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At least 199 records · Page 11

Collaborative Research: Understanding Nanoparticle-Plasma Interactions in Dusty Non-Thermal Plasmas by Nanoparticle Probes and Online Aerosol Characterization (Final Technical Report)

This report describes results from the University of Minnesota’s contribution to studies performed under the award DE-SC0018202 (principal Investigator: Christopher J. Hogan Jr.. This award is a collaborative research grant with support equally provided to Case Western Reserve University and to the University of Illinois (with principal investigator R. Mohan Sankaran). To date ten peer-reviewed published papers have resulted from the studies performed with University of Minnesota personnel contributing; this report describes the results of these studies as well as several unpublished studies, grouped into seven separate study types. The overarching goal of the carried out studies was to understand nanoparticle behavior and dynamics in non-thermal plasma synthesis reactors, specifically adapting aerosol measurement technology to provide online measurements of particle size, charge, and structure in plasma reactor systems.

42 ENGINEERING↗

FY23 Update: Aerosol Sampling for the Canister Deposition Field Demonstration

This report describes the results of preliminary testing of aerosol monitoring equipment that will be used to continuously monitor the aerosol source term for the multi-year Canister Deposition Field Demonstration (CDFD). These data are required inputs for the development and validation of models for the deposition of dust and potentially corrosive salts on the surface of spent nuclear fuel (SNF) dry storage canisters. Surface salt loads correlate with the extent of corrosion damage on a metal surface, and potentially to the likelihood and timing of initiation of stress corrosion cracks. Aerosols will be monitored at the CDFD site using three instruments. A Dekati ® ELPI+ cascade impactor will be used for real-time monitoring of aerosol particle sizes. It will also collect dust in 14 size bins on impactor targets that can be chemically analyzed to determine the soluble salts present as a function of particle size. However, this instrument can only measure dried aerosols, with a diameter of <10 µm. The second instrument is a Topas laser particle size spectrometer, which provides real-time monitoring of aerosol particle sizes up to ~40 µm in size. It monitors both the ambient (potentially deliquesced) aerosol particle size distributions required for the dust deposition models and the distributions of the equivalent dried particles, allowing correlation with the Dekati ® data. However, it does not discriminate between inert dust particles and salt aerosols, and it does not retain samples of the different particle sizes for later analysis. The third instrument that will monitor aerosols at the CDFD site is a Clean Air Status and Trends Network (CASTNET) tower, which uses a multiple canister system to collect weekly samples for analysis to total suspended aerosol particle compositions and atmospheric gas concentrations. This status report describes work in FY23 to develop the capabilities for using these tools. In two training exercises, the cascade impactor and laser particle sizer were deployed in two different testing environments, one indoor and one outdoor. For the cascade impactor, the tests provided opportunities for the operators to familiarize themselves with impactor substrate preparation, and post-test sample removal and analysis. For the laser particle sizer, the tests were used to evaluate different instrument parameters, to determine the most appropriate settings for capturing transient events. Data and samples were collected for weeks to months for each test, and the results are presented here. In addition to the preliminary testing, contracts were developed with WSP Analytical Labs for sample preparation and analysis of the cascade impactor samples. The impactor tower from outdoor test was delivered to WSP and used to train the staff there in disassembly, sample extraction, sample analysis, and tower reassembly with new target substrates. These are tasks that WSP will be performing routinely for the CDFD project. The CASTNET system cannot be purchased or tested until an actual site has been selected for the CDFD test. Work for this FY has been restricted to preparation of contracts for purchasing the CASTNET tower, and for sample analysis, once the tower is in operation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

U Metal Oxidation with Steam (U)

The Savannah Rive National Laboratory 9SRNL) is evaluating a method to produce uranium oxide (UO 2 ) from uranium metal using steam. The typical methods for making UO 2 yield powders with particle-size ranges of 1 to 50 micron. The goal of the steam oxidation is to produce a depleted uranium (DU) product with a larger particle size that can be used as a surrogate for testing physical and mechanical process techniques to refine uranium and/or plutonium bearing residues. Several studies in the literature indicated that reactions between uranium metal and steam will yield UO 2 as fine powders in the 160 to 500 °C range, but granular materials form above 500°C. Above 880 °C, a hard compact scale forms on the U metal. Furthermore, sintering of UO 2 occurs at about 1300 °C, but it has been stated that the presence of steam enhances the sintering characteristics of UO 2 . Initial studies into the oxidation of DU metal in an atmosphere of argon and steam have been completed. Oxidation of depleted uranium metal in Ar/steam at 600, 710, 700, and 830 °C yielded at UO 2 product with little or no impurity at each temperature. Although not enough sample was available to perform sieve analysis for particle size distribution, SEM images reveal that a significant volume fraction of the products at 710, 770, and 830 °C exceeds 100 microns. The material produced at 600 °C was too fine for programmatic needs. Questions associated with the UO 2 include morphology of product, mechanical strength of the particles, and performance in milling operations. The size of the samples produced in these tests did not allow for quantitative assessment of particle size of mechanical strength. A qualitative assessment of the particles formed at 710, 770, and 830 °C was that the samples produced at 710 and 770 °C were friable, and the sample produced 830 °C had more mechanical strength. Sintering of the samples in Ar/steam at 970 °C appeared to increase the strength of the particles without changing their general particle size characteristics. Due to the small sample sizes, the increase in strength could not be quantified. If the sintering at 970 °C is inadequate, higher sintering temperatures in Ar/steam can be evaluated. Future work will increase scale of the steam oxidation conditions which yield the most-favorable particle-size distributions with sufficient mechanical strength for programming usage. Further consideration will be given to oxidation temperature, steam addition to the reaction vessel, U metal pretreatment, and sintering conditions after oxidation. The UO 2 production could involve a two-step process where particles are formed in steam at lower temperatures (700-850 °C) and then sintered in Ar/steam at elevated temperatures (950-1200 °C). Larger samples (50-100 g each) will provide sufficient UO 2 product for sieve analysis and assessment of mechanical strength relatives to subsequent milling operations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Computational fluid dynamic analysis of a novel particle-to-air fluidized-bed heat exchanger for particle-based thermal energy storage applications

Long-duration energy storage technologies are being targeted to enable cost-effective, decarbonized energy systems. Particle-based thermal energy storage systems are one promising technology by storing excess electricity or heat as sensible thermal energy in inexpensive, solid, inert particles. These systems are only possible if an effective and economical particle-to-working fluid heat exchanger exists. This study predicts the performance of a proposed, direct-contact, particle-to-air, pressurized fluidized-bed heat exchanger using computational fluid dynamics. The common Eulerian-Eulerian framework for modeling fluidized beds is first benchmarked to experimental results at a previously untested operating condition and application. Then, the benchmarked model evaluates the performance of a proposed design for a commercial-scale version of the novel particle-to-air heat exchanger. The results show pressure drop and gas-phase approach temperatures are advantageous compared to other proposed designs for particle-to-air heat exchangers in the literature; approach temperatures were less than 5 °C and gas-phase pressure drop across the fluidized bed was 32 kPa. The model also highlights the importance of gas distributor design and representation in the Eulerian-Eulerian framework to control fluidization behavior. In conclusion, the model built and benchmarked in this study can be leveraged to advance the design and analysis of these heat exchangers critical to the deployment of a promising long-duration energy storage technology.

25 ENERGY STORAGE↗

Quasilinear theory of general electromagnetic fluctuations including discrete particle effects for magnetized plasmas: General analysis

The general quasilinear Fokker–Planck kinetic equation for the gyrophase-averaged plasma particle distribution functions in magnetized plasmas is derived, making no restrictions on the energy of the particles and on the frequency of the electromagnetic fluctuations and avoiding the often made Coulomb approximation of the electromagnetic interactions. Here, the inclusion of discrete particle effects breaks the dichotomy of nonlinear kinetic plasma theory divided into the test particle and the test fluctuation approximation because it provides expression of both the non-collective and collective electromagnetic fluctuation spectra in terms of the plasma particle distribution functions. Within the validity of the quasilinear approach, the resulting full quasilinear transport equation can be regarded as a determining nonlinear equation for the time evolution of the plasma particle distribution functions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Particle balance of deuterium during deuterium shattered pellet injection shutdown in DIII-D

A particle balance analysis was conducted during a deuterium (D 2 ) shattered pellet injection-induced plasma shutdown on the DIII-D tokamak to determine why less than 20% of the pellet material is assimilated into the core plasma by the mid-current quench (CQ). Initially, most of the D 2 is injected as frozen shards and ionized upon entering the vessel. During the thermal quench, ionized particles move to the divertors and subsequently to the center post (CP) walls, where they rapidly recycle and partially accumulate as neutrals without assimilating into the core plasma. In contrast, the particle flux to the outer midplane walls is negligible, despite being accompanied by hot plasma with electron temperatures exceeding 100 eV. During mid-CQ, volume recombination effects, although not large enough to impact overall particle balance, were significant enough to require accounting for accurate interpretation of fast-framing camera D-alpha signals and the estimation of the CP wall particle flux. In addition, toroidal asymmetries, observed in measurements of toroidal electron density perturbations and the phase of magnetohydrodynamic modes, are present throughout the shutdown and can account for a discrepancy in the assimilation rate for up to 50% of the observed D 2 particle inventory. These sources and sinks of particles and fluxes were identified using absolutely calibrated D-alpha brightness and Langmuir probes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Real-time biomass feedstock particle quality detection using image analysis and machine vision

Abstract A common and costly challenge in the nascent biorefinery industry is the consistent handling and conveyance of biomass feedstock materials, which can vary widely in their chemical, physical, and mechanical properties. Solutions to cope with varying feedstock qualities will be required, including advanced process controls to adjust equipment and reject feedstocks that do not meet a quality standard. In this work, we present and evaluate methods to autonomously assess corn stover feedstock quality in real time and provide data to process controls with low-cost camera hardware. We explore the use of neural networks to classify feedstocks based on actual processing behavior and pixel matrix feature parameterization to further assess particle attributes that may explain the variable processing behavior. We used the pretrained ResNet neural network coupled with a gated recurrent unit (GRU) time-series classifier trained on our image data, resulting in binary classification of feedstock anomalies with favorable performance. The textural aspects of the image data were statistically analyzed to determine if the textural features were predictive of operational disruptions. The significant textural features were angular second moment, prominence, mean height of surface profile, mean resultant vector, shade, skewness, variation of the polar facet orientation, and direction of azimuthal facets. Expansion of these models is recommended across a wider variety of labeled feedstock images of different qualities and species to develop a more robust tool that may be deployed using low-cost cameras within biorefineries.

09 BIOMASS FUELS↗

A novel closed-form inversion of the convection–diffusion equation for rapid convection, diffusion, and source profile estimation

To simplify and routinize particle transport analysis in fusion devices, a novel closed form linear inversion of the 1-D convection diffusion equation to estimate diffusion and convection profiles D(r ⃗ ), v(r ⃗ ) and source distribution s(r ⃗ ), of a single species from measured data is derived and demonstrated on synthetic data. Profile estimates of D(r ⃗ ), v(r ⃗ ), s(r ⃗ ) and their uncertainties are given as a matrix expression constructed directly from the incoming density data of the transported species in space and time, as well as physics assumptions such as particle conservation and experimental geometry. The derived matrix expression can be applied to a pumped or non-pumped recycling species, or a non-recycling species that is effectively “pumped” by plasma-facing surfaces.

Hinson, Edward [ORNL] (ORCID:000000019713140X)↗

Microextraction-Single Particle-Inductively Coupled Plasma-Mass Spectrometry for the Direct Analysis of Nanoparticles on Surfaces

A novel employment of single particle-inductively coupled plasma-mass spectrometry (SP-ICP-MS) was developed, where a microextraction (ME) probe is used to sample nanoparticles from a surface and analyze them in a single analytical step. The effects of several parameters on the performance of ME-SP-ICP-MS were investigated, including the flow rate, choice of carrier solution, particle size, and the design of the microextraction probe head itself. The optimized ME-SP-ICP-MS technique was used to compare the extraction efficiency (EE, defined as the ratio of particles measured to particles deposited on the surface) of the commercial probe head to a newly designed SP polyether ether ketone (PEEK) probe head. The SP PEEK probe head was found to have increased EE compared to the commercial probe head (8.5 ± 3% vs 3.9 ± 3%, respectively). Increasing the carrier solution flow rate was found to decrease the total analysis time at the cost of decreasing EE. Extraction efficiencies for ME-SP-ICP-MS were typically 4–10%, which is similar to transport efficiencies (1–10%) for conventional SP-ICP-MS. Lastly, ME-SP-ICP-MS was employed for the analysis of nano- and microparticles. The sizes of gold nanoparticles, 30 ± 3 and 51 ± 1.9 nm (certified sizes), and iron-based microparticles, 1000 ± 50 nm (certified size), were accurately determined to be 32.2 ± 2.5, 50.8 ± 3.4, and 1030 ± 57 nm, respectively, by ME-SP-ICP-MS. Further, this work demonstrates the potential of ME-SP-ICP-MS for the direct analysis of particles on common collection surfaces (GSR tabs, carbon planchettes, etc.) while retaining spatial information on particle distribution across the surface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Effect of an electric field on liquid helium scintillation produced by fast electrons

The dependence on applied electric field (0–40 kV/cm) of the scintillation light produced by fast electrons and α particles stopped in liquid helium in the temperature range of 0.44 K to 3.12 K is reported. For both types of particles, the reduction in the intensity of the scintillation signal due to the applied field exhibits an apparent temperature dependence. Using an approximate solution of the Debye-Smoluchowski equation, we show that the apparent temperature dependence for electrons can be explained by the time required for geminate pairs to recombine relative to the detector signal integration time. This finding indicates that the spatial distribution of secondary electrons with respect to their geminate partners possesses a heavy, non-Gaussian tail at larger separations and has a dependence on the energy of the primary ionization electron. Here, we discuss the potential application of this result to pulse shape analysis for particle detection and discrimination.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Ion-Exchange Modeling of Crystalline Silicotitanate for Cesium Removal - 20283

The Tank Closure Cesium Removal (TCCR) system is a Savannah River Site (SRS) demonstration 'at-tank' process designed to remove {sup 137}Cs from the high-level aqueous tank waste so that the decontaminated solution can be disposed as low-level waste. Cesium is removed by ion exchange (IX) columns using engineered IONSIV{sup TM} R9120-B form of the Crystalline Silicotitanate (CST) media. The TCCR system is deployed at Tanks 10 and Tank 11 in the SRS H Tank Farm. Water is added to the salt-cake in Tank 10 H to dissolve it. The dissolved salt solution waste is pumped out of Tank 10H (feed tank), through filters and IX columns. The decontaminated salt solution is transferred to Tank 11 (receipt tank), and on to Tank 50H for final disposal in the Saltstone Production Facility. The current TCCR can accommodate lead-lag (two-column) or lead-lag-guard (three-column) configurations to optimize media utilization and achieve the target decontamination. To assist the TCCR operations, a parametric study was conducted to evaluate the impact of different parameters (e.g., column configurations (single column, two columns or three columns in series), waste characteristics, operating temperature, process flow rate, CST average particle size) on the IX column performance including CST bed utilization. The initial results indicate that the IX column performance is improved at slower process flow rate, at lower operating temperature, and with smaller CST average particle size. Multi-column configurations are recommended, because the single-column configuration does not utilize CST bed effectively. This paper demonstrates the versatility of the ion exchange modeling to evaluate the effects of CST characteristics and operational parameters on IX column performances. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Machine Learning for Anomaly Detection in Neural Network Security and SRF Cavities

This dissertation explores the development and deployment of machine learning approaches to address critical challenges in anomaly detection across two distinct domains: neural network security in federated learning settings and cavity behavior analysis in particle accelerator operations at Jefferson Lab in Newport News, Virginia. Anomaly detection identifies deviations from expected patterns, safeguarding systems in cybersecurity, industry, and research against malicious activities and failures. This dissertation demonstrates how our machine learning approaches enhance detection accuracy and efficiency in both neural network security and industrial applications. First, we investigate vulnerabilities in deep neural networks deployed in federated learning. Although federated learning preserves user privacy by training models locally, it remains vulnerable to backdoor attacks, in which malicious participants embed hidden triggers that induce targeted misbehavior. We propose a self-supervised contrastive learning framework to detect and mitigate such backdoor attacks. In our experiments, this method achieves higher detection accuracy and lower false positive rates than existing defenses, while operating without access to local model updates or original training data and thus preserving the privacy guarantees of the federated setting. Second, we address the operational reliability of superconducting radio-frequency (SRF) cavities at the Continuous Electron Beam Accelerator Facility (CEBAF). Our research leverages an unsupervised learning approach, combined with Principal Component Analysis (PCA) and k-means clustering, to identify anomalous behaviors in SRF cavities. Our method detects subtle anomalous behavior by analyzing SRF signal data. This knowledge allows for the early detection and resolution of potential faults, significantly improving the efficiency and reliability of operations. Third, we extend these insights to time-series anomaly detection more broadly. We design a contrastive-learning based model tailored to increasingly dynamic environments and academic research. This model improves detection accuracy in settings that require real-time monitoring and predictive maintenance. Our research underscores the broader applicability and impact of advanced machine learning techniques in anomaly detection. By extracting meaningful patterns from complex data, machine learning can significantly enhance security in distributed neural networks and improve the efficiency of particle accelerator operations. This dissertation serves as a stepping stone for future investigations into the vast possibilities of anomaly detection, inspiring further exploration and development of machine learning techniques in this field.

Ferguson, Hal [Old Dominion University]↗

Non-Gaussianities in collider energy flux

The microscopic dynamics of particle collisions is imprinted into the statistical properties of asymptotic energy flux, much like the dynamics of inflation is imprinted into the cosmic microwave background. This energy flux is characterized by correlation functions < E(n → 1 )…E(n → k ) > of energy flow operators E(n → ). There has been significant recent progress in studying energy flux, including the calculation of multi-point correlation functions and their direct measurement inside high-energy jets at the Large Hadron Collider (LHC). In this paper, we build on these advances by defining a notion of “celestial non-gaussianity” as a ratio of the three-point function to a product of two-point functions. We show that this celestial non-gaussianity is under perturbative control within jets at the LHC, allowing us to cleanly access the non-gaussian interactions of quarks and gluons. We find good agreement between perturbative calculations of the non-gaussianity and a charged-particle-based analysis using CMS Open Data, and we observe a strong non-gaussianity peaked in the “flattened triangle” regime. The ability to robustly study three-point correlations is a significant step in advancing our understanding of jet substructure at the LHC. We anticipate that the celestial non-gaussianity, and its generalizations, will play an important role in the development of higher-order parton showers simulations and in the hunt for ever more subtle signals of potential new physics within jets.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

System Configuration Evaluation for Process Settling of Hanford Waste Solid Particles

Direct Feed High-Level Waste (DFHLW) is a potential flowsheet operations approach to initiating high-level waste (HLW) vitrification prior to completion of the Hanford Waste Treatment and Immobilization Plant (WTP) Pretreatment Facility. A settle/decant process has been proposed to concentrate solids prior to delivery to the WTP HLW Facility during DFHLW operations, wherein the solids in a settled layer would be remixed with the supernatant liquid remaining after decanting operations to provide the feed at required solids concentrations. Settling would be used in lieu of purpose-built filtration or other solids separation equipment. Pacific Northwest National Laboratory (PNNL) is providing baseline technical support to the Washington River Protection Solutions (WRPS) Flowsheet Integration group. To support planning for DFHLW, WRPS previously requested that PNNL evaluate the current data set available to predict the time needed for HLW solids to settle and the solids concentration and strength of that settled layer, to identify gaps in the understanding and predictive capability of HLW solids waste settling times, and to provide scoping estimates of the potential settling times. Eight technical gaps were identified for predicting settling times and characteristics of the formed sediment layers. In addition to the data gaps, an overarching observation was made that there is significant variation in behavior of settling rate and settled layer data. The settling time required to concentrate solids via a settle/decant process was determined from the limited data to have a difference of potentially more than a factor of 5,000 in the estimated settling times, varying from 0.2 to 1,060 days for example depending on process vessel depth and final sediment solids concentration. In contrast, successful processes of liquid-forward output streams resulting from in-tank settling and decanting forward liquid have been reported for operations conducted at the Hanford Site. The purpose of this current report is to further support DFHLW planning by evaluating double-shell tank (DST) and alternate vessel equipment and operational configurations to enable optimization of the settle/decant process to concentrate solids. Hanford waste processing behavior specific to liquid feed availability following a slurry transfer in a DST is summarized, including process stream characteristics and process equipment configurations. The performance of DST process equipment configurations is evaluated for possible improvements using computational fluid dynamics (CFD) and simple analytical models. Potential new vessel design(s) specific to enabling effective settle/decant processes, and cursory summary of other separate and inline solids separations processes, are also provided. The CFD results indicated that improvement in outflow solids concentration was promoted by a reduction in the slurry flow rate, angling the distributor nozzles downward, and lifting the transfer pump. The solid-liquid analysis evaluating particle trajectory confirmed that the potential for particle ingestion (in the transfer pump) was decreased with increased radial separation between the inlet and outlet (transfer pump inlet), decreased inlet flow, and decreased liquid density and viscosity for a neutrally buoyant inlet flow. An assessment was also made of the potential for inflow configuration changes to result in the discrete mounding or piling of solids within the tank. Based on the characterization of the settled waste to date, HLW sediments will be unlikely to sustain a substantial angle of repose to facilitate significant variations in the elevation of the settled solids.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Cross-correlation image analysis for real-time single particle tracking

Accurately measuring the translations of objects between images is essential in many fields, including biology, medicine, chemistry, and physics. One important application is tracking one or more particles by measuring their apparent displacements in a series of images. Popular methods, such as the center of mass, often require idealized scenarios to reach the shot noise limit of particle tracking and, therefore, are not generally applicable to multiple image types. More general methods, such as maximum likelihood estimation, reliably approach the shot noise limit, but are too computationally intense for use in real-time applications. These limitations are significant, as real-time, shot-noise-limited particle tracking is of paramount importance for feedback control systems. To fill this gap, we introduce a new cross-correlation-based algorithm that approaches shot-noise-limited displacement detection and a graphics processing unit-based implementation for real-time image analysis of a single particle.

Instruments & Instrumentation↗

Search for resonant production of dark quarks in the dijet final state with the ATLAS detector

This paper presents a search for a new Z' resonance decaying into a pair of dark quarks which hadronise into dark hadrons before promptly decaying back as Standard Model particles. This analysis is based on proton-proton collision data recorded at $\sqrt{s}$ = 13 TeV with the ATLAS detector at the Large Hadron Collider between 2015 and 2018, corresponding to an integrated luminosity of 139 fb –1 . After selecting events containing large-radius jets with high track multiplicity, the invariant mass distribution of the two highest-transverse-momentum jets is scanned to look for an excess above a data-driven estimate of the Standard Model multijet background. No significant excess of events is observed and the results are thus used to set 95% confidence-level upper limits on the production cross-section times branching ratio of the Z' to dark quarks as a function of the Z' mass for various dark-quark scenarios.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

RIMS analysis of isotopically tagged uranium particles with application to Intentional Forensics

Traditional nuclear forensics approaches leverage isotopic measurements for characterizing nuclear forensics signatures in fuel cycle materials. To aid in provenance assessment, isotopically perturbed transition metal taggants can be added to fuel cycle materials. We present a case study for examining natural uranium oxide powder that was tagged with isotopically perturbed Mo before and after irradiation using resonance ionization mass spectrometry. In conclusion, this method accurately and precisely measures taggant and uranium compositions, rapidly enabling the ability to clearly discriminate between tagged particles and other material with application for robust assessment of material provenance.

Forensic Anthropology↗

Polymer coatings on zirconia microspheres via rotating flow fluid dynamics

Conventional tristructural isotropic (TRISO) coatings for nuclear fuels require multi-step and expensive formation processes; any breakage of the coatings may lead to fission species release. Polymer derived ceramic (PDC) coatings can be a suitable alternative to address these issues. In this study, allylhydridopolycarbosilane (SMP-10) coatings were created on yttria stabilized zirconia (YSZ) microspheres using a Rotating Flow Fluid Dynamics (RFFD) coating method. The effects of curing temperature, rotation speed, and coating cycle/time on the coating were analyzed. Surface functionalization of YSZ microspheres with NaOH resulted in good adhesion between the polymer precursor and the YSZ kernel particles. Spectroscopy analysis revealed complete curing of SMP-10 coated YSZ at 160 °C. Rotation speed and coating time significantly affect the coating characteristics. After 3 cycles at lower rotation speed (50 rpm) for 10 min each, the coating obtained was uniform and homogeneous. In comparison, the coating showed almost 10 times less eccentricity at a high rotation speed of 300 rpm. Compared with the coatings prepared at 300 rpm condition, the coatings have higher sphericity and lower eccentricity at 50 rpm. Overall, this study provides a novel and effective route for fabricating and curing SMP-10 precursor coatings on YSZ microspheres.

Ravi, Nivetha [University of Alabama, Birmingham]↗