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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Key Elements of Auroral Substorm Development and their Relationship to Recent Observations of Detached Sub-Auroral Phenomena Including STEVE-like Emissions

Since Akasofu introduced the concept of the substorm in 1964, numerous refinements have been added to the phenomenological model of how auroral substorms develop. Here, we review several of the most important of these including; polar cap patches, intensifications of the Polar Activated Band (PAB) at the poleward edge of the bulge, the development of new arcs poleward, the generation of auroral streamers, the evolution of streamers into auroral torches and omega bands, the association of streamers with particle injection and BBF activity in the tail, and wedgelet-like magnetic perturbations on the ground. We also review the concept of “contact breakups” which are breakups that appear to be triggered by the arrival of streamer-like forms in the equatorward regions of the oval. Finally, we remind the community that the addition of detached sub-auroral emissions was made to the phenomenological picture of substorm develop in the late 1960s along with the concept of auroral streamers. Newer observations of detached sub-auroral (STEVE-like emissions) from the Viking/UVI and POLAR/VIS imagers are presented which confirm that they are east-west aligned bands of emission that separate away from the equatorward edge of the auroral oval in response to intensifications of the poleward edge of the bulge and subsequent streamer production. We propose a new model for the formation of detached sub-auroral (STEVE-like) emissions in which a non-linear growth of a SAPS-driven instability (e.g. like the shear-flow/ballooning instability) at the plasmapause results in the disruption of the boundary separating hot plasma sheet particle from the cold plasmaspheric plasma. It is proposed that the resulting intermixing of plasma populations leads to both the observed STEVE-like emissions and also provides a source of cold plasma on open drift paths that can feed the long-lived drainage plumes that have recently been discovered.

58 GEOSCIENCES↗
DOE OSTI2025

A conserved chaperone protein is required for the formation of a noncanonical type VI secretion system spike tip complex

Type VI secretion systems (T6SSs) are dynamic protein nanomachines found in Gram-negative bacteria that deliver toxic effector proteins into target cells in a contact-dependent manner. Prior to secretion, many T6SS effector proteins require chaperones and/or accessory proteins for proper loading onto the structural components of the T6SS apparatus. However, despite their established importance, the precise molecular function of several T6SS accessory protein families remains unclear. In this study, we set out to characterize the DUF2169 family of T6SS accessory proteins. Using gene co-occurrence analyses, we find that DUF2169-encoding genes strictly co-occur with genes encoding T6SS spike complexes formed by valine-glycine repeat protein G (VgrG) and DUF4150 domains. Although structurally similar to Pro-Ala-Ala-Arg (PAAR) domains, “PAAR-like” DUF4150 domains lack PAAR motifs and instead contain a conserved PIPY motif, leading us to designate them PIPY domains. Next, we present both genetic and biochemical evidence that PIPY domains require a cognate DUF2169 protein to form a functional T6SS spike complex with VgrG. This contrasts with canonical PAAR proteins, which bind VgrG on their own to form functional spike complexes. By solving the first crystal structure of a DUF2169 protein, we show that this T6SS accessory protein adopts a novel protein fold. Furthermore, biophysical and structural modeling data suggest that DUF2169 contains a dynamic loop that physically interacts with a hydrophobic patch on the surface of its cognate PIPY domain. Based on these findings, we propose a model whereby DUF2169 proteins function as molecular chaperones that maintain VgrG–PIPY spike complexes in a secretion-competent state prior to their export by the T6SS apparatus.

DUF2169↗
DOE OSTI2024

Specific iron binding to natural sphingomyelin membrane induced by non-specific co-solutes

Sphingomyelin (SPM), a crucial phospholipid in the myelin sheath, plays a vital role in insulating nerve fibers. We hypothesize that iron ions selectively bind to the phosphatidylcholine (PC) template within the SPM membrane under near-physiological conditions, resulting in disruptions to membrane organization. These interactions could potentially contribute to the degradation of the myelin sheath, thereby playing a role in the development of neurodegenerative diseases. We utilized synchrotron-based X-ray spectroscopy and diffraction techniques to study the interaction of iron ions with a bovine spinal-cord SPM monolayer (ML) at the liquid-vapor interface under physiological conditions. The SPM ML serves as a model system, representing localized patches of lipids within a more complex membrane structure. The experiments assessed iron binding to the SPM membrane both in the presence of salts and with additional evaluation of the effects of various ion species on membrane behavior. Grazing incidence X-ray diffraction was employed to analyze the impact of iron binding on the structural integrity of the SPM membrane. Furthermore, our results demonstrate that iron ions in dilute solution selectively bind to the PC template of the SPM membrane exclusively at near-physiological salt concentrations (e.g., NaCl, KCl, KI, or CaCl 2 ) and are pH-dependent. In-significant binding was detected in the absence of these salts or at near-neutral pH with salts. The surface adsorption of iron ions is correlated with salt concentration, reaching saturation at physiological levels. In contrast, multivalent ions such as La 3+ and Ca 2+ do not bind to SPM under similar conditions. Notably, iron binding to the SPM membrane disrupts its in-plane organization, suggesting that these interactions may compromise membrane integrity and contribute to myelin sheath damage associated with neurological disorders.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Application of lipid-stabilized liquid-liquid interfaces in 3D printing of biomaterials

Developing strategies to stabilize liquid-liquid interfaces is essential for advancing applications in various biomedical systems. This study introduces a novel biocompatible in situ-forming material in which lipid self-assembly stabilizes water–oil interfaces, enabling controlled structuring of liquids through liquid-in-liquid 3D printing. The stabilization process, driven by the formation of nanostructures at the interface, is thoroughly analyzed through small-angle X-ray scattering (SAXS), rheometry, and microscopy techniques. This material system enables the fabrication of complex 3D constructs, including fibers, substrates, and microneedle patches, which exhibit outstanding mechanical properties and biocompatibility, as confirmed by tensile testing and cell viability tests. Here, by leveraging the unique properties of lipid-stabilized interfaces, this work demonstrates the potential of this approach for diverse biomedical applications such as drug delivery and tissue engineering while establishing a foundation for future advancements in liquid-in-liquid 3D printing technology.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Optimizing the hypre solver for manycore and GPU architectures

The solution of large-scale combustion problems with codes such as Uintah on modern computer architectures requires the use of multithreading and GPUs to achieve performance. Uintah uses a low-Mach number approximation that requires iteratively solving a large system of linear equations. The Hypre iterative solver has solved such systems in a scalable way for Uintah, but the use of OpenMP with Hypre leads to at least slowdown due to OpenMP overheads. The proposed solution uses the MPI Endpoints within Hypre, where each team of threads acts as a different MPI rank. This approach minimizes OpenMP synchronization overhead and performs as fast or (up to 1.44) faster than Hypre's MPI-only version, and allows the rest of Uintah to be optimized using OpenMP. The profiling of the GPU version of Hypre shows the bottleneck to be the launch overhead of thousands of micro-kernels. The GPU performance was improved by fusing these micro-kernels and was further optimized by using Cuda-aware MPI, resulting in an overall speedup of 1.16—1.44 compared to the baseline GPU implementation. The above optimization strategies were published in the International Conference on Computational Science 2020 [1]. This work extends the previously published research by carrying out the second phase of communication-centered optimizations in Hypre to improve its scalability on large-scale supercomputers. Additionally, this includes an efficient non-blocking inter-thread communication scheme, communication-reducing patch assignment, and expression of logical communication parallelism to a new version of the MPICH library that utilizes the underlying network parallelism [2]. The above optimizations avoid communication bottlenecks previously observed during strong scaling and improve performance by up to 2 on 256 nodes of Intel Knight's Landing processor.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Primal interface debonding formulation for finite strain isotropic plasticity

In this work, a framework is developed for modeling ductile damage of nonlinear materials whose plastic deformation is characterized using rate independent classical plasticity. This method relies on the assumption that the free energy can be decomposed into elastic, plastic and damage parts. A thermodynamically consistent method is derived which satisfies the second law of thermodynamics in the Clausius–Duhem inequality form. The dissipation associated with plasticity takes place in the domain only, while damage dissipation is localized to the interface. The method is developed using Variational Multiscale ideas to obtain definitions of the interface fluxes within a primal formulation analogous to the Discontinuous Galerkin method, which ensures weakly vanishing interface gap prior to reaching a damage initiation criterion. The local nonlinear problem to calculate both plastic deformation gradient and damage variable follows an incremental approach similar to classical plasticity return mapping algorithm. This elastoplastic damage formulation is developed for material undergoing finite strain, and it naturally accommodates a trapezoidal traction separation law (TSL) whose shape can be varied to model either ductile interface behavior or brittle interface behavior. The formulation's performance is assessed through modeling a patch test and a compact tension specimen.

42 ENGINEERING↗
DOE OSTI2022

NaroNet: Discovery of tumor microenvironment elements from highly multiplexed images

Understanding the spatial interactions between the elements of the tumor microenvironment -i.e. tumor cells. fibroblasts, immune cells- and how these interactions relate to the diagnosis or prognosis of a tumor is one of the goals of computational pathology. We present NaroNet, a deep learning framework that models the multi-scale tumor microenvironment from multiplex-stained cancer tissue images and provides patient-level interpretable predictions using a seamless end-to-end learning pipeline. Trained only with multiplex-stained tissue images and their corresponding patient-level clinical labels, NaroNet unsupervisedly learns which cell phenotypes, cell neighborhoods, and neighborhood interactions have the highest influence to predict the correct label. To this end, NaroNet incorporates several novel and state-of-the-art deep learning techniques, such as patch-level contrastive learning, multi-level graph embeddings, a novel max-sum pooling operation, or a metric that quantifies the relevance that each microenvironment element has in the individual predictions. We validate NaroNet using synthetic data simulating multiplex-immunostained images where a patient label is artificially associated to the -adjustable- probabilistic incidence of different microenvironment elements. We then apply our model to two sets of images of human cancer tissues: 336 seven-color multiplex-immunostained images from 12 high-grade endometrial cancer patients; and 382 35-plex mass cytometry images from 215 breast cancer patients. In both synthetic and real datasets, NaroNet provides outstanding predictions of relevant clinical information while associating those predictions to the presence of specific microenvironment elements.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Ultra-fast and sensitive magneto-optical hydrogen sensors using a magnetic nano-cap array

Magnetism in curved nano-geometries has opened a new path to design novel characteristics and phenomena that could greatly impact the future fundamental and applied studies of materials. Here, in this report, a hexagonally-packed array of magnetic nano-caps (or nano-patches, NP) exhibiting unique magnetic anisotropy and optimal nanostructure for fast hydrogen kinetics is explored as a sensing element for the spark-free magnetic-circular-dichroism (MCD) H 2 sensor. The MCD H 2 sensor outperforms the state-of-the-art optical sensors reported to date and satisfies the most challenging performance targets imposed by US Department of Energy. In particular, a Pd 67 Co 33 NP sensor exhibits response time of t 90 < 0.9 s, recovery time of t 10 < 9.0 s over the 1-100 mbar H 2 partial pressure range, and limit of detection (LOD) of ~1 ppm. The LOD improves to <700 ppb, when the signal-to-noise ratio is enhanced by stacking three NP arrays. Using a 30-nm TAF (Teflon AF 2400) polymer coating, the sorption kinetics of the Pd 67 Co 33 /TAF sensor are significantly accelerated, with t 90 < 0.4 s and t 10 < 2.8 s over the same pressure range. When the Pd 67 Co 33 /TAF sensor is further coated with a 100-nm poly(methyl methacrylate) (PMMA) layer, a rapid sorption time of t 90 < 0.5 s, LOD < 1 ppm and excellent sensor accuracy (<2.5% full scale) are maintained, while the sensor obtains strong selectivity against interference gases and moisture and a negligible aging effect. The MCD nano-cap sensor platform may have a great impact on the future deployment of H 2 fuel, H 2 environmental monitoring sensors, and fast proton-based magneto-ionic devices.

Fast and sensitive hydrogen sensors↗
DOE OSTI2021

Leaf-cutting ant (Atta cephalotes) nests may be hotspots of methane and carbon dioxide emissions in tropical forests

Leaf-cutting ants of the genus Atta are widely distributed throughout the American tropics and subtropics and rival other herbivores in the consumption of surrounding foliage. Although numerous studies have been conducted on the role these insects play in herbivory and organic matter dynamics, only a handful of studies have examined their impacts on soil greenhouse gas emissions. Our study investigated fluxes of carbon dioxide (CO 2 ) and methane (CH 4 ) from three nests of Atta cephalotes using a portable greenhouse gas analyzer, and measured CO 2 and CH 4 emissions from soils containing nest holes that ranged 5.2–152.1 g CO 2 -C and –1.1 to 15,264.7 mg CH 4 -C m -2 day -1 , respectively. Fluxes of CO 2 and CH 4 were positively correlated above nest holes, but not in patches of soil away from leaf-cutting ant nests. Nearby non-nest soil emissions were significantly lower, ranging from 0.6 to 6.0 g CO 2 -C and –1.3 to 0.77 mg CH 4 -C m -2 day -1 . Fluxes of both gases among nests and among holes within a single nest were highly variable. This preliminary dataset is small in scale both temporarily and geographically, but the discovery of substantial greenhouse gas fluxes from Atta cephalotes nests may have important implications for carbon budgets of tropical and subtropical American forests. Further work will be necessary to determine the mechanisms behind enhanced greenhouse gas emissions from leaf-cutting ant nests, and how this may alter ecosystem-scale CO 2 emissions and CH 4 sink strength in tropical forest soils.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Quality control and crop characterization framework for multi-temporal UAV LiDAR data over mechanized agricultural fields

Recent developments in remote sensing are enabling automatic, high resolution, and non-destructive survey of agriculture fields, providing the key basis for advancing plant breeding. Among the used remote sensing modalities, LiDAR has attracted wide attention for its ability to directly provide accurate 3D information. Despite the increasing utilization of LiDAR technology in phenotyping, there is still a lack of effective quality control strategies, in particular, quality control of LiDAR data collected on a multi-temporal basis. This study proposes a targetless framework for multi-temporal LiDAR data quality control and crop characterization in mechanized agricultural fields. Features extracted from the fields – terrain patches and row/alley locations – are utilized for evaluating the vertical and planimetric relative accuracy of the point clouds. Row/alley locations in the field are automatically identified from the point clouds based on the assumption that higher point density and/or higher elevation correspond to plant locations. The performance of the proposed quality control strategies is evaluated using multi-temporal datasets collected in agricultural fields of different sizes, orientation, crops, and growth stages. The result shows that the net vertical and planimetric discrepancies between multi-temporal point clouds are ±3 cm and ±8 cm, respectively. While the former reflects the actual accuracy of the point clouds, the latter is a combined effect of the LiDAR point cloud accuracy, rasterization artifacts, crop type, growth pattern, and wind condition during data acquisition. In terms of row and alley detection, the result shows that the proposed strategy achieves high performance and can deal with different planting orientation, crop types, growth stages, canopy cover, and planting density. In conclusion, this study presents a quality control framework for multi-temporal LiDAR data. Finally, the row and alley detection leads to automated extraction of plots, and hence facilitates the use of remotely sensed data for automated phenotyping.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

An ecologically-constrained deep learning model for tropical leaf phenology monitoring using PlanetScope satellites

In tropical forests, leaf phenology signals leaf-on/off status and exhibits considerable variability across scales from a single tree-crown to the entire forest ecosystem. Such phenology signals importantly regulate large-scale biogeochemical cycles and regional climate. PlanetScope CubeSats data with a 3-m resolution and near-daily global coverage provide an unprecedented opportunity to monitor both fine- and ecosystem-scale phenology variability along large environmental gradients. However, a scalable method that accurately characterizes leaf phenology from PlanetScope with biophysically meaningful metrics remains lacking. Here we developed an index-guided, ecologically constrained autoencoder (IG-ECAE) method to automatically derive a deciduousness metric (i.e. percentage of tree canopies with leaf-off status within an image pixel) from PlanetScope. The IG-ECAE first estimated the reflectance spectra of leafy/leafless canopies based on their spectral indices characteristics, then used the derived reflectance spectra to guide an autoencoder deep learning method with additional ecological constraints to refine the reflectance spectra, and finally used linear spectral unmixing to estimate the relative abundance of leafless canopies (or deciduousness) per PlanetScope image pixel. We tested the IG-ECAE method at 16 tropical forest sites spanning multiple continents and a large precipitation gradient (1470-2819 mm year -1 ). Among these sites, we evaluated the PlanetScope-derived deciduousness with corresponding measures derived from WorldView-2 (n=9 sites) and local phenocams (n=9 sites). Our results show that PlanetScope-derived deciduousness agrees: 1) with that derived from WorldView-2 at the patch level (90m×90m) with r 2 =0.89 across all sites; and 2) with that derived from phenocams to quantify ecosystem-scale seasonality with r 2 ranging from 0.62-0.96. These results demonstrate the effectiveness and scalability of IG-ECAE in characterizing the wide variability in deciduousness across scales from pixels to forest ecosystems, and from a single date to the full annual cycle, indicating the potential for using high-resolution satellites to track the large-scale phenological patterns and response of tropical forests to climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

The stability of FeH x and hydrogen transport at Earth’s core mantle boundary

Iron hydride in Earth’s interior can be formed by the reaction between hydrous minerals (water) and iron. Studying iron hydride improves our understanding of hydrogen transportation in Earth’s interior. Our high-pressure experiments found that face-centered cubic (fcc) FeH x (x≤1) is stable up to 165 GPa, and our ab initio molecular dynamics simulations predicted that fcc FeH x transforms to a superionic state under lower mantle conditions. In the superionic state, H-ions in fcc FeH become highly diffusive-like fluids with a high diffusion coefficient of ~3.7 × 10 -4 cm 2 s -1 , which is comparable to that in the liquid Fe-H phase. The densities and melting temperatures of fcc FeH x were systematically calculated. Similar to superionic ice, the extra entropy of diffusive H-ions increases the melting temperature of fcc FeH. Further, the wide stability field of fcc FeH enables hydrogen transport into the outer core to create a potential hydrogen reservoir in Earth’s interior, leaving oxygen-rich patches (ORP) above the core mantle boundary (CMB).

58 GEOSCIENCES↗
DOE OSTI2025

Tomographic assessment of peening for metallurgical bonding in cold spray

It is widely asserted that peening densifies cold spray coatings and improves particle–particle and particle–substrate bonding, yet systematic studies analyzing the evolution of bonding due to peening particle strikes are scarce. We explore peening at the level of individual particle impacts, by creating two-particle Cu-on-Cu stacks using laser-induced particle impact testing. Exploring impact velocities that range from the onset of bonding at the “critical velocity”, V cr , to its peak near 1.4⋅V cr , we perform full 3D tomography of the particle stacks to characterize the bonding state at the particle-substrate interface. Direct labeling of non-bonded patches and the total particle-substrate interface permits quantification and comparison of bonding in single impacts with bonding after subsequent impacts to reveal the origins of the peening effect. The data reveal a surprising finding: although a second impact directly atop the first particle increases the area of the particle-substrate interface (~40% area increase), there is no improvement in metallurgical bonding. Analysis of these data suggest that not only area expansion (and associated oxide rarefication), but also stress-induced extrusion of metal at that interface needs to occur to achieve metal-on-metal contact to see an enhancement in bonding. Furthermore, our analysis suggests that the subsequent impacting particle needs to have ~70% more kinetic energy to produce additional bonding; this implies that particle and velocity distributions within a spray may be helpful, and that peening may rely on unaligned impacts.

Bonding↗
DOE OSTI2020

A systematic strategy for estimating hERG block potency and its implications in a new cardiac safety paradigm

Introduction: hERG block potency is widely used to calculate a drug's safety margin against its torsadogenic potential. Previous studies are confounded by use of different patch clamp electrophysiology protocols and a lack of statistical quantification of experimental variability. Since the new cardiac safety paradigm being discussed by the International Council for Harmonisation promotes a tighter integration of nonclinical and clinical data for torsadogenic risk assessment, a more systematic approach to estimate the hERG block potency and safety margin is needed. Methods: A cross-industry study was performed to collect hERG data on 28 drugs with known torsadogenic risk using a standardized experimental protocol. A Bayesian hierarchical modeling (BHM) approach was used to assess the hERG block potency of these drugs by quantifying both the inter-site and intra-site variability. A modeling and simulation study was also done to evaluate protocol-dependent changes in hERG potency estimates. Results: A systematic approach to estimate hERG block potency is established. The impact of choosing a safety margin threshold on torsadogenic risk evaluation is explored based on the posterior distributions of hERG potency estimated by this method. The modeling and simulation results suggest any potency estimate is specific to the protocol used. Discussion: This methodology can estimate hERG block potency specific to a given voltage protocol. The relationship between safety margin thresholds and torsadogenic risk predictivity suggests the threshold should be tailored to each specific context of use, and safety margin evaluation may need to be integrated with other information to form a more comprehensive risk assessment.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

A quantitative assessment of the model form error of friction models across different interface representations for jointed structures

Hysteretic models are widely used to model frictional interactions in joints to recreate experimental behavior. However, it is unclear which models are best suited for fitting or predicting the responses of structures. Here, the present study evaluates 26 friction model/interface representation combinations to quantify the model form error. A Quasi-Static Modal Analysis approach (termed Rayleigh Quotient Nonlinear Modal Analysis) is adopted to calculate the nonlinear system response, and a Multi-Objective Optimization is solved to fit experimental data of the first mode of the Brake-Reuß Beam. Optimized parameters from the first mode are applied to the second and third bending modes to quantify the predictive ability of the models. Formulations for both tracing full hysteresis loops and recreating hysteresis loops from a single loading curve (Masing assumptions) are considered. Smoothly varying models applied to a five patch representation showed the highest flexibility (for fitting mode 1) and good predictive potential (for modes 2 and 3). For a second formulation, which uses 152 frictional elements to represent the interface, the physically motivated spring in series with a Coulomb slip model (elastic dry friction) has high error for fitting mode 1 and performs near the middle for predicting higher modes. For both interface representation, the best fit models are not the most physical, but rather the ones with the most parameters (as expected); however, the more physical models perform somewhat better for predicting the higher modes.

42 ENGINEERING↗
DOE OSTI2020

Zonally dominated dynamics and Dimits threshold in curvature-driven ITG turbulence

The saturated state of turbulence driven by the ion-temperature-gradient instability is investigated using a two-dimensional long-wavelength fluid model that describes the perturbed electrostatic potential and perturbed ion temperature in a magnetic field with constant curvature (a $Z$ -pinch) and an equilibrium temperature gradient. Numerical simulations reveal a well-defined transition between a finite-amplitude saturated state dominated by strong zonal-flow and zonal temperature perturbations, and a blow-up state that fails to saturate on a box-independent scale. We argue that this transition is equivalent to the Dimits transition from a low-transport to a high-transport state seen in gyrokinetic numerical simulations (Dimits et al. , Phys. Plasmas , vol. 7, 2000, 969). A quasi-static staircase-like structure of the temperature gradient intertwined with zonal flows, which have patch-wise constant shear, emerges near the Dimits threshold. The turbulent heat flux in the low-collisionality near-marginal state is dominated by turbulent bursts, triggered by coherent long-lived structures closely resembling those found in gyrokinetic simulations with imposed equilibrium flow shear (van Wyk et al. , J. Plasma Phys. , vol. 82, 2016, 905820609). The breakup of the low-transport Dimits regime is linked to a competition between the two different sources of poloidal momentum in the system – the Reynolds stress and the advection of the diamagnetic flow by the $\boldsymbol {E}\times \boldsymbol {B}$ flow. By analysing the linear ion-temperature-gradient modes, we obtain a semi-analytic model for the Dimits threshold at large collisionality.

Physics↗
DOE OSTI2024

Understanding Anomalous Gas-Phase Peak Shifts in Dip-and-Pull Ambient Pressure XPS Experiments

Dip-and-pull ambient pressure X-ray photoelectron spectroscopy (AP-XPS) holds promise to uncover elementary processes of (photo)electrochemistry. We show, however, that the sample for such experiments should preferably be nonporous and the potential on the surface homogeneous. We carried out dip-and-pull AP-XPS experiments on a hematite thin film sample under the photoelectrochemical oxygen evolution reaction (OER) and find unexpected O 1s core level shifts. Upon electrochemical biasing under simulated solar light illumination, the gas-phase water peak shifted more than the electrolyte peak. To uncover the origin of the unexpected larger shift of the gas-phase peak, we performed electrostatic simulations using COMSOL, to map the potential field in the relevant volume between the sample and the first aperture of the XPS spectrometer. A number of geometric models were considered. We find that when the potential on the sample surface is inhomogeneous, e.g., with ionically isolated electrolyte patches, the gas-phase peak of the spectrum can shift more than the peak due to the electrolyte film. This suggests that at the measured sample position, the local potential was not as set by the potentiostat. Despite this, we find reversible consumption and replenishment of hydroxide in the spectra, which, due to OH– being the reactant of the OER in alkaline electrolyte, makes sense chemically. We propose that this is linked to OH– diffusion across the measured sample position, driven by the potential dependent consumption and replenishment of OH– at the nearby well-connected surface regions.

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

Operando XPS for Plasma Process Monitoring: A Case Study on the Hydrogenation of Copper Oxide Confined under h-BN

Here, we demonstrate that ambient pressure x-ray photoelectron spectroscopy (APXPS) can be used for in situ studies of dynamic changes in surface chemistry in a plasma environment. This opens a new and vast application space for XPS and greatly complements modern spectroscopy techniques to probe plasma-solid/liquid interactions relevant to process monitoring in the semiconductor industry, bio-medical plasma applications and plasma remediation technologies. Hexagonal boron nitride (h-BN) grown on Cu was used in this study as a well-defined model system for plasma process monitoring and because of its unique chemical, optical and electrical properties that make it a prospective material for advanced electronics. To better understand the stability and surface chemistry of h-BN during plasma assisted processing, we track in real time the plasma-induced chemical state changes of B, N and the underlying Cu substrate using APXPS equipped with an AC discharge plasma source operating at 13 Pa. Residual gas analysis (RGA) mass-spectra were concurrently collected during plasma-XPS to track reaction products formed during plasma exposure. A clear reduction of Cu x O is seen, while an h-BN layer remains intact, suggesting hydrogen radical (H • ) species can attack the exposed and h-BN covered Cu oxide patches and partially reduce the underlying substrate without significantly damaging the overlaying h-BN, which is of practical importance for development of h-BN encapsulated devices and interfaces. In addition to demonstration of plasma-XPS capabilities we discuss the observed challenges (e.g., parasitic plasma-chamber walls reactions and charging effects) and propose potential solutions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗