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At least 397 records · Page 22

Satellite-based evaluation of AeroCom model bias in biomass burning regions

Global models are widely used to simulate biomass burning aerosol (BBA). Exhaustive evaluations on model representation of aerosol distributions and properties are fundamental to assess health and climate impacts of BBA. Here we conducted a comprehensive comparison of Aerosol Comparisons between Observations and Models (AeroCom) project model simulations with satellite observations. A total of 59 runs by 18 models from three AeroCom Phase-III experiments (i.e., biomass burning emissions, CTRL16, and CTRL19) and 14 satellite products of aerosols were used in the study. Aerosol optical depth (AOD) at 550 nm was investigated during the fire season over three key fire regions reflecting different fire dynamics (i.e., deforestation-dominated Amazon, Southern Hemisphere Africa where savannas are the key source of emissions, and boreal forest burning in boreal North America). The 14 satellite products were first evaluated against AErosol RObotic NETwork (AERONET) observations, with large uncertainties found. But these uncertainties had small impacts on the model evaluation that was dominated by modeling bias. Through a comparison with Polarization and Directionality of the Earth’s Reflectances measurements with the Generalized Retrieval of Aerosol and Surface Properties algorithm (POLDER-GRASP), we found that the modeled AOD values were biased by –93 % to 152 %, with most models showing significant underestimations even for the state-of-the-art aerosol modeling techniques (i.e., CTRL19). By scaling up BBA emissions, the negative biases in modeled AOD were significantly mitigated, although it yielded only negligible improvements in the correlation between models and observations, and the spatial and temporal variations in AOD biases did not change much. For models in CTRL16 and CTRL19, the large diversity in modeled AOD was in almost equal measures caused by diversity in emissions, lifetime, and the mass extinction coefficient (MEC). We found that in the AeroCom ensemble, BBA lifetime correlated significantly with particle deposition (as expected) and in turn correlated strongly with precipitation. Additional analysis based on Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) aerosol profiles suggested that the altitude of the aerosol layer in the current models was generally too low, which also contributed to the bias in modeled lifetime. Modeled MECs exhibited significant correlations with the Ångström exponent (AE, an indicator of particle size). Comparisons with the POLDER-GRASP-observed AE suggested that the models tended to overestimate the AE (underestimated particle size), indicating a possible underestimation of MECs in models. The hygroscopic growth in most models generally agreed with observations and might not explain the overall underestimation of modeled AOD. Our results imply that current global models contain biases in important aerosol processes for BBA (e.g., emissions, removal, and optical properties) that remain to be addressed in future research.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Developing and Testing a Novel Stochastic Ice Microphysics Parameterization for Cloud and Climate Models Using ARM Field Campaign Data (Final Progress Report)

The major goals of this project were: 1) to use field campaign measurements from DOE’s Atmospheric Radiation Measurement (ARM) program to characterize variability of important parameters describing properties of ice particles in the atmosphere; 2) based on this observational analysis, to develop a parameterization scheme for weather and climate models that stochastically varies these parameters, and implement the new scheme into a weather model called the Weather Research and Forecasting model (WRF); 3) to use WRF coupled with the new stochastic scheme to simulate ARM field campaign thunderstorm cases and analyze how accounting for this parameter variability affects the model simulations. This work was performed jointly between the National Center for Atmospheric Research, University of Oklahoma, and University of Utah. To accomplish these goals, we extended an approach previously developed to characterize the variability in the size distribution of ice particles to parameters that are explicitly represented in models (i.e., relationships between ice particle mass and size, and between particle fall velocity and size). Our project was, to our knowledge, the first to apply observationally-constrained estimates of this parameter variability describing mass-size and fall velocity-size in a modeling framework. Our results showed efficacy of the approach, evaluated using ARM observations. Similarly, to our knowledge, work in this project was the first to propose and evaluate in detail a stochastic approach for unresolved turbulent mixing in high-resolution model simulations against detailed, benchmark large eddy simulations and ARM observations. Results showed some promising behavior, particularly with increased mixing and dilution of air in thunderstorm cores with surrounding environmental air, bringing the stochastic simulations closer to the benchmark large eddy simulations; however, results were somewhat degraded using stochastic mixing compared to observations from the AMIE/DYNAMO field campaign. This project also further refined and applied a modeling methodology called “piggybacking” that can robustly separate dynamical and thermodynamic impacts of model changes, and comparison studies of different models based on cases developed from ARM observations. Finally, this project directly supported three graduate students who completed their PhDs as well as a postdoctoral research fellow.

54 ENVIRONMENTAL SCIENCES↗

Kinetic model describing self-limiting CO 2 diffusion in supported amine adsorbents

A reaction–diffusion shrinking core model describing the decay in diffusivity of supported amine sorbents upon CO 2 sorption under both simulated direct air capture and point source capture conditions is described. The decay in CO 2 diffusivity is associated with crosslinking in the aminopolymer samples and general pore blockage in the amino-silane derived samples, which occurs as CO 2 is adsorbed. The model is used to extract four kinetic parameters that govern the CO 2 uptake kinetics and working capacity: an apparent reaction rate constant, an initial effective diffusivity, and two dimensionless decay parameters. Ideally, an initially reaction limited system would allow for direct determination of the intrinsic reaction rate constant; however, sorption experiments suggest mass transfer resistances related to gas mixing, external boundary layers and intraparticle diffusion are present. Reaction rate constants are determined and agree well with theoretical values predicted with the Eyring equation parameterized using density functional theory energies from literature sources. The kinetic performance is expressed as the average effective diffusivity as a function of average conversion, which can be correlated to the dispersion of sorption sites on the support and the morphology of the active sorbent phase. Four supports are impregnated or grafted with amines, SBA-15, single-walled zeolite nanotubes (ZNT), Syloid SiO 2 , and γ-Al 2 O 3 . Due to its pore structure, γ-Al 2 O 3 supported amines can be modeled at the μm scale or at the nm scale, where the shell balance is on the μm-sized macroporous particle aggregate or on the nm-sized amine film on the surface of the Al 2 O 3 nanoparticles, which comprise the spherical particle aggregates. Faster diffusion rates are maintained under 400 ppm rather than 10% CO 2 due to a slower reaction rate giving a slower decay in diffusivity. In conclusion, this work provides a first principles kinetic analysis of CO 2 sorption where previous models are semi-empirical and use arbitrary kinetic parameters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Composition, Activity, and Stability of IrO x Oxygen Evolution Reaction Electrocatalysts

The oxygen evolution reaction (OER) is integral to several electrochemical energy conversion and storage technologies, including carbon dioxide reduction to value added fuels, nitrogen reduction to ammonia, reversible fuel cells, rechargeable metal−air batteries, and water electrolysis to produce hydrogen. Iridium oxide (IrO x ) is widely recognized as the benchmark OER catalyst for acidic environments. Despite widespread use of IrO x catalysts, most notably in proton-exchange membrane water electrolyzers (PEMWEs), a comprehensive understanding of the physicochemical properties of commercial catalysts and the impact of these properties on both the activity and stability of these catalysts is lacking. Here, we study commercial IrO x catalysts with different physicochemical properties, three nominally considered amorphous and three rutile, to elucidate how structural and compositional variations affect OER activity and stability. Utilizing standardized aqueous electrochemical protocols, time-resolved dissolution quantification using inductively-coupled plasma mass spectrometry, and physicochemical characterization, including multiple synchrotron X-ray techniques, we systematically correlate catalyst properties with OER performance and degradation behavior aided by principal component analysis (PCA). Our results demonstrate the general trend of amorphous IrO x having higher intrinsic activity but limited stability and crystalline rutile IrO 2 having lower activity but enhanced stability against dissolution. The trends within the amorphous and rutile catalyst groups correlate with inherent material properties, including phase composition and structure, crystallinity, particle size, surface area, and surface structure/chemistry. Notably, we identify a rutile catalyst with the largest crystallite/ domain sizes, moderate surface area, a small fraction of hydrous phase, and a favorable pore structure (trimodal distributions of pore sizes ranging from 2−5 nm) that exhibits the best balance between activity and stability among the six catalysts studied here. These findings illustrate a fundamental structure-governed trade-off between activity and stability and highlight the critical role of surface chemistry modification and structure engineering in IrO x catalyst optimization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Sterilization of N95 Respirators via Gamma Radiation: Comparison of Post-sterilization Efficacy

This study evaluated gamma irradiation for sterilization and reuse of two models of N95 respirators after gamma radiation sterilization as a method to increase availability of N95 respirators during a shortage. The Sandia National Laboratories Gamma Irradiation Facility was used to irradiate two different models of N95 filtering facepiece respirators at doses ranging from 0 kGy(tissue) to 50 kGy(tissue). The following tests were used to determine the efficacy of the respirator after irradiation sterilization: Ambient Aerosol Condensation Nuclei Counter Quantitative Fit Test, tensile test, strain cycling, oscillatory dynamic mechanical analysis, microscopic image analysis of fiber layers, and electrostatic field measurements. Both of the respirator models exhibited statistically significant changes after gamma irradiation as shown by the Quantitative Fit Test, electrostatic testing and the aerosol testing. The change in electrostatic charge of the filter was correlated with a reduction in capturing particles near the 200 nm size by approximately 40-50%. Both tested respirators showed statistically significant changes associated with gamma sterilization. However, our results indicate that choices in materials and manufacturing methods to achieve N95 filtration lead to different magnitudes of damage when exposed to gamma radiation at sterilization relevant doses. This damage results in lower filtration performance. While our sample size (2 different types of respirators) was small, we did observe a change in electrostatic properties on a filter layer that coincided with the failure on the Quantitative Fit Test and reduction in aerosol filtering efficiency. Key Words: N95 respirators, respirators, airborne transmission, pandemic prevention, COVID-19, gamma sterilization

COVID-19↗

CST R9120-B 30x60 Media Pretreatment and Digestion Standard Development to Support Tank Closure Cesium Removal 1A (TCCR-1A) Operations

In support of continued operations of Savannah River Remediation’s (SRR) ion exchange process to remove radioactive cesium from Savannah River Site (SRS) dissolved saltcake, referred to as the Tank Closure Cesium Removal 1A process (TCCR-1A; containing the second set of at-tank ion exchange columns), SRNL was tasked with: 1) validating the field protocol planned for pretreating the crystalline silicotitanate (CST) ion exchange media to be used in the columns, 2) preparing CST media for use in in-tank batch contact testing, and 3) developing a digestion standard to verify complete CST dissolution prior to characterization following each in-tank batch contact test. A procedure (SRNL L29 Manual, ITS-0229) was developed previously in support of the TCCR Demonstration (which contained the first set of ion exchange columns) based on evaluations of a different CST production lot with a larger particle size range to document the protocol for pretreating CST utilizing conditions similar to what will be performed in the field.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Dam-Break Flow Measurements of Liquid–Granular Mixtures in a Channelized Reservoir

Dam-break flows of granular materials exhibit a complex non-Newtonian rheology, which is strongly influenced by various factors, such as the characteristics of the granular material, the degree of initial compaction, and saturation level of the granular matrix. Specially adapted nonintrusive techniques are required to investigate these flows in the laboratory. This paper investigated the nonintrusive technique of image analysis. The methodologies used in the measurement of bulk flow parameters, such as flow depth, front velocity, and flow rate, and the extraction of detailed flow characteristics such as velocity profiles, were discussed in the context of a series of granular dam-break flow experiments. These experiments were performed under three types of initial conditions: dry, saturated (water filling the pore space), and submerged (a layer of saturated granular material submerged under water) using four types of granular materials—PET pellets, crushed walnut shells, urea, and sand—with grain sizes ranging from 200 μm to 2.9 mm. High-speed cameras were used to capture the evolution and local properties of the flow, such as velocity fields using particle image velocimetry (PIV). Bulk properties of the flow were obtained by tracking the surface profile of the granular matrix and the water table. The extracted profiles were used to measure the evolution of the volume of the granular matrix and the fluid phase separately upstream and downstream of the gate, which allowed measuring the dilatancy (increase in pore space). The study showed that the image analysis techniques are versatile and can be adapted to measure different flow parameters in a variety of granular flows to better understand and analyze their complex behavior. Finally, the advantages and drawbacks of each image analysis technique were discussed and best-practice recommendations were provided.

42 ENGINEERING↗

Interlaminar improvement of carbon fiber/epoxy composites via fluorine‐containing high‐epoxy‐value sizing agent

Abstract To improve the interfacial bonding effect of carbon fibers (CFs) and epoxy resins, we prepared a fluorine‐containing high‐epoxy‐value sizing agent (named TS) in this article. It is an emulsion with a more uniform particle size distribution and higher stability better than a commercial Takemoto sizing agent. In addition, sulfonic acid groups can improve the hydrophilicity of the TS, and the presence of epoxy groups enhances the wettability between CFs and the matrix. The properties of the sizing agents were examined by Fourier transform infrared spectroscopy, dynamic light scattering, and thermogravimetric analysis. The sized CFs were evaluated by scanning electron microscopy, x‐ray photoelectron spectroscopy, monofilament tensile test, and dynamic contact angle. Afterward, CF/epoxy composites were prepared, and their fracture morphology and interlaminar shear strength (ILSS) were examined. Results indicated that the TS sizing significantly increased the content of activated carbon on the surface of the CFs and improved the bonding effect between the fiber and the matrix. After TS was sized, the ILSS increased from 49.64 to 58.74 MPa, 18.34% higher than unsized CF/epoxy composites, showing the prominent interfacial reinforcement better than commercial Takemoto.

Qiu, Zhijie↗

Spinel high-entropy oxides (FeNiCrMnZnX) 3 O 4 (X = Al, mg) as anode materials for high-performance lithium-ion batteries

To address the high cost, cobalt dependency, and resource constraints typical of conventional high-entropy oxide (HEO) anodes, this study reports the successful synthesis of two Co-free, six-component spinel-type HEOs(FeNiCrMnZnAl) 3 O 4 (HEO-Al) and (FeNiCrMnZnMg) 3 O 4 (HEO-Mg), via a sol-gel method. The distinct effects of Al 3+ and Mg 2+ incorporation on the electrochemical performance and lithium storage kinetics were systematically investigated. XRD, Raman, and TEM characterizations confirm that both materials possess a pure spinel phase, uniform particle size, and homogeneous elemental distribution. Notably, electrochemical evaluations reveal that HEO-Al delivers a superior reversible capacity of 480.7 mAh g −1 after 100 cycles at 0.1 A g −1 , and maintains 354.5 mAh g −1 after 1000 long-term cycles at 1 A g −1 , significantly outperforming HEO-Mg. Kinetic analysis indicates that HEO-Al exhibits lower charge transfer resistance, a higher Li + diffusion coefficient, and a pseudocapacitive contribution of up to 82%. Furthermore, these findings demonstrate that Al substitution effectively optimizes the structural stability and lithium storage kinetics of Co-free HEOs, providing a viable strategy for designing low-cost, highly stable HEO anode systems.

Anode materials↗

Source apportionment of soot particles and aqueous-phase processing of black carbon coatings in an urban environment

Abstract. The impacts of soot particles on climate and human health depend on the concentration of black carbon (BC) as well as the thickness and composition of the coating material, i.e., organic and inorganic compounds internally mixed with BC. In this study, the size-resolved chemical composition of BC-containing aerosol was measured using a high-resolution soot particle aerosol mass spectrometer (SP-AMS) during wintertime in Fresno, California, a location influenced by abundant combustion emissions and frequent fog events. Concurrently, particle optical properties were measured to investigate the BC absorption enhancement. Positive matrix factorization (PMF) analysis was performed on the SP-AMS mass spectral measurements to explore the sources of soot particles and the atmospheric processes affecting the properties of BC coatings. The analysis revealed that residential woodburning and traffic are the dominant sources of soot particles. Alongside primary soot particles originating from biomass burning (BBOABC) and vehicles (HOABC) two distinct types of processed BC-containing aerosol were identified: fog-related oxidized organic aerosol (FOOABC) and winter-background OOABC (WOOABC). Both types of OOABC showed evidence of having undergone aqueous processing, albeit with differences. The concentration of FOOABC was substantially elevated during fog events, indicating the formation of aqueous secondary organic aerosol (aqSOA) within fog droplets. On the other hand, WOOABC was present at a relatively consistent concentration throughout the winter and was likely related to the formation of secondary organic aerosol (SOA) in both the gas phase and aerosol liquid water. By comparing the chemical properties and temporal variations in FOOABC and WOOABC, we gain insights into the key aging processes of BC aerosol. It was found that aqueous-phase reactions facilitated by fog droplets had a significant impact on the thickness and chemical composition of BC coatings, thereby affecting the light absorption and hygroscopic properties of soot particles. These findings underscore the important role of chemical reactions occurring within clouds and fogs and influencing the climate forcing of BC aerosol in the atmosphere.

54 ENVIRONMENTAL SCIENCES↗

Developing tools and process controls to manufacture energy-efficient powders for additive manufacturing feedstocks: Computational analysis of metal powder manufacturing via machining

Traditionally, metal powders have been produced through methods such as grinding, atomization, and electrolysis. In contrast to these techniques, Metal Powder Works, Inc. has pioneered a methodology based on metal cutting. This innovative approach utilizes a vibrating cutting tool to machine metal particles, in the form of chips, from a workpiece. This technique allows for control of powder particle size, morphology, and avoids any thermally induced material changes. This collaboration aims to elucidate metal cutting characteristics and assess performance on tough materials like Inconel alloys. Computational models, using FEA and SPH techniques, will be developed initially, focusing on aluminum alloy (Al 7075-T6) for studying mesh sensitivity, cutting forces, and chip morphology.

99 GENERAL AND MISCELLANEOUS↗

Soft matter approach for creating novel protein hydrogels using fractal whey protein assemblies as building blocks

In this study, mesoscopic sized fractal assembly (FA) particles were prepared using whey protein isolate; the coldset gelation properties of FA particles were investigated in-depth. Two types of FA particles (FA -62 and FA -90) with different mean sizes were synthesized through controlled thermal treatment of whey protein solutions at two concentrations (62 g/L and 90 g/L). Particle characteristics e.g. hydrodynamic radius, ζ-potential and surface hydrophobicity were dependent on pH and structure of FA. Transmission electron microscopy (TEM) observation confirmed the fractal morphology and small-angle X-ray scattering (SAXS) analysis suggested an internal fractal structure for the obtained FA particles. Eight cold-set FA protein gels (2 % w/v) were manufactured by controlling two gelling factors at two levels: pH (5.8 and 7.0) and Ca 2+ content (5 mM and 10 mM). Rheological characteristics in the large amplitude oscillatory shear regime revealed that pH 7.0 gels were softer and elastic while pH 5.8 gels were harder and brittle. Rheology Pipkin diagrams demonstrated that the strain softening/stiffening and the shear-thinning/thickening behaviors may be fine-tuned by manipulating the key gelation factors: e.g. FA structure, pH, and Ca 2+ . The entrainment speed-dependent friction coefficient curves showed that at an intermediate velocity regime (6-250 mm s -1 ), FA -90 particles induced hydrogels had superior lubrication effect compared to FA -62 gels. Further, this work demonstrated a food structure design approach regarding tuning texture and lubrication properties of protein gels without changing protein content and protein composition. The optimized protein hydrogels may be used as texturizer for "cleaner label" food formulas and/or as delivery system for carrying micronutrients.

60 APPLIED LIFE SCIENCES↗

Thermal Hysteresis and Ordering Behavior of Magnetic Skyrmion Lattices

The physics of phase transitions in two-dimensional (2D) systems underpins research in diverse fields including statistical mechanics, nanomagnetism, and soft condensed matter. However, many aspects of 2D phase transitions are still not well understood, including the effects of interparticle potential, polydispersity, and particle shape. Magnetic skyrmions are chiral spin-structure quasi-particles that form two-dimensional lattices. Here, in this study, we show, by real-space imaging using in situ cryo-Lorentz transmission electron microscopy coupled with machine learning image analysis, the ordering behavior of Néel skyrmion lattices in van der Waals Fe 3 GeTe 2 . We demonstrate a distinct change in the skyrmion size distribution during field-cooling, which leads to a loss of lattice order and an evolution of the skyrmion liquid phase. Remarkably, the lattice order is restored during field heating and demonstrates a thermal hysteresis. This behavior is explained by the skyrmion energy landscape and demonstrates the potential to control the lattice order in 2D phase transitions.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Arctic Cloud‐Base Ice Precipitation Properties Retrieved Using Bayesian Inference

Abstract Cloud‐climate feedbacks are still the greatest source of uncertainty in current climate projections. Arctic clouds, which are predominantly stratiform and supercooled, often long‐lived, and nearly continuously precipitate ice particles, contribute roughly 10% of the uncertainty attributed to the global cloud feedback. This Arctic cloud uncertainty is driven by incomplete observational and theoretical knowledge required to estimate and explain the state and active processes occurring in those clouds. A focus on ice precipitation properties at Arctic cloud base rather than the surface deconfounds the product of cloud condensate sink processes from the influence of the atmospheric thermodynamic state below cloud base, rendering cloud‐base properties a more appealing target for inference and evaluation of model simulations. Here I describe an inverse model for the estimation of cloud base ice precipitation properties over Utqiagvik, North Slope of Alaska, using the synthesis of ground‐based radar and lidar measurements. By leveraging a Markov Chain Monte Carlo algorithm as the core of the inverse model, a wide range of particle size distributions are sampled, and different combinations of ice habit models are examined, both of which are typically fixed in other retrieval methods. Results show intriguing links between different cloud base thermodynamic and ice precipitation properties. Apparent ice number concentration enhancements at temperatures of −5 and −15°C suggest possible secondary ice production (SIP). The analysis alludes to an overestimation of SIP occurrence and intensity, especially in studies relying only on radar or lidar measurements. Finally, reflectivity‐dependent ice precipitation rate and ice water content parameterizations are presented.

54 ENVIRONMENTAL SCIENCES↗

Measurements of $\pi ^\pm $, $K^\pm $, p and $\bar{p}$ spectra in $^{40}\hbox {Ar+}^{45}\hbox {Sc}$ collisions at 13A to 150A $\text{ Ge }\hspace{-1.00006pt}\text{ V }\!/\!c$

The NA61/SHINE experiment at the CERN Super Proton Synchrotron studies the onset of deconfinement in strongly interacting matter through a beam energy scan of particle production in collisions of nuclei of varied sizes. This paper presents results on inclusive double-differential spectra, transverse momentum and rapidity distributions and mean multiplicities of $\pi ^\pm $, $K^\pm $, p and $\bar{p}$ produced in $^{40}\hbox {Ar+}^{45}\hbox {Sc}$ collisions at beam momenta of 13A, 19A, 30A, 40A, 75A and 150A $\text{ Ge }\hspace{-1.00006pt}\text{ V }\!/\!c$. The analysis uses the 10% most central collisions, where the observed forward energy defines centrality. The energy dependence of the $K^\pm $/$\pi ^\pm $ ratios as well as of inverse slope parameters of the $K^\pm $ transverse mass distributions are placed in between those found in inelastic $p+p$ and central Pb + Pb collisions. The results obtained here establish a system-size dependence of hadron production properties that so far cannot be explained either within statistical or dynamical models.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Online Parameter Estimation Methods for Adaptive Cruise Control Systems

Modeling Adaptive Cruise Control (ACC) vehicles enables the understanding of the impact of these vehicles on traffic flow. In this work, two online methods are used to provide real time system identification of ACC enabled vehicles. The first technique is a recursive least squares (RLS) approach, while the second method solves a nonlinear joint state and parameter estimation problem via particle filtering (PF). We provide a parameter identifiability analysis for both methods to analytically show that the model parameters are not identifiable using equilibrium driving. The accuracy and computational runtime of the online methods are compared to a commonly used offline simulation-based optimization (i.e., batch optimization) approach. The methods are tested on synthetic data as well as on empirical data collected directly from a 2019 model year ACC vehicle using data from sensors that are part of the stock ACC system. The online methods are scalable and provide comparable accuracy to the batch method. RLS runs in real time and is two orders of magnitude faster than the batch method for modest sized (e.g., 15 min) datasets. The particle filter also runs in real- time, and is also suitable in streaming applications in which the datasets can grow arbitrarily large.

33 ADVANCED PROPULSION SYSTEMS↗

High-Energy X-ray Tomographic Analysis of Precursor Metal Powders (Ti-6Al-4V) Used for Additive Manufacturing

We utilized high-energy x-ray tomography to characterize Ti-6Al-4V metal powders (both as-received and recycled) used in powder-bed additive manufacturing process. The image processing workflow was developed to process and analyze large amount of data objectively by computer program. The distribution of size and shape of the metal particles as well as defect (mainly porosity) inside the particles was analyzed with the statistical representation and resolution in micrometer. The result revealed that circular-shaped porosity with various sizes could be embedded in the powder particles. These porosities could potentially be transferred to the 3D printed part and critically affect the mechanical performance of the component. The present study shows the effectiveness of characterizing metal powders using x-ray imaging techniques where sufficient number of particles can be sampled within tens of minutes with a minimum sample preparation and high accuracy. Clear structural differences in the as-received and recycled powders were delineated that helps in determining the feasibility of using the recycled powders.

36 MATERIALS SCIENCE↗

Simulations of biomass pyrolysis using glued-sphere CFD-DEM with 3-D intra-particle models

The shape of biomass particles influences intra-particle heat transfer, particle-particle collisions, interphase momentum, heat transfer, and pyrolysis yield. In this research, the effects of these multi-scale phenomena are captured using a glued-sphere computational fluid dynamic discrete element method (CFD-DEM) with 3-D intra-particle models. The glued-spheres resolved the shapes of particles and intra-particle temperature and species distributions. The implementation was validated using the pyrolysis data of a spherical particle and a cylindrical particle. Then, the influences of biomass shapes and sizes on pyrolysis were investigated. The results revealed the significant influence of surface areas and mass distributions on interphase heat transfer and chemical reactions. The intra-particle heat transfer is neglectable for a Biot number smaller than 0.41. Finally, the pyrolysis of irregularly shaped biomass particles in a fixed bed, fluidized bed, and spouted bed was simulated. Analysis of conversion distributions showed the largest deviations in the fixed bed and the slowest conversion rate in the spouted bed. A good balance between uniform and fast conversion is achieved in the fluidized bed. The multi-scale method proposed in this research provides a tool for the evaluation of large irregular-shaped biomass particle pyrolysis in different types of reactors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗