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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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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Modeling Pb(II) Adsorption on Mineral Surfaces: Bridging Density Functional Theory and Experiment with Thermodynamic Insights

Despite decades of work on aqueous lead (Pb) adsorption on a-Fe2O3 (hematite) and a-Al2O3 (alumina), gaps between measurements and modeling obscure molecular-level understanding. Achieving well-matched geometries between theory and experimental for mineral-water interfaces is a hurdle, as surface functional group type and distribution must be accounted for in determining mechanisms. Additionally, computational methods that can describe the substrate are often not appropriate to capture aqueous effects. Progress requires focusing on well-studied and relevant systems, such as key facets (001),(012), and (110) of hematite and alumina, and ubiquitous contaminants such as aqueous Pb. In the past, bulk-parametrized bond-valence principles were used to rationalize Pb(II) adsorption trends. These approaches can break down at surfaces, where flexible bonding environments and adsorption-induced surface relaxations play a critical role. Here, we adapt and apply a density functional theory (DFT) and thermodynamics framework, integrating DFT-calculated energies with experimental data and electrochemical principles, to predict Pb(II) adsorption. Our model results capture trends across the full set of surfaces and predict that inner-sphere Pb(II) sorption on (001) alumina varies from unfavorable to weakly favorable across a range of pH conditions. This aligns with experiment insights that Pb(II) interacts at that surface through outer-sphere interactions. Extending to Fe(II) adsorption, we demonstrate a coverage-dependent site preference, potentially explaining disorder in overlayers grown by the oxidative adsorption of Fe(II) on hematite (001).

lead contamination↗
DOE OSTI2023

Hydrogen Evolution on Electrode‐Supported Pt n Clusters: Ensemble of Hydride States Governs the Size Dependent Reactivity

Abstract We report the size‐dependent activity and stability of supported Pt 1,4,7,8 for electrocatalytic hydrogen evolution reaction, and show that clusters outperform polycrystalline Pt in activity, with size‐dependent stability. To understand the size effects, we use DFT calculations to study the structural fluxionality under varying potentials. We show that the clusters can reshape under H coverage and populate an ensemble of states with diverse stoichiometry, structure, and thus reactivity. Both experiment and theory suggest that electrocatalytic species are hydridic states of the clusters (≈2 H/Pt). An ensemble‐based kinetic model reproduces the experimental activity trend and reveals the role of metastable states. The stability trend is rationalized by chemical bonding analysis. Our joint study demonstrates the potential‐ and adsorbate‐coverage‐dependent fluxionality of subnano clusters of different sizes and offers a systematic modeling strategy to tackle the complexities.

Zhang, Zisheng↗
DOE OSTI2020

Controlling Hydrocarbon (De)Hydrogenation Pathways with Bifunctional PtCu Single-Atom Alloys

The conversions of surface-bound alkyl groups to alkanes and alkenes are important steps in many heterogeneously catalyzed reactions. On the one hand, while Pt is ubiquitous in industry because of its high activity toward C–H activation, many Pt-based catalysts tend to overbind reactive intermediates, which leads to deactivation by carbon deposition and coke formation. On the other hand, Cu binds intermediates more weakly than Pt, but activation barriers tend to be higher on Cu. We examine the reactivity of ethyl, the simplest alkyl group that can undergo hydrogenation and dehydrogenation via β-elimination, and show that isolated Pt atoms in Cu enable low-temperature hydrogenation of ethyl, unseen on Cu, while avoiding the decomposition pathways on pure Pt that lead to coking. Lastly, we confirm the predictions of our theoretical model and experimentally demonstrate that the selectivity of ethyl (de)hydrogenation can be controlled by changing the surface coverage of hydrogen.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Hydrogen Dissociation Controls 1-Hexyne Selective Hydrogenation on Dilute Pd-in-Au Catalysts

Increasing the selectivity of the catalytic hydrogenation of alkynes to alkenes is of major importance for the processing of petrochemicals and the production of fine chemicals. Achieving high selectivity for alkene formation at high conversions, however, remains a long-standing challenge in heterogeneous catalysis. Here, the mechanism and origin of the high selectivity of dilute Pd-in-Au catalysts has been studied by a combination of first-principles calculations, microkinetic simulations, and isotopic exchange hydrogenation experiments using Pd 0.04 Au 0.96 nanoparticles embedded in raspberry colloid-templated silica. The Pd is predominantly in the form of isolated atoms, only surrounded by Au atoms, based on prior studies. The simulations indicate that the rate-limiting process for 1-hexyne hydrogenation on Pd monomers in Au(111) is H 2 dissociation, which has a large free energy barrier of 0.86 eV at 363 K and 0.2 bar of H 2 . The C–H bond formation steps, on the other hand, proceed with lower barriers, which contrasts with previous studies of extended Pd catalysts. The microkinetic simulations identify the sizable H 2 dissociation barrier and the small barrier for the hydrogenation of 1-hexyne as key factors that lead to a high selectivity for the production of 1-hexene from 1-hexyne, even at high conversion. The unconventional H 2 dissociation limiting process in combination with the low coverage of weakly bound hydrocarbon intermediates explains the near-zero order of 1-hexyne found experimentally. Furthermore, the partial hydrogenation of 1-hexyne to form 1-hexene is shown to be an irreversible process from our isotopic exchange hydrogenation experiments and is explained by the strongly exothermic nature of the reaction. Diluting active species, like Pd, in a less active host metal, like Au, hence appears promising as a means of tuning the binding energy of reactants and altering reaction profiles, leading to distinct kinetic behavior for an optimal catalytic activity and selectivity. Furthermore, the combination of microkinetic modeling, density functional theory calculations, and isotopic exchange experiments is thus demonstrated to be an effective approach to modeling important catalytic phenomena.

1-hexyne↗
DOE OSTI2022

Quantifying the impact of temporal analysis of products reactor initial state uncertainties on kinetic parameters

The temporal analysis of products (TAP) reactor, a transient kinetic tool, provides users with information as the catalyst state evolves. However, the state of the art for TAP uncertainty quantification only considers the experimental noise present in the outlet flow signal. Additional sources of uncertainty, including, but not limited to, initial surface coverages, the catalyst zone location, the inert void fraction, and the gas pulse intensity and pulse delay, are not included. For this reason, a framework for quantifying all uncertainty sources present in TAP experiments is presented and applied to a carbon monoxide oxidation case study. Herein, two methods for quantifying these sources of uncertainty are introduced. The first utilizes initial state sensitivities to approximate the parameter variances, as well as to provide insights into the structural certainty of the model. The second generates parameter confidence distributions through an ensemble-based sampling algorithm. This initial state covariance matrix can ultimately be merged with the experimental noise covariance matrix, providing a unified description of the parameter uncertainties for a single TAP experiment.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Hydrogen Evolution on Electrode–Supported Ptn Clusters: Ensemble of Hydride States Governs the Size Dependent Reactivity

We report the size-dependent activity and stability of supported Pt1,4,7,8 for electrocatalytic hydrogen evolution reaction, and show that clusters outperform polycrystalline Pt in activity, with sizedependent stability. To understand the size effects, we use DFT calculations to study the structural fluxionality under varying potentials. We show that the clusters can reshape under H coverage and populate an ensemble of states with diverse stoichiometry, structure, and thus reactivity. Both experiment and theory suggest that electrocatalytic species are hydridic states of the clusters (~2 H/Pt). An ensemble-based kinetic model reproduces the experimental activity trend and reveals the role of metastable states. Furthermore, the stability trend is rationalized by chemical bonding analysis. Our joint study demonstrates the potential- and adsorbate-coverage-dependent fluxionality of subnano clusters of different sizes and offers a systematic modeling strategy to tackle the complexities.

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

Correcting distortions of thin-walled machined parts by machine hammer peening

Thin-walled aerostructural components frequently get distorted after the machining process. Reworking to correct distortions or eventually rejecting parts significantly increases the cost. This paper proposes a new approach to correct distortions in thin-walled components by strategically applying hammer peening on target surfaces of a machined component. Aluminium alloy 7475-T7351 was chosen for this research. The study was divided in two stages. First, the residual stresses (RS) induced by four different pneumatic hammer peening conditions (modifying the stepover distance and initial offset) were characterised in a test coupon, and one of the conditions was selected for the next stage. In the second stage, a FEM model was used to predict distortions caused by machining in a representative workpiece. Then, the RS induced by hammer peening were included in an FEM model to define two hammer peening strategies (varying the coverage area) to analyse the capability to reduce distortions. Two workpieces were machined and then treated with the simulated hammer peening strategies for experimental validation. Results in the test coupon showed that pneumatic hammer peening can generate high compressive RS (-50 to –350 MPa) up to 800 μm depth, with their magnitude increasing with a reduced stepover distance. Application of hammer peening over 4% of the surface of the representative workpiece reduced the machining-induced distortions by 37%, and a coverage area of 100% led to and overcorrection by a factor of five. This confirms that hammer peening can be strategically applied (in target areas and changing the percentage of coverage) to correct low or severe distortions.

42 ENGINEERING↗
DOE OSTI2020

SPRUCE High-Resolution Minirhizotrons in an Experimentally-Warmed Peatland Provide an Unprecedented Glimpse at Fine Roots and their Fungal Partners: Supporting Data

Images were collected using first of their kind, non-destructive, high-resolution automated minirhizotrons (RhizoSystems, LLC) to assess the response of plant fine-root and fungal mycelium dynamics to elevated temperatures after 4-6 years of whole-ecosystem warming and exposure to elevated carbon dioxide concentrations (e[CO2]) in a peat bog where the SPRUCE (Spruce and Peatland Responses Under Changing Environments) experiment is located. We focused on two SPRUCE experimental plots: Plot 10 has elevated temperature (+9°C) and plot 19 is a control (+0°C). Both have elevated carbon dioxide (e[CO2]). Changes in root and fungal abundance with warming were estimated from a timeseries of landscape-level mosaiced images for each plot by measuring the proportional abundance of five belowground classes: fine roots of vascular plants, ectomycorrhizas, fungal hyphae, fungal rhizomorphs, and fungal sporocarps. To examine root and fungal phenology responses to warming, the length per individual root or fungal structure (except fungal hyphae that did not grow linearly but rather increased in areal coverage) were measured per image area of a set of timeseries patch-level mosaiced images for each plot. The experimental work was conducted in a Picea mariana [black spruce] – Sphagnum spp. bog forest in northern Minnesota, 40 km north of Grand Rapids, in the USDA Forest Service Marcell Experimental Forest (MEF). This ecosystem, which is located at the southern margin of the boreal forest, is considered especially vulnerable to climate change and anticipated to be near its tipping point. These data were used in analyses published in Defrenne et al (2021). This dataset contains 5 data files in comma-separate values (*.csv) format and a compressed folder (*.zip) containing 383 JPEG (*.jpg) images. Data files contain landscape-level assessment of belowground class abundance, patch-level growth phenology, and environmental variables (originally published in Hanson et al., 2016 and Hanson et al 2020). Images were collected with automated minirhizotrons and analyzed for phenology. Additional metadata are provided: 5 data dictionaries and a file-level metadata file in comma-separate values (.csv) format and a user guide in PDF (*.pdf) format.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Comparing the performance of density functionals in describing the adsorption of atoms and small molecules on Ni(111)

Reaction networks calculated using density functional theory (DFT) play a crucial role in understanding and predicting heterogeneous catalyst performance. However, results obtained using different density functionals can vary significantly. Accordingly, it is important to assess the accuracy of available functionals in capturing adsorption energetics derived from single-crystal adsorption microcalorimetry experiments. Here, we evaluate how different density functionals describe the molecular and dissociative adsorption of CH 3 I, the adsorption of CH 3 , I, and H, and the dissociative adsorption of CH 4 on Ni(111). First, we identify energetically-preferred adsorbed states for each adsorbate at three surface coverages and calculate the corresponding enthalpies of adsorption at 160 K. Then, we compare the results to experimental measurements published in the literature. For each adsorption process we find at least one functional that is quantitatively accurate within experimental error, but no functional is accurate (within experimental error) for all adsorption processes studied. Even when assuming an additional DFT error of ±20 kJ/mol on top of the experimental error, only the PBE-D3 and RPBE-D3 functionals are accurate for all considered adsorption systems. Overall, these results indicate that quantitative agreement between density functional theory calculations and experimental measurements is both system- and functional-dependent. Importantly, single-crystal adsorption microcalorimetry experiments will continue to play an important role for benchmarking density functionals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Hybrid Quantum Mechanical, Molecular Mechanical, and Machine Learning Potential for Computing Aqueous-Phase Adsorption Free Energies on Metal Surfaces

Performing reliable computer simulations of elementary processes occurring at metal–water interfaces is pivotal for novel catalyst design in sustainable energy applications. Computational catalyst design hinges on the ability to reliably and efficiently compute the potential energy surface (PES) of the system. Here, due to the large system sizes needed for studying processes at liquid water–metal interfaces, these systems can currently not be described using density functional theory (DFT). In this work, we used a hybrid quantum mechanical, molecular mechanical, and machine learning potential for studying the adsorption behavior of phenol, atomic hydrogen, 2-butanol, and 2-butanone on the (0001) facet of Ru under reducing conditions when Ru is not oxidized. Specifically, we describe the adsorbate and the surrounding metal atoms at the DFT level of theory. Here, we also considered the electrostatic field effect of the water molecules on adsorbate–metal interactions. Next, for the water–water and water–adsorbate interactions, we used established classical force fields. Finally, for the water–Ru surface interaction, for which no reliable force fields have been published, we used Behler–Parrinello high-dimensional neural network potentials (HDNNPs). Employing this setup, we used our explicit solvation for metal surface (eSMS) approach to compute the aqueous-phase effect on the low-coverage adsorption of selected molecules and atoms on the (0001) facet of Ru. In agreement with previous experimental and computational studies of oxygenated molecules over transition metal facets, we found that liquid water destabilizes the tested adsorbates on Ru(0001). Interestingly, our findings indicate that adsorbates on Ru are less affected by the presence of an aqueous phase than on other transition metals (e.g., Pt), highlighting the necessity of experimental investigations of Ru-based catalytic systems in liquid water.

Adsorption↗
DOE OSTI2020

FPDetect: Efficient Reasoning About Stencil Programs Using Selective Direct Evaluation

We present FPDetect, a low-overhead approach for detecting logical errors and soft errors affecting stencil computations without generating false positives. We develop an offline analysis that tightly estimates the number of floating-point bits preserved across stencil applications. This estimate rigorously bounds the values expected in the data space of the computation. Violations of this bound can be attributed with certainty to errors. FPDetect helps synthesize error detectors customized for user-specified levels of accuracy and coverage. FPDetect also enables overhead reduction techniques based on deploying these detectors coarsely in space and time. Experimental evaluations demonstrate the practicality of our approach.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Integrated modeling of boron powder injection for real-time plasma-facing component conditioning

An integrated modeling framework for investigating the application of solid boron (B) powder injection for real-time surface conditioning of plasma-facing components (PFCs) in tokamak environments is presented. Utilizing the DIII-D impurity powder dropper (IPD) setup, this study simulates B powder injection scenarios ranging from milligrams to tens of milligrams per second, corresponding to boron flux rates of 10 20 –10 21 B/s in standard L-mode conditions. The comprehensive modeling approach combines EMC3-EIRENE for simulating the deuterium plasma background and the Dust Injection Simulator (DIS) for the ablation and transport of the boron powder particles. EMC3 trace impurity fluid modeling results show substantial boron transport to the inboard lower divertor, predominantly influenced by the main ion plasma flow. The dependency on powder particle size (5-250 µm) was found to be insignificant for the scenario considered. The effects of erosion and redeposition were considered to reconcile the discrepancies with experimental observations, which saw substantial deposition on the outer divertor plasma-facing components. For this purpose, the WallDYN3D code was updated to include boron sources within the plasma domain and integrated into the modeling framework. The mixed-material migration modeling shows evolving boron deposition patterns, suggesting the formation of mixed B-C layers or predominantly B coverage depending on the powder mass flow rate. While the modeling outcomes at lower B injection rates tend to align with DIII-D experimental observations, the prediction of near-pure boron layers at higher rates has yet to be experimentally verified in the carbon environment of the DIII-D tokamak. The extensive reach of boron layers found in the modeling suggests the need for modeling that encompasses the entire wall geometry for more accurate experimental correlations. This integrated approach sets a precedent for analyzing and applying real-time in-situ boron coating techniques in advanced tokamak scenarios, potentially extendable to ITER.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Kinetics of low-temperature methane activation on IrO 2 (1 1 0): Role of local surface hydroxide species

The ability of the IrO 2 (1 1 0) surface to promote CH 4 activation at low temperatures (~150 K) suggests possibilities for developing IrO 2 -based catalysts to selectively convert light alkanes to high-value chemicals. In this study, we present experimental results and microkinetic simulations, based on density functional theory (DFT) calculations, of temperature programmed reaction spectra (TPRS) obtained for CH 4 σ-complexes adsorbed on IrO 2 (1 1 0), and focus on clarifying how surface OH groups modify the branching between CH 4 desorption, activation and subsequent reactions during TPRS. Our DFT results predict that surface OH groups strongly destabilize CH 4 σ-complexes on IrO 2 (1 1 0) in addition to deactivating surface O-atoms that are needed to achieve CH 4 activation at low temperature. We demonstrate that a microkinetic model that incorporates the influence of surface OH groups on the CH 4 binding and reactivity reproduces experimental TPRS results which show that adsorbed CH 4 σ-complexes preferentially dissociate at low CH 4 coverage, but that an increasing fraction of the adsorbed CH 4 desorbs at low temperature (~120 K) with increasing initial CH 4 or H coverage. The simulations reveal that low-temperature CH4 desorption during TPRS arises primarily from CH 4 σ-complexes that are kinetically-trapped between adjacent surface OH groups, and are thus destabilized and unable to access reactive O-atoms. In addition, when the effect of adjacent OH groups is incorporated we find that the PBE-D3 functional incorporating dispersion provides CH 4 binding energies that agree more closely with that obtained from the TPRS experiments. Overall, our results demonstrate that the local effect of adjacent OH groups must be incorporated into any microkinetic models to properly capture the selectivity between extensive and partial oxidation in alkane conversion on IrO 2 (1 1 0) under reaction conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Global root traits (GRooT) database

Motivation: Trait data are fundamental to the quantitative description of plant form and function. Although root traits capture key dimensions related to plant responses to changing environmental conditions and effects on ecosystem processes, they have rarely been included in large-scale comparative studies and global models. For instance, root traits remain absent from nearly all studies that define the global spectrum of plant form and function. Thus, to overcome conceptual and methodological roadblocks preventing a widespread integration of root trait data into large-scale analyses we created the Global Root Trait (GRooT) Database. GRooT provides readyto- use data by combining the expertise of root ecologists with data mobilization and curation. Specifically, we (a) determined a set of core root traits relevant to the description of plant form and function based on an assessment by experts, (b) maximized species coverage through data standardization within and among traits, and (c) implemented data quality checks. Main types of variables contained: GRooT contains 114,222 trait records on 38 continuous root traits. Spatial location and grain: Global coverage with data from arid, continental, polar, temperate and tropical biomes. Data on root traits were derived from experimental studies and field studies. Time period and grain: Data were recorded between 1911 and 2019. Major taxa and level of measurement: GRooT includes root trait data for which taxonomic information is available. Trait records vary in their taxonomic resolution, with subspecies or varieties being the highest and genera the lowest taxonomic resolution available. It contains information for 184 subspecies or varieties, 6,214 species, 1,967 genera and 254 families. Owing to variation in data sources, trait records in the database include both individual observations and mean values. Software format: GRooT includes two csv files. A GitHub repository contains the csv files and a script in R to query the database.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Development of NDE/NDT Tools for High-Volume & High-Speed Inspection of CFRP Structures in Automotive Manufacturing

Main advantages of the air-coupled ultrasound testing (ACUT) and electromagnetic testing (EMT) techniques for NDE of CFRP composites were non-contact sensing, scalability for high-speed inspection, cost-effectiveness, and non-hazardous operation. Despite these advantages, no systems that would satisfy the project requirements were commercially available. Hence, one of the major efforts of the Michigan State University (MSU) team at the initial stage of the project was to close this technological gap by developing, optimizing, and validating array sensors that would provide sufficient sensitivity, spatial coverage, and resolution for robust defect detection. Optimization of the ACUT and EMT sensor designs was performed using experimentally validated finite element models. Initial experiments using array probes were conducted on relatively flat CFRP samples. In parallel, the MSU team designed and assembled a portable platform with two robotic arms. The robots were equipped with newly designed sensors that enabled high-speed NDE of curved CFRP parts. Presently, the developed robotic platform can be used as a demo/template NDE system, which is easily adaptable to manufacturing environments and in-line NDE. The ACUT NDE system developed by the MSU team used a high-power 4-channel pulser receiver for parallel data acquisition. The array probes were designed by stacking commercially available ACUT transducers, which operated in the frequency range between 100 kHz and 500 kHz. MSU optimized the excitation procedure and developed wave focusing cones so as to reduce the crosstalk between the transducers and to provide higher pulse repletion frequency (PRF). The through-transmission (TT) and single-side access (SSA) inspection modes were successfully implemented. In the TT-ACUT, structural defects in CFRP were detected by passing ultrasonic waves through the test part. Hence, the ACUT transmitters and receivers needed to be placed on the opposite sides of the test part. In the SSA-ACUT, guided waves (GW) were excited in the test part using the transmitters and were sensed by the receivers from the same side. Multi-channel TT-ACUT and SSA-ACUT provided high-speed NDE, and were successfully validated on CFRP test samples with interlaminar delaminations and other embedded defects The EM techniques developed by the MSU team included: 1) eddy current testing (ECT), 2) capacitive imaging (CI) and hybrid dual-mode imaging. In ECT, structural damage was detected in CFRP using coils sensor arrays. In ECT, the excitation magnetic field is generated by passing an alternating current through a coil, which is placed above the test sample. The excitation field penetrates the conductive sample and induces the eddy currents in its transect. In turn, the eddy currents generate the reaction field, which affects the total field sensed by a coil. Hence, the presence of structural flaws will alter the eddy current flow and the picked-up signal. ECT is mostly sensitive to local changes of the electric conductivity of the test sample, and CFRPs are mostly conductive in the direction of carbon fibers. Hence, ECT was well suited for the detection of fiber damage/fiber irregularities. The MSU team developed printed circuit boards (PCB) with coil sensor arrays optimized for NDE of CFRP. Unlike most commercial probes designed for ECT of metallic structures, the MSU array probes were designed for operation in [1-10] MHz frequency range, which was optimal for low-conductive CFRP. Multiple sensing topologies (coil groups excitation/sensing arrangements) were implemented and successfully validated. Capacitive Imaging (CI) technique developed by MSU was complementary to ECT. In contrast to ECT, which was sensitive to local changes of the electrical conductivity, the CI was sensitive to local changes of the dielectric constant. Therefore, CI could provide information about matrix damage/matrix irregularities in CFRP. The MSU CI sensor arrays were made of multiple circular or rectangular open-plate capacitors printed on PCB. Sensors of this type are not commercially available. In addition to ECT and CI, the MSU team developed a hybrid (dual-mode) inductive/capacitive measurement technique that synergistically combined the benefits of inductive and capacitive sensing for rapid NDE of fiber reinforced polymer (FRP) composite structures. Fiber damage and fiber irregularities in FRPs were detected by configuring hybrid sensors as coil sensors. Similarly, matrix damage, matrix irregularities and interlaminar delaminations were detected by configuring hybrid sensors as capacitive sensors. ECT and CI were performed sequentially by means of electronic switching. Hence, eliminating the need for mounting two separate sensor arrays on the probe. Portable robotic platform was developed by MSU for multi-technique high-speed NDE of CFRP test parts. The platform had two 6-axis robots, which enabled inspection of curved parts in approximately a 6×6×6 ft 3 active scan area. On the software side, the MSU team integrated scripts for NDE hardware control with scripts for robot motion control. MSU also implemented automated path planning for the robots, reconstruction of part’s surfaces via stereovision, 3D rendering of inspection data, and image processing algorithms for enhanced defect detection. Automotive composite parts manufactured by Plasan Composites from Phase I were used to validate the ACUT and EMT techniques on representative testbeds. Among those parts were three X-braces for a Dodge Viper, one composite calibration plaque with known defects at known locations, and four other test sections, including sections from a front splitter, a corner section from a composite hood, and a high-pressure RTM panel made using non crimp fabric. Other test samples included CFRP and GFRP calibration plates with fiber/matrix defects fabricated at MSU/CVRC.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Determining Catalytically Relevant Surfaces through Coverage-Dependent Lattice Gas Models: Carbon Adsorption on Fe(100)

Here, we have quantified the C–C lateral interactions on Fe(100) using a density functional theory (DFT)-parameterized lattice gas cluster expansion (LG CE) model trained using 265 unique configurations spanning a C coverage from 0 to 1 monolayer (ML). Our LG CE model shows high predictive accuracy with a leave-multiple-out cross-validation score of 10.2 and 16.6 meV/site for systems with and without the top two layers of Fe atoms fixed, respectively. Electronic ground-state structures identified from the lattice gas model (including the structures at 0 and 1 monolayers) were further used to generate ab initio phase diagrams under a range of temperatures and pressures. At low temperatures (<400 K), we found that the 1.0 monolayer structure is dominant, whereas at higher temperatures (>500 K), the 0.88 ML structure is most likely to form on the Fe surface. Interestingly, our model identified a c (2 × 2) ordered structure at 1/2 ML, which correlates well with previous DFT studies for carbon adsorption on iron surfaces and matches with the experimentally observed low-energy electron diffraction structure. Overall, the DFT-parameterized energies for the C/Fe system including effects of coverage and configurational space can further help in developing multiscale models for various heterogeneous reactions involving C–C and C–Fe interactions.

08 HYDROGEN↗
DOE OSTI2021

Gold-in-copper at low *CO coverage enables efficient electromethanation of CO 2

The renewable-electricity-powered CO 2 electroreduction reaction provides a promising means to store intermittent renewable energy in the form of valuable chemicals and dispatchable fuels. Renewable methane produced using CO 2 electroreduction attracts interest due to the established global distribution network; however, present-day efficiencies and activities remain below those required for practical application. Here we exploit the fact that the suppression of *CO dimerization and hydrogen evolution promotes methane selectivity: we reason that the introduction of Au in Cu favors *CO protonation vs. C-C coupling under low *CO coverage and weakens the *H adsorption energy of the surface, leading to a reduction in hydrogen evolution. We construct experimentally a suite of Au-Cu catalysts and control *CO availability by regulating CO 2 concentration and reaction rate. This strategy leads to a 1.6× improvement in the methane:H 2 selectivity ratio compared to the best prior reports operating above 100 mA cm -2 . We as a result achieve a CO 2 -to-methane Faradaic efficiency (FE) of (56 ± 2)% at a production rate of (112 ± 4) mA cm -2 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Surface Phase Stability of Fe 2 O 3 (001) in Hydrogen Reducing Environments: A DFT and XPS Analysis

Here, this study combines density functional theory (DFT) and ab initio thermodynamics calculations with X-ray photoelectron spectroscopy (XPS) investigations to identify the reduction properties of the Fe 2 O 3 (001) surface with implications for corrosion resistance, hydrogen transport, and energy safety. Ab initio thermodynamics modeling predicts fully hydroxylated surface stability across a broad range of pressures (1 × 10 –23 to 1 × 10 5 mbar) and temperatures below 700 K, consistent with previous experimental studies. Above 800 K, exposures to 1 × 10 –4 mbar H 2 , 1 × 10 –4 mbar O 2 , or 1 × 10 –4 mbar H 2 + 1 × 10 –4 mbar O 2 each yield unique XPS signals indicating a loss of −OH coverage, aligning with DFT predictions. Insight into the mechanism of reduction as a function of H 2 exposure is provided, as well as conditions that promote further reduction toward Fe 3 O 4 . Theoretical and experimental investigations indicate the ability to maintain the Fe 2 O 3 protective layer of iron oxides that have been exposed to H 2 environments by including trace amounts of aqueous O2.

77 NANOSCIENCE AND NANOTECHNOLOGY↗