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NASA NTRS1994

LSENS, A General Chemical Kinetics and Sensitivity Analysis Code for Homogeneous Gas-Phase Reactions: Code Description and Usage - Part 2

LSENS, the Lewis General Chemical Kinetics and Sensitivity Analysis Code, has been developed for solving complex, homogeneous, gas-phase chemical kinetics problems and contains sensitivity analysis for a variety of problems, including nonisothermal situations. This report is part II of a series of three reference publications that describe LSENS, provide a detailed guide to its usage, and present many example problems. Part II describes the code, how to modify it, and its usage, including preparation of the problem data file required to execute LSENS. Code usage is illustrated by several example problems, which further explain preparation of the problem data file and show how to obtain desired accuracy in the computed results. LSENS is a flexible, convenient, accurate, and efficient solver for chemical reaction problems such as static system; steady, one-dimensional, inviscid flow; reaction behind incident shock wave, including boundary layer correction; and perfectly stirred (highly backmixed) reactor. In addition, the chemical equilibrium state can be computed for the following assigned states: temperature and pressure, enthalpy and pressure, temperature and volume, and internal energy and volume. For static problems the code computes the sensitivity coefficients of the dependent variables and their temporal derivatives with respect to the initial values of the dependent variables and/or the three rate coefficient parameters of the chemical reactions. Part I (NASA RP-1328) derives the governing equations and describes the numerical solution procedures for the types of problems that can be solved by LSENS. Part III (NASA RP-1330) explains the kinetics and kinetics-plus-sensitivity-analysis problems supplied with LSENS and presents sample results.

Radhakrishnan, Krishnan↗
DOE OSTI2025

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

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

Additive manufacturing↗
NASA NTRS2011

The Invasive Species Forecasting System

The Invasive Species Forecasting System (ISFS) provides computational support for the generic work processes found in many regional-scale ecosystem modeling applications. Decision support tools built using ISFS allow a user to load point occurrence field sample data for a plant species of interest and quickly generate habitat suitability maps for geographic regions of management concern, such as a national park, monument, forest, or refuge. This type of decision product helps resource managers plan invasive species protection, monitoring, and control strategies for the lands they manage. Until now, scientists and resource managers have lacked the data-assembly and computing capabilities to produce these maps quickly and cost efficiently. ISFS focuses on regional-scale habitat suitability modeling for invasive terrestrial plants. ISFS s component architecture emphasizes simplicity and adaptability. Its core services can be easily adapted to produce model-based decision support tools tailored to particular parks, monuments, forests, refuges, and related management units. ISFS can be used to build standalone run-time tools that require no connection to the Internet, as well as fully Internet-based decision support applications. ISFS provides the core data structures, operating system interfaces, network interfaces, and inter-component constraints comprising the canonical workflow for habitat suitability modeling. The predictors, analysis methods, and geographic extents involved in any particular model run are elements of the user space and arbitrarily configurable by the user. ISFS provides small, lightweight, readily hardened core components of general utility. These components can be adapted to unanticipated uses, are tailorable, and require at most a loosely coupled, nonproprietary connection to the Web. Users can invoke capabilities from a command line; programmers can integrate ISFS's core components into more complex systems and services. Taken together, these features enable a degree of decentralization and distributed ownership that have helped other types of scientific information services succeed in recent years.

Schnase, John↗
DOE OSTI2025

Validating sequential Monte Carlo for gravitational-wave inference

Nested sampling (NS) is the preferred stochastic sampling algorithm for gravitational-wave inference for compact binary coalescences. It can handle the complex nature of the gravitational-wave likelihood surface and provides an estimate of the Bayesian model evidence. However, there is another class of algorithms that meets the same requirements, but has not been used for gravitational-wave analyses: sequential Monte Carlo (SMC), an extension of importance sampling that maps samples from an initial density to a target density via a series of intermediate densities. In this work, we validate a type of SMC algorithm, called persistent sampling (PS), for gravitational-wave inference. We consider a range of different scenarios including binary black holes and binary neutron stars and real and simulated data and show that PS produces results that are consistent with NS whilst being, on average, 2 times more efficient and 2.74 times faster. This demonstrates that PS is a viable alternative to NS that should be considered for future gravitational-wave analyses.

black hole mergers↗
NASA NTRS1999

Thorium Enrichment within the Procellarum KREEP Terrane: The Record in Surface Deposits and Significance for Thermal Evolution

The nearside-farside structural and compositional asymmetry of the Moon was recognized during the early days of Apollo and the suggestion was made that the migration of mantle melts to the nearside would have been favored by early Earth-Moon orbital dynamics and nonuniform planetesimal bombardment. Recent global geochemical mapping by Lunar Prospector has provided additional data, particularly in the Th distribution, that strongly supports the notion of global, preferential melt migration, which led in part to the development of the Procellarum KREEP Terrane (PKT) [2-5]. The surface distribution of Th was then reshaped by basin-forming impacts into the PKT, especially the Imbrium impact, which was the last and largest to strike in that region. The Imbrium event probably excavated material from a partially molten zone deep in the crust and delivered Th-rich ejecta Moon-wide. A fundamentally important but poorly understood aspect of the global Th distribution is the concentration of Th in the subsurface rocks of the PKT crustal section. For example, depending on what assumptions are made, the PKT crustal section, which is about 12% of the crust and only about 1.2% of the whole Moon, may contain as much as 40% of the Moon's entire Th budget. Such a distribution of Th and related heat-producing elements would have had a profound effect on melting, mixing, and the thermal evolution of the PKT and the underlying mantle. In this abstract, we examine the compositions of terra formations within the PKT and relate them to some of the Th-bearing rock types known from the Apollo samples. It appears that the existence of the PKT may be a unifying concept for a number of petrologic and geochemical observations. From the initial Lunar Prospector gamma-ray spectrometer data(-about 5 deg. resolution) and from the preliminary low-orbit data, there appears to be a number of relatively hotter "spots" within the PKT in terms of Th concentration. Some of the hotter spots correspond to intermediate-sized craters that penetrated volcanic flows and excavated Th-rich, submare material, such as Aristarchus, Aristillus, and Kepler. Other spots, however, correspond to surficial formations that constitute mainly rough topography associated with Imbrium ejecta or circum-Imbrium ring mountains and do not necessarily imply the presence of exposed KREEP basalts. The Fra Mauro Formation south of Copernicus toward the Apollo 14 site and regions of the Alpes Formation southwest of Copernicus in the vicinity of Reinhold lie within the most prominent hotspot; here them concentration is consistent with that found in the Apollo 14 soils (about 12-13 ppm) when the proportions of Fra Mauro Formation and mare basalt are considered. The area between Copernicus and Kepler and northwest of Copernicus in terra extending to the Carpathians is similarly enriched in Th. The Apennines from Eratosthenes toward the Apollo 15 site contain elevated Th concentrations, as does the northwestern quadrant of circum-Imbrium terra, especially between (but not including) La Condamine and Plato, and in the region northwest of the Jura mountains extending southward past Mairan to the Gruithuisen-Domes region. Within the main topographic rim of Imbrium, the Apennine Bench formation south of Archimedes appears to have relatively elevated Th concentration. Comparing the map of Th distribution to a digital-elevation map derived from Clementine altimetry, it appears that most of the areas richest in Th occur where the surface is elevated relative to the majority of PKT volcanic plains. Not all rough topography within the PKT has such elevated Th, however. Based on an analysis of the 5 deg. data, and using the calibration of, the mean Th concentrations for mainly volcanic-resurfaced terrain and rugged terrain are similar (about 5.5 ppm). This occurs in part because craters that penetrated mare basalt excavated Th-rich material. Even so, there appear to be extensive areas of volcanic resurfacing that have no obvious extrinsic source of Th-rich material, suggesting that the basalts, themselves, may contain as much as 5-6 ppm Th. High-FeO concentrations (18 to >20 wt%) indicate that these are not KREEP basalts but mare basalts. If so, this is surprising because most of the Apollo-sampled mare basalts have very low-Th (typically <2 ppm). A variety of Th-rich materials occur in the sample collection, particularly in the samples from the Apollo 12,14, and 15 sites. The most abundant Th-rich rock types are the mafic impact-melt breccias, which although found at all sites, are most abundant at Apollo 14, where they dominate the rock samples and make up some 40% of the rock particles in the soil. These have Th concentrations ranging up to about 30 ppm and averaging about 18 ppm. The Apollo 14 soils contain about 13 ppm Th, reflecting the high abundance of this melt-breccia component. At the nearby Apollo 12 site, the rocks consist mainly of mare basalts, and these have low-Th concentrations, mostly <1 ppm. Among the nonmare rocks, however, a few such as complex breccia 12013 contain a variety of evolved lithologies and represent potential sources of Th-rich components ranging from 17 to 50 ppm. A single fragment of KREEP basalt from the Apollo 12 soil contains about 50 ppm Th. Despite the identification of highly Th-enriched lithologic components at the Apollo 12 site, the soils there vary linearly in composition so as to extrapolate to a moderate Th KREEP-basalt component or a composition like that of the Fra Mauro formation as reflected by Apollo 14 soil (14 ppm Th at 10 wt% FeO). The nearby Lansberg Crater (39-km diameter) is a likely candidate to have delivered submare material such as buried Fra Mauro or Alpes material to the Apollo 12 site. Additional information contained in the original.

Jolliff, B. L.↗
NASA NTRS2017

Correlations Among Microstructure, Morphology, Chemistry, and Isotopic Systematics of Hibonite in CM Chondrites

Introduction: Hibonite is a primary refractory phase occurring in many CAIs, typically with spinel and perovskite. Our microstructural studies of CAIs from carbonaceous chondrites reveal a range of stacking defect densities and correlated non-stoichiometry in hibonite. We also conducted a series of annealing experiments, demonstrating that the Mg-Al substitution stabilized the formation of defect-structured hibonite. Here, we continue a detailed TEM analysis of hibonite-bearing inclusions from CM chondrites that have been well-characterized isotopically. We examine possible correlations of microstructure, morphology, mineralogy, and chemical and isotopic systematics of CM hibonites in order to better understand the formation history of hibonite in the early solar nebula. Methods: Fifteen hibonite-bearing inclusions from the Paris CM chondrite were analyzed using a JEOL 7600F SEM and a JEOL 8530F electron microprobe. In addition to three hibonite-bearing inclusions from the Murchison CM chondrite previously reported, we selected three inclusions from Paris, Pmt1-6, 1-9, and 1-10, representing a range of 26Al/27Al ratios and minor element concentrations for a detailed TEM study. We extracted TEM sections from hibonite grains using a FEI Quanta 3D field emission gun SEM/FIB. The sections were then examined using a JEOL 2500SE field-emission scanning TEM equipped with a Thermo-Noran thin window EDX spectrometer. Results and Discussion: A total of six hibonite-bearing inclusions, including two platy hibonite crystals (PLACs) and four spinel-hibonite inclusions (SHIBs), were studied. There are notable differences in chemical and isotopic compositions between the inclusions (Table 1), indicative of their different formation environment or timing. Our TEM observations show perfectly-ordered, stoichiometric hibonite crystals without stacking defects in two PLACs, 2-7-1 and 2-8-2, and in three SHIBs, Pmt1-6, 1-9, and 1-10. In contrast, SHIB 1-9-5 hibonite grains contain a low density of stacking defects linked to an increase in MgO contents, indicating complex, disordered intergrowths of stoichiometric and MgO-enriched hibonites. From the data collected to date, we find no clear correlation between the microstructures of hibonite and its morphological and mineralogical types that reflect distinct chemical and isotopic systematics [6-8,10]. Interestingly, the presence of no or few stacking defects in hibonite from the PLACs and SHIBs are in contrast to our experimental studies that produced very high densities of stacking defects in hibonite [3-5]. Unlike our experi-ments, electron microprobe data from the PLACs and SHIBs hibonite grains show a strong correlation between (Ti4++Si4+) and Mg2+ cations, suggesting that coupled substitutions of (Ti4++Mg2+) and (Si4++Mg2+) for 2Al3+ inhibit the formation of defect-structured hibonite. However, our experimental studies suggest that kinetics (e.g., cooling rate) or other thermal effects also exert a strong control on the microstructures and chemical compositions of hibonite. In Pmt1-6, elongated perovskite grains present at the hibonite grain boundaries display (121) twinning, indicative of a fast cooling (>50degC/min) after high-temperature events. Therefore, the nebular microstructural characteristics of hibonite, at least in this inclusion, would not have destroyed by subsequent high-temperature annealing. Conclusions: Our TEM observations thus far show no clear correlation in microstructures, morphological and mineralogical characteristics, and chemical and isotopic systematics of hibonites from CM chondrites. The observed variation in stacking defect densities in the hibonites may be controlled by thermal processes in the early solar nebula. A detailed TEM analysis of additional CM hibonite samples is underway to evaluate this hypothesis.

Han, J.↗
DOE OSTI2019

Comparative Study of the Nernst–Ettingshausen Coefficient in the Normal Phase in the Y{sub 1 –} {sub x}Pr{sub x}Ba{sub 2}Cu{sub 3}O{sub y} and Y{sub 0.85 –} {sub x}Pr{sub x}Ca{sub 0.15}Ba{sub 2}Cu{sub 3}O{sub y} Systems

The results of the comparative study of the modification of the temperature dependences of the Nernst–Ettingshausen coefficient Q in the normal phase of two series of the samples of the Y{sub 1 –} {sub x}Pr{sub x}Ba{sub 2}Cu{sub 3}O{sub y} and Y{sub 0.85 –} {sub x}Pr{sub x}Ca{sub 0.15}Ba{sub 2}Cu{sub 3}O{sub y} compositions due to praseodymium doping are presented. The specific features of dependences Q(T) and Q{sub 300 K}(T) appeared as additional calcium ions exist in the YBa{sub 2}Cu{sub 3}O{sub y} lattice have been revealed and analyzed. It is shown that dependences Q(T) and the temperature dependences of the thermopower coefficient obtained for the same samples previously are completely described in terms of the narrow-band model for both systems under study. The charge carrier mobilities and the degrees of asymmetry of the dispersion law are determined using a quantitative analysis of the experimental data. It is shown that the existence of additional calcium ions in the lattice does not influence a change in the asymmetry of the dispersion law with an increase in the praseodymium content, but strongly influences the character of changing the mobility. The found dependence of the mobility on the level of doping in the two systems and the observed difference in the characters of the changes in the absolute values of the thermopower coefficient and the Nernst–Ettingshausen coefficient in the Y{sub 0.85 –} {sub x}Pr{sub x}Ca{sub 0.15}Ba{sub 2}Cu{sub 3}O{sub y} system are explained on the basis of the analysis of the mechanisms of influence of the energy spectrum parameters on the charge carrier mobility in the YBa{sub 2}Cu{sub 3}O{sub y} system.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS2007

Characterization of Forested Landscapes From Remotely Sensed Data Using Fractals and Spatial Autocorrelation

The characterization of forested areas is frequently required in resource management practice. Passive remotely sensed data, which are much more accessible and cost effective than are active data, have rarely, if ever, been used to characterize forest structure directly, but rather they usually focus on the estimation of indirect measurement of biomass or canopy coverage. In this study, some spatial analysis techniques are presented that might be employed with Landsat TM data to analyze forest structure characteristics. A case study is presented wherein fractal dimensions, along with a simple spatial autocorrelation technique (Moran s I), were related to stand density parameters of the Oakmulgee National Forest located in the southeastern United States (Alabama). The results of the case study presented herein have shown that as the percentage of smaller diameter trees becomes greater, and particularly if it exceeds 50%, then the canopy image obtained from Landsat TM data becomes sufficiently homogeneous so that the spatial indices reach their lower limits and thus are no longer determinative. It also appears, at least for the Oakmulgee forest, that the relationships between the spatial indices and forest class percentages within the boundaries can reasonably be considered linear. The linear relationship is much more pronounced in the sawtimber and saplings cases than in samples dominated by medium sized trees (poletimber). In addition, it also appears that, at least for the Oakmulgee forest, the relationships between the spatial indices and forest species groups (Hardwood and Softwood) percentages can reasonably be considered linear. The linear relationship is more pronounced in the forest species groups cases than in the forest classes cases. These results appear to indicate that both fractal dimensions and spatial autocorrelation indices hold promise as means of estimating forest stand characteristics from remotely sensed images. However, additional work is needed to confirm that the boundaries identified for Oakmulgee forest and the linear nature of the relationship between image complexity indices and forest characteristics are generally evident in other forests. In addition, the effects of other parameters such ,as topographic relief and image distortion due to sun angle and cloud cover, for example, need to be examined.

Al-Hamdan, Mohammad Z.↗
NASA NTRS2013

Elucidating Microbial Adaptation Dynamics via Autonomous Exposure and Sampling

The adaptation of micro-organisms to their environments is a complex process of interaction between the pressures of the environment and of competition. Reducing this multifactorial process to environmental exposure in the laboratory is a common tool for elucidating individual mechanisms of evolution, such as mutation rates. Although such studies inform fundamental questions about the way adaptation and even speciation occur, they are often limited by labor-intensive manual techniques. Current methods for controlled study of microbial adaptation limit the length of time, the depth of collected data, and the breadth of applied environmental conditions. Small idiosyncrasies in manual techniques can have large effects on outcomes; for example, there are significant variations in induced radiation resistances following similar repeated exposure protocols. We describe here a project under development to allow rapid cycling of multiple types of microbial environmental exposure. The system allows continuous autonomous monitoring and data collection of both single species and sampled communities, independently and concurrently providing multiple types of controlled environmental pressure (temperature, radiation, chemical presence or absence, and so on) to a microbial community in dynamic response to the ecosystem's current status. When combined with DNA sequencing and extraction, such a controlled environment can cast light on microbial functional development, population dynamics, inter- and intra-species competition, and microbe-environment interaction. The project's goal is to allow rapid, repeatable iteration of studies of both natural and artificial microbial adaptation. As an example, the same system can be used both to increase the pH of a wet soil aliquot over time while periodically sampling it for genetic activity analysis, or to repeatedly expose a culture of bacteria to the presence of a toxic metal, automatically adjusting the level of toxicity based on the number or growth rate of surviving cells. We are on our second prototype iteration, with demonstrated functions of microbial growth monitoring and dynamic exposure to UV-C radiation and temperature. We plan to add functionality for general chemical presence or absence by Nov. 2013. By making the project low-cost and open-source, we hope to encourage others to use it as a basis for future development of a common microbial environmental adaptation testbed.

Microbiology↗
DOE OSTI2019

Managing genomic variant calling workflows with Swift/T

Bioinformatics research is frequently performed using complex workflows with multiple steps, fans, merges, and conditionals. This complexity makes management of the workflow difficult on a computer cluster, especially when running in parallel on large batches of data: hundreds or thousands of samples at a time. Scientific workflow management systems could help with that. Many are now being proposed, but is there yet the “best” workflow management system for bioinformatics? Such a system would need to satisfy numerous, sometimes conflicting requirements: from ease of use, to seamless deployment at peta- and exa-scale, and portability to the cloud. We evaluated Swift/T as a candidate for such role by implementing a primary genomic variant calling workflow in the Swift/T language, focusing on workflow management, performance and scalability issues that arise from production-grade big data genomic analyses. In the process we introduced novel features into the language, which are now part of its open repository. Additionally, we formalized a set of design criteria for quality, robust, maintainable workflows that must function at-scale in a production setting, such as a large genomic sequencing facility or a major hospital system. The use of Swift/T conveys two key advantages. (1) It operates transparently in multiple cluster scheduling environments (PBS Torque, SLURM, Cray aprun environment, etc.), thus a single workflow is trivially portable across numerous clusters. (2) The leaf functions of Swift/T permit developers to easily swap executables in and out of the workflow, which makes it easy to maintain and to request resources optimal for each stage of the pipeline. While Swift/T’s data-level parallelism eliminates the need to code parallel analysis of multiple samples, it does make debugging more difficult, as is common for implicitly parallel code. Nonetheless, the language gives users a powerful and portable way to scale up analyses in many computing architectures.

Science & Technology - Other Topics↗
DOE OSTI2021

3-D Geologic Controls of Hydrothermal Fluid Flow at Brady Geothermal Field, Nevada using PCA

In many hydrothermal systems, fracture permeability along faults provides pathways for groundwater to transport heat from depth. Faulting generates a range of deformation styles that cross-cut heterogeneous geology, resulting in complex patterns of permeability, porosity, and hydraulic conductivity. Vertical connectivity (a through going network of permeable areas that allows advection of heat from depth to the shallow subsurface) is rare and is confined to relatively small volumes that have highly variable spatial distribution. This local compartmentalization of connectivity represents a significant challenge to understanding hydrothermal circulation and for exploring, developing, and managing hydrothermal resources. Here, we present an evaluation of the geologic characteristics that control this compartmentalization in hydrothermal systems through 3-D analysis of the Brady geothermal field in western Nevada. A published 3-D geologic map of the Brady area is used as a basis to develop structural and geological variables that are hypothesized to control or effect permeability or connectivity. The 3-D distribution of these variables is compared to the distribution of productive and non-productive fluid flow intervals along production wells and non-productive wells via principal component analysis (PCA). This comparison elucidates which geologic and structural variables are most closely associated with productive fluid flow intervals. Results indicate that production intervals at Brady are located: (1) within or near to known and stress-loaded macro-scale faults, and (2) in areas of high fault and fracture density. This submission includes the published journal article detailing this work, the published 3-D geologic map of the Brady Geothermal Area used as a basis to develop structural and geological variables that are hypothesized to control or effect permeability or connectivity, 3-D well data, along which geologic data were sampled for PCA analyses, and associated metadata file. This work was done using existing R programs.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Nevada Higher Education Benefits from US Department of Energy (DOE) Environmental Management (EM) Nevada Program's Transfer of Geologic Samples - 20442

The Nevada National Security Site (NNSS), formerly the Nevada Test Site, was the location of 100 historic atmospheric and 828 historic underground nuclear tests from 1951 to 1992. Related to this historic nuclear testing, geologic and hydrologic studies of the site were conducted utilizing the skills and the expertise of the U.S. Geological Survey (USGS) and national laboratories (Los Alamos National Laboratory, Lawrence Livermore National Laboratory), who were principal in leading the development of weapons and were responsible for specific underground testing programs. The subsurface samples and technical/scientific data associated with NNSS geologic studies (past and present) are preserved and stored at the USGS Mercury Core Library and Data Center located at the NNSS. Currently, the facility stores over 2,000,000 linear feet of cores and cuttings from more than 2,600 drill holes that can be accessed for study. Most of the samples and historic geologic work was focused directly on subsurface geologic settings that relate directly to historic underground nuclear testing. Since 1992, the United States has observed a unilateral moratorium on full-scale nuclear testing, and the U.S. Department of Energy (DOE) Environmental Management (EM) Nevada Program is now responsible for hydrogeologic characterization of the potential impacts to the natural groundwater systems that may have resulted from historic underground nuclear tests. As part of this effort, the EM Nevada Program Underground Test Area (UGTA) Activity has drilled and completed over 58 deep (2,000 - 7,000 ft.) characterization wells, totaling in excess of 170,000 linear feet of cuttings and core samples. Cutting samples were collected as triplicate samples for each respective depth interval, to account for potential later nondestructive/destructive analysis and to preserve samples for regulatory purposes. Recently, it was recognized by the EM Nevada Program that opportunities may exist to reduce the cost and floor space required for the storage of geologic samples at the Mercury Core Library without impacting the integrity and representative nature of the samples necessary for project execution. An initiative was sponsored by EM Nevada Program to evaluate several options: 1) disposal of a portion of cuttings and cores in a land fill setting; 2) reduction in sample volume through skeletonizing core and cuttings from wells to a representative but much smaller number of samples; and 3) solicit potential interest in the academic community where other geoscientists could freely access the samples for studies. The Nevada state university system through the Nevada Bureau of Mines and Geology responded positively to the opportunity to receive these NNSS samples from the EM Nevada Program. In June 2019, approximately 17,000 geologic samples, representing greater than 170,000 linear feet of drilling and weighing over 20,000 pounds, were shipped from the NNSS to the Great Basin Science Sample and Records Library located in Reno, Nevada. The benefits resulting from this transfer were realized by the EM Nevada Program in terms of cost and space savings for geologic sample storage at the NNSS. The transfer did not impact the EM Nevada Program mission as access to representative geologic samples for regulatory and scientific purposes was preserved. Moreover, the Nevada Bureau of Mines and Geology acquired a significant resource of subsurface geologic samples and supporting technical data to support academic and scientific studies in a complex volcanic setting in southwest Nevada. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Impact of organic acids and sulfate on the biogeochemical properties of soil from urban subsurface environments

Urban subsurface environments are often different from undisturbed subsurface environments due to the impacts of human activities. For example, deterioration of underground infrastructure can introduce elevated levels of Ca, Fe, and heavy metals into subsurface soils and groundwater. Likewise, leakage from sewer systems can lead to contamination by organic C, N, S, and P. However, the impact of these organic and inorganic compounds on biogeochemical processes including microbial redox reactions, mineral transformations, and microbial community transitions in urban subsurface environments is poorly understood. Here we conducted a microcosm experiment with soil samples from an urban construction site to investigate the possible biotic and abiotic processes impacted when sulfate and acetate or lactate were introduced into an urban subsurface environment. In the top-layer soil (0-0.3 m) microcosms, which were highly alkaline (pH > 10), the major impact was on abiotic processes such as secondary mineral precipitation. In the mid-layer (2-3 m) soil microcosms, the rate of Fe(III)-reduction and the amount of Fe(II) produced were greatly impacted by the specific organic acid added, and sulfate-reduction was not observed until after Fe(III)-reduction was complete. Near the end of the incubation, some genera related to syntrophic acetate oxidation and methanogenesis were observed in the lactateamended microcosms. In the bottom-layer (7-8 m) soil microcosms, the rate of Fe(III)-reduction and the amount of Fe(II) produced were affected by the concentration of amended sulfate. Sulfate-reduction was concurrent with Fe(III)-reduction, suggesting that Fe(II) production was likely due to abiotic reduction of Fe(III) by sulfide produced by microbial sulfate reduction. The slightly acidic initial pH (~5.8) of the mid-soil system was a major factor controlling sequential microbial Fe(III) and sulfate reduction versus parallel Fe(III) and sulfate reduction in the bottom soil system, which had a neutral initial pH (~7.2). Finally, 16S rRNA gene-based community analysis revealed a variety of indigenous microbial groups including alkaliphiles, dissimilatory iron and sulfate reducers, syntrophes, and methanogens tightly coupled with, and impacted by, these complex abiotic and biogeochemical processes occurring in urban subsurface environments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

In-situ hydrogen microstructural characterization of Si heterojunction passivation: Addressing V OC degradation and mitigation pathways

Si heterojunction (SHJ) solar cells have demonstrated record efficiency >27%, approaching the theoretical limit of ≈ 29%, primarily due to best surface/interface defect passivation provided by deposited thin layers of hydrogenated amorphous silicon (a-Si:H). Such excellent surface/interface passivation reduces recombination loss and result in >100 mV improvement of cell open circuit voltage (V OC ) to ≈ 750 mV, thus the cell efficiency. However, fielded SHJ modules exhibit loss of V OC and hence efficiency over time in years, presumably due to degradation related to a-Si:H layers. This adversely affects the technology’s market acceptance, and levelized cost of energy (LCOE). It is hypothesized that the origin of a-Si:H degradation is somehow related to the presence of weak Si–Si bonds and hydrogen in a-Si:H films. The objective of this project is to test this hypothesis by directly measuring chemical and structural changes occurring within SHJ component layers and solar cells. This is achieved by developing an innovative in-situ Fourier transform infrared (FTIR) spectrometry apparatus to monitor hydrogen microstructural changes occurring within amorphous silicon and decipher hydrogen evolution kinetics over time when samples are exposed to heat and/or light stress. These in-situ measured hydrogen microstructural changes are correlated to the changes in effective minority carrier lifetime (τ eff ), implied V OC (iV OC ), surface recombination velocity (S), and cell V OC . These mechanistic understandings will provide critical guidance to mitigate the V OC -driven degradation of SHJ solar cell performance. Passivation optimization and degradation analysis of individual SHJ component structures were achieved through systematic deposition of three symmetric structures and the completed SHJ solar cell structure. The three symmetric structures used were intrinsic a-Si:H [(i)a-Si:H] layers in a bilayer structure, intrinsic and p-type doped stacked layers [(i-p)a-Si:H] representing the front heterojunction in the SHJ cell, and intrinsic and n-typed doped stacked layers [(i-n)a-Si:H] representing the back-side back surface field (BSF) in the SHJ cell. State-of-the-art passivation qualities are demonstrated by a champion iV OC of 740 mV for the (i)a-Si:H layers, and the (i-n)a-Si:H symmetric structure. A 725 mV iV OC is observed for the (i-p)a-Si:H symmetric structure. These symmetric passivated SHJ component structures were subsequently subjected to different accelerated lifetime (ALT) stressors to identify which conditions contribute the most to iV OC degradation. Degradation of the thin (10 nm) (i)a-Si:H passivation layers without any additional overlying layers is minimal; complexity of this study arises due to unavoidable surface oxidation of (i)a-Si:H layer during most of the stress application, which is likely irrelevant for a full SHJ cell configuration with overlying protective layers. The iV OC degradation of symmetric structures is found to occur primarily at the (i-p)a-Si:H passivation stack under dark heat stress with associated hydrogen loss from the (p)a-Si:H layer. An activation energy for increase in S (defect creation) of 0.65 eV can be correlated to the activation energy of ≈ 0.4 eV for hydrogen loss from the (i-p)a-Si:H stack. This also suggests the presence of weakly bonded hydrogen in the (p)a-Si:H films, which effuses out of the film stack at such low activation energy. When light and heat stress are applied together, similar hydrogen loss from (i-p)a-Si:H stack is observed, however, does not appreciably degrade iV OC or increase S. This is an important result and departure from direct correlation between hydrogen loss and defect creation. This perhaps indicates additional defect chemistries or annealing that might be occurring in the presence of light requiring further detailed defect measurements. The full SHJ cell structure used for this project is depicted in Fig.1(d). SHJ cells with an initial V OC ≈ 700 mV were fabricated and subjected to similar ALT stress conditions. Cell V OC is found to degrade the most under dark heat stress and is confirmed by observed hydrogen migration out of the (i-p)a-Si:H stack. However, hydrogen cannot escape from the cell stack, it accumulates near the (p)a-Si:H/ITO contact interface, where ITO acts as a barrier preventing hydrogen loss. Furthermore, light-heat combined stress does not degrade V OC appreciably, confirming the occurrence of a defect annealing process.

14 SOLAR ENERGY↗
NASA NTRS2012

Strategies for Distinguishing Abiotic Chemistry from Martian Biochemistry in Samples Returned from Mars

A key goal in the search for evidence of extinct or extant life on Mars will be the identification of chemical biosignatures including complex organic molecules common to all life on Earth. These include amino acids, the monomer building blocks of proteins and enzymes, and nucleobases, which serve as the structural basis of information storage in DNA and RNA. However, many of these organic compounds can also be formed abiotically as demonstrated by their prevalence in carbonaceous meteorites [1]. Therefore, an important challenge in the search for evidence of life on Mars will be distinguishing between abiotic chemistry of either meteoritic or martian origin from any chemical biosignatures from an extinct or extant martian biota. Although current robotic missions to Mars, including the 2011 Mars Science Laboratory (MSL) and the planned 2018 ExoMars rovers, will have the analytical capability needed to identify these key classes of organic molecules if present [2,3], return of a diverse suite of martian samples to Earth would allow for much more intensive laboratory studies using a broad array of extraction protocols and state-of-theart analytical techniques for bulk and spatially resolved characterization, molecular detection, and isotopic and enantiomeric compositions that may be required for unambiguous confirmation of martian life. Here we will describe current state-of-the-art laboratory analytical techniques that have been used to characterize the abundance and distribution of amino acids and nucleobases in meteorites, Apollo samples, and comet- exposed materials returned by the Stardust mission with an emphasis on their molecular characteristics that can be used to distinguish abiotic chemistry from biochemistry as we know it. The study of organic compounds in carbonaceous meteorites is highly relevant to Mars sample return analysis, since exogenous organic matter should have accumulated in the martian regolith over the last several billion years and the analytical techniques previously developed for the study of extraterrestrial materials can be applied to martian samples.

Glavin, D. P.↗
DOE OSTI2021

Machine learning to discover mineral trapping signatures due to CO 2 injection

Mineral trapping is pursued as a geological CO 2 sequestration (GCS) mechanism because it permanently stores CO 2 in solid phases or minerals. However, CO 2 mineral-trapping mechanisms are poorly understood due to (1) lack of sufficient field and laboratory data characterizing these complex processes, and (2) challenges to develop site-specific reactive-transport models coupling fluid flow and geochemical reactions occurring at various temporal (from milliseconds to years) and spatial (from pore (millimeters) to field (kilometers)) scales. Reactive transport with additional complexities such as heterogeneity can make the simulation outputs even more difficult to interpret because of complex nonlinearity and multi-scale interdependencies. Furthermore, the values of model outputs such as concentrations can vary by several orders of magnitude, making it harder to correlate and characterize the impact of the variables via traditional data interpretation techniques such as exploratory data analyses. Recently, machine learning (ML) has shown promise in feature discovery and in highlighting hidden mechanisms that cannot be obtained by existing data-analytics and statistical methods. In this study, we applied an unsupervised ML approach, non-negative matrix factorization with custom -means clustering (NMF) to the data generated by reactive-transport simulations of GCS. The reactive-transport data consisted of 19 attributes, including four physio-chemical variables (pH, porosity, aqueous CO 2 , and sequestered CO 2 ), six chemical species (K + , Na + , HCO, Ca 2+ , Mg 2+ , Fe 2+ ), and four carbonate minerals (calcite, dolomite, siderite, and ankerite), a feldspar mineral (albite), and four clay minerals (illite, clinochlore, kaolinite, and smectite) over a period of 200 years of simulation time. Furthermore, the simulation data used was for Morrow B sandstone at the Farnsworth hydrocarbon unit in Texas. Data are sampled at two locations within the model domain: (1) at the injection well and (2) 200 m west of the injection well. The injection was performed for a period of 10 years. Using NMF, we estimated the temporal interdependencies among the 19 attributes over a span of 200 years. We found that NMF was able to identify four reaction stages and their dominant attributes; these cannot be directly discerned through traditional visualization (e.g., line plots, Pareto analysis, Glyph-based visualization methods) or exploratory data analysis tools of the simulation data. The four stages were: reactions in the injection phase followed by short-, mid-, and long-term reactions. The NMF analysis also revealed that 10 among the 19 attributes are dominant. These dominant attributes for mineral trapping include calcite, dolomite at injection well, siderite at 200 m away from the injection well, clinochlore, kaolinite, Na + , K + , Ca 2+ , Mg 2+ , pH, and aqeuous CO 2 . Finally, at late times (65–200 years), our results showed that calcite plays a major role in mineral trapping with insignificant contribution from siderite, ankerite, and clay minerals. These findings make the proposed unsupervised ML-model attractive for reactive-transport sensing towards real-time GCS monitoring.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

SENTRA: A Modular Computational Graph Framework for Critical Mineral and Materials Supply Chains: Part I: Network Construction Latent-Quantity Estimation, and Temporal Graph Forecasting

Global supply chains for critical minerals and materials are complex, evolving networks of countries, products, production stages, and trade relationships. Existing analytical approaches are limited by fragmented data and static network representations that do not capture the dynamic production dependencies linking raw materials, intermediate products, and final goods across multiple countries. Trade and production statistics provide only a partial view of domestic production, inventories, and material flows, making it difficult to identify indirect sourcing pathways, hidden dependencies, and embedded foreign exposures. This paper introduces the Supply Chain Exposure Network Tracking and Risk Assessment (SENTRA) framework, a modular graph-based computational framework for constructing, analyzing, and forecasting dynamic supply chain networks. As the first paper in a three-part methodological series, it establishes the computational foundation of SENTRA by constructing a temporal attributed multi-relational graph whose nodes represent product–country pairs and whose edges encode observed trade and within-country value-chain relationships. Statistical estimation and constrained optimization recover latent production, final demand, and product input dependency coefficients while enforcing economic accounting constraints. Graph-derived exposure measures quantify direct, transshipment, value-chain, and multi-hop supply chain dependencies independently of the forecasting model. A temporal graph forecasting architecture based on a relational graph neural network then forecasts the evolution of the graph under mass-balance constraints with distribution-free conformal uncertainty quantification. Validation on the global aluminum supply chain shows that the learned graph representations recover economically meaningful supply chain structure, accurately forecast out-of-sample trade relationships, and produce well-calibrated prediction intervals. Subsequent papers apply this computational foundation to exposure assessment, disruption analysis, and scenario-based policy analysis, and extend the framework to multimaterial supply chain modeling and decision support.

36 MATERIALS SCIENCE↗
NASA NTRS2024

Experimental Studies on the Effect of Impact Processes on the Formation and Evolution of Amino Acids

Introduction: A critical step in the emergence of life on Earth was the synthesis of larger organic molecules from simple building blocks such as NH3, CO2, H2O, and CH3OH. The presence of amino acids and other complex organics in comets and meteorites demonstrates that widespread organic synthesis likely occurred across the early solar system. Building on previous work [e.g., 1-3], we systematically explore impact-driven chemical evolution of exogenous organics and their precursors. Collisional processes may also have provided a source of energy for the formation of more complex organics from endogenous building blocks. The high flux of impactors to Earth immediately prior to and during the origins of life suggests that impacts could have played a critical role. Key Questions: 1. How are the formation and evolution of amino acids affected by the presence of a mineral matrix during cometary and asteroidal impacts onto the early Earth? 2. Do some minerals (e.g., phyllosilicates) provide a more robust protective framework or reactive surface site for amino-acid formation and/or polymerization? 3. Does the abundance of ices and/or amino acids relative to that of the mineral matrix affect the formation and evolution of amino acids? 4. Are there impact velocities/shock pressures at which formation or polymerization of amino acids is favored or precluded? Experimental Approach: This study systematically examines the conditions under which amino acids and other organic molecules can form, be polymerized, and/or be destroyed during impact events into particulate regolith simulants. Variable parameters include the modal composition of this regolith (silicate matrices, ratios of ices, silicates, and amino acids) and impact velocities/shock pressures. Impacts experiments were performed using the two-stage light-gas gun (LGG), vertical gun (VG), and flat-plate accelerator (FPA) in the Experimental Impact Lab at JSC. FPA experiments were performed over a range of shock pressures (11.3-31.5 GPa) using CM chondrite simulant mixed with amino acids at ratios of 0:10, 1:10, 1:103, and 1:106 (amino acid:host). Techniques for mixing cometary ices have been optimized and test runs have been performed using the LGG (see figure below). Analysis: Post-impact, samples are heated in water to extract amino acids and peptides. Extracts are characterized via liquid chromatography-mass spectrometry (LC-MS) and the mineralogies of solid residues are characterized using X-ray diffraction, scanning electron microscopy and transmission electron microscopy. Additional LC-MS and mineralogical analyses are underway.

Eve L Berger↗