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At least 91 records · Page 5

Evaluation of Global Simulations of Aerosol Particle and Cloud Condensation Nuclei Number, with Implications for Cloud Droplet Formation

A total of 16 global chemistry transport models and general circulation models have participated in this study; 14 models have been evaluated with regard to their ability to reproduce the near-surface observed number concentration of aerosol particles and cloud condensation nuclei (CCN), as well as derived cloud droplet number concentration (CDNC). Model results for the period 2011-2015 are compared with aerosol measurements (aerosol particle number, CCN and aerosol particle composition in the submicron fraction) from nine surface stations located in Europe and Japan. The evaluation focuses on the ability of models to simulate the average across time state in diverse environments and on the seasonal and short-term variability in the aerosol properties. There is no single model that systematically performs best across all environments represented by the observations. Models tend to underestimate the observed aerosol particle and CCN number concentrations, with average normalized mean bias (NMB) of all models and for all stations, where data are available, of -24% and -35% for particles with dry diameters > 50 and > 120nm, as well as -36% and -34% for CCN at supersaturations of 0.2% and 1.0%, respectively. However, they seem to behave differently for particles activating at very low supersaturations (< 0.1%) than at higher ones. A total of 15 models have been used to produce ensemble annual median distributions of relevant parameters. The model diversity (defined as the ratio of standard deviation to mean) is up to about 3 for simulated N3 (number concentration of particles with dry diameters larger than 3 nm) and up to about 1 for simulated CCN in the extra-polar regions. A global mean reduction of a factor of about 2 is found in the model diversity for CCN at a supersaturation of 0.2% (CCN(0.2)) compared to that for N3, maximizing over regions where new particle formation is important. An additional model has been used to investigate potential causes of model diversity in CCN and bias compared to the observations by performing a perturbed parameter ensemble (PPE) accounting for uncertainties in 26 aerosol-related model input parameters. This PPE suggests that biogenic secondary organic aerosol formation and the hygroscopic properties of the organic material are likely to be the major sources of CCN uncertainty in summer, with dry deposition and cloud processing being dominant in winter. Models capture the relative amplitude of the seasonal variability of the aerosol particle number concentration for all studied particle sizes with available observations (dry diameters larger than 50, 80 and 120nm). The short-term persistence time (on the order of a few days) of CCN concentrations, which is a measure of aerosol dynamic behavior in the models, is underestimated on average by the models by 40% during winter and 20% in summer.

cloud droplets↗

Vertical Aerosol Profiling during SAIL (VAPS) Field Campaign Report

To more fully address the science goals of the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility’s Surface Atmosphere Integrated Field Laboratory (SAIL) campaign, particularly the key science question of “How strongly do aerosols affect the surface energy and water balance by altering clouds, precipitation, and surface albedo, and how do these impacts vary seasonally?”, our campaign added instrumentation to planned tethered balloon system (TBS) flights in May and July of 2022. A key aspect of aerosol-cloud interactions is understanding cloud condensation nuclei (CCN) and ice nucleating particle (INP) populations, and how they vary seasonally and spatially. Because the interactions between aerosols and clouds is the target of this work, vertical distributions are particularly important to evaluate. Measurements of aerosol at ground level, below-cloud, and in-cloud will allow a better understanding of the airmasses that are feeding cloud-active particles into low- and mid-level clouds. Measurements of INP and aerosol populations often differ between the ground and aloft, with relationships that likely depend on regional and seasonal. Because of this, collocated measurements of aerosol, CCN, and INP, across different seasons, are crucial to reducing uncertainties in relationships between ground-level and cloud-base aerosol populations. Our campaign added online measurements of CCN using a compact CCN counter and offline filter collections for measurement of INP populations to the SAIL campaign TBS flights in May and July of 2022. The CCN instrument, the CloudPuck, flew and successfully collected data for a total of eight flights across both campaign periods. The IcePuck flew for most flights during the same period. Both instruments have continued to be used for other campaign requests in the SAIL domain. Analysis of this data was proposed through a concurrent DOE Atmospheric System Research (ASR) project submission, which was not funded in 2022. A similar proposal, which would involve analysis of the samples and data collected from this campaign, has been resubmitted in 2023 but a funding decision has not yet been made. If the proposal is again declined, we will seek other resources to ensure that this data can be analyzed.

54 ENVIRONMENTAL SCIENCES↗

Machine-learning-revealed statistics of the particle-carbon/binder detachment in lithium-ion battery cathodes

The microstructure of a composite electrode determines how individual battery particles are charged and discharged in a lithium-ion battery. It is a frontier challenge to experimentally visualize and, subsequently, to understand the electrochemical consequences of battery particles’ evolving (de)attachment with the conductive matrix. Herein, we tackle this issue with a unique combination of multiscale experimental approaches, machine-learning-assisted statistical analysis, and experiment-informed mathematical modeling. Our results suggest that the degree of particle detachment is positively correlated with the charging rate and that smaller particles exhibit a higher degree of uncertainty in their detachment from the carbon/binder matrix. We further explore the feasibility and limitation of utilizing the reconstructed electron density as a proxy for the state-of-charge. Our findings highlight the importance of precisely quantifying the evolving nature of the battery electrode’s microstructure with statistical confidence, which is a key to maximize the utility of active particles towards higher battery capacity.

25 ENERGY STORAGE↗

Multiscale electro-chemo-mechanical model of high-capacity amorphous silicon anode material in sodium-ion batteries

The growing interest in sodium-ion batteries (SIBs) is fueled by their abundant resources and environmentally friendly nature, with amorphous silicon (a-Si) emerging as a promising anode material for enhancing capacity. However, the key challenge lies in sustaining reversible capacity during cycling. Here, in this work, we developed a multiscale electrochemical model incorporating an a-Si anode to elucidate the performance parameters of SIBs. Additionally, we integrated an electro-chemo-mechanical model at the particle level to capture stress generation, an essential factor in the degradation of high-capacity electrodes. Unlike existing models, our approach accounts for large-deformation chemo-mechanics at the particle scale and includes simulations under varying charge rates to explore multiscale behavior. The results reveal that coupled sodiation significantly prolongs complete cycling times and influences discharge dynamics, indicating that neglecting this coupling leads to an underestimation of actual capacity. Furthermore, we observed pronounced polarization effects at higher charge rates, resulting in heterogeneous stress distributions across the anode. With the identification of critical failure parameters for both active particles and binder materials, offering novel insights for mitigating degradation in high-capacity electrode systems.

Amorphous silicon anode↗

Direct Simulation of Multiple Scattering by Discrete Random Media Illuminated by Gaussian Beams

The conventional orientation-averaging procedure developed in the framework of the superposition T-matrix approach is generalized to include the case of illumination by a Gaussian beam (GB). The resulting computer code is parallelized and used to perform extensive numerically exact calculations of electromagnetic scattering by volumes of discrete random medium consisting of monodisperse spherical particles. The size parameters of the scattering volumes are 40, 50, and 60, while their packing density is fixed at 5%. We demonstrate that all scattering patterns observed in the far-field zone of a random multisphere target and their evolution with decreasing width of the incident GB can be interpreted in terms of idealized theoretical concepts such as forward-scattering interference, coherent backscattering (CB), and diffuse multiple scattering. It is shown that the increasing violation of electromagnetic reciprocity with decreasing GB width suppresses and eventually eradicates all observable manifestations of CB. This result supplements the previous demonstration of the effects of broken reciprocity in the case of magneto-optically active particles subjected to an external magnetic field.

Mackowski, Daniel W.↗

Out-of-equilibrium interactions and collective locomotion of colloidal spheres with squirming of nematoelastic multipoles

Many living and artificial systems show similar emergent behavior and collective motions on different scales, starting from swarms of bacteria to synthetic active particles, herds of mammals, and crowds of people. What all these systems often have in common is that new collective properties like flocking emerge from interactions between individual self-propelled or driven units. Such systems are naturally out-of-equilibrium and propel at the expense of consumed energy. Mimicking nature by making self-propelled or externally driven particles and studying their individual and collective motility may allow for deeper understanding of physical underpinnings behind collective motion of large groups of interacting objects or beings. Here, in this work, using a soft matter system of colloids immersed into a liquid crystal, we show that resulting so-called nematoelastic multipoles can be set into a bidirectional locomotion by external oscillating electric fields. Out-of-equilibrium elastic interactions between such colloidal objects lead to collective flock-like behaviors emerging from time-varying elasticity-mediated interactions between externally driven propelling particles. Repulsive elastic interactions in the equilibrium state can be turned into attractive interactions in the out-of-equilibrium state under applied external electric fields. We probe this behavior at different number densities of colloidal particles and show that particles in dense dispersions collectively select the same direction of a coherent motion due to elastic interactions between near neighbors. In our experimentally implemented design, their motion is highly ordered and without clustering or jamming often present in other colloidal transport systems, which is promising for technological and fundamental-science applications, like nano-cargo transport, out-of-equilibrium assembly, and microrobotics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Programmable chiral states in flocks of active magnetic rollers

Inspired by nature, active matter exemplified by self-organization of motile units into macroscopic structures holds great promise for advanced tunable materials capable of flocking, shape-shifting, and self-healing. Active particles driven by external fields have repeatedly demonstrated potential for complex self-organization and collective behavior, yet how to guide the direction of their collective motion largely remains unexplored. Here, we report a system of microscopic ferromagnetic rollers driven by an alternating magnetic field that demonstrates programmable control of the direction of a self-organized coherent vortical motion (i.e., chirality). Facilitated by a droplet confinement, the rollers get synchronized and display either right- or left-handed spontaneous vortical motion, such that their moving direction determines the vortex chirality. Here, we reveal that one can remotely command a flock of magnetic rollers to switch or maintain its chiral state by modulating a phase shift of the sinusoidal magnetic field powering the active rollers. Building on our findings, we realize a self-assembled remotely controlled micro-pump architecture capable of switching the fluid transport direction on demand. Our studies may stimulate new design strategies for directed transport and flocking robotics at the microscale based on active colloids.

36 MATERIALS SCIENCE↗

Quantifying Negative Effects of Carbon-Binder Networks from Electrochemical Performance of Porous Li-Ion Electrodes

Porous Li-ion electrodes contain active particles, ion transporting electrolyte, and carbon-binder networks. While macrohomogeneous models are often used to predict electrode behavior, accurate predictions remain challenging, owing to the incomplete understanding of the critical role of carbon-binder networks and how they affect the electrochemical response. The present study systematically characterizes these effects in terms of effective properties by utilizing macrohomogeneous models to analyze the measured responses for electrodes with different carbon-binder content, electrode thickness, and porosity but with identical materials. We find that the impact of the carbon-binder network is more severe than previously thought. Even for low carbon-binder content (5 %wt. dry electrode), the presence of the network decreases the reaction area and increases the ion transport resistance, negatively impacting electrode performance. These effects scale with not just porosity or active material volume but also with carbon-binder content. The findings underscore the importance of connecting all effective properties to electrode specifications in a full factorial sense to transform the electrode design paradigm.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Assessment of Thin Plastic Scintillation Detectors for Beta-Particle Measurements at the Advanced Test Reactor Critical Facility

The Fission Wire Measurement System is a custom measurement system designed in the 1960s to measure the beta-particle activity of irradiated uranium-aluminum fission wires. This measurement is conducted to determine the fission rate profile of the Advanced Reactor Test Critical facility. The Advanced Test Reactor Critical facility is an open-pool, low-power test reactor used to qualify experiment configurations and verify core models prior to full-power experiment irradiations in the Advanced Test Reactor. Power distribution measurements in ATR-C use uranium-aluminum wires that are distributed throughout the core to validate simulation and modeling results. These measurements require from 340 to 1500 wires to be irradiated and measured within a 12-hour window. The system consists of 4 measurement channels and one reference channel, each with a 2-pi proportional gas flow detector and the measurement channels each have an automated sample changer. The gas flow detectors are of a custom design for this detector system that use methane gas with a large anode wire compared to modern proportional counters. These detectors, which are nearly 60 years old are irreplaceable. The measurements from these gas detectors are affected by the gas flow rate, atmospheric and line pressure, and are very sensitive to the applied high voltage. Recent improvements have been made to the control and data acquisition system, but the detectors have remained the same. The nature of the measurement of the fission product decay activity is such that the energy spectrum of the signal is changing with time. Thin, 250-um thick, plastic scintillators were commercially obtained as a potential replacement for the gas flow detectors. The original calibration of the uranium-aluminum fission wires was conducted in 1965 using a series of irradiations of gold foils and the wires in a well-characterized thermal neutron field. These measurements provided a time-dependent fission rate conversion factor from the gold foil data to calibrate the fission wires based on the response from the 2-pi proportional gas detectors. Transitioning to the new detectors requires qualification and testing. The sensitivity of the scintillators to changes in the energy spectrum of the fission wires and translation of the calibration factor have been completed. These measurements indicated that the sensitivity of the scintillators over time changes at a different rate than the sensitivity of the gas flow detectors. However, the inverse activity of measurements of both detector types is linear with time. Initial results indicate that the scintillator detectors will be a sufficient replacement for the gas detectors with minor adjustments to the fission rate conversion factor. Replacement of the detectors will improve the fission wire measurements and provide a more stable and reliable measurement system.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

Spectroscopic Evidence Against Nitric Acid Trihydrate in Polar Stratospheric Clouds

Heterogeneous reactions on polar stratospheric clouds (PSC's) play a key role in the photochemical mechanism thought to be responsible for ozone depletion in the Antarctic and Arctic. Reactions of PSC particles activate chlorine to forms that are capable of photochemical ozone destruction, and sequester nitrogen oxides (NOx) that would otherwise deactivate the chlorine. Although the heterogeneous chemistry is now well established, the composition of the clouds themselves is uncertain. It is commonly thought that they are composed of nitric acid trihydrate, although observations have left this question unresolved. Here we reanalyse infrared spectra of type 1 PSCs obtained in Antarctica in September 1987, using recently measured optical constants of the various compounds that might be present in PSCs. We find these PSCs were not composed of nitric acid trihydrate but instead had a more complex compositon, perhaps that of a ternary solution. Because cloud formation is sensitive to their composition, this finding will alter our understanding of the locations and conditions in which PSCs form. In addition, the extent of ozone loss depends on the ability of the PSCs to remove NOx permanently through sedimentation, The sedimentation rates depend on PSC particle size which in turn is controlled by the composition and formation mechanism.

Toon, Owen B.↗

Spectroscopic Evidence Against Nitric Acid Trihydrate in Polar Stratospheric Clouds

Heterogeneous reactions on polar stratospheric clouds (PSC's) play a key role in the photochemical mechanisms thought to be responsible for ozone depletion in the Antarctic and the Arctic. Reactions on PSC particles activate chlorine to forms that are capable of photochemical ozone destruction, and sequester nitrogen oxides (NOx) that would otherwise deactivate the chlorine. Although the heterogeneous chemistry is now well established, the composition of the clouds themselves is uncertain. It is commonly thought that they are composed of nitric acid trihydrate, although observations have left this question unresolved. Here we reanalyse infrared spectra of type I PCS's obtained in Antarctica in September 1987, using recently measured optical constraints of the various compounds that might be present in PSC's. We find that these PSC's were not composed of nitric acid trihydrate but instead had a more complex composition perhaps that of a ternary solution. Because cloud formation is sensitive to their composition, this finding will alter our understanding of the locations and conditions in which PSCs form. In addition, the extent of ozone loss depends on the ability of the PSC's to remove NOx permanently through sedimentation. The sedimentation rates depend on PSC particle size which in turn is controlled by the composition and formation mechanism.

Toon, Owen B.↗

Apparent Increasing Lithium Diffusion Coefficient with Applied Current in Graphite

In this study, we assert that the apparent lithium diffusion coefficient in graphite active particles in the negative electrodes of lithium-ion cells increases appreciably with the intercalation rate. This assertion is based on an electrochemical model analysis of a wide range of electrochemical micro-reference electrode full cell studies on a coated natural graphite and other literature results. Although the mechanism for this increase is a subject of further investigation, the results of our study suggest that the lithium transport in the graphite does not limit the maximum attainable charging rate in typical lithium-ion cells for electric vehicles.

25 ENERGY STORAGE↗

Demonstration of a Particle Impact Monitoring System for Crewed Space Exploration Modules

When micrometeorite or debris impacts occur on a space habitat, crew members need to be quickly informed of the likely extent of damage, and be directed to the impact location for possible repairs. The goal of the Habitat Particle Impact Monitoring System (HIMS) is to develop a fully automated, end-to-end particle impact detection system for crewed space exploration modules, both in space and on the surfaces of Solar System bodies. The HIMS uses multiple thin film piezo-polymer vibration sensors to detect impacts on a surface, and computer processing of the acoustical signals to characterize the impacts. Development and demonstration of the HIMS is proceeding in concert with NASA's Habitat Demonstration Unit (HDU) Project. The HDU Project is designed to develop and test various technologies, configurations, and operational concepts for exploration habitats. This paper describes the HIMS development, initial testing, and HDU integration efforts. Initial tests of the system on the HDU were conducted at NASA?s 2010 Desert Research and Technologies Studies (Desert-RATS). Four sensor locations were assigned near the corners of a rectangular pattern. To study the influence of wall thickness, three sets of four sensors were installed at different layer depths: on the interior of the PEM wall, on the exterior of the same wall, and on the exterior of a layer of foam insulation applied to the exterior wall. Once the system was activated, particle impacts were periodically applied by firing a pneumatic pellet gun at the exterior wall section. Impact signals from the sensors were recognized by a data acquisition system when they occurred, and recorded on a computer for later analysis. Preliminary analysis of the results found that the HIMS system located the point of impact to within 8 cm, provided a measure of the impact energy / damage produced, and was insensitive to other acoustic events. Based on this success, a fully automated version of this system will be completed and demonstrated as part of a crew "Caution/Warning" system at the 2011 Desert-RATS, along with a crew response procedure.

Opiela, J. N.↗

Deep-Learning-Enabled Crack Detection and Analysis in Commercial Lithium-Ion Battery Cathodes

We report in Li-ion batteries, the mechanical degradation initiated by micro cracks is one of the bottlenecks for enhancing the performance. Quantifying the crack formation and evolution in complex composite electrodes can provide important insights into electrochemical behaviors under prolonged and/or aggressive cycling. However, observation and interpretation of the complicated crack patterns in battery electrodes through imaging experiments are often time-consuming, labor intensive, and subjective. Herein, a deep learning-based approach is developed to extract the crack patterns from nanoscale hard X-ray holo-tomography data of a commercial 18650-type battery cathode. Efficient and effective quantification of the damage heterogeneity with automation and statistical significance is demonstrated. The crack characteristics are further associated with the active particles’ packing densities and a potentially viable architectural design is discussed for suppressing the structural degradation in an industry-relevant battery configuration.

25 ENERGY STORAGE↗

On the Impact of Mechanics on Electrochemistry of Lithium-Ion Battery Anodes

Abstract Models exploring electrochemistry-mechanics coupling in liquid electrolyte lithium-ion battery anodes have traditionally incorporated stress impact on thermodynamics, bulk diffusive transport, and fracture, while stress-kinetics coupling is more explored in the context of all solid-state batteries. Here, we showcase the existence of strong link between active particle surface pressure and reaction kinetics affecting performance even in liquid electrolyte systems. Traction-free and immobile particle surface mechanical boundary conditions are used to delineate the varying pressure magnitudes in graphite host during cycling. Both tensile and compressive stresses are generated in traction-free case, while a fixed surface subjects the entire particle to a compression state. Pressure magnitudes are nearly two to three orders of magnitude higher for the latter resulting in significant depression of open circuit potential and improvement of exchange current densities compared to stress-free state. The results demonstrate the need for incorporating stress-kinetics linkage in models and provide a rationale for putting battery electrodes under compression to improve kinetics.

25 ENERGY STORAGE↗

Electrochemical-mechanical coupling failure mechanism of composite cathode in all-solid-state batteries

Composite cathode composed of active particles and solid electrolytes (SEs) can considerably enlarge the particle-SE contact areas and achieve high areal loadings in all-solid-state batteries (ASSBs). However, the challenging interfacial instability and particle damage problems remain unsolved. Herein, we establish a 3D electrochemical-mechanical coupled model to investigate the underlying failure mechanism by considering the governing electrochemical and physics processes. Micro-scale heterogeneous primary particles with random crystallographic orientation and size inside the LiNi 1/3 Co 1/3 Mn 1/3 O 2 (NCM111) secondary particle of the model result in the anisotropic Li diffusion and volume variation within the secondary particle, leading to significant nonuniformity of the Li concentration, and GPa-level stress distributions at primary particle boundaries, and finally causing the particle internal cracks. The particle volume shrinkage under the constraint of stiff Li 7 La 3 Zr 2 O 12 (LLZO) SE triggers the interface debonding (gap>50 nm) with increased interfacial impedance to degrade cell capacity. Higher C-rates result in larger residual stress (~100 MPa)/strain/debonding gap at dis-charging end, more likely to deteriorate the cell performance. Increasing the interfacial strength between the particle and SE can suppress the interface debonding but induces high stress (up to 10 GPa). In conclusion, results reveal the underlying mechanism of the electrochemical-mechanical coupling failure mechanism for composite cathode and provide promising guidance on the further improvement of a more robust composite cathode for ASSBs.

25 ENERGY STORAGE↗

IImprove hydrogen sorption kinetics of MgH2 by doping carbon-encapsulated iron-nickel nanoparticles

Magnesium hydride (MgH2) with excellent hydrogen storage kinetics is important for the wide application of hydrogen energy. Herein, to accelerate the sorption kinetics of MgH2 and lower its dehydrogenation temperature, we design and prepare a carbon film coated dual transition metal alloy, the Fe0.64Ni0.36@C composite with a coreshell structure, and employ it as an additive to synthesize MgH2–Fe0.64Ni0.36@C system by ball-milling and hydriding combustion method. In contrast to pure MgH2, the initial hydrogen release temperature of the MgH2–Fe0.64Ni0.36@C composite lowers to 250°C from 480°C and the composite can absorb 5.18 wt% H2 within 20 min (150°C, 3 MPa H2). More importantly, the apparent activation energy of the dehydrogenation for decomposition of Fe0.64Ni0.36@C-doped MgH2 reduced from 162.8 ± 8.3 kJ/mol to 86.9 ± 4.6 kJ/mol. It is believed that the Fe@C and Mg2Ni/Mg2NiH4 formed on the surface of Mg/MgH2 act as intermediates of electron transfer between Mg2+ and H–, which synergistically enhanced the hydrogen absorption and desorption kinetics properties of the MgH2. Moreover, the MgH2 co-doped with the multiple in-situ formed active particles shows excellent cycling performance, indicative of potential application in practical hydrogen storage in the near future.

Ding, Zhenmin↗

Deep learning-based segmentation of lithium-ion battery microstructures enhanced by artificially generated electrodes

Accurate 3D representations of lithium-ion battery electrodes, in which the active particles, binder and pore phases are distinguished and labeled, can assist in understanding and ultimately improving battery performance. Here, we demonstrate a methodology for using deep-learning tools to achieve reliable segmentations of volumetric images of electrodes on which standard segmentation approaches fail due to insufficient contrast. We implement the 3D U-Net architecture for segmentation, and, to overcome the limitations of training data obtained experimentally through imaging, we show how synthetic learning data, consisting of realistic artificial electrode structures and their tomographic reconstructions, can be generated and used to enhance network performance. We apply our method to segment x-ray tomographic microscopy images of graphite-silicon composite electrodes and show it is accurate across standard metrics. We then apply it to obtain a statistically meaningful analysis of the microstructural evolution of the carbon-black and binder domain during battery operation.

25 ENERGY STORAGE↗