skip to main content


The NSF Public Access Repository (NSF-PAR) system and access will be unavailable from 5:00 PM ET until 11:00 PM ET on Friday, June 21 due to maintenance. We apologize for the inconvenience.

Title: Spray Pyrolysis‐Aerosol Deposition for the Production of Thick Yttria‐Stabilized Zirconia Coatings
  more » « less
Award ID(s):
Author(s) / Creator(s):
 ;  ;  ;  ;  
Publisher / Repository:
Wiley Blackwell (John Wiley & Sons)
Date Published:
Journal Name:
Advanced Engineering Materials
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Abstract

    Aerosol deposition with gas phase‐synthesized chain‐like nanoaggregates can yield dense coatings from the impaction of particles on a substrate; however, dense coating formation is not well understood. Here, we study coating consolidation at the single nanoaggregate level. Flame spray pyrolysis‐made tin oxide nanoaggregates are mobility (size) filtered, accelerated through a de Laval nozzle, and impacted on alumina substrates. TEM images obtained from low velocity collection and supersonic deposition are compared via quantitative image analysis, which reveals that upon supersonic impact nanoaggregates fragment into smaller aggregates. This suggests that fragmentation is a key step in producing coatings denser than the depositing nanoaggregates themselves. We supplement experiments with detailed particle trajectory calculations, which show that the impact energies per atom during nanoaggregate deposition are below 0.2 eV/molecule. These results suggest that fragmentation can only occur at locations where nanoaggregates bonded by van der Waals and capillary interactions.

    more » « less
    more » « less
  3. Abstract

    We propose a novel framework that combines state-of-the-art deep learning approaches with pre- and post-processing algorithms for particle detection in complex/heterogeneous backgrounds common in the manufacturing domain. Traditional methods, like size analyzers and those based on dilution, image processing, or deep learning, typically excel with homogeneous backgrounds. Yet, they often fall short in accurately detecting particles against the intricate and varied backgrounds characteristic of heterogeneous particle–substrate (HPS) interfaces in manufacturing. To address this, we've developed a flexible framework designed to detect particles in diverse environments and input types. Our modular framework hinges on model selection and AI-guided particle detection as its core, with preprocessing and postprocessing as integral components, creating a four-step process. This system is versatile, allowing for various preprocessing, AI model selections, and post-processing strategies. We demonstrate this with an entrainment-based particle delivery method, transferring various particles onto substrates that mimic the HPS interface. By altering particle and substrate properties (e.g., material type, size, roughness, shape) and process parameters (e.g., capillary number) during particle entrainment, we capture images under different ambient lighting conditions, introducing a range of HPS background complexities. In the preprocessing phase, we apply image enhancement and sharpening techniques to improve detection accuracy. Specifically, image enhancement adjusts the dynamic range and histogram, while sharpening increases contrast by combining the high pass filter output with the base image. We introduce an image classifier model (based on the type of heterogeneity), employing Transfer Learning with MobileNet as a Model Selector, to identify the most appropriate AI model (i.e., YOLO model) for analyzing each specific image, thereby enhancing detection accuracy across particle–substrate variations. Following image classification based on heterogeneity, the relevant YOLO model is employed for particle identification, with a distinct YOLO model generated for each heterogeneity type, improving overall classification performance. In the post-processing phase, domain knowledge is used to minimize false positives. Our analysis indicates that the AI-guided framework maintains consistent precision and recall across various HPS conditions, with the harmonic mean of these metrics comparable to those of individual AI model outcomes. This tool shows potential for advancing in-situ process monitoring across multiple manufacturing operations, including high-density powder-based 3D printing, powder metallurgy, extreme environment coatings, particle categorization, and semiconductor manufacturing.

    more » « less
  4. Conformal coating of nanopores with functional polymer nanolayers is the key to many emerging technologies such as miniature sensors and membranes for advanced molecular separations. While the polymer coatings are often used to introduce functional moieties, their controlled growth under nanoconfinement could serve as a new approach to manipulate the size and shape of coated nanopores, hence, enabling novel functions like molecular separation. However, precise control of coating thickness in the longitudinal direction of a nanopore is limited by the lack of a characterization method to profile coating thickness within the nanoconfined space. Here, we report an experimental approach that combines ion milling (IM) and high-resolution field emission scanning electron microscopy (FESEM) for acquiring an accurate depth profile of ultrathin (∼20 nm or less) coatings synthesized inside nanopores via initiated chemical vapor deposition (iCVD). The enhanced capability of this approach stems from the excellent x–y resolution achieved by FESEM (i.e., 4.9 nm/pixel), robust depth ( z) control enabled by IM (step size as small as 100 nm with R2 = 0.992), and the statistical power afforded by high-throughput sampling (i.e., ∼2000 individual pores). With that capability, we were able to determine with unparalleled accuracy and precision the depth profile of coating thickness and iCVD kinetics along 110-nm-diameter nanopores. That allowed us to uncover an unexpected coating depth profile featuring a maximum rate of polymerization at ∼250 nm underneath the top surface, i.e., down the pores, which we termed “necking.” The necking phenomenon deviates considerably from the conventionally assumed monotonous decrease in thickness along the longitudinal direction into a nanopore, as predicted by the diffusion-limited kinetics model of free radical polymerization. An initiator-centric collision model was then developed, which suggests that under the experimental conditions, the confinement imposed by the nanopores may lead to local amplification of the effective free radical concentration at z ≤ 100 nm and attenuation at z ≥ 500 nm, thus contributing to the observed necking phenomenon. The ion-milling-enabled depth profiling of ultrathin coatings inside nanopores, along with the initiator-mediated coating thickness control in the z-direction, may serve to enhance the performance of size-exclusion filtration membranes and even provide more flexible control of nanopore shape in the z dimension.

    more » « less
  5. Abstract

    Gelatin coatings are effective in increasing the retention of MSCs injected into the heart and minimizing the damage from acute myocardial infarction (AMI), but early studies suffered from low fractions of the MSCs coated with gelatin. Biotinylation of the MSC surface is a critical first step in the gelatin coating process, and in this study, we evaluated the use of biotinylated cholesterol “lipid insertion” anchors as a substitute for the covalent NHS‐biotin anchors to the cell surface. Streptavidin‐eosin molecules, where eosin is our photoinitiator, can then be bound to the cell surface through biotin‐streptavidin affinity. The use of cholesterol anchors increased streptavidin density on the surface of MSCs further driving polymerization and allowing for an increased fraction of MSCs coated with gelatin (83%) when compared to NHS‐biotin (52%). Additionally, the cholesterol anchors increased the uniformity of the coating on the MSC surface and supported greater numbers of coated MSCs even when the streptavidin density was slightly lower than that of an NHS‐biotin anchoring strategy. Critically, this improvement in gelatin coating efficiency did not impact cytokine secretion and other critical MSC functions. Proper selection of the cholesterol anchor and the biotinylation conditions supports cellular function and densities of streptavidin on the MSC surface of up to ~105streptavidin molecules/μm2. In all, these cholesterol anchors offer an effective path towards the formation of conformal coatings on the majority of MSCs to improve the retention of MSCs in the heart following AMI.

    more » « less