Particle Population Research Articles

Impact of Non-Thermal Particle Acceleration on Radiative Signatures of AGN Jet-Cloud Interactions

This study investigates the complex dynamics of AGN (Active Galactic Nucleus) jet-cloud interactions, particularly focusing on the impact of non-thermal particle acceleration on the resulting radiative signatures. We utilize advanced computational simulations, tracking changes in jet properties and emissions over a span of 0.2 Myr (millions of years). The research design incorporates the modeling of jet-cloud interactions, with a key focus on variations in the jet's density, velocity, and magnetic field. Findings reveal a two-fold increase in the magnetic field strength up to ~5 μG due to cloud incorporation, which, coupled with an elevated non-thermal particle population, enhances synchrotron emissions, shifting the spectral index from 2.2 to 2.4. Inverse Compton scattering saw a 30% increase within the first 0.125 Myr, reflecting in an abrupt X-ray and gamma-ray emissions spike. Furthermore, the jet's light curve flux variability in the X-ray band showcased an initial peak increase of about 28% by 0.175 Myr, settling to a 20% increase by 0.2 Myr, attributable to cloud disruption and absorption. Conclusions drawn from these findings confirm our hypothesis that non-thermal particle acceleration dramatically influences the radiative signatures of AGN jet-cloud interactions .It underscores the necessity of considering such acceleration processes in modeling AGN jet-cloud interactions and posits that these changes could be instrumental as observational indicators, thereby contributing to more accurate interpretations of AGN activity and evolution.

Understanding HDL Metabolism and Biology Through In Vivo Tracer Kinetics.

HDL (high-density lipoprotein), owing to its high protein content and small size, is the densest circulating lipoprotein. In contrast to lipid-laden VLDL (very-low-density lipoprotein) and LDL (low-density lipoprotein) that promote atherosclerosis, HDL is hypothesized to mitigate atherosclerosis via reverse cholesterol transport, a process that entails the uptake and clearance of excess cholesterol from peripheral tissues. This process is mediated by APOA1 (apolipoprotein A-I), the primary structural protein of HDL, as well as by the activities of additional HDL proteins. Tracer-dependent kinetic studies are an invaluable tool to study HDL-mediated reverse cholesterol transport and overall HDL metabolism in humans when a cardiovascular disease therapy is investigated. Unfortunately, HDL cholesterol-raising therapies have not been successful at reducing cardiovascular events suggesting an incomplete picture of HDL biology. However, as HDL tracer studies have evolved from radioactive isotope- to stable isotope-based strategies that in turn are reliant on mass spectrometry technologies, the complexity of the HDL proteome and its metabolism can be more readily addressed. In this review, we outline the motivations, timelines, advantages, and disadvantages of the various tracer kinetics strategies. We also feature the metabolic properties of select HDL proteins known to regulate reverse cholesterol transport, which in turn underscore that HDL lipoproteins comprise a heterogeneous particle population whose distinct protein constituents and kinetics likely determine its function and potential contribution to cholesterol clearance.

Discovery of an extended GeV counterpart to the TeV source 1LHAASO J1945+2424 in Fermi-LAT data

ABSTRACT With almost 15 yr of data taken by the Large Area Telescope (LAT) onboard the Fermi satellite we discovered an extended source of GeV emission in the region of the very high energy (TeV) source 1LHAASO J1945+2424. This TeV source is more extended than the LAT source. The spectrum of the GeV emission is hard (with a photon spectral index ∼1.5) and connects smoothly with that of the TeV source, indicating a likely common origin. In order to explain the origin of the γ-rays we explore scenarios that are typically used for supernova remnants (SNRs) and pulsar wind nebulae (PWNe). For an SNR with a single particle population, a leptonic particle distribution in the form of a broken power law with a break energy of ∼3.7 TeV explains the spectra well, while in the hadronic scenario a simple power law with a hard spectral index of ∼1.64 is necessary. In the PWN scenario, reasonable parameters are obtained for a source age of 10 kyr and current pulsar spin-down luminosity of ∼1034 erg s−1.

CLASS Observations of Atmospheric Cloud Polarization at millimeter Wavelengths

The dynamic atmosphere imposes challenges to ground-based cosmic microwave background observation, especially for measurements on large angular scales. The hydrometeors in the atmosphere, mostly in the form of clouds, scatter the ambient thermal radiation and are known to be the main linearly polarized source in the atmosphere. This scattering-induced polarization is significantly enhanced for ice clouds due to the alignment of ice crystals under gravity, which are also the most common clouds seen at the millimeter-astronomy sites at high altitudes. This work presents a multifrequency study of cloud polarization observed by the Cosmology Large Angular Scale Surveyor experiment on Cerro Toco in the Atacama Desert of northern Chile, from 2016–2022, at the frequency bands centered around 40, 90, 150, and 220 GHz. Using a machine-learning-assisted cloud classifier, we made connections between the transient polarized emission found in all four frequencies with the clouds imaged by monitoring cameras at the observing site. The polarization angles of the cloud events are found to be mostly 90° from the local meridian, which is consistent with the presence of horizontally aligned ice crystals. The 90 and 150 GHz polarization data are consistent with a power law with a spectral index of 3.90 ± 0.06, while an excess/deficit of polarization amplitude is found at 40/220 GHz compared with a Rayleigh scattering spectrum. These results are consistent with Rayleigh-scattering-dominated cloud polarization, with possible effects from supercooled water absorption and/or Mie scattering from a population of large cloud particles that contribute to the 220 GHz polarization.

The Why and How of Ultrasmall Nanoparticles.

ConspectusIn this Account, we describe our research into ultrasmall nanoparticles, including their unique properties, and outline some of the new opportunities they offer. We will summarize our perspective on the current state of the field and highlight what we see as key questions that remain to be solved. First, there are several nanostructure size-scale regimes, with qualitatively distinct functional biological attributes. Broadly generalized, larger particles (e.g., larger than 300 nm) tend to be more efficiently swept away by the first line of the immune system (for example macrophages). In the "middle-sized" regime (20-300 nm), nanoparticle surfaces and shapes can be recognized by energy-dependent cellular reorganizations, then organized locally in a spatial and temporally coherent way. That energy is gated and made available by specific cellular recognition processes. The relationship between particle surface design, endogenously derived nonspecific biomolecular corona, and architectural features recognized by the cell is complex and only purposefully and very precisely designed nanoparticle architectures are able to navigate to specific targets. At sufficiently small sizes (<10 nm including the ligand shell, associated with a core diameter of a few nm at most) we enter the "quasi-molecular regime" in which the endogenous biomolecular environment exchanges so rapidly with the ultrasmall particle surface that larger scale cellular and immune recognition events are often greatly simplified. As an example, ultrasmall particles can penetrate cellular and biological barriers within tissue architectures via passive diffusion, in much the same way as small molecule drugs do. An intriguing question arises: what happens at the interface of cellular recognition and ultrasmall quasi-molecular size regimes? Succinctly put, ultrasmall conjugates can evade defense mechanisms driven by larger scale cellular nanoscale recognition, enabling them to flexibly exploit molecular interaction motifs to interact with specific targets. Numerous advances in control of architecture that take advantage of these phenomena have taken place or are underway. For instance, syntheses can now be sufficiently controlled that it is possible to make nanoparticles of a few hundreds of atoms or metalloid clusters of several tens of atoms that can be characterized by single crystal X-ray structure analysis. While the synthesis of atomically precise clusters in organic solvents presents challenges, water-based syntheses of ultrasmall nanoparticles can be upscaled and lead to well-defined particle populations. The surface of ultrasmall nanoparticles can be covalently modified with a wide variety of ligands to control the interactions of these particles with biosystems, as well as drugs and fluorophores. And, in contrast to larger particles, many advanced molecular analytical and separation tools can be applied to understand their structure. For example, NMR spectroscopy allows us to obtain a detailed image of the particle surface and the attached ligands. These are considerable advantages that allow further elaboration of the level of architectural control and characterization of the ultrasmall structures required to access novel functional regimes and outcomes. The ultrasmall nanoparticle regime has a unique status and provides a potentially very interesting direction for development.

Optofluidic Flow Cytometer with In-Plane Spherical Mirror for Signal Enhancement.

Statistical analysis of the properties of single microparticles, such as cells, bacteria or plastic slivers, has attracted increasing interest in recent years. In this regard, field flow cytometry is considered the gold standard technique, but commercially available instruments are bulky, expensive, and not suitable for use in point-of-care (PoC) testing. Microfluidic flow cytometers, on the other hand, are small, cheap and can be used for on-site analyses. However, in order to detect small particles, they require complex geometries and the aid of external optical components. To overcome these limitations, here, we present an opto-fluidic flow cytometer with an integrated 3D in-plane spherical mirror for enhanced optical signal collection. As a result, the signal-to-noise ratio is increased by a factor of six, enabling the detection of particle sizes down to 1.5 µm. The proposed optofluidic detection scheme enables the simultaneous collection of particle fluorescence and scattering using a single optical fiber, which is crucial to easily distinguishing particle populations with different optical properties. The devices have been fully characterized using fluorescent polystyrene beads of different sizes. As a proof of concept for potential real-world applications, signals from fluorescent HEK cells and Escherichia coli bacteria were analyzed.

Thermo-Mechanical and Mechano-Thermal Effects in Liquids Explained by Means of the Dual Model of Liquids

We pursue to illustrate the capabilities of the Dual Model of Liquids (DML) showing that it may explain crossed effects notable in Non-Equilibrium Thermodynamics (NET). The aim of the paper is to demonstrate that the DML may correctly model the thermodiffusion, in particular getting formal expressions for positive and negative Soret coefficient, and another “unexpected” mechano-thermal effect recently discovered in liquids submitted to shear strain, for which the first-ever theoretical interpretation is provided. Both applications of the DML are supported by the comparison with experimental data. The phenomenology of liquids, either pure or mixtures, submitted to external force fields is characterized by coupled effects, for instance mechano-thermal and thermo-mechanical effects, depending on whether the application of a mechanical force field generates a coupled thermal effect in the liquid sample or vice-versa. Although these phenomena have been studied since their discoveries, dating back to the XIX century, no firm theoretical interpretation exists yet. Very recently the mesoscopic model of liquids DML has been proposed and its validity and applicability demonstrated in several cases. According to DML, liquids are arranged on a mesoscopic scale by means of aggregates of molecules, or liquid particles. These structures share the liquid world with a population of lattice particles, i.e., elastic waves that interact with the liquid particles by means of an inertial force, allowing the mutual exchange of energy and momentum between the two populations. The hit particle relaxes the acquired energy and momentum due to the interaction, giving them back to the system a step forward and a time-lapse later, alike in a tunnel effect.

The deactivation effects of Nd3+ ion for 2.85 μm laser in Ho3+/Nd3+ co-doped fluorotellurite glass

The 2.85 μm band has garnered significant attention for its wide range of applications in the mid-infrared region, and Ho3+ doped fluorotellurite fiber shows great promise as a gain medium for the 2.85 μm fiber laser. To achieve efficient population inversion for Ho3+ ions at 2.85 μm, Ho3+/Nd3+ co-doped fluorotellurite glasses with low hydroxyl were synthesized. The deactivation effect of Nd3+ ions to Ho3+: 5I7 levels was investigated through emission spectra and lifetime decay curves under 890 nm excitation. The results show that Nd3+ ions can effectively quench the Ho3+: 2.05 μm emission and help the Ho3+: 5I6 → 5I7 transition to overcome the bottleneck of particle population inversion. Ultimately, the particle population inversion corresponding to 2.85 μm luminescence was realized in the Ho3+/Nd3+ co-doped fluorotellurite glass, and indicates that a maximum of 1.64 W laser at 2.85 μm with a slope efficiency of 8.72 % can be realized under 890 nm pump by numerical simulations.

Abstract 17049: Specific Subspecies of High Density Lipoprotein are Associated With Arterial Stiffness in Youth With and Without Diabetes

Introduction: Early vascular aging (EVA), a risk factor for cardiovascular disease (CVD), is evident in youth with diabetes. The mechanisms responsible for EVA are not well understood. Causal relationship of HDL-C with CVD is doubtful, but HDL particle concentration (HDL-P) and HDL function (cholesterol efflux capacity, CEC) are associated with incident and prevalent CVD independent of HDL-C. We investigated whether these metrics associate with EVA in youth. Methods: We studied three cohorts of youth with T1D (n=173), T2D (n=214) and healthy controls (n=116). We quantified total HDL-P and 6 HDL subspecies by differential ion mobility, serum HDL CEC (total and ABCA1-specific), and investigated their association with arterial stiffness (tonometric carotid-femoral pulse wave velocity, PWV) with multivariate regression. Results: PWV was not associated with total HDL-P in any of the three groups, but was associated positively with concentration of extra-small (xsHDL, 7.6nm, r=0.22, P=0.004) in T1D, small (sHDL, 8.2nm) particles in T1D (r=0.31, P&lt;0.0001) and T2D (r=0.17, P=0.02), and negatively with large HDL particles (lHDL, 11.5 nm) in T1D (r=-0.19, P=0.01). None of the HDL subspecies associated with PWV in healthy subjects. The association of sHDL with PVW remained significant after adjustment for age, sex, BMIz, mean arterial pressure (MAP), and diabetes status when analyzing T1D and controls or T2D and control subjects (Table 1). Both HDL-CEC metrics were significantly associated with higher PWV in T1D cohort but not T2D cohort, however, in multivariate models neither remained significant after adjusting the model for MAP (Table 1). Conclusions: A specific population of small HDL particles, but not HDL CEC, is associated with EVA, a predictor of CVD, independent of traditional risk factors and distending pressure (MAP). How the small HDL particles relate to EVA and whether they may be a novel target for intervention to prevent EVA in youth remains to be investigated.

Optimizing heat transfer characteristics in dry centrifugal Granulation: Impact of particle population trajectory and cooling strategies

Efficient recovery of heat and utilize blast furnace slag resources are crucial for achieving energy savings and reducing consumption in the steel industry. This study focuses on applying dry centrifugal pelletizing technology for recovering waste heat from slag. A comprehensive two-dimensional model was developed to investigate heat transfer dynamics within particle clusters, considering the variable physical parameters of the slag, latent heat of the phase change, and slag particle characteristics. Through an extensive analysis of the heat exchange within the granulation bin, we examined the temperature variations of slag particles and the distribution of absorbed heat by the water-cooled and air. Findings underscore the significant influence of flight trajectory, residence time, air-inlet flow rate, and temperature on heat exchange efficiency. Additionally, we explored the impact of auxiliary cooling measures and investigated how slag particle characteristics affect the bin wall, highlighting their importance for safe operations. Our results provide valuable insights for enhancing waste heat recovery efficiency from blast furnace slag and optimizing the implementation of dry centrifugal granulation technology. It serves as a vital reference for promoting energy-saving initiatives and reducing consumption in the steel industry.

Heat transfer characteristics of high-temperature particle population in ultra-dilute phase: Particle-fluid-surface heat transfer during falling

In dry centrifugal granulation technology, the liquid slag is granulated in the granulator to produce a particle population with a high-temperature dilute-phase distribution. During the falling process, inadequate heat transfer can cause the droplets to fail to solidify completely, greatly reducing the safety of the heat recovery bed operation. In this work, A heat transfer model for a particle population of ultra-dilute phase slag was developed, to investigate the particle-fluid-surface heat transfer characteristics of the particle population around the tube, and obtain the changing law of particle population cooling and tube surface heat transfer characteristics. The conclusions of the study show that the fluid flows close to the tube, which is due to particle perturbation. The separation point is to be shifted back, from 180°∼210° to the top 90°∼120°, resulting in a local heat transfer coefficient maximum at the upper of the tube. The amplitude of the fluctuations in the local heat transfer coefficients exhibits the dominance of the different heat transfer types, the percentage of radiant heat transfer is above 60% in all cases. The extended particle residence time can effectively increase the particle cooling rate, the particle cooling rate is above 230 K/s. This study reveals the heat exchange mechanism between the gas-solid phase of the ultra-dilute particle population and the horizontal tube during the falling process, positive performance of horizontal tubes on heat transfer to particle populations was confirmed. Combined heat transfer between the surfaces of dilute-phase particle populations is proposed as a new research content in the field of high-temperature melt granulation, expanding the prospects of industrial applications of combined heat transfer between the surfaces of fluid-solid multiphase flows.

Sub-Visible Particle Classification and Label Consistency Analysis for Flow-Imaging Microscopy Via Machine Learning Methods

Sub-visible particles can be a quality concern in pharmaceutical products, especially parenteral preparations. To quantify and characterize these particles, liquid samples may be passed through a flow-imaging microscopy instrument that also generates images of each detected particle. Machine learning techniques have increasingly been applied to this kind of data to detect changes in experimental conditions or classify specific types of particles, primarily focusing on silicone oil. That technique generally requires manual labeling of particle images by subject matter experts, a time-consuming and complex task.In this study, we created artificial datasets of silicone oil, protein particles, and glass particles that mimicked complex datasets of particles found in biopharmaceutical products. We used unsupervised learning techniques to effectively describe particle composition by sample. We then trained independent one-class classifiers to detect specific particle populations: silicone oil and glass particles. We also studied the consistency of the particle labels used to evaluate these models. Our results show that one-class classifiers are a reasonable choice for handling heterogeneous flow-imaging microscopy data and that unsupervised learning can aid in the labeling process. However, we found agreement among experts to be rather low, especially for smaller particles (< 8 µm for our Micro-Flow Imaging data). Given the fact that particle label confidence is not usually reported in the literature, we recommend more careful assessment of this topic in the future.

Electron-field instability: Excitation of electron plasma waves by an electric field

Electric fields are commonplace in plasmas and affect transport by driving currents and, in some cases, instabilities. The necessary condition for instability in collisionless plasmas is commonly understood to be described by the Penrose criterion, which quantifies a sufficient relative drift between different populations of particles that must be present for wave amplification via inverse Landau damping. For example, electric fields generate drifts between electrons and ions that can excite the ion-acoustic instability. Here, we use particle-in-cell simulations and linear stability analysis to show that the electric field can drive a fundamentally different type of kinetic instability, named the electron-field instability. This instability excites electron plasma waves with wavelengths ≳30λDe, has a growth rate that is proportional to the electric field strength, and does not require a relative drift between electrons and ions. The Penrose criterion does not apply when accounting for the electric field. The large value of the observed frequency, near the electron plasma frequency, further distinguishes it from the standard ion-acoustic instability, which oscillates near the ion plasma frequency. The ubiquity of macroscopic electric fields in quasineutral plasmas suggests that this instability is possible in a host of systems, including low-temperature and space plasmas. In fact, damping from neutral collisions in such systems is often not enough to completely damp the instability, adding to the robustness of the instability across plasma conditions.

Density Enhancement Streams in The Solar Wind

This Letter describes a new phenomenon on the Parker Solar Probe of recurring plasma density enhancements that have Δn/n ∼ 10% and that occur at a repetition rate of ∼5 Hz. They were observed sporadically for about 5 hr between 14 and 15 solar radii on Parker Solar Probe orbit 12 and they were also seen in the same radial range on both the inbound and outbound orbits 11. Their apparently steady-state existence suggests that their pressure gradient was balanced by the electric field. The X-component of the electric field component produced from this requirement is in good agreement with that measured. This provides strong evidence for the measurement accuracy of the density fluctuations and the X- and Y-components of the electric field (the Z-component was not measured). The electrostatic density waves were accompanied by an electromagnetic low-frequency wave, which occurred with the electrostatic harmonics. The amplitudes of these electrostatic and electromagnetic waves at ≥1 Hz were greater than the amplitude of the Alfvénic turbulence in their vicinity so they can be important for the heating, scattering, and acceleration of the plasma. The existence of this pair of waves is consistent with the observed plasma distributions and is explained as an oscilliton due to the nonlinear coupling between the kinetic Alfvén wave and the ion cyclotron mode, which belongs with the minor population of alpha particles.

Irregular Proton Injection to High Energies at Interplanetary Shocks

How thermal particles are accelerated to suprathermal energies is an unsolved issue, crucial for many astrophysical systems. We report novel observations of irregular, dispersive enhancements of the suprathermal particle population upstream of a high-Mach-number interplanetary shock. We interpret the observed behavior as irregular “injections” of suprathermal particles resulting from shock front irregularities. Our findings, directly compared to self-consistent simulation results, provide important insights for the study of remote astrophysical systems where shock structuring is often neglected.

Confined run-and-tumble model with boundary aggregation: Long-time behavior and convergence to the confined Fokker–Planck model

The motile micro-organisms such as Escherichia coli, sperm, or some seaweed are usually modeled by self-propelled particles that move with the run-and-tumble process. Individual-based stochastic models are usually employed to model the aggregation phenomenon at the boundary, which is an active research field that has attracted a lot of biologists and biophysicists. Self-propelled particles at the microscale have complex behaviors, while characteristics at the population level are more important for practical applications but rely on individual behaviors. Kinetic PDE models that describe the time evolution of the probability density distribution of the motile micro-organisms are widely used. However, how to impose the appropriate boundary conditions that take into account the boundary aggregation phenomena is rarely studied. In this paper, we propose the boundary conditions for a 2D confined run-and-tumble model (CRTM) for self-propelled particle populations moving between two parallel plates with a run-and-tumble process. The proposed model satisfies the relative entropy inequality and thus long-time convergence. We establish the relation between CRTM and the confined Fokker–Planck model (CFPM) studied in [J. Fu, B. Perthame and M. Tang, Fokker–Plank system for movement of micro-organism population in confined environment, J. Statist. Phys. 184 (2021) 1–25]. We prove theoretically that when the tumble is highly forward peaked and frequent enough, CRTM converges asymptotically to the CFPM. A numerical comparison of the CRTM with aggregation and CFPM is given. The time evolution of both the deterministic PDE model and individual-based stochastic simulations are displayed, which match each other well.

Exploring particle populations of common inorganic gunshot residue interferences through single particle inductively coupled plasma time-of-flight mass spectrometry

Inorganic gunshot residue (IGSR) has certain environmental and occupational interferent-particle sources known to display similar morphologies and elemental compositions to IGSR. These interferences can make detecting and identifying IGSR particles difficult, especially when IGSR particle number concentrations are low. Here, single-particle inductively coupled plasma time-of-flight mass spectrometry (spICP-TOFMS) is used to explore the particle types measured from IGSR and three important interferent-particle sources: brake pads, fireworks, and mineral sunscreen. spICP-TOFMS offers results in as little as 2 min per sample. With spICP-TOFMS, the mass of most elements, down to the 10s of attograms, can be detected and quantified in individual particles with diameters from 10s to 100s of nm. At this size range, almost all interferent sources produce particles with elemental compositions that overlap with ASTM-defined particle compositions used for identifying leaded and lead-free IGSR. We establish probabilities for detecting IGSR-like particles from interference sources through the analysis of thousands of particles from each interference. Based on this analysis, robust sample-specific ‘characteristic’ particle types can be used to classify leaded and unleaded IGSR particles, even in the presence of interferent particles. Of the interference sources studied, particles from brake pads and fireworks are most similar to leaded IGSR; however, IGSR particles could be unequivocally classified based on detection of lead and antimony. Particles from mineral sunscreen are most similar to those from lead-free IGSR; however, lead-free IGSR particles exhibit a unique titanium-zinc-copper elemental fingerprint that is not detected in mineral sunscreen particles. Within mixtures of interference particles and IGSR, IGSR is accurately identified with limited false positives, even when the number of interference particles is over 200-times greater than that of IGSR. Our results suggest that spICP-TOFMS is a useful approach for rapid and accurate IGSR identification even in samples with high concentrations of interferent background particles.

Gas fluidization of natural graphite flakes

Demand for high purity graphite is expected to greatly increase in the coming decades. Mined graphite is purified to the final purity specification via thermal and/or chemical fluid-solid processes. As fluidized bed electro-thermal purification is a promising technology, the physical characterization and cold-flow fluidization of Canadian natural flake graphite was undertaken to better understand the gas-solid dynamics. Three commercial graphite particle batches were characterized. Mean Sauter diameters of the three particle populations measured by microscopy were 89, 63 and 51 μm. The modified sieve analysis and permeametry yielded similar mean diameters. Particle sphericities were determined to be 0.34, 0.36 and 0.40 respectively. Channelling near the surface occurred near minimum fluidization (vmf) but eventually disappeared with increasing gas velocity. This led to a partial fluidization state before achieving complete fluidization with the delay, which was observed to be up to around 3vmf, being greater for the smaller particles. Minimum fluidization velocity was determined to be 0.063, 0.028 and 0.011 m/s respectively. Complete fluidization was observed at velocities of approximately 0.070, 0.046 and 0.035 m/s respectively. Finally, wall effects due to the presence of a central electrode did not significantly impact overall fluidization characteristics.

Multiscale Analysis of Electrocatalytic Particle Activities: Linking Nanoscale Measurements and Ensemble Behavior.

Nanostructured electrocatalysts exhibit variations in electrochemical properties across different length scales, and the intrinsic catalytic characteristics measured at the nanoscale often differ from those at the macro-level due to complexity in electrode structure and/or composition. This aspect of electrocatalysis is addressed herein, where the oxygen evolution reaction (OER) activity of β-Co(OH)2 platelet particles of well-defined structure is investigated in alkaline media using multiscale scanning electrochemical cell microscopy (SECCM). Microscale SECCM probes of ∼50 μm diameter provide voltammograms from small particle ensembles (ca. 40-250 particles) and reveal increasing dispersion in the OER rates for samples of the same size as the particle population within the sample decreases. This suggests the underlying significance of heterogeneous activity at the single-particle level that is confirmed through single-particle measurements with SECCM probes of ∼5 μm diameter. These measurements of multiple individual particles directly reveal significant variability in the OER activity at the single-particle level that do not simply correlate with the particle size, basal plane roughness, or exposed edge plane area. In combination, these measurements demarcate a transition from an "individual particle" to an "ensemble average" response at a population size of ca. 130 particles, above which the OER current density closely reflects that measured in bulk at conventional macroscopic particle-modified electrodes. Nanoscale SECCM probes (ca. 120 and 440 nm in diameter) enable measurements at the subparticle level, revealing that there is selective OER activity at the edges of particles and highlighting the importance of the three-phase boundary where the catalyst, electrolyte, and supporting carbon electrode meet, for efficient electrocatalysis. Furthermore, subparticle measurements unveil heterogeneity in the OER activity among particles that appear superficially similar, attributable to differences in defect density within the individual particles, as well as to variations in electrical and physical contact with the support material. Overall this study provides a roadmap for the multiscale analysis of nanostructured electrocatalysts, directly demonstrating the importance of multilength scale factors, including particle structure, particle-support interaction, presence of defects, etc., in governing the electrochemical activities of β-Co(OH)2 platelet particles and ultimately guiding the rational design and optimization of these materials for alkaline water electrolysis.

Simulation of noble metal particle growth and removal in the molten salt fast reactor

In the Molten Salt Fast Reactor (MSFR), fuel is dissolved in a liquid salt, causing the formation and decay of fission products, such as noble metals, to be inside the salt. Noble metals have very low solubility and do not dissolve in the salt. They are known to agglomorate into particles which, in turn, diffuse, drift or sediment to interfaces such as walls, free surfaces and bubbles, where they deposit. Leveraging this in the MSFR, online or offline helium bubbling is foreseen to act as a means to extract noble metal particles from the salt. This can potentially limit strong deposition of particles onto walls (i.e., plating), preventing dangerous decay heat hotspots in the heat exchangers or other primary circuit components. In this paper, we investigate the efficiency of particle removal by helium bubbles in the MSFR using Computational Fluid Dynamics (CFD). Theoretical estimates of equilibrium particle size distributions are used as initial condition, based on previous work. CFD calculations are performed in a simplified MSFR geometry. Bubble expansion, turbulent bubble coalescence and turbulent break-up are accounted for using the poly-disperse Log-normal Method of Moments (LogMoM) model, embedded in the two-fluid framework in OpenFOAM. The CFD analyses presented in this paper, in conjunction with the developed theory of noble metal particle formation, growth and capture, will help in the understanding and optimization of the fuel cycle in the MSFR or any other molten salt reactor design. The precise knowledge of how noble metal particle populations in the salt can be controlled, and how plating of noble metal particles onto primary circuit reactor components can be reduced, contributes to safe molten salt reactor operation.