation in fog requires knowledge of the aerosol hygroscopicity as well as particle size distribution, and relatively few values have been reported in the literature. Here we use κ-Köhler theory to derive aerosol activation properties based on particle hygroscopicity and dry particle size distributions, and then estimate the effective peak supersaturation during eight cases of radiative fog at the Southern Great Plains site in rural north-central Oklahoma, USA. The mean hygroscopicity parameter κ of particles likely to act as cloud condensation nuclei varied from 0.14 to 0.43. Ambient effective peak supersaturation during the fog episodes was between 0.01%–0.07%, with most values below 0.04%. Furthermore, the minimum 50% dry activation diameter generally ranged between 300–400 nm with little activation of particles with diameters below 300 nm.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

1,10-Phenanthroline-Iron Complex-Derived Fe-N-C Electrocatalysts: Enhanced Oxygen Reduction Activity and Stability Through Synthesis Tuning

The development of electrocatalysts composed of earth-abundant elements is essential for advancing the commercial application of Proton Exchange Membrane Fuel Cells (PEMFC). Among these, single-atom electrocatalysts, such as Fe-N-C, show great promise for the oxygen reduction reaction (ORR). This study aims to improve the ORR activity and stability of Fe-N-C electrocatalysts by fine-tuning the straightforward 1,10-phenanthroline-iron complexation synthesis method. Key parameters, including iron-to-phenanthroline ratio, carbon powder surface area, and pyrolysis temperature were systematically varied to evaluate their influence on the resulting electrocatalysts. The findings of this study revealed that the electrocatalysts synthesized with 1,10-phenanthroline (Phen) and high-surface-area Black Pearls (BP) possessed much better ORR activity than electrocatalysts prepared by using Vulcan carbon (lower surface area). Interestingly, electrocatalysts prepared with BP, but with a non-bidentate nitrogen-containing ligand molecule, such as imidazole, showed a much poorer activity, as the resulting material predominantly consisted of inactive structures, such as encapsulated iron nanoparticles and iron oxide, as evidenced by HR-TEM, EXAFS, and XRD. Therefore, the results suggest that only the synergistic combination of the bidentate ligand phenanthroline (Phen) and the high-surface-area carbon support (BP) favored the formation of ORR-active Fe-N-C single-atom species upon pyrolysis. The study also unveiled a significant enhancement in electrocatalyst stability during accelerated durability tests (and air storage) as the pyrolysis temperature was increased from 700 to 1300 °C, albeit at the expense of ORR activity, likely resulting from the generation of iron particles. Pyrolysis at 1050 °C yielded the electrocatalyst with the most favorable balance of activity and stability in rotating disk measurements, while maintaining moderate durability under PEM fuel cell operation. The insights obtained in this study may guide the development of more active efficient and durable electrocatalysts, synthesized via a simple method using earth-abundant elements, for application in PEMFC cathodes.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2020

Comparison of Eulerian Bin and Lagrangian Particle-Based Schemes in Simulations of Pi Chamber Dynamics and Microphysics

This paper presents a comparison of simulations applying either a traditional Eulerian bin microphysics or a novel particle-based Lagrangian approach to represent CCN activation and cloud droplet growth. The Eulerian microphysics solve the evolution equation for the spectral density function, whereas the Lagrangian approach follows computational particles referred to as superdroplets. Each superdroplet represents a multiplicity of natural droplets that makes the Lagrangian approach computationally feasible. The two schemes apply identical representation of CCN activation and use the same droplet growth equation; these make direct comparison between the two schemes practical. The comparison, the first of its kind, applies an idealized simulation setup motivated by laboratory experiments with the Pi Chamber and previous model simulations of the Pi Chamber dynamics and microphysics. The Pi Chamber laboratory apparatus considers interactions between turbulence, CCN activation, and cloud droplet growth in moist Rayleigh–Bénard convection. Simulated steady-state droplet spectra averaged over the entire chamber are similar, with the mean droplet concentration, mean radius, and spectral width close in Eulerian and Lagrangian simulations. Small differences that do exist are explained by the inherent differences between the two schemes and their numerical implementation. The local droplet spectra differ substantially, again in agreement with the inherent limitations of the theoretical foundation behind each approach. There is a general agreement between simulations and Pi Chamber observations, with simplifications of the CCN activation and droplet growth equation used in the simulations likely explaining specific differences.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Atomically Precise Nanoclusters as Co‐Catalysts for Light‐Activated Microswimmer Motility

Microswimmers are self-propelled particles that navigate fluid environments, offering significant potential for applications in environmental pollutant decomposition, biosensing, and targeted drug delivery. Their performance relies on engineered catalytic surfaces. Gold nanoclusters (AuNCs), with atomically precise structures, tunable optical properties, and high surface area-to-volume ratio, provide a new optimal catalyst for enhancing microswimmer propulsion. Unlike bulk gold or nanoparticles, AuNCs may deliver tunable photocatalytic activity and increased catalytic specificity, making them ideal co-catalysts for hybrid microswimmers. For the first time, this study combines AuNCs with TiO 2 /Cr 2 O 3 Janus microswimmers, combining the unique properties of both materials. This hybrid system capitalizes on the tuned optical properties of AuNCs and their role as co-catalysts with TiO 2 , driving enhanced photocatalytic performance under ultraviolet (UV) excitation. Using motion analysis, it is shown that the AuNC-microswimmers exhibit significantly greater propulsion and mean squared displacement (MSD) as compared to controls. These findings suggest that the integration of nanoclusters with semiconductor materials enables state of the art, light-switchable microswimmers. These AuNC-microswimmer systems may thus offer new opportunities for environmental catalysis and other applications, providing precise control over catalytic and motile behaviors at the microscale.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Electronic impact of Ni2P nanoparticle size on hydrogenation rates

Nickle phosphide, Ni2P, nanoparticles supported on SiO2 show a marked volcano shaped size dependence. Kinetic analysis and physicochemical characterization shows the electron density of Ni to increase with increasing Ni2P size, enhancing in turn the H2 adsorption strength. For particles below 15 nm, H adsorbs weakly causing a low surface coverage of H, gradually increasing with particle size. For large particles, hydrogen binds too strongly causing a high coverage but low catalytic activity. The remarkable size dependence of the electronic properties show that Ni2P particle size can be used to fine-tune its activity for hydrogenation.

Ni2P size effect, Electron density, H2 adsorption ↗
DOE OSTI2022

Installation of a solid state neutral particle analyzer array on mega ampere spherical tokamak upgrade

A compact solid state neutral particle analyzer (SSNPA) diagnostic, previously installed at NSTX-U, has been moved to MAST-U and successfully operated in the first physics campaign (MU01). The SSNPA operates by detecting the flux of fast neutral particles produced by charge exchange (CX) reactions to diagnose the fast ion distribution. The diagnostic consists of three 16-channel sensors, which provide a radial view of the plasma and have a sightline intersection with the South–South neutral beam line. From this radial geometry, active CX signals from mostly trapped particles are observed. Each channel has a spatial resolution of 3–4 cm, a temporal resolution of 200 kHz, and an average pitch angle resolution of a few degrees. The three-sensor configuration allows for coarse energy resolution of the CX signals; each sensor sees similar sightlines but different filter thicknesses alter the energy cutoffs by known amounts. Experimental data show that all channels are collecting data as intended. The signal to noise ratio is typically around 15. Preliminary data analysis shows a correlation between the SSNPA signal and magnetohydrodynamic activity in the plasma as expected.

Instruments & Instrumentation↗
DOE OSTI2022

Quantifying the effect of CO 2 gasification on pulverized coal char oxy-fuel combustion

Previous research has provided strong evidence that CO 2 and H 2 O gasification reactions can provide non-negligible contributions to the consumption rates of pulverized coal (pc) char during combustion, particularly in oxy-fuel environments. Fully quantifying the contribution of these gasification reactions has proven to be difficult, due to the dearth of knowledge of gasification rates at the elevated particle temperatures associated with typical pc char combustion processes, as well as the complex interaction of oxidation and gasification reactions. Gasification reactions tend to become more important at higher char particle temperatures (because of their high activation energy) and they tend to reduce pc oxidation due to their endothermicity (i.e. cooling effect). The work reported here attempts to quantify the influence of the gasification reaction of CO 2 in a rigorous manner by combining experimental measurements of the particle temperatures and consumption rates of size-classified pc char particles in tailored oxy-fuel environments with simulations from a detailed reacting porous particle model. The results demonstrate that a specific gasification reaction rate relative to the oxidation rate (within an accuracy of approximately +/- 20% of the pre-exponential value), is consistent with the experimentally measured char particle temperatures and burnout rates in oxy-fuel combustion environments. Conversely, the results also show, in agreement with past calculations, that it is extremely difficult to construct a set of kinetics that does not substantially overpredict particle temperature increase in strongly oxygen-enriched N2 environments. This latter result is believed to result from deficiencies in standard oxidation mechanisms that fail to account for falloff in char oxidation rates at high temperatures.

42 ENGINEERING↗
DOE OSTI2022

Polarized blazar X-rays imply particle acceleration in shocks

Most of the light from blazars, active galactic nuclei with jets of magnetized plasma that point nearly along the line of sight, is produced by high-energy particles, up to around 1 TeV. Although the jets are known to be ultimately powered by a supermassive black hole, how the particles are accelerated to such high energies has been an unanswered question. The process must be related to the magnetic field, which can be probed by observations of the polarization of light from the jets. Measurements of the radio to optical polarization—the only range available until now—probe extended regions of the jet containing particles that left the acceleration site days to years earlier and hence do not directly explore the acceleration mechanism, as could X-ray measurements. Here we report the detection of X-ray polarization from the blazar Markarian 501 (Mrk 501). We measure an X-ray linear polarization degree Π X of around 10%, which is a factor of around 2 higher than the value at optical wavelengths, with a polarization angle parallel to the radio jet. This points to a shock front as the source of particle acceleration and also implies that the plasma becomes increasingly turbulent with distance from the shock.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

High resolution variability in wet deposition in the southeastern United States

Rainwater chemistry is determined by atmospheric pollutants and particles which vary spatially and temporally. Industrial and agricultural activities and meteorological events (e.g. sea breezes, severe weather, blowing dust) alter atmospheric particle and trace gas compositions. These gases and particles are scavenged by cloud and rain droplets that drive wet deposition. During an Intensive Operation Period (IOP) from April to October 2021, rainwater was collected at higher frequency intervals, usually daily, after precipitation events at three locations on the Savannah River Site (SRS). The farthest locations were separated by approximately 20 km. The mean concentration (μeq/L) of seven ions followed the Cl⁻ > SO 4 2− > Na⁺ > NO 3 ⁻ > K⁺ > Mg 2+ > Ca 2+ downward trend. Ion concentrations were compared to background ion concentrations from the National Atmospheric Deposition Program (NADP). The high frequency monthly averaged SRS data compared well with the monthly averaged NADP background but demonstrated extensive variability. In some months in 2021, the high frequency data compared better to the NADP site near the coast while in other months inland sites compared better. Strong spatial variability for ion concentrations was observed across SRS which was attributed to localized impacts in rainfall spatial variability. High frequency measurements allowed for comparison to regional weather patterns indicating influences from the Atlantic Ocean, Gulf of Mexico, and cities. This can account for spatial variability in the wet deposition flux. Sea breezes, Saharan dust, and anthropogenic sources were shown to impact wet deposition flux variability. Higher frequency precipitation chemistry sampling at numerous locations better captures ion concentration variability and improves measurement representativeness.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Surface Self-Diffusion Induced Sintering of Nanoparticles

Despite the critical role of sintering phenomena in constraining the long-term durability of nanosized particles, a clear understanding of nanoparticle sintering has remained elusive due to the challenges in atomically tracking the neck initiation and discerning different mechanisms. Through the integration of in situ transmission electron microscopy and atomistic modeling, this study uncovers the atomic dynamics governing the neck initiation of Pt–Fe nanoparticles via a surface self-diffusion process, allowing for coalescence without significant particle movement. Real-time imaging reveals that thermally activated surface morphology changes in individual nanoparticles induce significant surface self-diffusion. Further, the kinetic entrapment of self-diffusing atoms in the gaps between closely spaced nanoparticles leads to the nucleation and growth of atomic layers for neck formation. This surface self-diffusion-driven sintering process is activated at a relatively lower temperature compared to the classic Ostwald ripening and particle migration and coalescence processes. The fundamental insights have practical implications for manipulating the morphology, size distribution, and stability of nanostructures by leveraging surface self-diffusion processes.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Evaluation of Properties for Microsample Identification

A study was conducted to determine if individual particle characteristics could be used to identify particles of interest, sub-samples, from bulk post-detonation debris. Three archived post-detonation debris samples were used for this effort. Particles from these samples were identified as active (produced fission tracks), and inactive (did not produce fission tracks), as the first defining characteristic. Morphology was the secondary characteristic to select particles for further study, i.e. spherical/non-spherical. Once particles were identified and isolated, they were characterized by optical microscopy for size in µm, number of fission tracks, morphology, transmitted light color, and reflected light color. Particles were then analyzed by scanning electron microscopy for morphology, elemental content, and compound identification. Raman spectroscopy was attempted on five particles with indeterminate results due to environmental mixing (heterogeneity) during the events of particle formation. Once all non-destructive analyses were completed all particles were analyzed by thermal ionization mass spectrometry to determine isotopic atom percents of plutonium and uranium, and an estimate of atoms of plutonium and uranium in each particle. An estimate of the ratio of uranium to plutonium was also obtained (U/Pu). Data analytics of the data from the particles showed that combining characteristics of the particles have a high probability of identifying particles of interest from bulk post-detonation debris samples. Please note that this version of the report is an abridged version of the full report (Wagnon et al. 2025) that has been edited to be appropriate for public release.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2024

Reduced‐Order Probabilistic Emulation of Physics‐Based Ring Current Models: Application to RAM‐SCB Particle Flux

Abstract In this work, we address the computational challenge of large‐scale physics‐based simulation models for the ring current. Reduced computational cost allows for significantly faster than real‐time forecasting, enhancing our ability to predict and respond to dynamic changes in the ring current, valuable for space weather monitoring and mitigation efforts. Additionally, it can also be used for a comprehensive investigation of the system. Thus, we aim to create an emulator for the Ring current‐Atmosphere interactions Model with Self‐Consistent magnetic field (RAM‐SCB) particle flux that not only improves efficiency but also facilitates forecasting with reliable estimates of prediction uncertainties. The probabilistic emulator is built upon the methodology developed by Licata and Mehta (2023), https://doi.org/10.1029/2022sw003345 . A novel discrete sampling is used to identify 30 simulation periods over 20 years of solar and geomagnetic activity. Focusing on a subset of particle flux, we use Principal Component Analysis for dimensionality reduction and Long Short‐Term Memory (LSTM) neural networks to perform dynamic modeling. Hyperparameter space was explored extensively resulting in about 5% median symmetric accuracy across all data sets for one‐step dynamic prediction. Using a hierarchical ensemble of LSTMs, we have developed a reduced‐order probabilistic emulator (ROPE) tailored for time‐series forecasting of particle flux in the ring current. This ROPE offers accurate predictions of omnidirectional flux at a single energy with no pitch angle information, providing robust predictions on the test set with an error score below 11% and calibration scores under 8% with bias under 2% providing a significant speed up as compared to the full RAM‐SCB run.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Chemical properties and single-particle mixing state of soot aerosol in Houston during the TRACER campaign

Abstract. A high-resolution soot particle aerosol mass spectrometer (SP-AMS) was used to selectively measure refractory black carbon (rBC) and its associated coating material using both the ensemble size-resolved mass spectral mode and the event trigger single particle (ETSP) mode in Houston, Texas, in summer 2022. This study was conducted as part of the Department of Energy Atmospheric Radiation Measurement (ARM) program's TRacking Aerosol Convection interactions ExpeRiment (TRACER) field campaign. The study revealed an average (±1σ) rBC concentration of 103 ± 176 ng m−3. Additionally, the coatings on the BC particles were primarily composed of organics (59 %; 219 ± 260 ng m−3) and sulfate (26 %; 94 ± 55 ng m−3). Positive matrix factorization (PMF) analysis of the ensemble mass spectra of BC-containing particles resolved four distinct types of soot aerosol, including an oxidized organic aerosol (OOABC,PMF) factor associated with processed primary organic aerosol, an inorganic sulfate factor (SO4,BC,PMF), an oxidized rBC factor (O-BCPMF), and a mixed mineral dust–biomass burning aerosol factor with significant contribution from potassium (K-BBBC,PMF). Additionally, K-means clustering analysis of the single-particle mass spectra identified eight different clusters, including soot particles enriched in hydrocarbon-like organic aerosol (HOABC,ETSP), sulfate (SO4,BC,ETSP), two types of rBC, OOA (OOABC,ETSP), chloride (ClBC,ETSP), and nitrate (NO3,BC,ETSP). The single-particle measurements demonstrate substantial variation in BC coating thickness with coating-to-rBC mass ratios ranging from 0.1 to 100. The mixing state index (χ), which denotes the degree of homogeneity of the soot aerosol, varied from 4 % to 94 % with a median of 40 %, indicating that the aerosol population lies in between internal and external mixing but has large temporal and source type variability. In addition, a significant fraction of BC-containing particles, a majority enriched with oxidized organics and sulfate, exhibit sufficiently high κ values and diameters conducive to activation as cloud nuclei under atmospherically relevant supersaturation conditions. This finding bears significance in comprehending the aging processes of rBC-containing particles and their activation into cloud droplets. Our analysis highlights the complex nature of soot aerosol and underscores the need to comprehend its variability across different environments for accurate assessment of climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Effects of particle size and AQDS on the flow of electron equivalents between magnetite and aqueous Fe2+

Magnetite can occur naturally in nano- to micro-size regimes and widely coexists with aqueous Fe2+ (Fe2+ (aq)) in natural environments. However, the effects of magnetite particle size on its interaction with Fe2+ (aq) in anoxic subsurface environments, particularly with redox-active organics, remain unclear. In this study, the interactions of Fe2+ (aq) with magnetite particles of 12 nm versus 109 nm (Mag-12 vs. Mag-109), with/without anthraquinone- 2,6-disulfonate (AQDS), were studied based on equilibrium Fe2+ (aq) concentrations, kinetics of AQDS reduction, and structural versus surface-localized Fe(II)/Fe(III) ratios (xstru and xsurf) of magnetite. In the absence of AQDS, Mag-12 tends to release Fe2+ (aq) at pH 7 but sorb Fe2+ (aq) at pH 8, while Fe2+ (aq) uptake by Mag-109 is observed at both pH 7 and 8. The amounts of Fe2+ (aq) adsorbed per unit area of Mag-109 is higher than that of Mag-12, due to the higher electron-accepting capacity of Mag-109 that facilitates interfacial electron transfer (IET) from surfaceassociated Fe(II) to structural Fe(III). The increases of xstru and xsurf in Mag-109 after reaction with Fe2+ (aq) at pH 7 and 8 suggest Fe2+ (aq) incorporation or electron injection into the structure of Mag-109. The presence of AQDS promotes Fe2+ (aq) uptake by both Mag-12 and Mag-109. However, AQDS reduction by Fe2+-amended Mag-12 results in the decrease of xstru and inhibits Fe2+ (aq) incorporation or electron injection into the structure. On the contrary, the increase of xstru observed in Fe2+-amended Mag-109 after reaction with AQDS suggests that Fe2+ (aq) incorporation or electron injection into the surface structure and then consequently into the interiors is more favorable for magnetite with larger particle sizes. The different flow directions of electron equivalents across the solid-solution interfaces can be attributed to the relatively higher electron-accepting capacity, i.e. redox potential, of Mag-109 than Mag-12; larger particle sizes facilitate IET from surface-associated Fe(II) to structural Fe(III) and promotes further Fe2+ (aq) uptake, culminating in the pronounced changes of redox potentials in magnetitebearing solutions. The results demonstrate that particle size and redox-active organics are important factors to affect reductive activity of Fe2+-magnetite system in redox-oscillating environments.

Peng, Huan↗
DOE OSTI2025

Radiation Imaging with Event Camera

Neuromorphic or event-based imaging is a new, commercially available sensor technology inspired by how the human eye works. Instead of measuring frames at a fixed rate, the camera measures changes in pixel intensity asynchronously. This difference in readout architecture results in a high dynamic range and low latency. Event-based cameras have been used in a variety of applications, including object tracking, navigation, and lidar technologies. However, event-based cameras have not been adequately researched for their ability to image high-energy particles. This report explores the use of an event camera for imaging alpha, beta, and X-rays particles, when coupled with scintillator screens to convert high-energy particles into visible light. Methods to process event data were developed and are presented here, along with the results. The event camera can measure alpha and beta particles with comparable performance to that of a conventional camera. Event cameras can also image higher-activity sources and offer the possibility of discriminating particle interaction types on the basis of timing differences, which typical cameras cannot do. Additionally, event cameras can image objects with an X-ray source when the source strength dynamically changes but does not create a high-contrast image during static X-ray measurement.

47 OTHER INSTRUMENTATION↗