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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Atomic Force Microscopy to Characterize Antimicrobial Peptide-Induced Defects in Model Supported Lipid Bilayers

Antimicrobial peptides (AMPs) interact with bacterial cell membranes through a variety of mechanisms, causing changes extending from nanopore formation to microscale membrane lysis, eventually leading to cell death. Several AMPs also disrupt mammalian cell membranes, despite their significantly different lipid composition and such collateral hemolytic damage hinders the potential therapeutic applicability of the AMP as an anti-microbial. Elucidating the mechanisms underlying the AMP–membrane interactions is challenging due to the variations in the chemical and structural features of the AMPs, the complex compositional variations of cell membranes and the inadequacy of any single experimental technique to comprehensively probe them. (1) Background: Atomic Force Microscopy (AFM) imaging can be used in combination with other techniques to help understand how AMPs alter the orientation and structural organization of the molecules within cell membranes exposed to AMPs. The structure, size, net charge, hydrophobicity and amphipathicity of the AMPs affect how they interact with cell membranes of differing lipid compositions. (2) Methods: Our study examined two different types of AMPs, a 20-amino acid, neutral, α-helical (amphipathic) peptide, alamethicin, and a 13-amino acid, non-α-helical cationic peptide, indolicidin (which intramolecularly folds, creating a hydrophobic core), for their interactions with supported lipid bilayers (SLBs). Robust SLB model membranes on quartz supports, incorporating predominantly anionic lipids representative of bacterial cells, are currently not available and remain to be developed. Therefore, the SLBs of zwitterionic egg phosphatidylcholine (PC), which represents the composition of a mammalian cell membrane, was utilized as the model membrane. This also allows for a comparison with the results obtained from the Quartz Crystal Microbalance with Dissipation (QCM-D) experiments conducted for these peptides interacting with the same zwitterionic SLBs. Further, in the case of alamethicin, because of its neutrality, the lipid charge may be less relevant for understanding its membrane interactions. (3) Results: Using AFM imaging and roughness analysis, we found that alamethicin produced large, unstable defects in the membrane at 5 µM concentrations, and completely removed the bilayer at 10 µM. Indolicidin produced smaller holes in the bilayer at 5 and 10 µM, although they were able to fill in over time. The root-mean-square (RMS) roughness values for the images showed that the surface roughness caused by visible defects peaked after peptide injection and gradually decreased over time. (4) Conclusions: AFM is useful for helping to uncover the dynamic interactions between different AMPs and cell membranes, which can facilitate the selection and design of more efficient AMPs for use in therapeutics and antimicrobial applications.

Swana, Kathleen W.↗
DOE OSTI2024

Dosimetric and biological impact of activity extravasation of radiopharmaceuticals in PET imaging

The increasing use of nuclear medicine and PET imaging has intensified scrutiny of radiotracer extravasation. To our knowledge, this topic is understudied but holds great potential for enhancing our understanding of extravasation in clinical PET imaging. This work aims to (1) quantify the absorbed doses from radiotracer extravasation in PET imaging, both locally at the site of extravasation and with the extravasation location as a source of exposure to bodily organs and (2) assess the biological ramifications within the injection site at the cellular level. A radiation dosimetry simulation was performed using a whole-body 4D Extended Cardiac-Torso (XCAT) phantom embedded in the GATE Monte Carlo platform. A 10-mCi dose of 18 F-FDG was chosen to simulate a typical clinical PET scan scenario, with 10% of the activity extravasated in the antecubital fossa of the right arm of the phantom. The extravasation volume was modeled as a 5.5 mL rectangle in the hypodermal layer of skin. Absorbed dose contributions were calculated for the first two half-lives, assuming biological clearance thereafter. Dose calculations were performed as absorbed doses at the organ and skin levels. Energy deposition was simulated both at the local extravasation site and in multiple organs of interest and converted to absorbed doses based on their respective masses. Each simulation was repeated ten times to estimate Monte Carlo uncertainties. Biological impacts on cells within the extravasated volume were evaluated by randomizing cells and exposing them to a uniform radiation source of 18 F and 68 Ga. Particle types, their energies, and direction cosines were recorded in phase space files using a separate Geant4 simulation to characterize their entry into the nucleus of the cellular volume. Subsequently, the phase space files were imported into the TOPAS-nBio simulation to assess the extent of DNA damage, including double-strand breaks (DSBs) and single-strand breaks (SSBs). Organ-level dosimetric estimations are presented for 18 F and 68 Ga radionuclides in various organs of interest. With 10% extravasation, the hypodermal layer of the skin received the highest absorbed dose of 1.32 ± 0.01 Gy for 18 F and 0.99 ± 0.01 Gy for 68 Ga. The epidermal and dermal layers received absorbed doses of 0.07 ± 0.01 Gy and 0.13 ± 0.01 Gy for 18 F, and 0.14 ± 0.01 Gy and 0.29 ± 0.01 Gy for 68 Ga, respectively. In the extravasated volume, 18 F caused an average absorbed dose per nucleus of 0.17 ± 0.01 Gy, estimated to result in 10.58 ± 0.50 DSBs and 268.11 ± 12.43 SSBs per nucleus. For 68 Ga, the absorbed dose per nucleus was 0.11 ± 0.01 Gy, leading to an estimated 6.49 ± 0.34 DSBs and 161.24 ± 8.12 SSBs per nucleus. Absorbed doses in other organs were on the order of micro-gray (µGy). The likelihood of epidermal erythema resulting from extravasation during PET imaging is low, as the simulated absorbed doses to the epidermis remain below the thresholds that trigger such effects. Moreover, the organ-level absorbed doses were found to be clinically insignificant across various simulated organs. The minimal DNA damage at the extravasation site suggests that long-term harm, such as radiation-induced carcinogenesis, is highly unlikely.

DNA strand breaks↗
DOE OSTI2020

Imaging Supramolecular Morphogenesis with Confocal Laser Scanning Microscopy at Elevated Temperatures

The morphogenesis of supramolecular assemblies is a highly dynamic process that has only recently been recognized, and our understanding of this phenomenon will require imaging techniques capable of crossing scales. Shape transformations depend both on the complex energy landscapes of supramolecular systems and the kinetically controlled pathways that define their structures and functions. We report here the use of confocal laser scanning microscopy coupled with a custom-designed variable-temperature sample stage that enables in situ observation of such shape changes. The submicrometer resolution of this technique allows for real-time observation of the nanostructures in the native liquid environments in which they transform with thermal energy. We use this technique to study the temperature-dependent morphogenic behavior of peptide amphiphile nanofibers and photocatalytic chromophore amphiphile nanoribbons. Furthermore, the variable-temperature confocal microscopy technique demonstrated in this work can sample a large volume and provides real-time information on thermally induced morphological changes in the solution.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Understanding important features of deep learning models for segmentation of high-resolution transmission electron microscopy images

Cutting edge deep learning techniques allow for image segmentation with great speed and accuracy. However, application to problems in materials science is often difficult since these complex models may have difficultly learning meaningful image features that would enable extension to new datasets. In situ electron microscopy provides a clear platform for utilizing automated image analysis. In this work, we consider the case of studying coarsening dynamics in supported nanoparticles, which is important for understanding, for example, the degradation of industrial catalysts. By systematically studying dataset preparation, neural network architecture, and accuracy evaluation, we describe important considerations in applying deep learning to physical applications, where generalizable and convincing models are required. With a focus on unique challenges that arise in high-resolution images, we propose methods for optimizing performance of image segmentation using convolutional neural networks, critically examining the application of complex deep learning models in favor of motivating intentional process design.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Rapid and flexible segmentation of electron microscopy data using few-shot machine learning

Abstract Automatic segmentation of key microstructural features in atomic-scale electron microscope images is critical to improved understanding of structure–property relationships in many important materials and chemical systems. However, the present paradigm involves time-intensive manual analysis that is inherently biased, error-prone, and unable to accommodate the large volumes of data produced by modern instrumentation. While more automated approaches have been proposed, many are not robust to a high variety of data, and do not generalize well to diverse microstructural features and material systems. Here, we present a flexible, semi-supervised few-shot machine learning approach for segmentation of scanning transmission electron microscopy images of three oxide material systems: (1) epitaxial heterostructures of SrTiO 3 /Ge, (2) La 0.8 Sr 0.2 FeO 3 thin films, and (3) MoO 3 nanoparticles. We demonstrate that the few-shot learning method is more robust against noise, more reconfigurable, and requires less data than conventional image analysis methods. This approach can enable rapid image classification and microstructural feature mapping needed for emerging high-throughput characterization and autonomous microscope platforms.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Understanding Portability of Automotive Workload: A Case Study with the Points-to-Image Kernel in SYCL on Heterogeneous Computing Platforms

SYCL is a promising programming model for heterogenous computing across vendors’ devices. In this paper, we study whether SYCL can be applied to an automotive workload and its portability on heterogeneous computing platforms. We explain the automotive benchmark, describe our implementations and optimizations of the benchmark, and evaluate the performance of the benchmarks using SYCL and other programming models on heterogeneous computing devices. The study also allows us to have a better understanding of portability of the benchmark across these platforms.

Jin, Zheming↗
DOE OSTI2024

The influence of laser energy on deuterium emission characteristics from a Zircaloy-4 plasma

Laser-produced plasma coupled with optical emission spectroscopy (OES) is a promising technique for detecting certain isotopes, with unique capabilities such as standoff and rapid detection and minimal to no sample preparation requirements. The key figure-of-merit for isotopic analysis using optical spectroscopy tools is the linewidth relative to the isotope shift. Although the isotopes of hydrogen (1H, 2H, and 3H) possess large isotopic shifts (1H–2H ≈ 180 pm, 1H–3H ≈ 240 pm), being a light element, the H transitions are susceptible to various broadening mechanisms in the plasma environment. One of the critical parameters that influence the linewidth of a transition in an LPP is the incident laser energy. In the present study, we evaluated the role of laser energy on plume expansion dynamics, deuterium emission intensity, and linewidth in a nanosecond laser-produced Zircaloy-4 plasma. The changes in 2Hα emission intensity and linewidth were investigated for varying laser fluence and time after plasma onset. Spatially resolved and spatially integrated OES were performed and compared to investigate the emission spectral features and linewidth of 2Hα. Monochromatic two-dimensional time-resolved imaging was also performed to understand the morphology of the deuterium and protium emission relative to all species in the plume. Our results showed that 1Hα and 2Hα emissions predominantly occur closer to the target. Measurements of 2Hα linewidth approached similar values at later times of plasma evolution regardless of the laser energy. The linewidths of the 2Hα transition showed insignificant differences between spatially resolved and spatially integrated measurements.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Mapping foliar photosynthetic capacity in sub-tropical and tropical forests with UAS-based imaging spectroscopy: Scaling from leaf to canopy

Accurate understanding of the variability in foliar physiological traits across landscapes is critical to improve parameterization and evaluation of terrestrial biosphere models (TBMs) that seek to represent the response of terrestrial ecosystems to a changing climate. Numerous studies suggest imaging spectroscopy can characterize foliar biochemical and morphological traits at the canopy scale, but there is only limited evidence for retrieving canopy photosynthetic capacity (e.g., maximum carboxylation rate, V c,max and maximum electron transport rate, J max ). Moreover, the effect of canopy structure within forest communities on scaling up spectra-trait relationships from leaf to canopy level is not well known. To advance the spectra-trait approach and enable the estimation of key traits using remote sensing, we collected imaging spectroscopy data from an Unoccupied Aerial System (UAS) platform over two forest sites in China (a subtropical forest in Mt. Dinghu and a tropical rainforest in Xishuangbanna). At these sites, we also collected ground measurements of leaf spectra and traits, including biochemical (leaf nitrogen, phosphorus, chlorophyll, and water content), morphological (leaf mass per area, LMA) and physiological (V c,max25 and J max25 ) traits (n=135 tree-crowns from 42 species across two sites). Using a partial least-squares regression (PLSR) approach, we built and tested spectra-trait models with repeated cross-validation. The spectral models developed with leaf spectra were directly transferred to canopy spectra to evaluate the effect of canopy structure. Here we further applied canopy spectral models to map these traits at individual tree-crown scale. The results demonstrate that (1) UAS-based canopy spectra can be used to estimate V c,max (R 2 =0.55, nRMSE=11.79%), Jmax (R 2 =0.54, nRMSE=12.34%), and five additional foliar traits (R 2 =0.38-0.60, nRMSE=10.11-13.56%) at the tree-crown scale with demonstrated generalizability across two sites; (2) canopy structure strongly affects the spectratrait relationships from leaf to canopy level, but the effects vary considerably across foliar traits and cannot be well captured by the 4SAIL canopy radiative transfer model. UAS-based imaging spectroscopy maps large variability in all foliar traits (including physiological traits) with spatially explicit information, reproducing the field-observed inter- and intra-specific variations. These results demonstrate the capability of using UAS-based imaging spectroscopy for characterizing the variability of foliar physiological traits at individual tree-crown scale over forest landscapes and highlight the similar generalizability but different biophysical mechanisms underlying spectra-trait relationships at leaf and canopy levels.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Atomic-scale secondary electron imaging for heterogeneous catalysis research

Surface characterization at the atomic scale is essential for understanding the catalytic properties of supported metal nanoparticles. Secondary electron (SE) imaging in scanning transmission electron microscopy (STEM) provides three-dimensional surface topographic information, enabling the characterization of the size, morphology, and distribution of supported nanoparticles. Furthermore, real-time observation of catalyst materials in a gaseous environment would enhance the understanding of catalyst dynamics under operational conditions. Ongoing technical developments in SE-STEM and advancements in computational methods are expected to facilitate atomic-scale surface observations and enable more quantitative and statistical analyses. This progress will not only elucidate fundamental mechanisms at the atomic level but also provide comprehensive and universal insights into catalyst performances. Here, this minireview showcases the recent advancements and research findings in surface-sensitive SE imaging in STEM for the characterization of active catalyst materials.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Imaging shapes of atomic nuclei in high-energy nuclear collisions

Atomic nuclei are self-organized, many-body quantum systems bound by strong nuclear forces within femtometre-scale space. These complex systems manifest a variety of shapes, traditionally explored using non-invasive spectroscopic techniques at low energies. However, at these energies, their instantaneous shapes are obscured by long-timescale quantum fluctuations, making direct observation challenging. Here we introduce the collective-flow-assisted nuclear shape-imaging method, which images the nuclear global shape by colliding them at ultrarelativistic speeds and analysing the collective response of outgoing debris. This technique captures a collision-specific snapshot of the spatial matter distribution within the nuclei, which, through the hydrodynamic expansion, imprints patterns on the particle momentum distribution observed in detectors. We benchmark this method in collisions of ground-state uranium-238 nuclei, known for their elongated, axial-symmetric shape. Our findings show a large deformation with a slight deviation from axial symmetry in the nuclear ground state, aligning broadly with previous low-energy experiments. This approach offers a new method for imaging nuclear shapes, enhances our understanding of the initial conditions in high-energy collisions and addresses the important issue of nuclear structure evolution across energy scales.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Imaging biomarkers in neurodegeneration: current and future practices

There is an increasing role for biological markers (biomarkers) in the understanding and diagnosis of neurodegenerative disorders. The application of imaging biomarkers specifically for the in vivo investigation of neurodegenerative disorders has increased substantially over the past decades and continues to provide further benefits both to the diagnosis and understanding of these diseases. This review forms part of a series of articles which stem from the University College London/University of Gothenburg course “Biomarkers in neurodegenerative diseases”. In this review, we focus on neuroimaging, specifically positron emission tomography (PET) and magnetic resonance imaging (MRI), giving an overview of the current established practices clinically and in research as well as new techniques being developed. We will also discuss the use of machine learning (ML) techniques within these fields to provide additional insights to early diagnosis and multimodal analysis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Combining Multicolor FISH with Fluorescence Lifetime Imaging for Chromosomal Identification and Chromosomal Sub Structure Investigation

Understanding the structure of chromatin in chromosomes during normal and diseased state of cells is still one of the key challenges in structural biology. Using DAPI staining alone together with Fluorescence lifetime imaging (FLIM), the environment of chromatin in chromosomes can be explored. Fluorescence lifetime can be used to probe the environment of a fluorophore such as energy transfer, pH and viscosity. Multicolor FISH (M-FISH) is a technique that allows individual chromosome identification, classification as well as assessment of the entire genome. Here we describe a combined approach using DAPI as a DNA environment sensor together with FLIM and M-FISH to understand the nanometer structure of all 46 chromosomes in the nucleus covering the entire human genome at the single cell level. Upon DAPI binding to DNA minor groove followed by fluorescence lifetime measurement and imaging by multiphoton excitation, structural differences in the chromosomes can be studied and observed. This manuscript provides a blow by blow account of the protocol required to perform M-FISH-FLIM of whole chromosomes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Nucleon helicity generalized parton distribution at physical pion mass from lattice QCD

The generalized parton distributions (GPDs) offer a window on three-dimensional imaging of the nucleon, providing understanding of how the fundamental properties of the nucleon, such as its mass and spin, arise from the underlying quark and gluon degrees of freedom. In this work, we present the first lattice calculation of the nucleon isovector helicity GPD at physical pion mass, using an a≈0.09 fm lattice ensemble with 2+1+1 flavors of highly improved staggered quarks generated by MILC Collaboration. We perform the GPD calculation in Breit frame using averaged nucleon boost momentum P z ≈2.2 GeV with nonzero momentum transfers in [0.2,1.0] GeV 2 . Nonperturbative renormalization in RI/MOM scheme is used to obtain the quasi-distribution before matching to the lightcone GPDs. The three-dimensional distribution $\tilde{H}$(x, Q 2 ) is presented, along with the three-dimensional nucleon tomography and impact-parameter-dependent distribution for selected Bjorken x at μ=3 GeV in $\overline{MS}$ scheme.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

How “hot” are hotspots: Statistically localizing the high-activity areas on soil and rhizosphere images

The topic of microbial hotspots in soil requires not only visualizing their spatial distribution and biochemical analyses, but also statistical approaches to identify these hotspots and separate them from the surrounding activities (background). We hypothesized that each hotspot type (e.g. enzyme activities in the rhizosphere, root exudation, localization of herbicide accumulation) is a result of local process driven by biotic and/or abiotic factors, and the process rates in the hotspots are much faster than those in the soil background. We further hypothesized that the background and hotspot activities in soil belong to different statistical distributions. Consequently, hotspot determination should be based on statistical separation of activities significantly higher than the background. We analyzed for the statistical distributions of grey values on three groups of published images: 1) 14 C images of carbon input by roots into the rhizosphere, 2) 14 C glyphosate accumulation in the plant, and 3) zymogram of leucine aminopeptidase activity in rooted soil. The two Gaussian distributions were fit (the first representing the background, the second the hotspots) to the distribution of grey values in the images, the parameters (means and standard deviations, SD) of the fitted distributions were calculated, and the background was removed. Thus, we identified hotspots as areas outside of the Mean+2SD image intensity (corresponding to the upper ~ 2.5% of activity, being over 97.5% of background values) and finally, visualized images of solely hotspot locations. Finally, these results were compared with previously used decisions on hotspot intensity thresholding (i.e. Top-25% and 17 standard thresholding approaches in ImageJ) and discussed the advantages of the Mean+2SD as well as Mean+3SD approaches. These advantages include: i) simple unification of the thresholding approach for several imaging methods with various principles of activity distribution, ii) identification of hotspots with various activity levels, iii) analysis of “time-specific” hotspots in temporal sequences of images. Compared with 17 standard thresholding methods, we concluded that objectively elucidating and separating the hotspots should be based on statistical distribution analysis, e.g. using the Mean+2SD or Mean+3SD approaches. Furthermore, this simple Mean+2SD approach delivered suitable results for three groups of images and so, helps to understand the processes responsible for the highest activities and elucidate hotspots.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Image registration for accurate electrode deformation analysis in operando microscopy of battery materials

Operando imaging techniques have become increasingly valuable in both battery research and manufacturing. However, the reliability of these methods can be compromised by instabilities in the imaging setup and operando cells, particularly when utilizing high-resolution imaging systems. The acquired imaging data often include features arising from both undesirable system vibrations and drift, as well as the scientifically relevant deformations occurring in the battery sample during cell operation. For meaningful analysis, it is crucial to distinguish and separately evaluate these two factors. To address these challenges, we employ a suite of advanced image-processing techniques. These include fast Fourier transform analysis in the frequency domain, power spectrum-based assessments for image quality, as well as rigid and non-rigid image-registration methods. These techniques allow us to identify and exclude blurred images, correct for displacements caused by motor vibrations and sample holder drift and, thus, prevent unwanted image artifacts from affecting subsequent analyses and interpretations. Additionally, we apply optical flow analysis to track the dynamic deformation of battery electrode materials during electrochemical cycling. This enables us to observe and quantify the evolving mechanical responses of the electrodes, offering deeper insights into battery degradation. Together, these methods ensure more accurate image analysis and enhance our understanding of the chemomechanical interplay in battery performance and longevity.

Sun, Tianxiao↗
DOE OSTI2023

Investigating Electric Field and Light Induced Degradation in Perovskite Solar Cells through Nanometer-Scale Potential Imaging

Electric field and light induced degradations in perovskite solar cells were evaluated through nanometer-scale potential imaging across the device by using in-situ Kelvin probe force microscopy (KPFM). We derived the electric field profile from potential profiles at different bias voltages to evaluate the locations and quality of junctions across the device. We found relative changes in electric field peak intensity at the HTL/perovskite and perovskite/ETL interfaces upon stressing devices separately under voltage or light. KPFM results during 12-hour stress/rest cycling under electrical bias show both reversible and irreversible changes in the device's interfacial fields. We also observed change in the electric field profile between control and degraded devices after 100 hours of stress/rest cycling under light. Our results demonstrate how nanometer-scale potential imaging can be used to understand the impacts of external electric fields and light soaking on both irreversible degradation and reversible metastability in perovskite solar cells.

Kelvin probe force microscopy↗
DOE OSTI2021

Interface-Driven Chiral Magnetism in Ultrathin Metallic Ferromagnets: Towards Skyrmion Spintronics

Magnetic skyrmions are localized chiral magnetic textures in the form of nanoscale vortices or bubbles that are topologically protected from being ‘unwound’. Their topological nature gives rise to rich behaviors including ordered lattice formation, emergent electrodynamics and robust current-driven displacement at remarkably low current densities. However, magnetic skyrmions have so far been restricted to just a few materials and observed only at low temperatures, limiting the experimental accessibility and technological application of these unique topological objects. This project aimed to realize magnetic skyrmions at room temperature in a new class of engineered chiral ferromagnets that exploit broken mirror symmetry at interfaces to generate helical magnetic order. Ultrathin magnetic heterostructures were engineered and patterned into laterally-confined nanostructures in which skyrmions were stabilized, manipulated, and detected for the first time under ambient conditions. Static and dynamic properties were examined using advanced x-ray imaging to provide a fundamental understanding of topological magnetic phases. The interactions between magnetic skyrmions and electron charge and spin currents were studied to identify fundamental new physics and enable device applications. These experimental studies, supported by detailed modeling, will help launch a new subfield of skyrmion-based spintronics in which individual skyrmions can be used to encode, store, and transport information in high-performance, low power memory and logic devices.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Ion irradiation effects on Cr-coated zircaloy-4 surface wettability and pool boiling critical heat flux.

The concept of coating the currently used nuclear fuel cladding (zirconium-based alloy, typically Zircaloy-4 or Zirc-4) with an oxidation preventive layer is a progressing Accident tolerant Fuel (ATF) candidate alloys. The coated Zirc-4-based alloys could be a solution to suppress undesirable fast reaction kinetics with high-temperature steam. Zirc-4 has been the most preferred cladding material in pressurized water reactors (PWRs). Chromium (Cr) based alloys as a coating material provides excellent corrosion protection and good strength and wear resistance. In this paper, we present the surface wettability measurements and pool boiling Critical Heat Flux (CHF) for Cr-coated Zirc-4 claddings pre- and post-exposure to an ion irradiation environment. The wettability measurements, including static contact angle (contact angle, θ) and average surface roughness (surface roughness, Ra), are introduced for samples of different coating thicknesses (5–30 μm thick). The coatings fabricated by the cold spray of Cr-Al particles to 10 mm × 10 mm × 1.95 mm Zirc-4 substrates. Post fabrication, a Pilgering (cold rolling) process, was applied to finalize the coating thickness and resulted in a significant reduction in surface roughness of initially fabricated rough surfaces. The process produced three distinguished samples 5-μm unpolished (as machined), 5-μm, and 30-μm polished (cold rolled). The measurements are presented for the three surfaces and bare Zirc-4 as a baseline surface. The contact angle analyses were implemented in theoretical models from the literature to predict pool boiling CHF. Pool boiling experiments were conducted to measure the pool boiling CHF values and compare them to the predicted values. Scanning Electron Microscope (SEM) images and Energy Dispersive X-ray Spectroscopy (EDS) analysis was performed to characterize the surfaces for better understanding and interpreting the results. The SEM images showed localized surface damage due to ion irradiation. No recognized change in the measured surface roughness due to ion irradiation. The contact angles of irradiated Cr-coated surfaces are consistently higher (10°) than pre-irradiated surfaces. Decreasing the Cr-coating layer thickness resulted in lower contact angle pre- and post- ion irradiation. The predicted pool boiling CHF using the Kandlikar model is in good agreement with the experimentally measured CHF values within ±12% for all samples.

36 MATERIALS SCIENCE↗