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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Discerning structure sensitivity of Ni-core Pd-shell nanoparticles for enhanced nitrite reduction

Denitrification using Pd-based catalysts converts N-oxyanions into harmless products. However, the metal cost and scarcity are barriers to application. In this work, we synthesize water-suspended, structure-controlled Ni-core/Pd-shell nanoparticles (Ni@Pd NPs) that show Pd-catalyzed nitrite (NO 2 − ) reduction catalysis promoted by Ni. The NPs immobilized on Al 2 O 3 (0.47 wt % Pd and 0.74 wt % Ni) have higher NH 4 + selectivity and higher catalytic activity than wet-impregnated Pd/Al 2 O 3 (1.0 wt % Pd), i.e., 315.4 vs. 132.1 Lg surface Pd −1 min −1 . X-ray photoelectron spectroscopy (XPS) and CO-diffuse reflectance infrared Fourier transform spectroscopy (CO-DRIFTS) analyses show that Ni increases Pd electron density, which is proposed to lower the bond dissociation energy barrier for nitric oxide surface intermediate. Low-coordinated Pd atoms correlate to high activity and low NH 4 + selectivity. Using CatCost software, we estimate Ni@Pd/Al 2 O 3 to have a ∼40% lower manufacturing cost compared to wet-impregnated Pd/Al 2 O 3 . This rationally designed catalyst illustrates how nickel promotes Pd catalysis and how Pd usage can be lowered for denitrification and other hydrogenation reactions.

CO-DRIFTS↗
DOE OSTI2024

Development of a Full-Scale Connected U-Net for Reflectivity Inpainting in Spaceborne Radar Blind Zones

CloudSat’s Cloud Profiling Radar is a valuable tool for remotely monitoring high-latitude snowfall, but its ability to observe hydrometeor activity near the Earth’s surface is limited by a radar blind zone caused by ground clutter contamination. This study presents the development of a deeply supervised U-Net-style convolutional neural network to predict cold season reflectivity profiles within the blind zone at two Arctic locations. The network learns to predict the presence and intensity of near-surface hydrometeors by coupling latent features encoded in blind zone-aloft clouds with additional context from collocated atmospheric state variables (i.e., temperature, specific humidity, and wind speed). Results show that the U-Net predictions outperform traditional linear extrapolation methods, with low mean absolute error, a 38% higher Sørensen–Dice coefficient, and vertical reflectivity distributions 60% closer to observed values. The U-Net is also able to detect the presence of near-surface cloud with a critical success index (CSI) of 72% and cases of shallow cumuliform snowfall and virga with 18% higher CSI values compared to linear methods. An explainability analysis shows that reflectivity information throughout the scene, especially at cloud edges and at the 1.2-km blind zone threshold, along with atmospheric state variables near the tropopause, are the most significant contributors to model skill. This surface-trained generative inpainting technique has the potential to enhance current and future remote sensing precipitation missions by providing a better understanding of the nonlinear relationship between blind zone reflectivity values and the surrounding atmospheric state.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Development and validation of a second-order thermal network model for residential buildings

Heating, Ventilation, and Air Conditioning (HVAC) systems can maintain the space air temperature of residential buildings, either directly by heating/cooling the air, or indirectly via heat transfer to and from the building structure that acts as a thermal mass. Hence, HVAC systems can help achieve load shifting, peak load reduction, and/or energy cost saving, thus enabling grid-interactive HVAC operation. A home thermal model that can accurately reflect the dynamics of the space air and interior wall surface temperatures, is therefore valuable. This paper develops such a model using the standard RC (resistance-capacitance) approach. The model contains a virtual envelope node and an internal space node and is thus second-order. A hybrid parameter identification scheme, made up of the least-squares and optimal search methods, is also developed. The proposed model and scheme were validated using data collected from a test home. It was found that a modest amount of training data was sufficient to yield reliable parameter estimates and accurate prediction. It was also found that when making 24-hour-ahead prediction of the space air temperature, both methods had comparable performances when the training data began in a transition season. However, when they began in an HVAC season, the optimal search method performed better. Furthermore, the least-squares method is recommended during a transition season due to its lower computational burden, while the optimal search method is recommended during an HVAC season due to its better estimation performance.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Integrated Evaporator for Efficient Solar-Driven Interfacial Steam Generation

Solar-driven interfacial steam generation is a promising technique for clean water production as it can minimize thermal loss by localizing solar-to-heat conversion at the air/liquid interface. Here we report an integrated solar-evaporator by partially growing two-dimensional polypyrrole microsheets within a melamine foam through chemical vapor polymerization. These microsheets can induce multiple light reflections within the foam, enable omnidirectional light absorption, provide abundant surfaces to promote heat transfer, and achieve spatially-defined hydrophobicity to facilitate vapor escape. Meanwhile, the inherent hydrophilicity of the bottom part of the foam promotes spontaneous upward water transport and suppresses heat loss. The composite foam exhibits an excellent apparent evaporation rate of ~2 kg/(m 2 ·h) and solar-to-vapor efficiency of ~91%. Here, the combined advantages of large surface area, high efficiency, low cost, all weather application, excellent durability, and scalable manufacturing make our integrated design promising for fabricating large-scale solar steam generation systems that are suitable for practical clean water production.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Cuboidal Liquid Crystal Phases Under Multiaxial Geometrical Frustration.

Cuboidal liquid crystal phases - the so-called blue phases - consist of a network of topological defects arranged into a cubic symmetry. They exhibit striking optical properties, including Bragg reflection in the visible range and fast response times. Confining surfaces can interfere with the packing of such a network, leading to structures that have not been explored before. In this work, a Landau-de Gennes free energy formalism for the tensor alignment field Q is used to investigate the behavior of chiral liquid crystals under non-isotropic confinement. The underlying free energy functional is solved by relying on a Monte Carlo method that facilitates efficient exploration of configuration space. The results of simulations are expressed in terms of phase diagrams as a function of chirality and temperature for three families of spheroids: oblate, spherical, and prolate. Upon deformation, blue phases adapt and transform to accommodate the geometrical constraints, thereby resulting in a wider range of thermal stability. For oblate spheroids, confinement interferes with the development of a full blue phase structure, resulting on a combination of half skyrmions. For prolate spheroids, the blue phases are hybridized and exhibit features of blue phases I and II. More generally, it is shown that mechanical deformation provides an effective means to control, manipulate and stabilize blue phases and cholesterics confined in tactoids.

Palacio-Betancur, Viviana↗
DOE OSTI2021

No ordinary proteins: Adsorption and molecular orientation of monoclonal antibodies

The interaction of monoclonal antibodies (mAbs) with air/water interfaces plays a crucial role in their overall stability in solution. We aim to understand this behavior using pendant bubble measurements to track the dynamic tension reduction and x-ray reflectivity to obtain the electron density profiles (EDPs) at the surface. Native immunoglobulin G mAb is a rigid molecule with a flat, “Y” shape, and simulated EDPs are obtained by rotating a homology construct at the surface. Comparing simulations with experimental EDPs, we obtain surface orientation probability maps showing mAbs transition from flat-on Y-shape configurations to side-on or end-on configurations with increasing concentration. The modeling also shows the presence of β sheets at the surface. Overall, the experiments and the homology modeling elucidate the orientational phase space during different stages of adsorption of mAbs at the air/water interface. These finding will help define new strategies for the manufacture and storage of antibody-based therapeutics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Evaluating seasonal and regional distribution of snowfall in regional climate model simulations in the Arctic

In this study, we investigate how the regional climate model HIRHAM5 reproduces the spatial and temporal distribution of Arctic snowfall when compared to CloudSat satellite observations during the examined period of 2007–2010. For this purpose, both approaches, i.e., the assessments of the surface snowfall rate (observation-to-model) and the radar reflectivity factor profiles (model-to-observation), are carried out considering spatial and temporal sampling differences. The HIRHAM5 model, which is constrained in its synoptic representation by nudging to ERA-Interim, represents the snowfall in the Arctic region well in comparison to CloudSat products. The spatial distribution of the snowfall patterns is similar in both identifying the southeastern coast of Greenland and the North Atlantic corridor as regions gaining more than twice as much snowfall as the Arctic average, defined here for latitudes between 66 and 81°N. Excellent agreement (difference less than 1%) in the Arctic-averaged annual snowfall rate between HIRHAM5 and CloudSat is found, whereas ERA-Interim reanalysis shows an underestimation of 45% and significant deficits in the representation of the snowfall rate distribution. From the spatial analysis, it can be seen that the largest differences in the mean annual snowfall rates are an overestimation near the coastlines of Greenland and other regions with large orographic variations as well as an underestimation in the northern North Atlantic Ocean. To a large extent, the differences can be explained by clutter contamination, blind zone or higher resolution of CloudSat measurements, but clearly HIRHAM5 overestimates the orographic-driven precipitation. The underestimation of HIRHAM5 within the North Atlantic corridor south of Svalbard is likely connected to a poor description of the marine cold air outbreaks which could be identified by separating snowfall into different circulation weather type regimes. By simulating the radar reflectivity factor profiles from HIRHAM5 utilizing the Passive and Active Microwave TRAnsfer (PAMTRA) forward-modeling operator, the contribution of individual hydrometeor types can be assessed. Looking at a latitude band at 72–73°N, snow can be identified as the hydrometeor type dominating radar reflectivity factor values across all seasons. The largest differences between the observed and simulated reflectivity factor values are related to the contribution of cloud ice particles, which is underestimated in the model, most likely due to the small sizes of the particles. The model-to-observation approach offers a promising diagnostic when improving cloud schemes, as illustrated by comparison of different schemes available for HIRHAM5.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

An Improved Algorithm for Estimating Surface Shortwave Radiation: Preliminary Evaluation With MODIS Products

Cloud parameters, as key inputs in radiative transfer algorithms, have a critical impact on surface shortwave radiation (SSR) computation. By introducing a parameterization of cloud transmittance and reflectance, based on radiative transfer simulations, this study improves the accuracy of an existing physically based model which severely underestimates SSR under thick cloud conditions. The cloud parameterization adopts the single-layer cloud model and simulates cloud transmittances and reflectances by varying cloud optical thickness, cloud particle size, and solar zenith angle. The revised model is applied to estimate instantaneous SSR using Moderate-resolution Imaging Spectroradiometer (MODIS) atmospheric and land products. The retrieved SSR is evaluated against observation data from 41 Baseline Surface Radiation Network (BSRN) stations and is also compared with the MODIS official SSR product. The root mean square error (RMSE) of the estimated instantaneous radiation is approximately 52 and 98 W m -2 under clear-sky and all-sky conditions, respectively. The accuracy of the improved parameterization is higher than that of the original model, and there is no obvious underestimation of SSR in the case of high cloud optical thickness. Therefore, the new algorithm improves the accuracy of SSR estimates in the presence of thick clouds. Retrievals with the improved model also achieve higher accuracy than the MODIS official SSR product (MCD18A1). To conclude, the reliable performance of the scheme at most BSRN stations illustrates that the improved model can be used to map SSR on a global scale.

42 ENGINEERING↗
DOE OSTI2021

Idealized Large-Eddy Simulations of Stratocumulus Advecting over Cold Water. Part I: Boundary Layer Decoupling

Abstract We explore the decoupling physics of a stratocumulus-topped boundary layer (STBL) moving over cooler water, a situation mimicking warm-air advection (WADV). We simulate an initially well-mixed STBL over a doubly periodic domain with the sea surface temperature decreasing linearly over time using the System for Atmospheric Modeling large-eddy model. Due to the surface cooling, the STBL becomes increasingly stably stratified, manifested as a near-surface temperature inversion topped by a well-mixed cloud-containing layer. Unlike the stably stratified STBL in cold-air advection (CADV) that is characterized by cumulus coupling, the stratocumulus deck in the WADV is unambiguously decoupled from the sea surface, manifested as weakly negative buoyancy flux throughout the subcloud layer. Without the influxes of buoyancy from the surface, the convective circulation in the well-mixed cloud-containing layer is driven by cloud-top radiative cooling. In such a regime, the downdrafts propel the circulation, in contrast to that in CADV regime for which the cumulus updrafts play a more determinant role. Such a contrast in convection regime explains the difference in many aspects of the STBLs including the entrainment rate, cloud homogeneity, vertical exchanges of heat and moisture, and lifetime of the stratocumulus deck, with the last being subject to a more thorough investigation in Part II. Finally, we investigate under what conditions a secondary stratus near the surface (or fog) can form in the WADV. We found that weaker subsidence favors the formation of fog whereas a more rapid surface cooling rate does not. Significant Statement The low-lying blanketlike clouds, called stratocumulus (Sc), reflect much incoming sunlight, substantially modulating Earth’s temperature. While much is known about how the Sc evolves when it moves over warmer water, few studies examine the opposite situation of Sc moving over colder water. We used a high-resolution numerical model to simulate such a case. When moving over cold water, the Sc becomes unambiguously decoupled from the water surface, distinctive from its warm counterpart in which the Sc interacts with the water surface via intermittent cauliflower-like clouds called cumulus clouds. Such decoupling influences many aspects of the Sc–sea surface system, which combine to alter the ability of the Sc to reflect sunlight, thereby influencing the climate. This work laid the foundation for future work that quantifies the contribution of such a decoupled Sc regime to Earth’s radiative budget and climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Which Plant Traits Increase Soil Carbon Sequestration? Empirical Evidence From a Long‐Term Poplar Genetic Diversity Trial

Plants play a key role in mediating soil response to global change, and breeding or engineering crops to increase soil organic carbon (SOC) storage is a potential route to land-based carbon dioxide removal in agricultural systems. However, due to limited observational datasets plus shifting paradigms of SOC stabilization, it is unclear which plant traits are most important for enhancing different types of soil organic matter. Existing long-term common gardens of genetically diverse plant populations may provide an opportunity to evaluate biological controls on SOC, separate from environmental or management variability. Here we report on soil and root chemical data collected for 24 genotypes within a 13-year-old common garden in northwestern Oregon planted with a large natural variant population of Populus trichocarpa. Fractionating surface soil (0–15 cm) revealed substantial variation in stocks of mineral-associated organic matter (MAOM; 18–67 t C/ha) and particulate organic matter (POM; 2–22 t C/ha). Tree genotype explained 24% and 26% of the MAOM and POM stock variability, respectively, after controlling for background variability. We found minimal association between SOC concentration and either aboveground tree productivity or root biomass recalcitrance (C/N ratios and lignin content). In contrast, root elemental content appeared influential for MAOM-C concentration, which showed a strong positive association with root aluminum (Al) and a strong negative association with root boron (B) and magnesium (Mg). Furthermore, root concentrations of these elements were highly heritable (57%–78%) and not simply a reflection of background variation in soil elemental concentrations. We estimate that surface SOC stocks under these 24 genotypes have diverged at rates of up to 1.2–4.3 t C/ha/year. These results suggest that long-term genetic diversity trials have value for elucidating biological controls on soil organic matter dynamics, and that traits associated with root elemental content may be a useful target for enhancing biosequestration.

biomass recalcitrance↗
DOE OSTI2024

Analytical Tools to Assess Polymer Biodegradation: A Critical Review and Recommendations

Many petroleum-derived plastic materials are highly recalcitrant and persistent in the environment, posing significant threats to human and ecological receptors due to their accumulation in ecosystems. In recent years, research efforts have focused on advancing biological methods for polymer degradation. Enzymatic depolymerization has emerged as particularly relevant for biobased plastic recycling, potentially scalable for industrial use. Biodegradation involves adsorption to the plastic solid surface, followed by an interfacial reaction, resulting in cleavage of bonds of polymer chains exposed on the surface. Here, widely varying substrate-specific kinetics are observed, with the polymer’s properties possessing a significant impact on the rate of this interfacial catalysis. Thus, there is a critical need for sensitive and accurate characterization of the material surface during and after interfacial depolymerization to fully understand the reaction mechanisms. Here, we provide a critical review of a range of techniques used in the analysis of material surfaces to characterize the chemical, topological, and morphological features relevant to the study of enzymatic biocatalysis, including microscopy techniques, spectroscopic techniques (e.g., X-ray diffraction analysis, Fourier transform infrared attenuated total reflectance spectroscopy, and mass spectrometry detection of analytes associated with degradation). Techniques for evaluation of surface energy and topology in their relevancy for sensitive detection of biological surface modifications are also discussed. In addition, this paper provides an overview of the strengths of these techniques and compares their performance in both sensitivity and throughput, including emerging techniques, which can be useful, particularly for the rapid analysis of the surface properties of polymeric materials in high-throughput screening of candidate biocatalysts. This research serves as a starting point in selecting and applying appropriate methodologies that provide direct evidence to the ongoing biotic degradation of polymeric materials.

Colachis, Matthew↗
DOE OSTI2024

Matrix-formation dynamics dictate methyl nitrite conformer abundance

Methyl nitrite has two stable conformational isomers resulting from rotation about the primary C–O–N–O dihedral angle: cis-CH 3 ONO and trans-CH 3 ONO, with cis being more stable by ∼5 kJ/mol. Here, the barrier to rotational interconversion (∼45 kJ/mol) is too large for isomerization to occur under ambient conditions. This paper presents evidence of a change in conformer abundance when dilute CH 3 ONO is deposited onto a cold substrate; the relative population of the freshly deposited cis conformer is seen to increase compared to its gas-phase abundance, measured by in situ infrared spectroscopy. We observe abundance changes depending on the identity of the bath gas (N 2 , Ar, and Xe) and deposition angle. The observations indicate that the surface properties of the growing matrix influence conformer abundance—contrary to the widely held assumption that conformer abundance in matrices reflects gas-phase abundance. We posit that differences in the angle-dependent host-gas deposition dynamics affect the growing surfaces, causing changes in conformer abundances. Quantum chemistry calculations of the binding energies between CH 3 ONO and a single bath-gas component reveal that significant energetic stabilization is not observed in 1:1 complexes of N 2 :CH 3 ONO, Ar:CH 3 ONO, or Xe:CH 3 ONO. From our results, we conclude that the growing surface plays a significant role in trapping cis-CH 3 ONO more effectively than trans-CH 3 ONO, likely because cis-CH 3 ONO is more compact. Taken together, the observations highlight the necessity for careful characterization of conformers in matrix-isolated systems, emphasizing a need for further study into the deposition dynamics and surface structure of chemically inert matrices.

Hockey, Emily K.↗
DOE OSTI2022

Temperature-dependent diffuse reflectance measurements of ceramic powders in the near- and mid-infrared spectra

Radiative properties are critical to quantify radiative energy fluxes between surfaces and in participating media. However, there is limited experimental data on temperature-dependent radiative properties of materials. Herein, this work focuses on experimentally measuring temperature-dependent diffuse reflectance in the near- and mid-infrared spectra (1–20 μm) for ceramic particles with applications as heat-transfer and thermal-storage media in concentrated solar power (CSP) plants. Specifically, a commercially available sintered bauxite proppant, ACCUCAST ID80, and its primary chemical constituents—alumina (Al 2 O 3 ) and silica (SiO 2 )—are measured in powder form using a Fourier transform infrared spectrometer (FTIR) coupled with a specialized diffuse reflectance accessory and a heated stage. Room-temperature diffuse reflectance measurements show increased absorption in tests with greater mass fractions of the ceramic samples. There is a strong correlation in the measured reflectance spectra of ACCUCAST with alumina and silica in the spectral range 2000–500 cm –1 (5–20 μm). Whereas, for shorter wavelengths (< 5 μm), the absorptance for ACCUCAST is greater than the absorptance for alumina and silica, indicating contributions from other chemical species present in the composite material. For the first time, temperature-dependent diffuse reflectance measurements are reported for ACCUCAST up to 1000 °C. These results are compared against those of alumina and silica through the calculation of a thermal emittance. All three materials exhibit a calculated emittance of ~0.9 at room temperature. However, this value decreases to ~0.6 for ACCUCAST and drops to less than 0.4 for alumina and silica at 1000 °C. Thermal cycling in air at 1000 °C resulted in a visible color change from dark grey to light orange for ACCUCAST and a subsequent larger increase in reflectance for wavelengths less than 5 μm as compared to ACCUCAST thermally cycled at 1000 °C in vacuum. Alumina and silica spectra proved to be largely unaffected by thermal cycling under atmospheric conditions. Overall, this study establishes a powerful technique for the characterization of radiative properties of particulate materials as a function of temperature and presents a detailed case study of ACCUCAST, a candidate for next-generation particle-based CSP.

14 SOLAR ENERGY↗
DOE OSTI2026

Adsorption of Mixed Micelles of Polysorbate 80 and Oleic Acid to the Air–Water Interface

The solubilization of long chain amphiphiles with limited solubility into mixed micelles composed of highly soluble surfactants plays a crucial role in modulating the stability and functionality of formulations in pharmaceutical and food systems. Subsequently, the mixed micelles adsorb from solution to the air−water surface, defining the transport mechanism of the insoluble amphiphiles to the interface. We use X-ray reflectivity to measure the composition and provide insight into the structure of these mixed monolayers, and, alongside interfacial tension measurements, we provide an understanding of how the bulk composition determines the surface composition and the dynamics of tension reduction. We use a model system consisting of an insoluble fatty acid, oleic acid (OA), and a soluble micelle-forming surfactant, polysorbate 80 (PS80). PS80 forms spherical micelles, and, above the critical micelle concentration (cmc), OA is readily solubilized inside the micelles. We show that the adsorption of PS80/OA mixed micelles to the air−water interface rapidly reduces the tension and lowers the equilibrium tension in proportion to the OA concentration. X-ray reflectivity data, fit using Parratt-slab models, quantitively demonstrates that the monolayers become enriched with OA, and we show how the OA intercalates into the PS80 monolayers.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Significant Roles of Surface Hydrides in Enhancing the Performance of Cu/BaTiO 2.8 H 0.2 Catalyst for CO 2 Hydrogenation to Methanol

Abstract Tuning the anionic site of catalyst supports can impact reaction pathways by creating active sites on the support or influencing metal‐support interactions when using supported metal nanoparticles. This study focuses on CO 2 hydrogenation over supported Cu nanoparticles, revealing a 3‐fold increase in methanol yield when replacing oxygen anions with hydrides in the perovskite support (Cu/BaTiO 2.8 H 0.2 yields ~146 mg/h/gCu vs. Cu/BaTiO 3 yields ~50 mg/h/gCu). The contrast suggests that significant roles are played by the support hydrides in the reaction. Temperature programmed reaction and isotopic labelling studies indicate that BaTiO 2.8 H 0.2 surface hydride species follow a Mars van Krevelen mechanism in CO 2 hydrogenation, promoting methanol production. High‐pressure steady‐state isotopic transient kinetic analysis (SSITKA) studies suggest that Cu/BaTiO 2.8 H 0.2 possesses both a higher density and more active and selective sites for methanol production compared to Cu/BaTiO 3 . An operando high‐pressure diffuse reflectance infrared spectroscopy (DRIFTS)‐SSITKA study shows that formate species are the major surface intermediates over both catalysts, and the subsequent hydrogenation steps of formate are likely rate‐limiting. However, the catalytic reactivity of Cu/BaTiO 2.8 H 0.2 towards the formate species is much higher than Cu/BaTiO 3 , likely due to the altered electronic structure of interface Cu sites by the hydrides in the support as validated by density functional theory (DFT) calculations.

He, Yang↗
DOE OSTI2021

Density Functional Tight-Binding Simulations Reveal the Presence of Surface Defects on the Quartz (101)–Water Interface

Understanding the structure and reactivity of quartz–water interfaces is critical for numerous applications in the geological, environmental, and biological sciences. However, disagreements on the atomic-level structure of the interfaces between experiments and simulations are hampering our ability to predict the surface reactivity. Here, we used density functional tight-binding (DFTB)-based molecular dynamics to simulate a series of quartz (101) surfaces having different types and densities of surface defects in water and compared them with the structures determined by X-ray reflectivity measurements. The DFTB simulations are able to reproduce previous classical and quantum mechanical predictions of the pristine quartz (101)–water interface that disagree with experimental observations. To remedy this situation, a set of defective quartz surfaces having various surface silicon (Si) vacancies were built as indicated by recent experimental studies. We found that the rotation of surface [SiO 4 ] tetrahedra near Si vacancies can lead to outward displacements of Si atoms similar to those observed in the experiments. The presence of additional surface Si vacancies caused inward relaxations of terminal oxygens through the formation of hydrogen bonds. Finally, the overall results indicate that the quartz (101)–water interface may include a mixture of geminal (≡Si–(OH) 2 )- and vicinal (≡Si–OH)-type silanol groups together with the presence of surface Si vacancies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Machine Learning-Enabled Quantitative Analysis of Optically Obscure Scratches on Nickel-Plated Additively Manufactured (AM) Samples

Additively manufactured metal components often have rough and uneven surfaces, necessitating post-processing and surface polishing. Hardness is a critical characteristic that affects overall component properties, including wear. This study employed K-means unsupervised machine learning to explore the relationship between the relative surface hardness and scratch width of electroless nickel plating on additively manufactured composite components. The Taguchi design of experiment (TDOE) L9 orthogonal array facilitated experimentation with various factors and levels. Initially, a digital light microscope was used for 3D surface mapping and scratch width quantification. However, the microscope struggled with the reflections from the shiny Ni-plating and scatter from small scratches. To overcome this, a scanning electron microscope (SEM) generated grayscale images and 3D height maps of the scratched Ni-plating, thus enabling the precise characterization of scratch widths. Optical identification of the scratch regions and quantification were accomplished using Python code with a K-means machine-learning clustering algorithm. The TDOE yielded distinct Ni-plating hardness levels for the nine samples, while an increased scratch force showed a non-linear impact on scratch widths. The enhanced surface quality resulting from Ni coatings will have significant implications in various industrial applications, and it will play a pivotal role in future metal and alloy surface engineering.

36 MATERIALS SCIENCE↗