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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Comparison of basin-scale in situ and meteoric 10 Be erosion and denudation rates in felsic lithologies across an elevation gradient at the George River, northeast Tasmania, Australia

Long-term erosion rates in Tasmania, at the south ern end of Australia’s Great Dividing Range, are poorly known; yet, this knowledge is critical for making informed land-use decisions and improving the ecological health of coastal ecosystems. Here, we present quantitative, geologically relevant estimates of erosion rates for the George River basin, in northeast Tasmania, based on in situ-produced 10 Be ( 10 Be i ) measured from stream sand at two trunk channel sites and seven tributaries (mean: 24.1 ± 1.4 Mg km -2 yr -1 ; 1σ). These new 10 Bei-based erosion rates are strongly related to elevation, which appears to control mean annual precipitation and temperature, suggesting that elevation-dependent surface processes influence rates of erosion in northeast Tas mania. Erosion rates are not correlated with slope in contrast to erosion rates along the mainland portions of Australia’s Great Dividing Range. We also extracted and measured meteoric 10 Be ( 10 Be m ) from grain coatings of sand-sized stream sediment at each site, which we normalize to measured concentrations of reactive 9 Be and use to estimate 10 Be m -based denudation rates for the George River. 10 Bem/ 9 Be reac denudation rates replicate 10 Be i erosion rates within a factor of 3 but are highly sensitive to the value of 9 Be that is found in bedrock ( 9 Be parent ), which was unmeasured in this study. 10 Bem/ 9 Be reac denudation rates seem sensitive to recent mining, forestry, and agricultural land use, all of which resulted in widespread topsoil disturbance. Our findings suggest that 10 Bem/ 9 Be reac denudation metrics will be most useful in drainage basins that are geologically homogeneous, where recent disturbances to topsoil profiles are minimal, and where 9 Be parent is well constrained.

58 GEOSCIENCES↗
DOE OSTI2023

A new method for detecting abrupt changes in the dependence among multivariate hydrological series based on moving cut total correlation

Knowledge of how to define and estimate the dependence among multivariate hydrological series is essential for detecting abrupt changes in the dependence. Here, in this paper, a new method (BMCTC) is proposed to detect all possible abrupt change points in the dependence among multivariate hydrological series. The total correlation estimated by the matrix-based Renyi's alpha-order entropy functional is firstly introduced to define and measure the dependence strength among multivariate hydrological series. Then, the moving cut total correlation (MCTC) sequence is built by the moving window technique, which is used to measure changes in the dependence strength among multivariate hydrological series. Finally, the Bernaola-Galvan algorithm is used to detect all change points of the MCTC sequence. Simulations are performed to compare the effectiveness of BMCTC with Pearson correlation (BMCPC) and Spearman correlation (BMCSC), Cramer-von Mises (CvM) and copula-based likelihood-ratio (CLR). The results show that all change points are detected by BMCTC regardless of the samples size, but wrong change points or no change points are detected by other methods in most cases. BMCTC is applied to detect change points in the dependence among annual runoff, precipitation and sediment discharge series in the Xiliugou and the Kuyehe River, China. It is found that the dependence among runoff, precipitation and sediment discharge changed abruptly in 1980 and 1996 in the Kuyehe River and in 1999 in the Xiliugou River. These changes are mainly caused by human activities such as construction of water conservancy projects and coal mining.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Cation and Anion Channelrhodopsins: Sequence Motifs and Taxonomic Distribution

Cation and anion channelrhodopsins (CCRs and ACRs, respectively) primarily from two algal species, Chlamydomonas reinhardtii and Guillardia theta, have become widely used as optogenetic tools to control cell membrane potential with light. We mined algal and other protist polynucleotide sequencing projects and metagenomic samples to identify 75 channelrhodopsin homologs from four channelrhodopsin families, including one revealed in dinoflagellates in this study. We carried out electrophysiological analysis of 33 natural channelrhodopsin variants from different phylogenetic lineages and 10 metagenomic homologs in search of sequence determinants of ion selectivity, photocurrent desensitization, and spectral tuning in channelrhodopsins. Our results show that association of a reduced number of glutamates near the conductance path with anion selectivity depends on a wider protein context, because prasinophyte homologs with a glutamate pattern identical to that in cryptophyte ACRs are cation selective. Desensitization is also broadly context dependent, as in one branch of stramenopile ACRs and their metagenomic homologs, its extent roughly correlates with phylogenetic relationship of their sequences. Regarding spectral tuning, we identified two prasinophyte CCRs with red-shifted spectra to 585 nm. They exhibit a third residue pattern in their retinal-binding pockets distinctly different from those of the only two types of red-shifted channelrhodopsins known (i.e., the CCR Chrimson and RubyACRs). In cryptophyte ACRs we identified three specific residue positions in the retinal-binding pocket that define the wavelength of their spectral maxima. Lastly, we found that dinoflagellate rhodopsins with a TCP motif in the third transmembrane helix and a metagenomic homolog exhibit channel activity. Channelrhodopsins are widely used in neuroscience and cardiology as research tools and are considered prospective therapeutics, but their natural diversity and mechanisms remain poorly characterized. Genomic and metagenomic sequencing projects are producing an ever-increasing wealth of data, whereas biophysical characterization of the encoded proteins lags behind. In this study, we used manual and automated patch clamp recording of representative members of four channelrhodopsin families, including a family in dinoflagellates that we report in this study. Our results contribute to a better understanding of molecular determinants of ionic selectivity, photocurrent desensitization, and spectral tuning in channelrhodopsins.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

From microbial diversity to functional potential using dimensionality reduction

The high dimensionality of microbial diversity data from ‘omics observations can be reduced using Machine Learning, with many recent studies showcasing ML utility for exploratory ecological feature finding and process prediction. Here, we compare the Self Organizing Map (SOM) dimensionality reduction method to the well-documented sample-based Principal Coordinate Analysis (PCoA) and taxa-based Weighted Gene Correlation Network Analysis (WGCNA) using near daily 16S rRNA gene amplicon sequencing data from the 2019 to 2020 MOSAiC International Arctic Drift Expedition. We then map k-means clustering outputs from each method to available metagenomes, extracting functionally distinct seasonal microbial ecotypes in the surface Arctic Ocean. Our results indicate the SOM method better represented expected seasonal transitions and identified a greater number of metabolically distinct functional groups than the more traditional PCoA ordination. Ultimately, we identified four community ecotypes with distinct taxonomic and functional cut-offs driven by seasonality, water mass, and substrate turnover, highlighting the importance of succession in functional diversity for the central Arctic Ocean. These results reinforce ML dimensionality reduction as a meaningful translator in the mining of historical amplicon datasets to address modern mechanistic questions and potentially provide ’omics informed ecotype diversity to leverage in mechanistic biogeochemical models.

Arctic Ocean↗
DOE OSTI2023

Determining best practices for using genetic algorithms in molecular discovery

Genetic algorithms (GAs) are a powerful tool to search large chemical spaces for inverse molecular design. However, GAs have multiple hyperparameters that have not been thoroughly investigated for chemical space searches. In this tutorial, we examine the general effects of a number of hyperparameters, such as population size, elitism rate, selection method, mutation rate, and convergence criteria, on key GA performance metrics. Here, we show that using a self-termination method with a minimum Spearman’s rank correlation coefficient of 0.8 between generations maintained for 50 consecutive generations along with a population size of 32, a 50% elitism rate, three-way tournament selection, and a 40% mutation rate provides the best balance of finding the overall champion, maintaining good coverage of elite targets, and improving relative speedup for general use in molecular design GAs.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Digging deeper for new physics in the LHC data

In this paper, we describe a novel, model-independent technique of “rectangular aggregations” for mining the LHC data for hints of new physics. A typical (CMS) search now has hundreds of signal regions, which can obscure potentially interesting anomalies. Applying our technique to the two CMS jets+MET SUSY searches, we identify a set of previously overlooked ~3σ excesses. Among these, four excesses survive tests of inter-and intra-search compatibility, and two are especially interesting: they are largely overlapping between the jets+MET searches and are characterized by low jet multiplicity, zero b -jets, and low MET and H T . We find that resonant color-triplet production decaying to a quark plus an invisible particle provides an excellent fit to these two excesses and all other data — including the ATLAS jets+MET search, which actually sees a correlated excess. We discuss the additional constraints coming from dijet resonance searches, monojet searches and pair production. Based on these results, we believe the wide-spread view that the LHC data contains no interesting excesses is greatly exaggerated.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

An Analysis of Possible Salt Fall Events in Historical Pressure Data from the U.S. Strategic Petroleum Reserve

The U.S. Strategic Petroleum Reserve (SPR) stores crude oil in underground storage caverns that have been solution mined from salt domes. Salt falls from the sides or top of a cavern pose a potential threat to cavern and well integrity and to operational readiness. Underground storage caverns require a suspended casing, or hanging string, to extend into the bottom part of the cavern for brine injection in order to remove oil from the top of the cavern; salt falls can break hanging strings, leaving the cavern inaccessible until a well workover is performed to replace or extend the string. Detecting salt falls is difficult, as string breaks may not occur and surface pressure signals are similar to operationally induced signals. SONAR based detection is possible, but SONAR surveys are expensive and conducted infrequently. Historical records from the SPR were examined to look for possible correlations to geographic or operational causes. A library of salt fall and operational signals was developed and three case studies are presented.

02 PETROLEUM↗
DOE OSTI2022

Uptake and speciation of trace metal inputs to Wetland Soils from Illinois and South Carolina and Stream Sediments from Tennessee

Metals occur in all ecosystems, although their concentrations vary depending on their natural geologic conditions and surrounding human activities. In addition to metals intrinsically present from the geology of a particular system, metals can enter environmental systems from a wide variety of natural and anthropogenic sources, such as sediment re-suspension, mining operations, industrial processes, agricultural activities, and atmospheric deposition. While metals can be toxic at high concentrations, some metals serve as essential micronutrients for biogeochemical processes. Metal transport and availability in engineered and natural water systems depend on processes of adsorption/desorption, oxidation/reduction, dissolution/precipitation, and ligand complexation. Insights into the speciation of metals and their bioavailability will also help advance understanding of the roles of metals in the biogeochemical cycling of nutrients. We conducted batch experiments under anoxic conditions on soils and sediments collected from three different natural aquatic systems to understand their response to influxes of dissolved Cu, Ni and Zn. While soils and sediments from all sites could strongly bind added trace metals, there were substantial differences in trace metal uptake trends between different sites, especially for Cu. There was no distinct correlation between trace metal uptake and the total organic matter, iron, and sulfur content present in the samples. X-ray absorption spectroscopy indicated that the speciation of the freshly added metals taken up by the solids differs substantially from the speciation of the metals originally present in unamended samples. Cu sulfides dominated speciation at low loadings (1 µmol/g), whereas complexation to thiol groups and formation of metallic Cu governed speciation at high loadings (10 µmol/g). For Ni and Zn, adsorption to mineral surfaces and organic matter governed their speciation in materials from most sites. This study suggests that the background speciation of metals in natural aquatic systems is a poor predictor of the speciation and lability of metals introduced to terrestrial aquatic systems from anthropogenic or natural processes. Our findings imply that geochemical processes controlling trace metal speciation may vary considerably with metal loading in different natural systems. Data are provided for marsh wetland soils at Argonne National Laboratory (Marsh 1 and Marsh 2), riparian wetland soils (Riparian 1 and Riparian 2) in the Tims Branch watershed at Savannah River National Laboratory, and stream bed sediments (Stream 1 and Stream 2) from East Fork Poplar Creek near Oak Ridge National Laboratory. Data package includes the results of trace metal uptake experiments conducted on the selected sites for determining their capacity to immobilize metals under different loadings. XANES spectra for Cu, Ni, ad Zn at different loadings are included in the package. The abundance of different trace metal species obtained using linear combination fitting in ATHENA are also included in the data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Bulk-scale stress–strain hysteresis in layered crystalline solids: A study of graphite and Ti 3 SiC 2

Polycrystalline graphite and the MAX phase Ti 3 SiC 2 are layered crystalline solids with similar deformation mechanisms, including basal slip, ripplocation boundaries (RBs), kink boundaries (KBs), and cracking. The interplay of these mechanisms, notably in energy dissipation, has been much discussed in the past twenty-five years. This study builds upon previous work, investigating deformation with a renewed emphasis on the bulk-scale and given recent findings concerning RBs. Our investigation compares the evolution of energy dissipation, nonlinear recoverable and irrecoverable strain, and damage upon increasing stress for graphite and Ti 3 SiC 2 . Benitez et al.’s (2016) methodology of compressive cyclic loading and post-mortem electron backscatter diffraction (EBSD) to assess the prevalence of kinking based on low-angle grain boundaries (LAGBs) was used. Strains were measured with digital image correlation and EBSD was conducted on Ti 3 SiC 2 leveraging dictionary indexing, which was necessary herein to identify LAGBs accurately. The stress–strain stages of Ti 3 SiC 2 agree with literature on Ti 2 AlC. Damage and energy dissipation were more accelerated in graphite. No significant difference was observed in the fraction of LAGBs between pristine and unloaded Ti 3 SiC 2 . Trends observed and EBSD evidence that KBs were not dominant suggest that RBs are the primary dissipator of energy in both materials.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Screening IMS Seismic Detections using Dynamic Correlation Processor: Progress report for 2020

LLNL completed the FY20 workplan entailing application of the Dynamic Correlation Processor (DCP) to International Monitoring System (IMS) primary seismic data in 2019 and 2020. The effective analysis period was curtailed to January 1 through November 12, 2019 due to a data compression change that rendered later data unusable. Fixing the data compression error is a priority for our data source, and we plan to extend the period of data analysis when the fix is implemented. We found that the percentage overlap between detections generated by the International Data Centre (IDC) DFX software and detections generated by DCP varied widely by station. Overlap is 30-40% at some stations, suggesting that a large percentage of DFX detections could be screened (removed) from the detection-event association algorithm. However, detection overlap was much lower, a few percent, at many stations and the percentage overlap was low at stations known to have many mines and other local sources of seismicity. Unexpectedly low detection overlap at many stations prompted us to examine results for the ARCES station in detail. There is considerable mine activity near ARCES, but our initial FY20 analysis found only ~2% DCP/DFX detection overlap. Differences in the pre-processing (e.g. beam recipes) used by DCP and DFX appear to be the cause of low detection overlap at ARCES. DCP uses wideband filters to improve detector robustness and the IDC uses narrow-band pre-filtering to improve sensitivity. After reprocessing ARCES using the IDC beam recipe, DCP/DFX overlap increased to ~74%. This result shows that we must reprocess the IMS network using the IDC station-specific beam recipes if we are to effectively screen DFX detections and improve automatic event building performance at the IDC.

58 GEOSCIENCES↗
NASA NTRS2004

Virtual Sensors: Using Data Mining Techniques to Efficiently Estimate Remote Sensing Spectra

Various instruments are used to create images of the Earth and other objects in the universe in a diverse set of wavelength bands with the aim of understanding natural phenomena. These instruments are sometimes built in a phased approach, with some measurement capabilities being added in later phases. In other cases, there may not be a planned increase in measurement capability, but technology may mature to the point that it offers new measurement capabilities that were not available before. In still other cases, detailed spectral measurements may be too costly to perform on a large sample. Thus, lower resolution instruments with lower associated cost may be used to take the majority of measurements. Higher resolution instruments, with a higher associated cost may be used to take only a small fraction of the measurements in a given area. Many applied science questions that are relevant to the remote sensing community need to be addressed by analyzing enormous amounts of data that were generated from instruments with disparate measurement capability. This paper addresses this problem by demonstrating methods to produce high accuracy estimates of spectra with an associated measure of uncertainty from data that is perhaps nonlinearly correlated with the spectra. In particular, we demonstrate multi-layer perceptrons (MLPs), Support Vector Machines (SVMs) with Radial Basis Function (RBF) kernels, and SVMs with Mixture Density Mercer Kernels (MDMK). We call this type of an estimator a Virtual Sensor because it predicts, with a measure of uncertainty, unmeasured spectral phenomena.

Srivastava, Ashok N.↗
DOE OSTI2019

Temporal multispectral and 3D analysis of Cerro de Pasco, Peru

Mining operations across the world often lead to contamination of land, water resources, ecosystems and in some cases, entire communities.Results of recent health and ground sampling studies revealed extensive lead contamination within the populace and around the City of Cerro de Pasco, Peru. Tailings excavated from a large open pit zinc mine in the center of the city have been aggregated in four large stockpiles within close proximity to neighborhoods, schools, and hospitals. Visual comparison of ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) imagery from 2001 and Sentinel-2 imagery from 2018 suggests a size increase in one tailing stockpile in particular near the neighborhood of Paragsha. Due to ongoing mining efforts, the hypothesis motivating the work presented here is that Pb-bearing minerals would be detectable through multispectral analysis, an increase in Pb mineral percent abundance would be observed and tailing stockpile volume would be detectable between 2001 and 2016. This hypothesis is tested using Spectral Angle Mapper (SAM), Adaptive Coherence Estimator (ACE), and Jeffries-Matusita distance calculation on ASTER (2001) and Sentinel-2 (2018) VNIR and SWIR bands. Volume and area estimate of tailing stockpiles were calculated using a photogrammetrically derived point cloud. SAM detected the presence of five Pb-bearing minerals around Cerro de Pasco and Paragsha. The results of the temporal SAM analysis displayed an increase of approximately 17% of Pb-bearing minerals around the greater Cerro de Pasco city area and approximately 11% for the neighborhood of Paragsha. Jeffries-Matusita distance results suggest clear correlation between contamination sources and affected locations. Total tailing stockpile volume was measured to be approximately 200,300,000 m 3 . Volume for Pile 4 was estimated to have increased by approximately 46,000,000 m 3 between 2001 and 2018. Lastly, these presented results will hopefully inspire and guide future remote sensing campaigns, perhaps involving a UAV or aircraft-based hyperspectral instrument.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Prediction of defect properties in concentrated solid solutions using a Langmuir-like model

The alleged existence of sluggish diffusion in high-entropy alloys has drawn controversy. In high-entropy alloys and, in general, in all solids, transport properties are controlled by point defect concentration, which must be known before performing atomistic simulations to compute transport coefficients. In this work, we present a general Langmuir-like model for defect concentration in an arbitrarily complex solid solution and apply this model to generate expressions for concentrations of vacancies and small interstitial atoms. We then calculate the vacancy concentration as a function of temperature in the equiatomic CoNiCrFeMn and FeAl alloys with modified embedded-atom-method potentials for various chemical orderings, showing there is no clear correlation between vacancy thermodynamics and chemical ordering in the CoNiCrFeMn alloy, but clear systematic patterns for FeAl. We believe this is due to the high stability of disordered, random, and ordered intermetallic phases, respectively, in the CoNiCrFeMn and FeAl systems. Finally, this work provides future avenues to the prediction of thermal interstitials and vacancies in solid solutions, which is necessary for models of nonequilibrium behavior of solid solutions.

composition↗
DOE OSTI2017

Identifying Rare Earth Elements and Thorium and Uranium in Iron Oxide–Apatite Deposit of Gazestan Bafgh, Southeast of Iran

The Gazestan magnetite-apatite deposit is one of Kiruna-type deposits located 78 km from Bafgh in the province of Yazd, in the Bafgh Posht-e-Badam district, southeast of Iran. In the mining region of Bafgh, volcanic rocks and Precambrian volcano-sedimentary are the main host of iron-apatite deposits. Iron deposits are essentially located in Bafgh region inside the green acidic metamorphic rocks. Volcanic rocks are basically rhyolite and rhyodacitic and the sedimentary units are mostly made of dolomite. Rock units of the region belong to the Rizzo series. The Bafgh apatite compounds are fluoride-type and seen in the monazite mineral. The similarity of the rare earth elements pattern in all samples indicates the magma source. The most amount of rare earth elements in the Gazestan deposit include 7766.25 ppm and the most amount of Th is equal to 65.1 ppm and U is equal to 8.33 ppm. The most amount of P2O5 s equal to 26.5 wt% and Fe is equal to 61.3 wt%. Also, it can be concluded that due to their high correlation with rare earth elements, the deposit is of Uranium Thorium-bearing type.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

AI-powered topic modeling: comparing LDA and BERTopic in analyzing opioid-related cardiovascular risks in women

Topic modeling is a crucial technique in natural language processing (NLP), enabling the extraction of latent themes from large text corpora. Traditional topic modeling, such as Latent Dirichlet Allocation (LDA), faces limitations in capturing the semantic relationships in the text document although it has been widely applied in text mining. BERTopic, created in 2022, leveraged advances in deep learning and can capture the contextual relationships between words. In this work, we integrated Artificial Intelligence (AI) modules to LDA and BERTopic and provided a comprehensive comparison on the analysis of prescription opioid-related cardiovascular risks in women. Opioid use can increase the risk of cardiovascular problems in women such as arrhythmia, hypotension etc. 1,837 abstracts were retrieved and downloaded from PubMed as of April 2024 using three Medical Subject Headings (MeSH) words: “opioid,” “cardiovascular,” and “women.” Machine Learning of Language Toolkit (MALLET) was employed for the implementation of LDA. BioBERT was used for document embedding in BERTopic. Eighteen was selected as the optimal topic number for MALLET and 23 for BERTopic. ChatGPT-4-Turbo was integrated to interpret and compare the results. The short descriptions created by ChatGPT for each topic from LDA and BERTopic were highly correlated, and the performance accuracies of LDA and BERTopic were similar as determined by expert manual reviews of the abstracts grouped by their predominant topics. The results of the t-SNE (t-distributed Stochastic Neighbor Embedding) plots showed that the clusters created from BERTopic were more compact and well-separated, representing improved coherence and distinctiveness between the topics. Our findings indicated that AI algorithms could augment both traditional and contemporary topic modeling techniques. In addition, BERTopic has the connection port for ChatGPT-4-Turbo or other large language models in its algorithm for automatic interpretation, while with LDA interpretation must be manually, and needs special procedures for data pre-processing and stop words exclusion. Therefore, while LDA remains valuable for large-scale text analysis with resource constraints, AI-assisted BERTopic offers significant advantages in providing the enhanced interpretability and the improved semantic coherence for extracting valuable insights from textual data.

Research & Experimental Medicine↗
NASA NTRS1989

Transonic aeroelasticity analysis for rotor blades

A numerical method is presented for calculating the unsteady transonic rotor flow with aeroelasticity effects. The blade structural dynamic equations based on beam theory were formulated by FEM and were solved in the time domain, instead of the frequency domain. For different combinations of precone, droop, and pitch, the correlations are very good in the first three flapping modes and the first twisting mode. However, the predicted frequencies are too high for the first lagging mode at high rotational speeds. This new structure code has been coupled into a transonic rotor flow code, TFAR2, to demonstrate the capability of treating elastic blades in transonic rotor flow calculations. The flow fields for a model-scale rotor in both hover and forward flight are calculated. Results show that the blade elasticity significantly affects the flow characteristics in forward flight.

Chow, Chuen-Yen↗
NASA NTRS2002

The 1999 Hector Mine Earthquake, Southern California: Vector Near-Field Displacements from ERS InSAR

Two components of fault slip are uniquely determined from two line-of-sight (LOS) radar interferograms by assuming that the fault-normal component of displacement is zero. We use this approach with ascending and descending interferograms from the ERS satellites to estimate surface slip along the Hector Mine earthquake rupture. The LOS displacement is determined by visually counting fringes to within 1 km of the outboard ruptures. These LOS estimates and uncertainties are then transformed into strike- and dip-slip estimates and uncertainties; the transformation is singular for a N-S oriented fault and optimal for an E-W oriented fault. In contrast to our previous strike-slip estimates, which were based only on a descending interferogram, we now find good agreement with the geological measurements, except at the ends of the rupture. The ascending interferogram reveals significant west-sidedown dip-slip (approximately 1.0 m) which reduces the strike-slip estimates by 1 to 2 m, especially along the northern half of the rupture. A spike in the strike-slip displacement of 6 m is observed in central part of the rupture. This large offset is confirmed by subpixel cross correlation of features in the before and after amplitude images. In addition to strike slip and dip slip, we identify uplift and subsidence along the fault, related to the restraining and releasing bends in the fault trace, respectively. Our main conclusion is that at least two look directions are required for accurate estimates of surface slip even along a pure strike-slip fault. Models and results based only on a single look direction could have major errors. Our new estimates of strike slip and dip slip along the rupture provide a boundary condition for dislocation modeling. A simple model, which has uniform slip to a depth of 12 km, shows good agreement with the observed ascending and descending interferograms.

Sandwell, David T.↗
DOE OSTI2026

Unravelling chemical pathways of H 2 on Ga 2 O 3 surfaces with spectro-electrochemistry

This work highlights the capability of coupled spectroscopic and electrochemical techniques to probe dynamic surface processes under realistic operating conditions. By simultaneously employing in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) and electrochemical impedance spectroscopy (EIS), we elucidate the mechanistic interaction between Ga 2 O 3 and hydrogen under elevated temperatures in a low-oxygen environment. This novel spectro-electrochemical approach allows chemistry to be correlated with the surface charge density of Ga 2 O 3 . Our results reveal a concentration-dependent transition in reaction pathway. At low concentrations, hydrogen reacts with ambient oxygen to form surface hydroxyls. At intermediate concentrations, hydrogen interacts with surface adsorbed oxygen to generate hydroxyl groups along with reducing the surface. Finally, at high H 2 concentrations, hydrogen reduces both hydroxyls and surface oxygen, leading to a highly conductive grain surface. As a result, hydrides form on the reduced Ga 2 O 3 surface. The gained insights are relevant for heterogeneous catalysis and gas sensing.

08 HYDROGEN↗