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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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NASA NTRS2004

Integration of a Micro-Chip Amino Acid Chirality Detector into the MOD Instrument Concept

The MOD (Mars Organic Detector) instrument concept consists of a sublimation apparatus for organic compound isolation connected to a microfabricated microfluidic analyzer containing a sipper, pumps and a separation channel for organic compound characterization. The target organic compounds are amino acids and polycyclic aromatic hydrocarbons (PAHs). Solid samples are placed within the sublimation apparatus and heated to release organic compounds which sublime onto a cold finger. Half of the cold finger is coated with fluorescamine. which reacts with amino acids and other primary amines to generate an intense fluorescent derivative while the other half is uncoated and is used to directly detect PAH fluorescence, A capillary sipper is then used to dissolve and sample the labeled amino acids and integrated microfabricated pumps transport the labeled amino acids to the chip for analysis. The sample is separated using capillary zone electrophoresis (CZE) together with chiral dextrins to determine amino acid composition and chirality. During the grant period, the following steps have been completed toward the development of a robust instrument and chemistry.

Bada, Jeffrey L.↗

DOE OSTI2022

SDSS-IV MaNGA: Unveiling Galaxy Interaction by Merger Stages with Machine Learning

We use machine-learning techniques to classify galaxy merger stages, which can unveil physical processes that drive the star formation and active galactic nucleus (AGN) activities during galaxy interaction. The sample contains 4690 galaxies from the integral field spectroscopy survey SDSS-IV MaNGA and can be separated into 1060 merging galaxies and 3630 nonmerging or unclassified galaxies. For the merger sample, there are 468, 125, 293, and 174 galaxies (1) in the incoming pair phase, (2) in the first pericentric passage phase, (3) approaching or just passing the apocenter, and (4) in the final coalescence phase or post-mergers. With the information of projected separation, line-of-sight velocity difference, Sloan Digital Sky Survey (SDSS) gri images, and MaNGA Hα velocity map, we are able to classify the mergers and their stages with good precision, which is the most important score to identify interacting galaxies. For the two-phase classification (binary; nonmerger and merger), the performance can be high (precision > 0.90) with LGBMClassifier . We find that sample size can be increased by rotation, so the five-phase classification (nonmerger, and merger stages 1, 2, 3, and 4) can also be good (precision > 0.85). The most important features come from SDSS gri images. The contribution from the MaNGA Hα velocity map, projected separation, and line-of-sight velocity difference can further improve the performance by 0%–20%. In other words, the image and the velocity information are sufficient to capture important features of galaxy interactions, and our results can apply to all the MaNGA data, as well as future all-sky surveys.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Evaluation of a high-throughput method for processing sponge-stick samples to detect viable, non-spore-forming biothreat agents

After a bioterrorism incident, surface sampling is often used to determine the extent of contamination and exposure, guiding decontamination efforts and decisions for re-occupancy of affected sites. The sponge-stick (SS) is a preferred and commonly used device for sample collection to detect both spore-forming and non-spore-forming biothreat agents from non-porous surfaces. Here, in this study, a recently developed high-throughput method (HTM) for processing SS samples to detect viable Bacillus anthracis spores was adapted for detection of non-spore-forming biothreat agents, Yersinia pestis and Francisella tularensis. The scalable HTM was used to process up to 20 SS samples simultaneously, compared to the current stomacher-based method which processes one SS at a time. Comparisons of the HTM and the stomacher-based method were statistically indistinguishable for most experiments (P > 0.05) with HTM recoveries of 37–60 % for Y. pestis inoculated at 102–103 cells/SS and held 48 h at 4 °C to mimic sample transport/storage. The HTM was integrated with Rapid Viability-Polymerase Chain Reaction (RV-PCR) analysis to detect viable Y. pestis in the presence of particulate contamination (Arizona Test Dust, ATD). This approach detected Y. pestis inoculated at 20 cells/SS and ATD did not impact detection (P > 0.05). F. tularensis showed significantly lower recoveries between no-hold time and 48-h hold time (4 °C, P < 0.05) using the HTM, which further testing showed could be due to toxicity of the neutralizing buffer used for SS pre-wetting. With modifications, this method could enhance throughput capacity while maintaining similar recovery efficiencies to current methods for other non-spore-forming bacterial pathogens.

Biological and medical sciences↗

DOE OSTI2023

MadNIS - Neural multi-channel importance sampling

Theory predictions for the LHC require precise numerical phase-space integration and generation of unweighted events. We combine machine-learned multi-channel weights with a normalizing flow for importance sampling, to improve classical methods for numerical integration. We develop an efficient bi-directional setup based on an invertible network, combining online and buffered training for potentially expensive integrands. We illustrate our method for the Drell-Yan process with an additional narrow resonance.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS1980

Flutter spectral measurements using stationary pressure transducers

Engine-order sampling was used to eliminate the integral harmonics from the flutter spectra corresponding to a case-mounted static pressure transducer. Using the optical displacement data, it was demonstrated that the blade-order sampling of pressure data may yield erroneous results due to the interference caused by blade vibration. Two methods are presented which effectively eliminate this interference yielding the blade-pressure-difference spectra. The phase difference between the differential-pressure and the displacement spectra was evaluated.

Kurkov, A. P.↗

NASA NTRS2015

Curating NASA's Astromaterials Collections: Past, Present, and Future

Planning for the curation of samples from future sample return missions must begin during the initial planning stages of a mission. Waiting until the samples have been returned to Earth, or even when you begin to physically build the spacecraft is too late. A lack of proper planning could lead to irreversible contamination of the samples, which in turn would compromise the scientific integrity of the mission. For example, even though the Apollo missions first returned samples in 1969, planning for the curation facility began in the early 1960s, and construction of the Lunar Receiving Laboratory was completed in 1967. In addition to designing the receiving facility and laboratory that the samples will be characterized and stored in, there are many aspects of contamination that must be addressed during the planning and building of the spacecraft: planetary protection (both outbound and inbound); cataloging, documenting, and preserving the materials used to build spacecraft (also known as coupons); near real-time monitoring of the environment in which the spacecraft is being built using witness plates for critical aspects of contamination (known as contamination control); and long term monitoring and preservation of the environment in which the spacecraft is being built for most aspects of potential contamination through the use of witness plates (known as contamination knowledge). The OSIRIS REx asteroid sample return mission, currently being built, is dealing with all of these aspects of contamination in order to ensure they return the best preserved sample possible. Coupons and witness plates from OSIRIS REx are currently being studied and stored (for future studies) at the Johnson Space Center. Similarly, planning for the clean room facility at Johnson Space Center to house the OSIRIS-REx samples is well advanced, and construction of the facility should begin in early 2017 (despite a nominal 2023 return date for OSIRIS-REx samples). Similar development is being done, in concert with JAXA, for the return of Hayabusa 2 samples (nominally in 2020). We are also actively developing advanced techniques like cold curation and organically clean curation in anticipation of future sample return missions such as comet nucleus sample return and Mars sample return.

Zeigler, Ryan↗

NASA NTRS2018

The Importance of Contamination Knowledge in Curation - Insights into Mars Sample Return

The Astromaterials Acquisition and Curation Office at NASA Johnson Space Center (JSC), in Houston, TX (henceforth Curation Office) manages the curation of extraterrestrial samples returned by NASA missions and shared collections from international partners, preserving their integrity for future scientific study while providing the samples to the international community in a fair and unbiased way. The Curation Office also curates flight and non-flight reference materials and other materials from spacecraft assembly (e.g., lubricants, paints and gases) of sample return missions that would have the potential to cross-contaminate a present or future NASA astromaterials collection.

Harrington, A. D.↗

DOE OSTI2023

WHONDRS River Corridor Sediment and Water Geochemistry and In Situ Sensor Data from Machine-Learning-Informed Sites across the Contiguous United States (v6)

This dataset supports a broader study examining hyporheic zone respiration rates to improve predictive models at a contiguous United States (CONUS) scale. The CONUS-Scale Model-Sample Study (CM) was designed following ICON (integrated, coordinated, open, and networked) principles to facilitate a model-experiment (ModEx) iteration approach, leveraging crowdsourced sampling across the CONUS. New machine learning models were created every month to guide sampling locations. Data from the resulting samples were used to test and rebuild the machine learning models for the next round of sampling guidance. Sampling began in April 2022 and ended in October 2023. In addition to the widely distributed CONUS sites, a more spatially focused sampling occurred in the Yakima River Basin, WA in summer 2022. Data from this more spatially intensive sampling occurred under the label “Second Spatial Study (SSS)” and were also included in the machine learning models. Other data types collected from SSS that were not part of CM were published in a separate data package (https://data.ess-dive.lbl.gov/view/doi:10.15485/1969566). This data package was originally published in February 2023. It was updated in June 2023 (v2; new and modified files); December 2023 (v3; new and modified files); June 2024 (v4; new and modified files); April 2024 (v5; new and modified files); and September 2025 (v6; modified files). See the change history section in the readme for more details. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. This dataset is comprised of two folders of field photos and videos, one folder of raw Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) data and one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) readme; (5) international generic sample number (IGSN) mapping file; (6) field protocols; (7) a subfolder with sample data; and (8) a subfolder with sensor data. The sample data subfolder contains (1) surface water and sediment dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data and averages; (2) surface water and sediment total nitrogen data and averages; (3) surface water major cations and anions and averages; (4) sediment grain size data; (5) sediment iron (II) data and averages; (6) wet sediment mass, dry sediment mass, water mass, and wet sediment volume in incubation and sediment ICR vials; (7) sediment incubation respiration rate data and averages; (8) normalized respiration rate data and averages; (9) methods codes; (10) sediment specific surface area; (11) sediment percent carbon and nitrogen; (12) sediment gravimetric moisture and averages; (15) sediment X-ray diffraction (XRD) data; (16) sediment adenosine triphosphate (ATP) and averages; (17) a subfolder with sediment incubation respiration data, scripts, and plots; (18) surface water and sediment FTICR methods; and (19) a subfolder of 9.4 Tesla (9.4T) FTICR-MS data. This folder contains five subfolders, one containing the sediment .xml data files, one containing the water .xml files, one containing the sediment CoreMS output files, one containing the water CoreMS output files, and the other containing instructions and scripts for processing the files in CoreMS (https://github.com/EMSL-Computing/CoreMS).The sensor data subfolder contains (1) a subfolder with miniDOT dissolved oxygen and temperature data and plots; (2) miniDOT dissolved oxygen and temperature summary data; and (3) miniDOT installation methods. All files are .csv, .pdf, .R, .xml, .d, .html, .Rmd, .py, .cal, .json, .jpg, .jpeg, .png, .mov, or .mp4. CORRECTION: Carbon and nitrogen content are reported as percentages. The current column headers "01395_C_percent_per_mg" and "01397_N_percent_per_mg" are incorrect. These should read "01395_C_percent" and "01397_N_percent" and will be corrected in the next version of this data package. We thank the United States Forest Service, Washington Department of Fish and Wildlife, Washington Department of Natural Resources, Cowiche Canyon Conservatory, Washington State Parks and Recreation Commission (Scientific Research Permit #210901), and the Confederated Tribes and Bands of the Yakama Nation for access to field locations where the samples labeled “SSS” were collected. We also thank the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview. WHONDRS consortium members were asked to provide any acknowledgments for the collection of samples labeled “CM” and the following is a list of acknowledgments that were submitted with their corresponding Site IDs: (MART) Research activities were conducted in part on the Wind River Experimental Forest within the Gifford Pinchot National Forest; (MP- 100379) Philadelphia is part of Lenapehoking, the ancestral homelands of the Lenape peoples; (MP-102398) Land surveyed is the ancestral homelands of the Nookhose'iinenno (Arapaho), Tsis tsis'tas (Cheyenne), and Nuuchu (Ute); (MP-100749 and MP- 100747) Georgia Coastal Ecosystem LTER, OCE-1832178; (SP-70 and SP-72) Eastern Shoshone, Shoshone-Bannock; (MP- 102944) Funded by Oregon Watershed Enhancement Board. On the traditional lands of the Confederated Tribes of the Siletz, Confederated Tribes of the Grand Rhonde, and the Clatsop-Nehalem Confederated Tribe; (MP- 100607) Holiday Creek is located on the traditional territory of the Monacan Indian Nation; (SP-45) Lafayette Blue Springs State Park; (MP-102420) NSF DEB-2016749; (MP-100019) New Hampshire Agriculture Experiment Station; (SP-35) Rayonier (land owner; https://www.rayonier.com/); (MP- 101276) US Department of Energy, Office of Science, Biological and Environmental Research, Subsurface Biogeochemical Research, Watershed Dynamics and Evolution SFA at ORNL; (MP- 103224) Watershed Dynamics and Evolution SFA at ORNL; (MP- 101584) Traditional lands of the Oceti Sakowin (Dakota, Lakota, Nakoda) and Anishinaabe Peoples.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

SDSS-IV MaNGA: Identification and multiwavelength properties of Type-1 AGN in the DR15 sample

ABSTRACT We present a method to identify type-1 active galactic nuclei (AGNs) in the central 3 arcsec integrated spectra of galaxies in the MaNGA DR15 sample. It is based on flux ratios estimates in spectral bands flanking the expected h α broad component h αBC. The high signal-to-noise ratio obtained (mean S/N = 84) permits the identification of h αBC without prior subtraction of the host galaxy (HG) stellar component. A final sample of 47 type-1 AGN is reported out of 4700 galaxies at z < 0.15. The results were compared with those from other methods based on the SDSS DR7 and MaNGA data. Detection of type-1 AGN in those works compared to our method goes from 26 per cent to 81 per cent. Spectral indexes were used to classify the type-1 AGN spectra according to different levels of AGN-HG contribution, finding 9 AGN-dominated, 14 intermediate, and 24 HG-dominated objects. Complementary data in NIR-MIR allowed us to identify type I AGN-dominated objects as blue and HG-dominated as red in the WISE colours. From NVSS and FIRST radio continuum data, we identify 5 HERGs (high-excitation radio galaxies) and 4 LERGs (low-excitation radio galaxies), three showing evidence of radio-jets in the FIRST maps. Additional X-ray data from ROSAT allowed us to build [O iii] and h αBC versus X-ray, NIR-MIR, and radio continuum diagrams, showing that L(h αBC) and L([O iii]) provide good correlations. The range in h αBC luminosity is wide 38 < logL(h αBC) < 44, with log FWHM(h αBC) ∼ 3–4, covering a range of Eddington ratios of −5.15 < log Lbol/LEdd < 0.70. Finally, we also identify and report ten possible changing-look AGN candidates.

Cortes-Suárez, Edgar↗

DOE OSTI2022

Upgrading the Performance and Stability of Lithium, Manganese-Rich Layered Oxide Cathodes with Combined-Formic Acid and Spinel Coating Treatment

We report improving sluggish rate performance and cycling stability of Li, Mn-rich cathode materials (LMR) is of great importance for practical implementation. Here, dual surface modification on LMR particles with formic acid washing and spinel coating improves the electrochemical performance. Dilute formic acid can remove the Li2CO3 surface impurities and selectively reduce Ni while significantly increasing specific surface area by ~32 %, unlocking more electrochemically active surfaces. Spinel coating enhances cycle stability by suppressing detrimental side reactions at electrode-electrolyte interfaces at high voltage. Post-annealing temperature was found to significantly affect the cathode performance. Higher temperature favors diffusion of transition metal (TM)/Li ions of the spinel coating from surface to the bulk, removing the coating by possible reconstruction into the layered structure and thus degrading the performance. The spinel coating also appears to increase Co 3+ segregation on the particle surface. Compared to the original material, the optimized sample demonstrates 47 % higher capacity retention at 3C and retains 89 % of initial capacity after 150 cycles at 0.5C. Besides, the specific energy density of 523 Wh kg -1 can be attained after 150 cycles at 0.5C. Moreover, the post-cycling analysis of modified sample verifies a better structural integrity with less particle cracking. Altogether, this study portrays an alternative strategy to overcome the shortcomings of LMR cathode materials.

25 ENERGY STORAGE↗

DOE OSTI2018

Stochastic Programming Approach for Resource Selection under Demand Uncertainty

Cost-efficient selection and scheduling of a subset of geographically distributed resources to meet the demands of a scientific workflow is a challenging problem. The problem is exacerbated by uncertainties in demand and availability of resources. In this paper, we present a stochastic optimization based framework for robust decision making in the selection of distributed resources over a planning horizon under demand uncertainty. We present a novel two-stage stochastic programming model for resource selection, and implement an L-shaped decomposition algorithm to solve this model. A Sample Average Approximation algorithm is integrated to enable stochastic optimization to solve problems with a large number of scenarios. Using the metric of stochastic solution, we demonstrate up to 30% cost reduction relative to solutions without explicit consideration of demand uncertainty for a 24-month problem. We also demonstrate up to 54% cost reduction relative to a previously developed solution for a 36-month problem. We further argue that the composition of resources selected is superior to solutions computed without explicit consideration of uncertainties. Given the importance of resource selection and scheduling of complex scientific workflows, especially in the context of commercial cloud computing, we believe that our novel stochastic programming framework will benefit many researchers as well as users of distributed computing resources.

scientific workflows, task scheduling, optimizatio↗

DOE OSTI2018

Search for supersymmetry in events with at least three electrons or muons, jets, and missing transverse momentum in proton-proton collisions at $ \sqrt{s}=13 $ TeV

A search for new physics is carried out in events with at least three electrons or muons in any combination, jets, and missing transverse momentum. Results are based on the sample of proton-proton collision data produced by the LHC at a center-of-mass energy of 13 TeV and collected by the CMS experiment in 2016. The data sample analyzed corresponds to an integrated luminosity of 35.9 fb$^{−1}$. Events are classified according to the number of b jets, missing transverse momentum, hadronic transverse momentum, and the invariant mass of same-flavor dilepton pairs with opposite charge. No significant excess above the expected standard model background is observed. Exclusion limits at 95% confidence level are computed for four different supersymmetric simplified models with pair production of gluinos or third-generation squarks. In the model with gluino pair production, with subsequent decays into a top quark-antiquark pair and a neutralino, gluinos with masses smaller than 1610 GeV are excluded for a massless lightest supersymmetric particle. In the case of bottom squark pair production, the bottom squark masses are excluded up to 840 GeV for charginos lighter than 200 GeV. For a simplified model of heavy top squark pair production, the $ {\tilde{\mathrm{t}}}_2 $ mass is excluded up to 720, 780, or 710 GeV for models with an exclusive $ {\tilde{\mathrm{t}}}_2\to {\tilde{\mathrm{t}}}_1\mathrm{H} $ decay, an exclusive $ {\tilde{\mathrm{t}}}_2\to {\tilde{\mathrm{t}}}_1\mathrm{Z} $ decay, or an equally probable mix of those two decays. In order to provide a simplified version of the analysis for easier interpretation, a small set of aggregate signal regions also has been defined, providing a compromise between simplicity and analysis sensitivity.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2019

Search for top quark partners with charge 5/3 in the same-sign dilepton and single-lepton final states in proton-proton collisions at $\sqrt{s}=13$ TeV

A search for the pair production of heavy fermionic partners of the top quark with charge 5/3 (X$_{5/3}$) is performed in proton-proton collisions at a center-of-mass energy of 13 TeV with the CMS detector at the CERN LHC. The data sample analyzed corresponds to an integrated luminosity of 35.9 fb$^{-1}$. The X$_{5/3}$ quark is assumed always to decay into a top quark and a W boson. Both the right-handed and left-handed X$_{5/3}$ couplings to the W boson are considered. Final states with either a pair of same-sign leptons or a single lepton are studied. No significant excess of events is observed above the expected standard model background. Lower limits at 95% confidence level on the X$_{5/3}$ quark mass are set at 1.33 and 1.30 TeV respectively for the case of right-handed and left-handed couplings to W bosons in a combination of the same-sign dilepton and single-lepton final states.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Observation of the ${B}_s^0$ → D* + D* - decay

The first observation of the $B^{0}_{s}$ → D* + D* - decay and the measurement of its branching ratio relative to the B 0 → D* + D* - decay are presented. The data sample used corresponds to an integrated luminosit y of 9 fb -1 of proton-proton collisions recorded by the LHCb experiment at centre-of-mass energies of 7, 8 and 13 TeV between 2011 and 2018. The decay is observed with more than 10 standard deviations and the time-integrated ratio of branching fractions is determined to be $\frac{\mathcal{B}(B^{0}_{s} → D*^+D*^-)}{\mathcal{B}(B^0 → D*^+D*^-)}$ = 0.269 ± 0.032 ± 0.011 ± 0.008, where the first uncertainty is statistical, the second systematic and the third due to the uncertainty of the fragmentation fraction ratio f s /f d . The $B^{0}_{s}$ → D* + D* - branching fraction is calculated to be $\mathcal{B}$ ($B^{0}_{s} → D*^+D*^-)$ = (2.15 ± 0.26 ± 0.09 ± 0.06 ± 0.16) X 10 -4 , where the fourth uncertainty is due to the B 0 → D* + D* - branching fraction. These results are calculated using the average $B^{0}_{s}$ meson lifetime in simulation. Correction factors are reported for scenarios where either a purely heavy or a purely light $B^{0}_{s}$ eigenstate is considered.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2019

Measurement of the production of charm jets tagged with D 0 mesons in pp collisions at $\sqrt{\mathrm{s}}=7$ TeV

The production of charm jets in proton-proton collisions at a center-of-mass energy of $\sqrt{\mathrm{s}}=7$ TeV was measured with the ALICE detector at the CERN Large Hadron Collider. The measurement is based on a data sample corresponding to a total integrated luminosity of 6.23 nb -1 , collected using a minimum-bias trigger. Charm jets are identified by the presence of a D 0 meson among their constituents. The D 0 mesons are reconstructed from their hadronic decay D 0 → $K^-π^+$. The D 0 -meson tagged jets are reconstructed using tracks of charged particles (track-based jets) with the anti-$k$ T algorithm in the jet transverse momentum range 5 < p T , j e t c h 30 GeV/ c and pseudorapidity |$η$ jet | < 0.5. The fraction of charged jets containing a D 0 -meson increases with p T , j e t c h from 0.042 ± 0.004 (stat) ± 0.006 (syst) to 0.080 ± 0.009 (stat) ± 0.008 (syst). The distribution of D 0 -meson tagged jets as a function of the jet momentum fraction carried by the D 0 meson in the direction of the jet axis ( z ∥ c h ) is reported for two ranges of jet transverse momenta, 5 < p T , j e t c h < 15 GeV/ c and 15 < p T , j e t c h < 30 GeV/ c in the intervals 0.2 < z ‖ c h < 1.0 and 0.4 < z ‖ c h < 1.0 respectively. The data are compared with results from Monte Carlo event generators (PYTHIA 6, PYTHIA 8 and Herwig 7) and with a Next-to-Leading-Order perturbative Quantum Chromodynamics calculation, obtained with the POWHEG method and interfaced with PYTHIA 6 for the generation of the parton shower, fragmentation, hadronisation and underlying event.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Predicting RNA structure and dynamics with deep learning and solution scattering

Advanced deep learning and statistical methods can predict structural models for RNA molecules. However, RNAs are flexible, and it remains difficult to describe their macromolecular conformations in solutions where varying conditions can induce conformational changes. Small-angle x-ray scattering (SAXS) in solution is an efficient technique to validate structural predictions by comparing the experimental SAXS profile with those calculated from predicted structures. There are two main challenges in comparing SAXS profiles to RNA structures: the absence of cations essential for stability and charge neutralization in predicted structures and the inadequacy of a single structure to represent RNA’s conformational plasticity. We introduce a solution conformation predictor for RNA (SCOPER) to address these challenges. This pipeline integrates kinematics-based conformational sampling with the innovative deep learning model, IonNet, designed for predicting Mg 2+ ion binding sites. Validated through benchmarking against 14 experimental data sets, SCOPER significantly improved the quality of SAXS profile fits by including Mg 2+ ions and sampling of conformational plasticity. We observe that an increased content of monovalent and bivalent ions leads to decreased RNA plasticity. Therefore, carefully adjusting the plasticity and ion density is crucial to avoid overfitting experimental SAXS data. SCOPER is an efficient tool for accurately validating the solution state of RNAs given an initial, sufficiently accurate structure and provides the corrected atomistic model, including ions.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

Geochemical and geomechanical alteration of siliciclastic reservoir rock by supercritical CO 2 -saturated brine formed during geological carbon sequestration

Geologic carbon sequestration (GCS) is a method for storing CO 2 and mitigating greenhouse gas emissions. During GCS, carbon dioxide dissolves into pore water, resulting in a low-pH brine that can react with reservoir rock minerals. This work evaluates the effects of geochemical reactions on geomechanical integrity of representative siliciclastic reservoir samples obtained from the Mt. Simon formation. Rock samples were aged 4 or 8 weeks in CO 2 -saturated brine under reservoir conditions, and in N 2 -saturated brine as a control. Post-aging, CT scans revealed more extensive micro-fracture development along horizontal bedding planes at grain edges in CO 2 versus N 2 -aged samples. Digital analysis of CO 2 -aged samples showed porosity increase from 8.1% to 15.8%. Scanning electron microscopy unearthed the loss of clay cementation, greater exposure of quartz and K-feldspar grains, and apparent surface roughening (confirmed by laser profilometry) in CO 2 -aged samples, but not in N 2 -aged samples. Fracture toughness as evaluated by scratch testing was reduced by 32.1% after 4 weeks in scCO 2 -saturated brine and 69.5% after 8 weeks. The main reason for weakening appears to be detachment of clays from quartz and feldspar grain surfaces, resulting in weakening of the rock matrix. Rock weakening may alter the geomechanical stability of storage formations.

58 GEOSCIENCES↗

DOE OSTI2024

SDYN-GANs: Adversarial learning methods for multistep generative models for general order stochastic dynamics

We introduce adversarial learning methods for data-driven generative modeling of dynamics of nth-order stochastic systems. Our approach builds on Generative Adversarial Networks (GANs) with generative model classes based on stable m-step stochastic numerical integrators. From observations of trajectory samples, we introduce methods for learning long-time predictors and stable representations of the dynamics. Our approaches use discriminators based on Maximum Mean Discrepancy (MMD), training protocols using both conditional and marginal distributions, and methods for learning dynamic responses over different time-scales. We show how our approaches can be used for modeling physical systems to learn force-laws, damping coefficients, and noise-related parameters. Our adversarial learning approaches provide methods for obtaining stable generative models for dynamic tasks including long-time prediction and developing simulations for stochastic systems.

• Artificial intelligence (AI) / machine learning ↗