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NASA NTRS2016

Identifying and Characterizing Impact Melt Outcrops in the Nectaris Basin

The Nectaris Basin is an 820-km diameter, multi-ring impact basin located on the near side of the Moon. Nectaris is a defining stratigraphic horizon based on relationships between ejecta units, giving its name to the Nectarian epoch of lunar history. Lunar basin chronology based on higher resolution LRO imagery and topography, while assigning some important basins like Serenitatis to pre-Nectarian time, were generally consistent with those previously derived. Based on this stratigraphy, at least 11 large basins formed in the time between Nectaris and Imbrium. The absolute age of Nectaris, therefore, is a crucial marker in the lunar time-stratigraphic sequence for understanding the impact flux on the Moon, and by extension, the entire inner solar system. For several decades, workers have attempted to constrain the age of the Nectaris basin through radiometric dating of lunar samples. However, there is little agreement on which samples in our collection represent Nectaris, if any, and what the correct radiometric age of such samples is. The importance of the age of Nectaris goes far beyond assigning a stratigraphic marker to lunar chronology. Several dynamical models use Nectaris as their pin date, so that this date becomes crucial in understanding the time-correlated effects in the rest of the solar system. The importance of the Nectaris basin age, coupled with its nearside, mid-latitude location, make remnants of the impact-melt sheet an attractive target for a future mission, either for in-situ dating or for sample return. We have started exploring this possibility. We have begun a consortium data-analysis effort bringing multiple datasets and analysis methods to bear on these putative impact-melt deposits to characterize their extent, elemental composition and mineralogy, maturity and geologic setting, and to identify potential landing sites that meet both operational safety and science requirements.

Nectaris Basin↗

DOE OSTI2026

Pattern-enhanced Resonant Soft X-ray Scattering for Operando monitoring of electrochemical solid-liquid interfaces

Unveiling interfaces at sub-nanometer scales is essential for advancing the understanding of complex chemical transformations. However, characterizing solid-liquid interfaces with high dimensional sensitivity and temporal resolution remains challenging, due to their dynamic nature and inaccessibility by conventional probes. Here we present an approach, Pattern-enhanced Resonant Soft X-ray Scattering, to overcome the challenges. Rooted in a “sample-as-optics” philosophy, this technique utilizes precisely engineered line-grating nanopatterns to modulate near-field X-ray illumination, coherently enhancing scattering signals from the line-gratings. We implement the method using Ni line-grating nanopatterns in electrochemical water oxidation. The periodic nanostructures serve as diffractive optical elements to reveal the Ni oxidation gradients and structural dynamics at the electrode-electrolyte interfaces. Finite-element simulations corroborate the observed trends by modeling variations in compositions and structures during electrocatalysis. Through integrating advanced sample design with coherent wave nature of soft X-rays, our approach opens accessible pathways to operando exploring chemical evolution and sub-nanometer dimensional variations simultaneously in electrochemical systems. This non-destructive method is efficient and element-specific, making it valuable for probing chemical and dimensional dynamics with appropriate modeling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2016

Li Intercalation into Graphite: Direct Optical Imaging and Cahn–Hilliard Reaction Dynamics

Lithium intercalation into graphite is a critical process in energy storage technology. Studies of Li intercalation kinetics have proved challenging due to structural and phase complexity, and sample heterogeneity. Here we report direct time- and space-resolved, all-optical measurement of Li intercalation. We use a single crystal graphite electrode with lithographically defined disc geometry. All-optical, Raman and reflectance measurements distinguish the intrinsic intercalation process from side reactions, and provide new insight into the microscopic intercalation process. The recently proposed Cahn–Hilliard reaction (CHR) theory quantitatively captures the observed phase front spatial patterns and dynamics, using a two-layer free-energy model with novel, generalized Butler–Volmer kinetics. This approach unites Cahn–Hilliard and electrochemical kinetics, using a thermodynamically consistent description of the Li injection reaction at the crystal edge that involves a cooperative opening of graphene planes. Here, the excellent agreement between experiment and theory presented here, with single-crystal resolution, provides strong support for the CHR theory of solid-state reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2015

Coalescence of silver clusters by immersion in diluted HF solution

The galvanic displacement deposition of silver on H-terminated Si (100) in the time scale of seconds is instantaneous and characterized by a cluster density of 10{sup 11}-10{sup 12} cm{sup −2}. The amount of deposited Ag follows a t{sup 1/2} dependence in agreement with a Cottrell diffusion limited mechanism. At the same time, during the deposition, the cluster density reduces by a factor 5. This behavior is in contrast with the assumption of immobile clusters. We show in the present work that coalescence and aggregation occur also in the samples immersed in the diluted hydrofluoric acid (HF) solution without the presence of Ag{sup +}. Clusters agglomerate according to a process of dynamic coalescence, typical of colloids, followed by atomic redistribution at the contact regions with the generation of multiple internal twins and stacking-faults. The normalized size distributions in terms of r/r{sub mean} follow also the prediction of the Smoluchowski ripening mechanism. No variation of the cluster density occurs for samples immersed in pure H{sub 2}O solution. The different behavior might be associated to the strong attraction of clusters to oxide-terminated Si surface in presence of water. The silver clusters are instead weakly bound to hydrophobic H-terminated Si in presence of HF. HF causes then the detachment of clusters and a random movement on the silicon surface with mobility of about 10{sup −13} cm{sup 2}/s. Attractive interaction (probably van der Waals) among particles promotes coarsening.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1983

Dynamic tooth loads and stressing for high contact ratio spur gears

An analysis and computer program were developed for calculating the dynamic gear tooth loading and root stressing for high contact ratio gearing (HCRG) as well as LCRG. The analysis includes the effects of the variable tooth stiffness during the mesh, tooth profile modification, and gear errors. The calculation of the tooth root stressing caused by the dynamic gear tooth loads is based on a modified Heywood gear tooth stress analysis, which appears more universally applicable to both LCRG and HCRG. The computer program is presently being expanded to calculate the tooth contact stressing and PV values. Sample application of the gear program to equivalent LCRG (1.566 contact ratio) and HCRG (2.40 contact ratio) revealed the following: (1) the operating conditions and dynamic characteristics of the gear system an affect the gear tooth loading and root stressing, and therefore, life significantly; (2) the length of the profile modification affect the tooth loading and root stressing significantly, the amount depending on the applied load, speed, and contact ratio; and (3) the effect of variable tooth stiffness is small, shifting and increasing the response peaks slightly from those for constant tooth stiffness.

Cornell, R. W.↗

NASA NTRS2008

Proceedings of the 39th Lunar and Planetary Science Conference

Sessions with oral presentations include: A SPECIAL SESSION: MESSENGER at Mercury, Mars: Pingos, Polygons, and Other Puzzles, Solar Wind and Genesis: Measurements and Interpretation, Asteroids, Comets, and Small Bodies, Mars: Ice On the Ground and In the Ground, SPECIAL SESSION: Results from Kaguya (SELENE) Mission to the Moon, Outer Planet Satellites: Not Titan, Not Enceladus, SPECIAL SESSION: Lunar Science: Past, Present, and Future, Mars: North Pole, South Pole - Structure and Evolution, Refractory Inclusions, Impact Events: Modeling, Experiments, and Observations, Mars Sedimentary Processes from Victoria Crater to the Columbia Hills, Formation and Alteration of Carbonaceous Chondrites, New Achondrite GRA 06128/GRA 06129 - Origins Unknown, The Science Behind Lunar Missions, Mars Volcanics and Tectonics, From Dust to Planets (Planetary Formation and Planetesimals):When, Where, and Kaboom! Astrobiology: Biosignatures, Impacts, Habitability, Excavating a Comet, Mars Interior Dynamics to Exterior Impacts, Achondrites, Lunar Remote Sensing, Mars Aeolian Processes and Gully Formation Mechanisms, Solar Nebula Shake and Bake: Mixing and Isotopes, Lunar Geophysics, Meteorites from Mars: Shergottite and Nakhlite Invasion, Mars Fluvial Geomorphology, Chondrules and Chondrule Formation, Lunar Samples: Chronology, Geochemistry, and Petrology, Enceladus, Venus: Resurfacing and Topography (with Pancakes!), Overview of the Lunar Reconnaissance Orbiter Mission, Mars Sulfates, Phyllosilicates, and Their Aqueous Sources, Ordinary and Enstatite Chondrites, Impact Calibration and Effects, Comparative Planetology, Analogs: Environments and Materials, Mars: The Orbital View of Sediments and Aqueous Mineralogy, Planetary Differentiation, Titan, Presolar Grains: Still More Isotopes Out of This World, Poster sessions include: Education and Public Outreach Programs, Early Solar System and Planet Formation, Solar Wind and Genesis, Asteroids, Comets, and Small Bodies, Carbonaceous Chondrites, Chondrules and Chondrule Formation, Chondrites, Refractory Inclusions, Organics in Chondrites, Meteorites: Techniques, Experiments, and Physical Properties, MESSENGER and Mercury, Lunar Science Present: Kaguya (SELENE) Results, Lunar Remote Sensing: Basins and Mapping of Geology and Geochemistry, Lunar Science: Dust and Ice, Lunar Science: Missions and Planning, Mars: Layered, Icy, and Polygonal, Mars Stratigraphy and Sedimentology, Mars (Peri)Glacial, Mars Polar (and Vast), Mars, You are Here: Landing Sites and Imagery, Mars Volcanics and Magmas, Mars Atmosphere, Impact Events: Modeling, Experiments, and Observation, Ice is Nice: Mostly Outer Planet Satellites, Galilean Satellites, The Big Giant Planets, Astrobiology, In Situ Instrumentation, Rocket Scientist's Toolbox: Mission Science and Operations, Spacecraft Missions, Presolar Grains, Micrometeorites, Condensation-Evaporation: Stardust Ties, Comet Dust, Comparative Planetology, Planetary Differentiation, Lunar Meteorites, Nonchondritic Meteorites, Martian Meteorites, Apollo Samples and Lunar Interior, Lunar Geophysics, Lunar Science: Geophysics, Surface Science, and Extralunar Components, Mars, Remotely, Mars Orbital Data - Methods and Interpretation, Mars Tectonics and Dynamics, Mars Craters: Tiny to Humongous, Mars Sedimentary Mineralogy, Martian Gullies and Slope Streaks, Mars Fluvial Geomorphology, Mars Aeolian Processes, Mars Data and Mission,s Venus Mapping, Modeling, and Data Analysis, Titan, Icy Dwarf Satellites, Rocket Scientist's Toolbox: In Situ Analysis, Remote Sensing Approaches, Advances, and Applications, Analogs: Sulfates - Earth and Lab to Mars, Analogs: Remote Sensing and Spectroscopy, Analogs: Methods and Instruments, Analogs: Weird Places!. Print Only Early Solar System, Solar Wind, IDPs, Presolar/Solar Grains, Stardust, Comets, Asteroids, and Phobos, Venus, Mercury, Moon, Meteorites, Mars, Astrobiology, Impacts, Outer Planets, Satellites, and Rings, Support for Mission Operations, Analog Education and Public Outreach.

Source record↗

NASA NTRS2018

Plasticity and Damage Modeling of Stress Asymmetry and Dynamic Behavior of AFS Additive Manufactured Aluminum Alloy 2219

The Solid State Additive Manufacturing (AM) process referred as MELD that fabricated the samples in this study, provides a new path for repairing, coating, joining and additive manufacturing metals and metal matrix composites. This research will be the first application of a physics-based microstructure dependent internal state variable (ISV) plasticity and damage material model to capture the mechanical response of an AM Aluminum Alloy (AA) 2219 via the MELD process. In this research, a microstructure-based internal state variable (ISV) plasticity-damage model was used to capture the mechanical behavior of AFS 2219 aluminum alloy. Aeroprobe Corporation, creator and patent holder for the MELD process, fabricated the material by pushing a solid filler rod of AA2219-T861 material through a hollow rotating tool onto an AA2219 T851 plate substrate. As feedstock, solid or powder precursor metals are pushed through a nonconsumable rotating cylindrical tool. Herein, added layers are deposited and metallurgically bonded to substrate material or previously deposited layers by the heat generated from the rotating tool through plastic deformation of the filler material. Once a layer has been added, the tool height increases, and starts the deposition of the next layer. This process results in beneficial properties such as grain refinement, homogenization and reduced porosity (fully dense). This process will experience temperatures similar to those in the weld nugget zone (WNZ) in friction stir welding (FSW), ranging from 0.6-0.9 Tm, with Tm being the melting point of the material. MELD is highly scalable with AA deposition rates reaching over 1000 cm3/hr, which allows for MELD being used for repairs, coatings, and building components. A motivating factor driving the research for physics-based history dependent material modeling of MELD components is the ability to accurately capture the stress-state and strain rate dependence in the material caused by variations in material microstructure from the MELD processing of new or repaired components. The ISV model incorporates microstructural content and is consistent with continuum level kinematics, kinetics, and thermodynamics. These features allow the ISV model to capture large deformations at the structural scale using the kinematic and isotropic hardening, while microscale damage is obtained from the microstructural features. The benefits of the ISV model arise from the inclusion of structure-property relationships identified from microstructural characterization and experimentation. The Bauschinger effect (BE) is an important concept, vital in the accurate prediction of cyclic stress-strain response of ductile materials such as metals. The ISV model has been successfully used to capture the behavior and damage, and the BE of different aluminum alloys and steels. The ISV model uses kinematic and isotropic hardening to help capture deformations of the material at the macro scale. To understand this hardening relationship, calculating the kinematic and isotropic hardening relationship in the material is warranted for a high-fidelity model. Electron Backscattered Diffraction (EBSD) was used to characterize the as-fabricated microstructure, where a fully-dense equiaxed grain morphology with average grain size of 2.5 μm was observed. Microhardness mapping of the as-built structures, monotonic tension and compression experiments at both quasi-static (0.001/s) strain rates, tension-followed-by-compression and compression-followed-by-tension experiments were performed to obtain the set of plasticity and damage constants necessary to capture strain rate and stress state behavior of this additive material. To calibrate the plasticity-damage model, a single set of constants were determined to capture the different stress states the MELD AA2219. One set of the constants was determined from experimental true stress-strain curves for the tension and compression data. Additionally, microstructural information and data from the open literature were used as the other model constants. This research is a first of its kind for AFS AA2219, includes correlating the ISV model to the monotonic experimental results that capture the isotropic and kinematic plasticity mechanical response.

Rivera, O. G.↗

DOE OSTI2023

Impact of Soret effect on hydrogen and helium retention in PFC tungsten under ELM-like conditions

Abstract In our previous work, we have demonstrated using nonequilibrium molecular-dynamics simulations that the fluxes of helium and self-interstitial atoms in the presence of a thermal gradient in tungsten are directed opposite to the heat flux, indicating that species transport is governed by a Soret effect, namely, thermal-gradient-driven diffusion, characterized by a negative heat of transport that drives species transport uphill, i.e. from the cooler to the hot regions of the tungsten sample. In this work, the findings of our thermal and species transport analysis have been implemented in our cluster-dynamics code, Xolotl, which has been used to compute temperature and species profiles over spatiotemporal scales representative of plasma-facing component (PFC) tungsten under typical reactor operating conditions, including extreme heat loads at the plasma-facing surface characteristic of plasma instabilities that induce edge localized modes (ELMs). We demonstrate that the steady-state species profiles, when properly accounting for the Soret effect, vary significantly from those where temperature-gradient-driven transport is not accounted for and discuss the implications of such a Soret effect on the response to plasma exposure of plasma-facing tungsten. Although our cluster-dynamics simulations do not yet include self-clustering of helium or hydrogen blister formation, our simulation results show that the Soret effect substantially reduces helium and hydrogenic species retention inside PFC tungsten.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Efficient learning of power grid voltage control strategies via model-based deep reinforcement learning

Here this article proposes a model-based deep reinforcement learning (DRL) method to design emergency control strategies for short-term voltage stability problems in power systems. Recent advances show promising results for model-free DRL-based methods in power systems control problems. But in power systems applications, these model-free methods have certain issues related to training time (clock time) and sample efficiency; both are critical for making state-of-the-art DRL algorithms practically applicable. DRL-agent learns an optimal policy via a trial-and-error method while interacting with the real-world environment. It is also desirable to minimize the direct interaction of the DRL agent with the real-world power grid due to its safety-critical nature. Additionally, the state-of-the-art DRL-based policies are mostly trained using a physics-based grid simulator where dynamic simulation is computationally intensive, lowering the training efficiency. We propose a novel model-based DRL framework where a deep neural network (DNN)-based dynamic surrogate model (SM), instead of a real-world power grid or physics-based simulation, is utilized within the policy learning framework, making the process faster and more sample efficient. However, having stable training in model-based DRL is challenging because of the complex system dynamics of large-scale power systems. We addressed these issues by incorporating imitation learning to have a warm start in policy learning, reward-shaping, and multi-step loss in surrogate model training. Finally, we achieved 97.5% reduction in samples and 87.7% reduction in training time for an application to the IEEE 300-bus test system.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2019

Electron-phonon coupling and superconductivity-induced distortion of the phonon lineshape in V 3 Si

Phonon measurements in the A15-type superconductors were complicated in the past because of the unavailability of large single crystals for inelastic neutron scattering, e.g., in the case of Nb 3 Sn, or unfavorable neutron scattering properties in the case of V 3 Si. Hence, only few studies of the lattice dynamical properties with momentum resolved methods were published, in particular below the superconducting transition temperature T c . Here, we overcome these problems by employing inelastic x-ray scattering and report a combined experimental and theoretical investigation of lattice dynamics in V 3 Si with the focus on the temperature-dependent properties of low-energy acoustic phonon modes in several high-symmetry directions. We paid particular attention to the evolution of the soft phonon mode of the structural phase transition observed in our sample at T s = 18.9 K, i.e., just above the measured superconducting phase transition at T c = 16.8 K. Theoretically, we predict lattice dynamics including electron-phonon coupling based on density-functional-perturbation theory and discuss the relevance of the soft phonon mode with regard to the value of T c . Furthermore, we explain superconductivity-induced anomalies in the lineshape of several acoustic phonon modes using a model proposed by Allen et al., [Phys. Rev. B 56, 5552 (19 7)].

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2023

Experimental and Numerical Investigation of Flow Boiling in Additive Manufactured Foam Structures With Vapor Pathways

Abstract The unique properties of metal foams make them potential candidates for a range of applications, including microsystem thermal management. Using additive manufacturing to create foam-type structures can improve upon prior thermal solutions by eliminating thermal interface materials and allowing for customization/local control of parameters. In the present investigation, flow boiling in additive-manufactured metal foams is investigated both experimentally and numerically. Two test samples, one with uniform structure and the other with pathways for vapor removal, are compared both experimentally and numerically. A conjugate computational fluid dynamics and heat transfer (CFD-HT) model utilizing a three-dimensional volume of fluid (VOF) model with accompanying evaporation/condensation model provided in-depth visualization of the boiling flow phenomena. The experiments generated the thermohydraulic performance over a range of heat fluxes, demonstrating that the sample incorporating dedicated vapor pathways performed better in both pressure and heat transfer performance metrics compared to the uniform foam. Additionally, negative system-level effects (i.e., hydraulic oscillations) were shown to be abated using the vapor removal structures. The numerical model yielded further insight into the factors contributing to the improved performance. Results indicated the pathways functioned as vapor removal channels, allowing the generated vapor to vent from the foam structure into the lanes. Further computational investigations demonstrated changes in flow regimes, where the addition of vapor channels caused the flow to change from churn to annular. Bubble behavior unique to the vapor pathway structure was studied, showing stagnant regions that eject vapor into the channel.

Engineering↗

NASA NTRS1987

Effect of control sampling rates on model-based manipulator control schemes

The effect of changing the control sampling period on the performance of the computed-torque and independent joint control schemes is discussed. While the former utilizes the complete dynamics model of the manipulator, the latter assumes a decoupled and linear model of the manipulator dynamics. Researchers discuss the design of controller gains for both the computed-torque and the independent joint control schemes and establish a framework for comparing their trajectory tracking performance. Experiments show that within each scheme the trajectory tracking accuracy varies slightly with the change of the sampling rate. However, at low sampling rates the computed-torque scheme outperforms the independent joint control scheme. Based on experimental results, researchers also conclusively establish the importance of high sampling rates as they result in an increased stiffness of the system.

Khosla, P. K.↗

DOE OSTI2021

Detection of significant antiviral drug effects on COVID-19 with reasonable sample sizes in randomized controlled trials: A modeling study

Development of an effective antiviral drug for Coronavirus Disease 2019 (COVID-19) is a global health priority. Although several candidate drugs have been identified through in vitro and in vivo models, consistent and compelling evidence from clinical studies is limited. The lack of evidence from clinical trials may stem in part from the imperfect design of the trials. We investigated how clinical trials for antivirals need to be designed, especially focusing on the sample size in randomized controlled trials. A modeling study was conducted to help understand the reasons behind inconsistent clinical trial findings and to design better clinical trials. We first analyzed longitudinal viral load data for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) without antiviral treatment by use of a within-host virus dynamics model. The fitted viral load was categorized into 3 different groups by a clustering approach. Comparison of the estimated parameters showed that the 3 distinct groups were characterized by different virus decay rates (p-value < 0.001). The mean decay rates were 1.17 d -1 (95% CI: 1.06 to 1.27 d -1 ), 0.777 d -1 (0.716 to 0.838 d -1 ), and 0.450 d -1 (0.378 to 0.522 d -1 ) for the 3 groups, respectively. Such heterogeneity in virus dynamics could be a confounding variable if it is associated with treatment allocation in compassionate use programs (i.e., observational studies). Subsequently, we mimicked randomized controlled trials of antivirals by simulation. An antiviral effect causing a 95% to 99% reduction in viral replication was added to the model. To be realistic, we assumed that randomization and treatment are initiated with some time lag after symptom onset. Using the duration of virus shedding as an outcome, the sample size to detect a statistically significant mean difference between the treatment and placebo groups (1:1 allocation) was 13,603 and 11,670 (when the antiviral effect was 95% and 99%, respectively) per group if all patients are enrolled regardless of timing of randomization. The sample size was reduced to 584 and 458 (when the antiviral effect was 95% and 99%, respectively) if only patients who are treated within 1 day of symptom onset are enrolled. We confirmed the sample size was similarly reduced when using cumulative viral load in log scale as an outcome. We used a conventional virus dynamics model, which may not fully reflect the detailed mechanisms of viral dynamics of SARS-CoV-2. The model needs to be calibrated in terms of both parameter settings and model structure, which would yield more reliable sample size calculation. In this study, we found that estimated association in observational studies can be biased due to large heterogeneity in viral dynamics among infected individuals, and statistically significant effect in randomized controlled trials may be difficult to be detected due to small sample size. The sample size can be dramatically reduced by recruiting patients immediately after developing symptoms. We believe this is the first study investigated the study design of clinical trials for antiviral treatment using the viral dynamics model.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

Generative learning for slow manifolds and bifurcation diagrams

In dynamical systems characterized by separation of time scales, the approximation of so called “slow manifolds”, on which the long term dynamics lie, is a useful step for model reduction. Initializing on such slow manifolds is a useful step in modeling, since it circumvents fast transients, and is crucial in multiscale algorithms (like the equation-free approach) alternating between fine scale (fast) and coarser scale (slow) simulations. In a similar spirit, when one studies the infinite time dynamics of systems depending on parameters, the system attractors (e.g., its steady states) lie on bifurcation diagrams (curves for one-parameter continuation, and more generally, on manifolds in state parameter space. Sampling these manifolds gives us representative attractors (here, steady states of ODEs or PDEs) at different parameter values. Algorithms for the systematic construction of these manifolds (slow manifolds, bifurcation diagrams) are required parts of the “traditional” numerical nonlinear dynamics toolkit. In more recent years, as the field of Machine Learning develops, conditional score-based generative models (cSGMs) have been demonstrated to exhibit remarkable capabilities in generating plausible data from target distributions that are conditioned on some given label. It is tempting to exploit such generative models to produce samples of data distributions (points on a slow manifold, steady states on a bifurcation surface) conditioned on (consistent with) some quantity of interest (QoI, observable). In this work, we present a framework for using cSGMs to quickly (a) initialize on a low-dimensional (reduced-order) slow manifold of a multi-time-scale system consistent with desired value(s) of a QoI (a “label”) on the manifold, and (b) approximate steady states in a bifurcation diagram consistent with a (new, out-of-sample) parameter value. This conditional sampling can help uncover the geometry of the reduced slow-manifold and/or approximately “fill in” missing segments of steady states in a bifurcation diagram. Finally, the quantity of interest, which determines how the sampling is conditioned, is either known a priori or identified using manifold learning-based dimensionality reduction techniques applied to the training data.

Dynamical systems↗

DOE OSTI2018

Generating porosity during olivine carbonation via dissolution channels and expansion cracks

Abstract. The olivine carbonation reaction, in which carbon dioxide is chemically incorporated to form carbonate, is central to the emerging carbon sequestration method using ultramafic rocks. The rate of this retrograde metamorphic reaction is controlled, in part, by the available reactive surface area: as the solid volume increases during carbonation, the feasibility of this method ultimately depends on the maintenance of porosity and the creation of new reactive surfaces. We conducted in situ dynamic X-ray microtomography and nanotomography experiments to image and quantify the porosity generation during olivine carbonation. We designed a sample setup that included a thick-walled cup (made of porous olivine aggregates with a mean grain size of either ∼ 5 or ∼ 80 µm) filled with loose olivine sands with grain sizes of 100–500 µm. The whole sample assembly was reacted with a NaHCO 3 aqueous solution at 200 °C, under a constant confining pressure of 13 MPa and a pore pressure of 10 MPa. Using synchrotron-based X-ray microtomography, the three-dimensional (3-D) pore structure evolution of the carbonating olivine cup was documented until the olivine aggregates became disintegrated. The dynamic microtomography data show a volume reduction in olivine at the beginning of the reaction, indicating a vigorous dissolution process consistent with the disequilibrium reaction kinetics. In the olivine cup with a grain size of ∼ 80 µm (coarse-grained cup), dissolution planes developed within 30 h, before any precipitation was observed. In the experiment with the olivine cup of ∼ 5 µm mean grain size (fine-grained cup), idiomorphic magnesite crystals were observed on the surface of the olivine sands. The magnesite shows a near-constant growth throughout the experiment, suggesting that the reaction is self-sustained. Large fractures were generated as the reaction proceeded and eventually disintegrated the aggregate after 140 h. Detailed analysis show that these are expansion cracks caused by the volume mismatch in the cup walls, between the expanding interior and the near-surface which keeps a nearly constant volume. Nanotomography images of the reacted olivine cup reveal pervasive etch pits and wormholes in the olivine grains. We interpret this perforation of the solids to provide continuous fluid access, which is likely key to the complete carbonation observed in nature. Reactions proceeding through the formation of nano- to micron-scale dissolution channels provide a viable microscale mechanism in carbon sequestration practices. For the natural peridotite carbonation, a coupled mechanism of dissolution and reaction-induced fracturing should account for the observed self-sustainability of the reaction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2016

Use of Interrupted Helium Flow in the Analysis of Vapor Samples with Flowing Atmospheric-Pressure Afterglow-Mass Spectrometry

The flowing atmospheric-pressure afterglow (FAPA) source was used for the mass-spectrometric analysis of vapor samples introduced between the source and mass spectrometer inlet. Through interrupted operation of the plasma-supporting helium flow, helium consumption is greatly reduced and dynamic gas behavior occurs that was characterized by schlieren imaging. Moreover, mass spectra acquired immediately after the onset of helium flow exhibit a signal spike before declining and ultimately reaching a steady level. This initial signal appears to be due to greater interaction of sample vapor with the afterglow of the source when helium flow resumes. In part, the initial spike in signal can be attributed to a pooling of analyte vapor in the absence of helium flow from the source. Finally, time-resolved schlieren imaging of the helium flow during on and off cycles provided insight into gas-flow patterns between the FAPA source and the MS inlet that were correlated with mass-spectral data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2017

Development of a Multi-Press Assembly Device for Planar Dynamic Material Property Targets

A class of dynamic material property (DMP) experiments on the Sandia National Laboratories (SNL) pulse power Z-Machine requires planar samples to be held in a panel assembly. A custom press device to fabricate the assemblies has the ability to assemble one sample, window, or stack at a time, resulting in a one week lead time for a typical three-pocket panel assembly. Fabrication of targets with more than three pockets can take longer. In late 2015, General Atomics (GA) conceptualized a new multi-press device to enable several samples, windows, or stacks to be assembled simultaneously, and a prototype was designed, procured, and outfitted in six months. Since June 2016, this multi-press design has successfully assembled 60 planar DMP targets. Furthermore, the development considerations for this new device and the resulting benefits for the fabrication of targets are discussed.

36 MATERIALS SCIENCE↗

DOE OSTI2016

Probing surface hydrogen bonding and dynamics by natural abundance, multidimensional, 17 O DNP-NMR spectroscopy

Dynamic nuclear polarization (DNP)-enhanced solid-state nuclear magnetic resonance (SSNMR) spectroscopy is increasingly being used as a tool for the atomic-level characterization of surface sites. DNP surface-enhanced SSNMR spectroscopy of materials has, however, been limited to studying relatively receptive nuclei, and the particularly rare 17 O nuclide, which is of great interest for materials science, has not been utilized. We demonstrate that advanced 17 O SSNMR experiments can be performed on surface species at natural isotopic abundance using DNP. We use 17 O DNP surface-enhanced 2D SSNMR to measure 17 O{ 1 H} HETCOR spectra as well as dipolar oscillations on a series of thermally treated mesoporous silica nanoparticle samples having different pore diameters. These experiments allow for a nonintrusive and unambiguous characterization of hydrogen bonding and dynamics at the surface of the material; no other single experiment can give such details about the interactions at the surface. Lastly, our data show that, upon drying, strongly hydrogen-bonded surface silanols, whose motions are greatly restricted by the interaction when compared to lone silanols, are selectively dehydroxylated.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗