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Wafer-scale waveguide sidewall roughness scattering loss characterization by image processing

Photonic integrated circuits (PICs) are vital for developing affordable, high-performance optoelectronic devices that can be manufactured at an industrial scale, driving innovation and efficiency in various applications. Optical loss of modes in thin film waveguides and devices is a critical measure of their performance. Thin film growth, lithography, masking, and etching processes are imperfect processes that introduce significant sidewall and top-surface roughness and cause dominating optical losses in waveguides and photonic structures. This roughness, as perturbations couple light from guided to far-field radiation modes, leads to scattering losses that can be estimated from theoretical models. Typically, with UV-based lithography, sidewall roughness is significantly larger than wafer-top surface roughness. Atomic force microscopy (AFM) imaging measurement gives a 3D and high-resolution roughness profile, but the measurement is inconvenient, costly, and unscalable for large-scale PICs and at wafer-scale. Here, we evaluate the sidewall roughness profile based on 2D high-resolution scanning electron microscope (SEM) imaging. We characterized the loss on two homemade nitride and oxide films on 3-inch silicon wafers with 12 waveguide devices on each and correlated the scattering loss estimated from a 2D image-based sidewall profile and theoretical Payne model. The lowest loss of guided fundamental transverse electric (TE 0 ) mode is found at 0.075 dB/cm at 633 nm across 24 devices, a record at visible wavelength. Our work shows 100% success (edge continuity span exceeding 95% of image width/height) in edge detection in image processing of all images to estimate autocorrelation function and optical mode loss. These demonstrations offer valuable insights into waveguide sidewall roughness and a comparison of experimental and 2D SEM image processing based loss estimations with applications in loss characterization at wafer-scale PICs.

Khurana, Mohit (ORCID:0000000207898672)↗

Recession of FEP specimens from trays D11 and B7

We report work done at Boeing Defense and Space Group on analysis of silvered teflon specimens taken from selected locations of the Long Duration Exposure Facility under support from a contract provided by NASA LaRC. The samples discussed in this presentation were taken from the unexposed side of D11 and extended through the folded area of this blanket into the exposed area. Two similar areas were cut from blanket B7, one from the edge of the blanket near row six and one from the edge of the blanket near row eight and within a few centimeters of the copper grounding strap for B7. The specimens were each divided into three sections by cutting with a scapel. Two of the sections were mounted in a potting compound, which was cut and polished such that the cross-sectional thickness of each was exposed. One piece was mounted straight and the other was mounted in an attempt to configure the specimens such that it was bent with a radius of curvature similar to the on-orbit configuration. The third portion of each specimen was used for SEM images to help define the angle of exposure with respect to the ram at each location on the specimen. Photomicrographs were taken in cross section from the edge of the blanket through the curved transition region into the exposed area of the blanket. The thickness of the Fluorinated Ethylene Propylene (FEP) layer was determined at known distances from the edge of the blanket. SEM images were obtained at known distances to help define the angle with respect to ram and therefore establish the atomic oxygen fluence on each location and correlate this exposure with thickness. Thickness measurements made with a two to three centimeter distance minimized the uncertainty arising from variations in the as-manufactured thickness of each blanket. The nominal angle from ram of the exposed portion of each blanket, and the fact that the unexposed edge portions are approximately at right angles to the exposed portion were also used to help define the angles. Thickness measurements were taken at specified locations. An average thickness for the unexposed portion of the blanket was determined. Changes in thickness were then determined by difference.

Pippin, H. Gary↗

Improving robustness for model discerning synthesis process of uranium oxide with unsupervised domain adaptation

The quantitative characterization of surface structures captured in scanning electron microscopy (SEM) images has proven to be effective for discerning provenance of an unknown nuclear material. Recently, many works have taken advantage of the powerful performance of convolutional neural networks (CNNs) to provide faster and more consistent characterization of surface structures. However, one inherent limitation of CNNs is their degradation in performance when encountering discrepancy between training and test datasets, which limits their use widely. The common discrepancy in an SEM image dataset occurs at low-level image information due to user-bias in selecting acquisition parameters and microscopes from different manufacturers. Therefore, in this study, we present a domain adaptation framework to improve robustness of CNNs against the discrepancy in low-level image information. Furthermore, our proposed approach makes use of only unlabeled test samples to adapt a pretrained model, which is more suitable for nuclear forensics application for which obtaining both training and test datasets simultaneously is a challenge due to data sensitivity. Through extensive experiments, we demonstrate that our proposed approach effectively improves the performance of a model by at least 18% when encountering domain discrepancy, and can be deployed in many CNN architectures.

scanning electron microscopy↗

A Study on Surface Texture and Wettability of Femtosecond Laser Treated Aluminum Alloys

This research aims to study the effects of femtosecond laser treatment on surface texture and wettability properties. The first portion of this research studies 2024-T3 aluminum alloy concerning surface texture (e.g., roughness), wettability, and surface free energy. SEM images help aid the researchers in detecting minuscule changes in surface texture. Profilometry extracts topographical data from the surface. A contact angle goniometer measures contact angle, which follows the sessile drop method. Owens, Wendt, Rabel, and Kaelble's method calculates the surface free energy in conjunction with the contact angle. Femtosecond laser modification produces relatively uniform surface morphology at the macroscale. When looking at the microscale, surface morphology differs depending on the interplay between material melting and self-assembly, where the surface becomes rougher after laser treatment. Contact angle results show that all but the control sample and sample 7 exhibit hydrophobic behavior, i.e., contact angle >90°, with Sample 1 having the most significant angle of 115°. The effects of laser parameters on surface energy is apparent. More work is needed to establish correlations among these three quantities: contact angle, surface energy, and laser parameters. The second portion of this research studies aluminum alloy 6061 as the subject material with the primary goal of creating a superhydrophobic surface. A central composite design creates the laser surface texturing design of experiments. SEM images help aid the researchers in detecting minuscule changes in surface texture. A 3D optical profiler extracts topographical data from the surface. The sessile drop method incorporates a contact angle goniometer to measure the contact angle. The response surface method builds a second-order polynomial model for the contact angle and obtains optimized parameters to maximize the contact angle. This research shows that laser surface texturing can generate a wide range of surface profiles and roughness values with geometric features ranging from hundreds of μm to submicron. All three laser parameters (pulse energy, pulse duration, repetition rate) affect surface roughness and contact angle to some degree. To quantify the relationship between the contact angle, pulse energy, and pulse repetition rate, a response surface model for Al 6061 is identified and used to find the optimal conditions of E=214 μJ, tp=10 ps, and fp=2427 Hz with a predicted maximum contact angle of 161°. A confirmation experiment produces a contact angle of 168°, in good agreement with the predicted value.

Angell, Dakota↗

Predicting U 3 O 8 powder processing conditions: An AI/ML approach analyzing deep learning embeddings of SEM micrographs

High-resolution SEM images of uranium-oxide powders encode micro- and nanoscale clues to their synthesis route and calcination temperature. We trained a ResNet-50 model on 11 commercial-scale U₃O₈ classes, ammonium diuranate (ADU) or uranyl peroxide (H₂O₂) precursors calcined at temperatures ranging from 400 to 750 °C and added a 256-D projection head before the classifier to analyze the learned representation. The best of eight seeds reached 92.4 % accuracy on reserved testing data, but our focus is the structure of the embedding space rather than the accuracy and labels. We quantify class relatedness in the original 256-D space using centroid similarity and distributional distances, and we use Uniform Manifold Approximation Projection (UMAP) for visualization. ‘Unknown’ images from different preparation methods, SEM operators, and from the literature localized near the expected classes under a nearest-centroid analysis without retraining, as well as clustered in similar UMAP space. In conclusion, this embedding-centered workflow complements black-box classification by providing quantitative, similarity-based comparisons of U₃O₈ morphologies and reduces storage space by up to 98 % for image data used in millisecond vector search comparisons.

36 MATERIALS SCIENCE↗

Effect of Coaxial Electrode Geometry on the Electric Field Enhancement Factor for a High Voltage Vacuum Gap

We present an experimental analysis of the change in the electric field enhancement factor with varying gap size and penetration depth (P.D) of cathode into anode for a coaxial vacuum gap, diagnosed using Fowler–Nordheim analysis and optical imaging via scanning electron microscope (SEM) and time integrated Digital single lens reflex camera (DSLR). Data were collected on the Coaxial Gap Breakdown Machine (240 A, 25 kV, 150 ns, 0.1 Hz). Experiments using five different gap sizes at nine different P.Ds are compared over runs comprising 50 shots for each case. The results show a strong link between enhancement factor and gap size, with P.D and surface topology. For large gap sizes, 150, 330, and 700 μm, the average enhancement factor value increases with increasing P.D. For smaller gap sizes, 50 and 100 μm, the average enhancement factor decreases with P.D. SEM imaging before and after plasma formation for each gap size allows for quantifying surface finish, microprotrusion growth, average blast diameter, and an estimation of the surface area breakdowns occupy. Time integrated DSLR imaging analysis of the gap at each shot allows for a determination of the distribution of breakdowns about the circumference of the gap for each case tested. Here, the Fowler–Nordheim analysis allows for a quantitative analysis of the surface roughness of all gap sizes tested. Results show that for large gap sizes, the gap geometry and increasing area of breakdown is the main cause for increasing average enhancement factor. For small gap sizes, the dominant driving factor for small average enhancement factors—that subsequently decrease with P.D—is significant changes in surface topology due to an increased number of breakdowns.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A fine pore-preserved deep neural network for porosity analytics of a high burnup U-10Zr metallic fuel

Abstract U-10 wt.% Zr (U-10Zr) metallic fuel is the leading candidate for next-generation sodium-cooled fast reactors. Porosity is one of the most important factors that impacts the performance of U-10Zr metallic fuel. The pores generated by the fission gas accumulation can lead to changes in thermal conductivity, fuel swelling, Fuel-Cladding Chemical Interaction (FCCI) and Fuel-Cladding Mechanical Interaction (FCMI). Therefore, it is crucial to accurately segment and analyze porosity to understand the U-10Zr fuel system to design future fast reactors. To address the above issues, we introduce a workflow to process and analyze multi-source Scanning Electron Microscope (SEM) image data. Moreover, an encoder-decoder-based, deep fully convolutional network is proposed to segment pores accurately by integrating the residual unit and the densely-connected units. Two SEM 250 × field of view image datasets with different formats are utilized to evaluate the new proposed model’s performance. Sufficient comparison results demonstrate that our method quantitatively outperforms two popular deep fully convolutional networks. Furthermore, we conducted experiments on the third SEM 2500 × field of view image dataset, and the transfer learning results show the potential capability to transfer the knowledge from low-magnification images to high-magnification images. Finally, we use a pre-trained network to predict the pores of SEM images in the whole cross-sectional image and obtain quantitative porosity analysis. Our findings will guide the SEM microscopy data collection efficiently, provide a mechanistic understanding of the U-10Zr fuel system and bridge the gap between advanced characterization to fuel system design.

36 MATERIALS SCIENCE↗

Argon broad ion beam sectioning and high resolution scanning electron microscopy imaging of hydrated alite

Highlights: • The native fibrous outer and dense inner C-S-H structure are preserved by using low energy argon broad ion beam sectioning. • Possible artefacts of the preparation and imaging of hydrated alite are shown and discussed. • An approach for a semi automated pore analysis of the obtained high resolution images is demonstrated. Scanning electron microscopy (SEM) imaging is able to visualize micro- to nano-structures of cement and concrete. A prerequisite is that the sample preparation preserves the native structure of the specimen. In this study, argon broad ion beam (BIB) sectioning is compared to state-of-the-art sample preparation (resin embedding, polishing) for hydrated alite. Additionally, it is investigated if during BIB, sample cooling is beneficial to avoid deterioration of cement hydrates. The aim is to quantitatively measure pore size distributions in hardened alite pastes. Therefore, not only optimized sample preparation but also optimized imaging conditions are investigated. Finally, it is demonstrated that by image analysis pores down to a diameter of 5 nm in hydrated alite pastes can be quantitatively analysed.

36 MATERIALS SCIENCE↗

2019 ARIA Proposal Final Report Public Abstract: What Happens to Life in an Ocean World Plume?

The NASA Cassini mission to Saturn discovered persistent jets of water being ejected into space from a subsurface ocean on the small moon Enceladus and evidence that this ocean is habitable for life. The ice resulting from these plumes forms the E Ring of Saturn. Missions are under study to fly through these plumes and collect and analyze samples to look for evidence of life. To support design and instrument selection for these missions, there is a critical need to understand what happens to microbial life adapted to a liquid environment when suddenly ejected into the vacuum of space. We experimentally determined the structural changes in microbial cells in liquid medium when ejected into vacuum. We first developed a vacuum chamber fitted with a feedthrough and nozzle allowing fluid to be injected into vacuum. The nozzle dispersed the fluid into micron-sized droplets. Fluid containing a population of E. Coli microbes was injected into the chamber and droplets were collected on microscope slides and small cups for imaging with a Scanning Electron Microscope (SEM). Epifluorescence microscopy, using a lipid stain, and SEM imaging were used to evaluate the cellular integrity of E. coli after injection through the pressurized nozzle into vacuum. The experimental samples showed a 94% decrease in visible intact E. coli cells as compared with control samples but showed a fluorescent residue in the shape of the sublimated droplets that indicated the presence of lipids. E. coli was selected for testing although other cell types could vary physiologically which could affect their response to a vacuum environment. More testing is needed to determine whether other types of microbial cells can survive the plume environment. However, these results suggest that lipids may be directly detectable evidence of life in icy world plumes, but organisms are unlikely to survive due to disruption of their cell walls.

C. R. Stoker↗

2D-to-3D image translation of complex nanoporous volumes using generative networks

Image-based characterization offers a powerful approach to studying geological porous media at the nanoscale and images are critical to understanding reactive transport mechanisms in reservoirs relevant to energy and sustainability technologies such as carbon sequestration, subsurface hydrogen storage, and natural gas recovery. Nanoimaging presents a trade off, however, between higher-contrast sample-destructive and lower-contrast sample-preserving imaging modalities. Furthermore, high-contrast imaging modalities often acquire only 2D images, while 3D volumes are needed to characterize fully a source rock sample. In this work, we present deep learning image translation models to predict high-contrast focused ion beam-scanning electron microscopy (FIB-SEM) image volumes from transmission X-ray microscopy (TXM) images when only 2D paired training data is available. We introduce a regularization method for improving 3D volume generation from 2D-to-2D deep learning image models and apply this approach to translate 3D TXM volumes to FIB-SEM fidelity. We then segment a predicted FIB-SEM volume into a flow simulation domain and calculate the sample apparent permeability using a lattice Boltzmann method (LBM) technique. Results show that our image translation approach produces simulation domains suitable for flow visualization and allows for accurate characterization of petrophysical properties from non-destructive imaging data.

58 GEOSCIENCES↗

Multiscale Characterization of Additive Manufacturing Components with Computed Tomography, 3D X-ray Microscopy, and Deep Learning

Additive manufacturing (AM) facilitates the creation of complex-geometry parts, driving advancements in lightweight aerospace components, high-efficiency engine cooling channels, and customized medical implants. However, ensuring the quality and reliability of AM parts remains challenging due to internal defects, surface irregularities, porosity, and residual trapped powder, which are often inaccessible to traditional inspection methods. Recent developments in X-ray computed tomography (XCT) and 3D X-ray microscopy (XRM), particularly systems equipped with resolution-at-a-distance (RaaD™) capabilities, enable high-resolution, non-destructive evaluation of AM components across multiple scales, from sub-micrometer to macroscopic levels. This paper explores modern XCT and XRM techniques for multiscale characterization of AM parts, focusing on their ability to detect and analyze defects such as porosity, cracks, inclusions, and surface roughness, while offering insights into defect formation mechanisms, material properties, and process-induced variations. The integration of deep learning (DL) frameworks, including Simurgh, DeepRecon, and DeepScout, enhances XCT/XRM workflows by reducing scan times, improving resolution recovery, and enabling accurate defect detection even with limited projection data. These DL-based methods overcome limitations of traditional reconstruction techniques, enabling faster, more reliable characterization of dense materials like Inconel 718 and novel alloys such as AlCe. Applications include process parameter optimization, high-throughput quality control, and multistage AM process evaluation, with DL-enhanced workflows accelerating analysis times from weeks to days. Correlative imaging approaches further validate XCT and XRM data against scanning electron microscopy (SEM) images of physically sectioned samples, confirming the accuracy of DL-based reconstructions and enabling comprehensive defect analysis. While challenges remain in generalizing DL models to diverse materials and imaging conditions, improvements in resolution, noise reduction, and defect detection highlight the transformative potential of these methods. This multiscale and correlative approach enables precise identification and correlation of microstructural features with the overall performance of AM components. By integrating advanced XCT, XRM, and DL techniques, this paper demonstrates a significant leap forward in AM characterization, offering valuable insights into the relationships between processing parameters, microstructure, and part performance, and driving innovations that enhance the quality and reliability of AM products for demanding industrial applications.

Additive manufacturing↗

Compositional and Microstructural Evolution of Olivine During Pulsed Laser Irradiation: Insights Based on a FIB/Field-Emission TEM Study

Introduction: The use of pulsed laser irradiation to simulate the short duration, high-energy conditions characteristic of micrometeorite impacts is now an established approach in experimental space weathering studies. The laser generates both melt and vapor deposits that contain nanophase metallic Fe (npFe(sup 0)) grains with size distributions and optical properties similar to those in natural impact-generated melt and vapor deposits. There remains uncertainty, however, about how well lasers simulate the mechanical work and internal (thermal) energy partitioning that occurs in actual impacts. We are currently engaged in making a direct comparison between the products of laser irradiation and experimental/natural hypervelocity impacts. An initial step reported here is to use analytical TEM is to attain a better understanding of how the microstructure and composition of laser deposits evolve over multiple cycles of pulsed laser irradiation. Experimental Methods: We irradiated pressed-powder pellets of San Carlos olivine (Fo(sub 90)) with up to 99 rastered pulses of a GAM ArF excimer laser. The irradiated surface of the sample were characterized by SEM imaging and areas were selected for FIB cross sectioning for TEM study using an FEI Quanta dual-beam electron/focused ion beam instrument. FIB sections were characterized using a JEOL2500SE analytical field-emission scanning transmission electron microscope (FE-STEM) optimized for quantitative element mapping at less than 10 nm spatial resolutions. Results: In the SEM the 99 pulse pressed pellet sample shows a complex, inhomogeneous, distribution of laser-generated material, largely concentrated in narrow gaps and larger depressions between grains. Local concentrations of npFe0 spherules 0.1 to 1 micrometers in size are visible within these deposits in SEM back-scatter images. Fig. 1 shows bright-field STEM images of a FIB cross-section of a one of these deposits that continuously covers the top and sloping side of an olivine grain. The deposit has 3 microstructurally distinct sub-layers composed of silicate glass with varying modal fractions and size distributions of npFe( sup 0) spherules, along with nanocrystalline silicate material. A relatively thin (50-300 nm) topmost surface layer has a high-concentration of npFe0 spherules 5-20 nm in size. Element mapping shows the layer to be enriched in Fe by a factor of 2.5 relative to the olivine substrate, with Mg and Si depleted by 20% and 10% respectively. This is compositionally complementary to the underlying, middle layer of the deposit that is depleted in Fe, enriched in Mg and has a much lower npFe0 concentration. A third layer of nanocrystalline olivine occurs at the substrate interface. Discussion: The FE-STEM results suggest the topmost layer is a vapor deposit, underlain by a thicker microstructurally complex melt-generated layer. The compositional relations suggest the melt layer was partially vaporized, preferentially losing more volatile elements (e.g., Fe). The vaporized material re-condensed to form the thin, npFe(sup 0)-rich surface deposit during or immediately after the scan cycle. Nanocrystalline olivine that grew within the melt layer as it formed and cooled is similar in volume and microstructure to what we have observed in the impact melt lining of a micrometeorite impact crater in olivine. This suggest the time-temperature relations attained in the laser sample may not be too different from a micrometeorite impact. Our TEM observations, however, do not show evidence for the same level of mechanical dam-age (e.g., fracturing) seen around the natural micrometeorite crater.

Christoffersen, R.↗

INFLUENCE OF SUPPLEMENTARY ARGON GAS SHIELDING ON THE MICROSTRUCTURE AND MECHANICAL BEHAVIOR OF SS316L ADDITIVELY MANUFACTURED BY DIRECTED ENERGY DEPOSITION

The dissolution of atmospheric gases into parts additively manufactured by directed energy deposition (DED) has long been of concern, and stock shielding solutions have usually proven inadequate at fully removing atmospheric gases from weld beads. The objective of this work was to design a new supplementary argon gas shroud for a specific DED printer and evaluate its effect on microstructure and macroscopic properties of SS316L and the potential for printing more reactive metals such as Ti-6Al-4V. This was investigated by printing four SS316L sample blocks, two with and two without the shroud, each printed in two different orientations. These samples were subsequently evaluated with inert gas fusion (IGF), SEM/EDS imaging, and tensile tests. The shroud reduced oxygen content by 0.019-0.031%, and SEM imaging revealed fewer oxide inclusions. A more dramatic reduction of 0.13% oxygen and 0.171% nitrogen was observed by the inert gas fusion of Ti-6Al-4V samples. Overall, the results indicated the shroud was successful at reducing atmospheric gas uptake within the print region and may enable the printing of reactive metal powders in DED systems.

Helvie, Kyle↗

Enabling the Acquisition of Electron Beam-Induced Current (EBIC) Images in Conventional SEM and STEM Instruments

Electron beam-induced current (EBIC) imaging is a well-established scanning electron microscope (SEM) technique used to analyze the behavior of microelectronic devices including solar cells. Recently, the application of EBIC imaging in an aberration-corrected scanning transmission electron microscope (STEM) has been demonstrated and offers great potential for the in situ study of electronic materials, correlating charge transport properties to atomic structural and elemental information. Here, this work presents two ways to implement EBIC imaging in conventional SEM and STEM systems: one relying on the instrument's inherent scanning and imaging electronics and the other involving third-party systems usually available in electron microscopes. The implementation of lock-in EBIC in systems equipped with a fast beam blanker is also described. In addition, this work shows and discusses the different mechanisms at play in EBIC imaging and their dependence on beam energy, sample impedance, and electrical measurement configuration, providing researchers with the basic information needed to apply the technique to their research.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

High-Resolution Thermal Profiling of a High-Power Diode Laser Facet During Aging

Here, we study the facet temperature distribution of a high-power diode laser over its lifetime using a noncontact, high spatial resolution CCD-based thermoreflectance technique. Based on the known correlation between non-radiative defects and heating, thermal maps can provide valuable information regarding the formation and evolution of small point defects that are at or near the facet during aging. In the laser under study in this work we measure the appearance of local hot spots on the facet, including concentrated hot spots that appear just before or just after COD and are correlated with loss of local light emission. The locations of these hot spots do not exhibit morphology changes in high-resolution SEM imaging of the facet, indicating that the related defects are too small to be observable in SEM or are located at some depth under the facet. Prior to COD, we measure a gradual facet temperature increase accompanied by a gradual optical power decrease and gradual facet optical absorption increase, indicating gradual degradation of the laser.

47 OTHER INSTRUMENTATION↗

Characterization of Field-Exposed Photovoltaic Modules Featuring Signs of Contact Degradation

Here, this work investigates several photovoltaic (PV) modules that have shown signs of metal contact corrosion due to field exposure in a hot and humid climate. This includes two multicrystalline silicon aluminum back surface field systems with 10 and 14 years of exposure and one monocrystalline silicon passivated emitter and rear cell system with four years of exposure. A comprehensive, multiscale characterization process is used to evaluate these PV modules in great detail. Current–voltage (I−V), Suns-V OC measurements, electroluminescence imaging, infrared imaging, and ultraviolet fluorescence imaging were performed, and locations of interest were cored and analyzed using cross-sectional scanning electron microscopy (SEM). A rigorous, quantitative analysis procedure for the cross-sectional SEM images is proposed and implemented. Careful characterization does reveal that some of these PV modules do indeed exhibit the same classic signs of acetic-acid-based corrosion of the glass frit that is present at the silver/silicon interface, which have been observed previously in PV modules exposed to damp heat in an environmental chamber.

14 SOLAR ENERGY↗

Investigation of Bipropellant Plume-Induced Contamination Effects on Coverglass Materials

Contamination and degradation of external spacecraft materials by unburned and partially combusted species from bipropellant thruster plumes has long been observed as a key component of the induced space environment. Space shuttle flight experiments and returned flight hardware from the International Space Station (ISS) have both experienced microscopic impact features induced by high-velocity thruster plume droplets. Analytical results have shown that droplet impingement angle relative to a receiving surface plays a key role in the surface damage. Although impacts with normal impingement angles contribute more severely to surface degradation than highly oblique angles, surface effects at higher impingement angles should not be dismissed. Thruster plume-induced materials degradation is a complex phenomenon that depends on a variety of parameters, including but not limited to material type, system temperature and pressure, plume composition, and thruster firing specifications such as number of pulses, pulse duration, and sample distance from the thruster. For space applications, attaining the vacuum pressure and temperature conditions necessary for flight-like plume expansion and exposure conditions is not a trivial task. The German Aerospace Center (Deutsches Zentrum für Luft- und Raumfahrt, DLR) is a facility uniquely capable of simulating such conditions. Test coupons were exposed to bipropellant thruster firings under high vacuum at the DLR facility. Percent area coverage (PAC) and droplet size distributions were evaluated for the uncoated and coated solar array coverglass materials over a range of impingement angles (0̊ to 75̊). A post-test imaging workflow was developed that aimed to quantify changes in sample surface morphology obtained from scanning electron microscopy (SEM) images using the Image Processing and Analysis in Java (ImageJ) tool; an opensource image processing software. The goal was to create a framework through which to evaluate the effect of bipropellant-induced PAC and droplet size distribution on solar array coverglass optical transmission losses. Understanding this relationship is important because optical transmission losses are known to lead to current reduction in solar power generation systems. In addition to the development of surface characterization workflows, valuable lessons learned as they pertain to future investigations and experiments will be discussed. The authors hope that sharing these lessons will facilitate more utilization of DLR’s unique capabilities as well as open the conversation for how best to address experimental characterization of flight-like plume expansion and its impacts on materials surface degradation effects.

Gateway↗

Characterization of Apollo Regolith by X-Ray and Electron Microbeam Techniques: An Analog for Future Sample Return Missions

The Apollo missions collected 382 kg of rock and regolith from the Moon; approximately 1/3 of the sample mass collected was regolith. Lunar regolith consists of well mixed rocks, minerals, and glasses less than 1-centimeter n size. The majority of most surface regolith samples were sieved into less than 1, 1-2, 2-4, and 4-10- millimiter size fractions; a portion of most samples was re-served unsieved. The initial characterization and classification of most Apollo regolith particles was done primarily by binocular microscopy. Optical classification of regolith is difficult because (1) the finest fraction of the regolith coats and obscures the textures of the larger particles, and (b) not all lithologies or minerals are uniquely identifiable optically. In recent years, we have begun to use more modern x-ray beam techniques [1-3], coupled with high resolution 3D optical imaging techniques [4] to characterize Apollo and meteorite samples as part of the curation process. These techniques, particularly in concert with SEM imaging of less than 1-millimeter regolith grain mounts, allow for the rapid characterization of the components within a regolith.

Zeigler, Ryan A.↗