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DOE OSTI2024

Machine Learning Correlation of Electron Micrographs and ToF-SIMS for the Analysis of Organic Biomarkers in Mudstone

The spatial distribution of organics in geological samples can be used to determine when and how these organics were incorporated into the host rock. Mass spectrometry (MS) imaging can rapidly collect a large amount of data, but ions produced are mixed without discrimination, resulting in complex mass spectra that can be difficult to interpret. Here, we apply unsupervised and supervised machine learning (ML) to help interpret spectra from time-of-flight-secondary ion mass spectrometry (ToF-SIMS) of an organic-carbon-rich mudstone of the Middle Jurassic of England (UK). It was previously shown that the presence of sterane molecular biomarkers in this sample can be detected via ToF-SIMS (Pasterski, M. J. et al., Astrobiology 2023, 23, 936). We use unsupervised ML on scanning electron microscopy–electron dispersive spectroscopy (SEM-EDS) measurements to define compositional categories based on differences in elemental abundances. We then test the ability of four ML algorithms─k-nearest neighbors (KNN), recursive partitioning and regressive trees (RPART), eXtreme gradient boost (XGBoost), and random forest (RF)─to classify the ToF-SIM spectra using (1) the categories assigned via SEM-EDS, (2) organic and inorganic labels assigned via SEM-EDS, and (3) the presence or absence of detectable steranes in ToF-SIMS spectra. In terms of predictive accuracy and balanced accuracy, KNN was the best performing model and RPART the worst. The feature importance, or the specific features of the ToF-SIM spectra used by the models to make classifications, cannot be determined for KNN, preventing posthoc model interpretation. Nevertheless, the feature importance extracted from the other models was useful for interpreting spectra. In conclusion, we determined that some of the organic ions used to classify biomarker containing spectra may be fragment ions derived from kerogen which is abundant in this mudstone sample.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1992

Color gradients in cooling flows in clusters of galaxies

U-, b-, V-, and I-band CCD images of 19 centrally dominant galaxies were obtained in cooling-flow clusters (CFDs) and four centrally dominant galaxies in clusters without cooling flows. Photometry through synthetic elliptical apertures was used to determine that many CFDs exhibit color-profile anomalies with respect to the control sample and to gE photometry from the recent literature. The anomalies are stronger and extend to larger galactic radii for higher mass accretion rates (HMARs) as estimated from X-ray observations. At least 11 CFDs with HMARs greater than or approximately equal to 70 solar masses/yr have blue color-profile anomalies that extend radially 5-20 kpc. Some CFDs with smaller HMARs have milder anomalies extending only less than or approximately equal to 5 kpc. The prevalence of color anomalies suggests that star formation which includes massive blue stars occurs continuously for a substantial fraction of the Hubble time, or in frequent episodes.

Mcnamara, Brian R.↗

DOE OSTI2022

Population Structure of White Sturgeon (Acipenser transmontanus) in the Columbia River Inferred from Single-Nucleotide Polymorphisms

White sturgeon (Acipenser transmontanus) are the largest freshwater fish in North America, with reproducing populations in the Sacramento-San Joaquin, Fraser, and Columbia River Basins. Of these, the Columbia River is the largest, but it is also highly fragmented by hydroelectric dams, and many segments are characterized by declining abundance and persistent recruitment failure. Efforts to conserve and supplement these fish requires an understanding of their spatial genetic structure. Here, we assembled a large set of samples from throughout the Columbia River Basin, along with representative collections from adjacent basins, and genotyped them using a panel of 325 single-nucleotide markers. Results from individual- and group-based analyses of these data indicate that white sturgeon in the uppermost Columbia River Basin, in the Kootenai and upper Snake Rivers, are the most distinct, while the remaining populations downstream in the basin can be described as a genetic gradient consistent with an isolation-by-distance effect. Notably, the population in the lowest reaches of the Columbia River is more distinct from the middle or upper reaches than from outside basins, and suggests historically a higher or more recent gene exchange through coastal routes than with populations in the interior Columbia Basin. Nonetheless, proximal reaches were generally only marginally or non-significantly divergent, suggesting that transplanting larvae or juveniles from nearby sources poses relatively little risk of outbreeding depression. Indeed, we inferred examples of dispersal between reaches via close-kin mark-recapture and genetic mark-recapture that indicate movement between nearby reaches is not unusual. Samples from the Kootenai and upper Snake Rivers exhibited notably lower genetic diversity than the remaining samples as a result of population bottlenecks, genetic drift, and/or historical divergence. Conservation actions, such as supplementation, are underway to maintain population viability and will require balanced efforts to increase demographic abundance while maintaining genetic diversity.

Willis, Stuart C.↗

DOE OSTI2021

The distribution and selective decontamination of carbon-14 from nuclear graphite

This work investigates 14 C release behaviour from UK Magnox reactor sourced irradiated graphite under relatively low temperature oxidation conditions: a 1% oxygen in argon atmosphere at temperatures ranging from 600°C to 700°C, and durations from 4 to 120 hours. A method is used for construction of a detailed 14 C release profile with mass loss. The 14 C release profile is predictable between samples, and an empirical release profile is derived to predict releases to higher mass losses than in this work. An accelerated 14 C release rate at small mass losses is observed, indicative of a 14 C-enriched surface region with a depleting concentration gradient into the material, and the source terms and complexities associated with predicting where the 14 C arose from are discussed. Selective decontamination of a fraction of the 14 C is possible, with the limitation of a reducing efficiency with mass loss and time. This work demonstrates a method for determining the distribution of 14 C between near-surface regions and the bulk material in differing sources of irradiated graphite, and provides data in support of making an informed assessment for the adoption of low temperature thermal treatment and isotopic reduction of irradiated graphite wastes.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2022

Calibration and Localization of Optically Pumped Magnetometers Using Electromagnetic Coils

In this paper, we propose a method to estimate the position, orientation, and gain of a magnetic field sensor using a set of (large) electromagnetic coils. We apply the method for calibrating an array of optically pumped magnetometers (OPMs) for magnetoencephalography (MEG). We first measure the magnetic fields of the coils at multiple known positions using a well-calibrated triaxial magnetometer, and model these discreetly sampled fields using vector spherical harmonics (VSH) functions. We then localize and calibrate an OPM by minimizing the sum of squared errors between the model signals and the OPM responses to the coil fields. We show that by using homogeneous and first-order gradient fields, the OPM sensor parameters (gain, position, and orientation) can be obtained from a set of linear equations with pseudo-inverses of two matrices. The currents that should be applied to the coils for approximating these low-order field components can be determined based on the VSH models. Computationally simple initial estimates of the OPM sensor parameters follow. As a first test of the method, we placed a fluxgate magnetometer at multiple positions and estimated the RMS position, orientation, and gain errors of the method to be 1.0 mm, 0.2°, and 0.8%, respectively. Lastly, we calibrated a 48-channel OPM array. The accuracy of the OPM calibration was tested by using the OPM array to localize magnetic dipoles in a phantom, which resulted in an average dipole position error of 3.3 mm. The results demonstrate the feasibility of using electromagnetic coils to calibrate and localize OPMs for MEG.

47 OTHER INSTRUMENTATION↗

NASA NTRS1991

The effect of processing conditions on solidified structures in immiscible systems

The incentive for low-gravity processing of immiscible alloys is usually tied to an attempt to eliminate sedimentation of the more dense immiscible liquid phase during processing. However, many other factors can influence the solidified structure of these alloys. For example, crucible wetting by one of the immiscible liquid phases during normal (non-directional) low-gravity solidification in a container has been shown to often lead to a completely separated structure. For containerless, low-gravity processing, alloy composition has a tremendous affect on the structure formed. During directional solidification, alloy composition, thermal gradient, solidification rate, convective instability and the miscibility gap height of the system all have a major effect on the structures obtained. This paper discusses the conditions necessary for the production of desired microstructures in each of these processing techniques. Examples are shown of samples processed under both desirable and undesirable conditions.

Andrews, J. B.↗

NASA NTRS1993

Formulation for Simultaneous Aerodynamic Analysis and Design Optimization

An efficient approach for simultaneous aerodynamic analysis and design optimization is presented. This approach does not require the performance of many flow analyses at each design optimization step, which can be an expensive procedure. Thus, this approach brings us one step closer to meeting the challenge of incorporating computational fluid dynamic codes into gradient-based optimization techniques for aerodynamic design. An adjoint-variable method is introduced to nullify the effect of the increased number of design variables in the problem formulation. The method has been successfully tested on one-dimensional nozzle flow problems, including a sample problem with a normal shock. Implementations of the above algorithm are also presented that incorporate Newton iterations to secure a high-quality flow solution at the end of the design process. Implementations with iterative flow solvers are possible and will be required for large, multidimensional flow problems.

Hou, G. W.↗

NASA NTRS2004

Comparison of Genotoxic Damage in Monolayer Cell Cultures and Three-Dimensional Tissue-Like Cell Assemblies

Assessing the biological risks associated with exposure to the high-energy charged particles encountered in space is essential for the success of long-term space exploration. Although prokaryotic and eukaryotic cell models developed in our laboratory and others have advanced our understanding of many aspects of genotoxicity, in vitro models are needed to assess the risk to humans from space radiation insults. Such models must be representative of the cellular interactions present in tissues and capable of quantifying I genotoxic damage. Toward this overall goal, the objectives of this study were to examine the effect of the localized microenvironment of cells, cultured as either 2-dimensional (2D) monolayers or 3-dimensional (3D) aggregates, on the rate and type of genotoxic damage resulting from exposure to iron charged particles, a significant portion of space radiation. We used rodent transgenic cell lines containing 50-70 copies of a LacI transgene to provide the enhanced sensitivity required to quantify mutational frequency and type in the 1,100-bp LacI target as well as assessment of DNA,damage to the entire 45-kbp construct. Cultured cells were exposed to high-ener~ir on charged particles at Brookhaven National Laboratory s Alternating Gradient Synchrotron facility for a total dose of 0, 0.1, 0.25,0.5, 1.0, or 2.0 Gy and allowed to recover for 0, 1, or 7 days, after which mutational type and frequency were evaluated. The mutational frequency was found to be higher in 3D samples than in 2D samples at all radiation doses. Mutational frequency also was higher at 7 days after irradiation than immediately after exposure. DNA sequencing of the mutant targets revealed that deletional mutations contributed an increasingly high percentage (up to 27%) of all mutations in cells as the dose was increased from 0.5 to 2 Gy. Several mutants also showed large and complex deletions in multiple locations within the Lac1 target. However, no differences in mutational type were found between the 2D and the 3D samples. These 3D tissue-like model systems can reduce the uncertainty involved in extrapolating risk between in vitro cellular and in vivo models.

Behravesh, E.↗

NASA NTRS2019

A Mixed Integer Efficient Global Optimization Algorithm with Multiple Infill Strategy - Applied to a Wing Topology Optimization Problem

With the advancement in high performance computing and numerical optimization techniques,engineering design optimization problems are becoming more complex, larger scale,higher fidelity, and computationally more demanding, requiring longer run times than ever before. There exists methodologies and techniques that can address some of these challenges but very few can address all, and most are limited in the extent that these concerns can be addressed. With the goal of addressing such challenging engineering problems, we developed anew optimization framework, named AMIEGO, that combines concepts from surrogate-based optimization approaches, gradient-based numerical methods, Partial Least Squares, evolutionary algorithms, and Branch-and-Bound, providing newer capabilities that were not previouslyperceived. However, the original version of this framework, in the process of adaptive samplingto explore and exploit the design space, finds only a single sample point per iteration. The efforthere builds upon this previously developed optimization framework to include multiple infillsampling capability that combines the concept of generalized expected improvement function,unsupervised learning, and multi-objective evolutionary technique. To demonstrate, AMIEGOwith the multiple infill capability (called AMIEGO-MIMOS) solves a series of increasingly difficultengineering design optimization problems. The results reveal the performance of the newapproach is problem dependent. When applied to a ten-bar truss problem, the newly proposedmultiple infill strategy consistently leads to a better design solutions when compared to theexisting CPTV method (implemented with the context of the AMIEGO framework). On theother hand, when applied to a mixed-integer high fidelity wing topology optimization problem- MIMOS, despite showing a steeper convergence at the start, eventually leads to an inferiorsolution as compared to CPTV approach. These results also reveal that a small number ofstarting points, in general, are sufficient to lead to a good overall solution.

Mixed-integer optimization↗

NASA NTRSDate not supplied

Analysis of CDC Bioreactor Internal Thermal Measurements and Sample Coupon Temperatures

The Center for Disease Control and Prevention (CDC) bioreactor is an integral laboratory tool for the Environmental Control and Life Support Systems (ECLSS) biofilm formation and growth research program. Critical to this research is the need to adjust and maintain various surface temperatures of the coupons housed within the CDC Bioreactor. The purpose of this study was to provide quantitative temperature gradient information when the CDC Bioreactor was operating according to several process scenarios. Two primary process parameters were evaluated. For the first set of test parameters, the liquid level was maintained at 350 mL, with an inlet flowrate of 0.1 mL/min, 1 mL/min, 10 mL/min. The liquid was allowed to gravity drain out of the outlet spout. For the second set of test parameters, the liquid level within the reactor was maintained at 550 mL, with an inlet flow of 0.1 mL/min, 1 mL/min, 10 mL/min and draining intermittently controlled to 0.8 mL/min to maintain the 550 mL level. Due to the placement of the thermocouple in the reactor, a difference in temperature occurred between the coupon surfaces and target Bioreactor temperature when operated according to the first set of test parameters. When the reactor was operated according to the second set of parameters, which resulted in the thermocouple being submerged, the temperature gradient was eliminated. The results demonstrated minimal temperature gradient between the top and bottom coupon surfaces for coupons placed in a single rod within the CDC Bioreactor for both sets of test parameters evaluated. The collection of this information helped to explain previous ECLSS biofilm formation test runs, along with providing guidance on best operating practices for future ECLSS experiments. The placement of the thermocouple also helps to explain the challenge of achieving and maintaining bulk liquid temperatures when biofilm is grown according to the standardized test methods.

CDC Bioreactor↗

DOE OSTI2025

Measuring the buried interphase between solid electrolytes and lithium metal using neutrons

Interfaces are the key to next-generation high-energy batteries including solid-state Li metal batteries. In solid-state batteries, the buried nature of solid–solid electrolyte–electrode interfaces makes studying them difficult. Neutrons have significant potential to non-destructively probe these buried solid–solid interfaces. This work presents a comparative study using both neutron depth profiling (NDP) and neutron reflectometry (NR) to study a model lithium metal–lithium phosphorus oxynitride (LiPON) solid electrolyte system. In the NDP data, no distinct interphase is observed at the interface. NR shows a difference between electrodeposited, and vapor deposited LiPON–Li interfaces but finds both are gradient interphases that are less than 30 nm thick. Additional simulations of the LiPON–Li 2 O–Li system demonstrate that NDP has an excellent resolution in the 50 nm–1 μm regime while NR has an ideal resolution from 0.1–200 nm with different sample requirements. Together NDP and NR can provide a complementary understanding of interfaces between Li metal and solid electrolytes across relevant length scales.

Westover, Andrew S. [Oak Ridge National Laboratory↗

DOE OSTI2024

Galaxies with biconical ionized structure in MaNGA – I. Sample selection and driven mechanisms

ABSTRACT Based on the integral field unit (IFU) data from Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey, we develop a new method to select galaxies with biconical ionized structures, building a sample of 142 edge-on biconical ionized galaxies. We classify these 142 galaxies into 81 star-forming galaxies, 31 composite galaxies, and 30 AGNs (consisting of 23 Seyferts and 7 LI(N)ERs) according to the [N ii]-BPT diagram. The star-forming bicones have bar-like structures while AGN bicones display hourglass structures, and composite bicones exhibit transitional morphologies between them due to both black hole and star formation activities. Star-forming bicones have intense star formation activities in their central regions, and the primary driver of biconical structures is the central star formation rate surface density. The lack of difference in the strength of central black hole activities (traced by dust attenuation corrected [O iii]λ5007 luminosity and Eddington ratio) between Seyfert bicones and their control samples can be naturally explained as that the accretion disc and the galactic disc are not necessarily coplanar. Additionally, the biconical galaxies with central LI(N)ER-like line ratios are edge-on disc galaxies that show strong central dust attenuation. The radial gradients of H α surface brightness follow the r−2.35 relation, roughly consistent with r−2 profile, which is expected in the case of photoionization by a central point-like source. These observations indicate obscured AGNs or AGN echoes as the primary drivers of biconical structures in LI(N)ERs.

Zhou, Zhi-Jie (ORCID:0000000317096005)↗

DOE OSTI2025

Microstructural evaluation of thin-wall sections of 316L stainless steel produced by laser powder-bed fusion processing

The synthesis of thin wall sections that are only 0.4 mm thick is achieved with LPBF AM. Sample preparation is optimized using metallographic polishing to produce samples with only 0.3 um rms roughness for scanning electron microanalysis with EBSD and EDS. A fully austenitic 316L phase is found without evidence of secondary phases. Unlike some AM products that can readily evidence composition segregation due to solute rejection as attributable to temperature gradients within the solidification

Jankowski, Alan F. [Sandia National Laboratories (↗

DOE OSTI2025

GEPA: Reflective Prompt Evolution Can Outperform Reinforcement Learning

Large language models (LLMs) are increasingly adapted to downstream tasks via reinforcement learning (RL) methods like Group Relative Policy Optimization (GRPO), which often require thousands of rollouts to learn new tasks. We argue that the interpretable nature of language often provides a much richer learning medium for LLMs, compared to policy gradients derived from sparse, scalar rewards. To test this, we introduce GEPA (Genetic-Pareto), a prompt optimizer that thoroughly incorporates natural language reflection to learn high-level rules from trial and error. Given any AI system containing one or more LLM prompts, GEPA samples trajectories (e.g., reasoning, tool calls, and tool outputs) and reflects on them in natural language to diagnose problems, propose and test prompt updates, and combine complementary lessons from the Pareto frontier of its own attempts. As a result of GEPA's design, it can often turn even just a few rollouts into a large quality gain. Across six tasks, GEPA outperforms GRPO by 6% on average and by up to 20%, while using up to 35x fewer rollouts. GEPA also outperforms the leading prompt optimizer, MIPROv2, by over 10% (e.g., +12% accuracy on AIME-2025), and demonstrates promising results as an inference-time search strategy for code optimization. We release our code at https://github.com/gepa-ai/gepa.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1973

Exploring Jupiter, Saturn and their satellites.

By exploring the outer solar system, it is possible to go back in time and sample the conditions and the energetics of primitive solar nebula from which the sun and the planets are believed to have condensed. With the aid of particle detectors and magnetometers on a spacecraft going to the outer planets, it will be possible to study the gradients of the solar plasma, cosmic rays, and the interplanetary magnetic field. A number of questions regarding the outer solar system are examined, giving attention to problems of the origin of excess energy in the case of Jupiter, Jupiter radio emissions, problems of planetary meteorology, the rings of Saturn, and the planetary satellites. Critical in situ measurements are discussed together with exploratory missions, spacecraft characteristics, and aspects of preliminary mission design.

Rasool, S. I.↗

NASA NTRS1988

Digital robust active control law synthesis for large order flexible structure using parameter optimization

A generic procedure for the parameter optimization of a digital control law for a large-order flexible flight vehicle or large space structure modeled as a sampled data system is presented. A linear quadratic Guassian type cost function was minimized, while satisfying a set of constraints on the steady-state rms values of selected design responses, using a constrained optimization technique to meet multiple design requirements. Analytical expressions for the gradients of the cost function and the design constraints on mean square responses with respect to the control law design variables are presented.

Mukhopadhyay, V.↗

NASA NTRS2012

Precision Subsampling System for Mars Surface Missions

The ability to analyze heterogeneous rock samples at fine spatial scales would represent a powerful addition to our planetary in situ analytical toolbox. This is particularly true for Mars, where the signatures of past environments and, potentially, habitability are preserved in chemical and morphological variations across sedimentary layers and among mineral pr.ases in a given rock specimen. On Earth, microbial life often associates with surfaces at the interface of chemical nutrients, and ultimately retains sub-millimeter to millimeter-scale layer confinement in fossilization. On Mars, and possibly other bodies, trace chemical markers (elemental, organic/molecular, isotopic, chiral, etc.) and fine-scale morphological markers (e.g., micro-fossils) may he too subtle, degraded, or ambiguous to be detected, using miniaturized instrumentation, without some concentration or isolation. This is because (i) instrument sensitivity may not be high enough to detect trace markers in bulk averages; and (ii) instrument s~lectiviry may not be sufficient to distinguish such markers from interfering/counteracting signals from the bulk. Moreover from a fundamental chemostratigraphic perspective there would be a great benefit to assessing specific chemical and stable isotopic gradients, over millimeter-to-centimeter scales and beyond, with higher precision than currently possible in situ. We have developed a precision subsampling system (PSS) that addresses this need while remaining relatively flexible to a variety of instruments that may take advantage of the capability on future missions. The PSS is relevant to a number of possible lander/rover missions, especially Mars Sample Return. Our specific PSS prototype is undergoing testing under Mars ambient conditions, on a variety of natural analog rocks and rock drill cores, using a set of complementary flight-compatible measurement techniques. The system is available for testing with other contact instruments that may benefit from precision sampling.

Mahaffy, P. R.↗

DOE OSTI2023

Determining the oxidation behavior of matrix graphite

This work presents the oxidation behavior of matrix graphite in air. Matrix graphite, graphite powder/flakes bonded by a small amount of non-graphitic carbon, surrounds coated fuel particles in order to form cylindrical fuel compacts (in prismatic core designs) or spheres (in pebble-bed reactor designs). This work focuses on oxidation tests conducted on two matrix graphite materials, one provided by Kairos Power and the other A3 matrix graphite. Some of the tests followed American Society for Testing and Materials (ASTM) oxidation testing standards using a vertical furnace system and others were performed in a thermogravimetric analyzer (TGA). It was determined that, at temperatures of 450 °C–700 °C, the oxidation rate of the Kairos matrix graphite follows the Arrhenius equation. In comparison with A3 matrix graphite, the Kairos matrix graphite shows better oxidation resistance at high temperatures (≥550 °C), but also a higher oxidation rate at low temperatures. Both the A3 matrix graphite and the Kairos matrix graphite materials may experience preferential oxidation of the partially graphitized binder. An oxygen penetration gradient was also observed when using the three characterization methods (i.e., optical microscope, x-ray tomography [XCT], and density profile by the lathe) enlisted in this research. In conclusion, the oxygen penetration depth increases with decreasing isothermal oxidation temperature, while the center of the oxidized samples (10% weight loss) remains almost untouched even at 500 °C.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗