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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 307 records · Page 17

Machine Learning Applied to a Variable Charge Atomistic Model for Cu/Hf Binary Alloy Oxide Heterostructures [Machine Learning a Variable Charge Atomistic Model for Cu/Hf Binary Alloy Oxide Heterostructures]

Alloy oxide heterostructures are essential for a wide variety of energy applications, including anticorrosion coatings, bifunctional catalysis, energy storage, as well as emerging platforms for multilevel nonvolatile memory and neuromorphic devices. The key role played by oxide composition, density, and stoichiometry in governing electrochemical reactions, interface structure, and ionic transport in alloy oxides remains largely unknown. This is primarily due to the lack of variable charge interatomic potential models that can adequately describe the various atomic/ionic interactions in alloy oxides within a unified framework. Here, we introduce a charge transfer ionic potential (CTIP) model for Cu/Hf/O alloy system and demonstrate its ability to accurately capture the complex potential energy surface owing to dynamically varying interactions, including metallic (Cu/Hf), ionic (Cu/Hf/Ox), mixed environment (interfaces). We leverage supervised machine learning methods powered by genetic algorithms coupled with local simplex optimization to efficiently navigate through a high-dimensional parameter space and identify an optimum set of an independent set of CTIP parameters. We train our model against an extensive first-principles based data set that includes lattice constants, cohesive energies, equations of state, and elastic constants of various experimentally observed polymorphs of hafnia, copper oxide, hafnium, as well as copper. Our machine-learned CTIP model captures the structure, elastic properties, thermodynamics, and energetic ordering of various polymorphs. It also accurately predicts the surface properties of both oxides and their metals. To demonstrate the suitability of our CTIP model for investigating dynamic processes, we employed it to identify the atomistic scale mechanisms associated with the initial nanoscale oxidation and surface oxide growth on Cu-doped hafnia surfaces. Here, our machine-learned CTIP model can be used to probe the dynamic response of Cu/Hf/O alloy interfaces subjected to external stimuli (e.g., electric field, pressure, temperature, strain, etc.) and a variety of atomistic phenomena including the dynamics of switching in emerging neuromorphic platforms.

36 MATERIALS SCIENCE↗

A new structural relaxation pathway of low-density amorphous ice

Low-density amorphous (LDA) ice is involved in critical cosmological processes and has gained prominence as one of the at least two distinct amorphous forms of ice. Despite these accolades, we still have an incomplete understanding of the structural diversity that is encompassed within the LDA state and the dynamic processes that take place upon heating LDA. Heating the high-pressure ice VIII phase at ambient pressure is a remarkable example of temperature-induced amorphisation yielding LDA. We investigate this process in detail using X-ray diffraction and Raman spectroscopy and show that the LDA obtained from ice VIII is structurally different from the more “traditional” states of LDA which are approached upon thermal annealing. This new structural relaxation pathway involves an increase of structural order on the intermediate range length scale. In contrast with other LDA materials the local structure is more ordered initially and becomes slightly more disordered upon annealing. We also show that the cascade of phase transitions upon heating ice VIII at ambient pressure includes the formation of ice IX which may be connected with the structural peculiarities of LDA from ice VIII. Overall, this study shows that LDA is a structurally more diverse material than previously appreciated.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

In-Situ X-Ray Imaging High Strain Rate Compression of Laminate Al-Graphene Composite and Mechanical Property Characterization

Owing to the opaque nature of the laminated structures, traditional high-speed optical camera cannot be used to detect the dynamic process of sub-surface deformation. In this article, we report a study of using high speed X-ray imaging to study the high strain rate deformation in laminated Al structures. We used a Kolsky bar apparatus to apply dynamic compression and a high-speed synchrotron X-ray phase contrast imaging (PCI) setup to conduct the in situ X-ray imaging study. The in situ X-ray imaging captures the shock wave propagation in the laminated structures. After shock compression, we characterized the microstructures by using transmission electron microscopy (TEM), which demonstrates an increase of dislocation density. In conclusion, the micro-pillar compression tests show that the yield strength at 0.2% offset of laminated Al-graphene composite has a significant increase of 67%, from 30 to 50 MPa, compared to laminate Al after shock loading.

36 MATERIALS SCIENCE↗

Anatomy of a fumarolic system inferred from a multiphysics approach

Fumaroles are a common manifestation of volcanic activity that are associated with large emissions of gases into the atmosphere. These gases originate from the magma, and they can provide indirect and unique insights into magmatic processes. Therefore, they are extensively used to monitor and forecast eruptive activity. During their ascent, the magmatic gases interact with the rock and hydrothermal fluids, which modify their geochemical compositions. These interactions can complicate our understanding of the real volcanic dynamics and remain poorly considered. Here, we present the first complete imagery of a fumarolic plumbing system using three-dimensional electrical resistivity tomography and new acoustic noise localization. We delineate a gas reservoir that feeds the fumaroles through distinct channels. Based on this geometry, a thermodynamic model reveals that near-surface mixing between gas and condensed steam explains the distinct geochemical compositions of fumaroles that originate from the same source. Such modeling of fluid interactions will allow for the simulation of dynamic processes of magmatic degassing, which is crucial to the monitoring of volcanic unrest.

58 GEOSCIENCES↗

Droplet bioprinting of acellular and cell-laden structures at high-resolutions

Advances in digital light projection(DLP) based (bio) printers have made printing of intricate structures at high resolution possible using a wide range of photosensitive bioinks. A typical setup of a DLP bioprinter includes a vat or reservoir filled with liquid bioink, which presents challenges in terms of cost associated with bioink synthesis, high waste, and gravity-induced cell settling, contaminations, or variation in bioink viscosity during the printing process. Here, we report a vat-free, low-volume, waste-free droplet bioprinting method capable of rapidly printing 3D soft structures at high resolution using model bioinks and model cells. A multiphase many-body dissipative particle dynamics model was developed to simulate the dynamic process of droplet-based DLP printing and elucidate the roles of surface wettability and bioink viscosity. Process variables such as light intensity, photo-initiator concentration, and bioink formulations were optimized to print 3D soft structures (∼0.4–3 kPa) with a typical layer thickness of 50 µm, an XY resolution of 38 ± 1.5 μm and Z resolution of 237 ± 5.4 µm. To demonstrate its versatility, droplet bioprinting was used to print a range of acellular 3D structures such as a lattice cube, a Mayan pyramid, a heart-shaped structure, and a microfluidic chip with endothelialized channels. Droplet bioprinting, performed using model C3H/10T1/2 cells, exhibited high viability (90%) and cell spreading. Additionally, microfluidic devices with internal channel networks lined with endothelial cells showed robust monolayer formation while osteoblast-laden constructs showed mineral deposition upon osteogenic induction. Overall, droplet bioprinting could be a low-cost, no-waste, easy-to-use, method to make customized bioprinted constructs for a range of biomedical applications.

DLP↗

Hydration-dependent dynamics of human telomeric oligonucleotides in the picosecond timescale: A neutron scattering study

The dynamics of the human oligonucleotide AG{sub 3}(T{sub 2}AG{sub 3}){sub 3} has been investigated by incoherent neutron scattering in the sub-nanosecond timescale. A hydration-dependent dynamical activation of thermal fluctuations in weakly hydrated samples was found, similar to that of protein powders. The amplitudes of such thermal fluctuations were evaluated in two different exchanged wave-vector ranges, so as to single out the different contributions from intra- and inter-nucleotide dynamics. The activation energy was calculated from the temperature-dependent characteristic times of the corresponding dynamical processes. The trends of both amplitudes and activation energies support a picture where oligonucleotides possess a larger conformational flexibility than long DNA sequences. This additional flexibility, which likely results from a significant relative chain-end contribution to the average chain dynamics, could be related to the strong structural polymorphism of the investigated oligonucleotides.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Inclusion of nuclear quantum effects for simulations of nonlinear spectroscopy

The computation and interpretation of nonlinear vibrational spectroscopy is of vital importance for understanding a wide range of dynamical processes in molecular systems. Here, we introduce an approach to evaluate multi-time response functions in terms of multi-time double symmetrized Kubo transformed thermal correlation functions. Furthermore, we introduce a multi-time extension of ring polymer molecular dynamics to evaluate these Kubo transforms. Benchmark calculations show that the approximations are useful for short times even for nonlinear operators, providing a consistent improvement over classical simulations of multi-time correlation functions. In conclusion, the introduced methodology thus provides a practical way of including nuclear quantum effects in multi-time response functions of non-linear optical spectroscopy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

SECULAR DYNAMICAL ANTI-FRICTION IN GALACTIC NUCLEI

We identify a gravitational-dynamical process in near-Keplerian potentials of galactic nuclei that occurs when an intermediate-mass black hole (IMBH) is migrating on an eccentric orbit through the stellar cluster towards the central supermassive black hole. We find that, apart from conventional dynamical friction, the IMBH experiences an often much stronger systematic torque due to the secular (i.e., orbit-averaged) interactions with the cluster's stars. The force which results in this torque is applied, counterintuitively, in the same direction as the IMBH's precession and we refer to its action as 'secular dynamical anti-friction' (SDAF). We argue that SDAF, and not the gravitational ejection of stars, is responsible for the IMBH's eccentricity increase seen in the initial stages of previous N-body simulations. Our numerical experiments, supported by qualitative arguments, demonstrate that (1) when the IMBH's precession direction is artificially reversed, the torque changes sign as well, which decreases the orbital eccentricity; (2) the rate of eccentricity growth is sensitive to the IMBH migration rate, with zero systematic eccentricity growth for an IMBH whose orbit is artificially prevented from inward migration; and (3) SDAF is the strongest when the central star cluster is rapidly rotating. This leads to eccentricity growth/decrease for the clusters rotating in the opposite/same direction relative to the IMBH's orbital motion.

79 ASTRONOMY AND ASTROPHYSICS↗

Imaging of dynamic magnetic fields with spin-polarized neutron beams

Precession of neutron spin in a magnetic field can be used for mapping of a magnetic field distribution, as demonstrated previously for static magnetic fields at neutron beamline facilities. The fringing in the observed neutron images depends on both the magnetic field strength and the neutron energy. In this paper we demonstrate the feasibility of imaging periodic dynamic magnetic fields using a spin-polarized cold neutron beam. Our position-sensitive neutron counting detector, providing with high precision both the arrival time and position for each detected neutron, enables simultaneous imaging of multiple phases of a periodic dynamic process with microsecond timing resolution. The magnetic fields produced by 5- and 15-loop solenoid coils of 1 cm diameter, are imaged in our experiments with ~100 μm resolution for both dc and 3 kHz ac currents. Our measurements agree well with theoretical predictions of fringe patterns formed by neutron spin precession. We also discuss the wavelength dependence and magnetic field quantification options using a pulsed neutron beamline. Furthermore, the ability to remotely map dynamic magnetic fields combined with the unique capability of neutrons to penetrate various materials (e.g., metals), enables studies of fast periodically changing magnetic processes, such as formation of magnetic domains within metals due to the presence of ac magnetic fields.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Expedited Real Time Processing for the NETL HYPER Cyber-Physical System (Final Report)

The primary objective of the proposed project was to provide the National Energy Technology Laboratory’s Hybrid Performance (Hyper) Facility the needed numerical methods algorithm(s), software development and implementation support to enact real time cyber-physical systems (CPSs) that simulate process dynamics on the order of five milliseconds or smaller. The proposed paths forward comprised three distinct approaches to hasten transient simulations. They fell under the numerical methods categorical options of: 1) optimizing key parameters within the facility’s pre-existing real time processing scheme; 2) introducing an “informed” processing approach wherein a priori computations expedite real time attempts; and 3) implementing alternatives to the employed explicit-implicit blended finite difference (spatio-temporal) approach. Each of these three classes were proposed independently as options for improvement, yet in some cases one class of approach could have complemented another.

20 FOSSIL-FUELED POWER PLANTS↗

Nanoscale defect evaluation framework combining real-time transmission electron microscopy and integrated machine learning-particle filter estimation

Observation of dynamic processes by transmission electron microscopy (TEM) is an attractive technique to experimentally analyze materials’ nanoscale phenomena and understand the microstructure-properties relationships in nanoscale. Even if spatial and temporal resolutions of real-time TEM increase significantly, it is still difficult to say that the researchers quantitatively evaluate the dynamic behavior of defects. Images in TEM video are a two-dimensional projection of three-dimensional space phenomena, thus missing information must be existed that makes image’s uniquely accurate interpretation challenging. Therefore, even though they are still a clustering high-dimensional data and can be compressed to two-dimensional, conventional statistical methods for analyzing images may not be powerful enough to track nanoscale behavior by removing various artifacts associated with experiment; and automated and unbiased processing tools for such big-data are becoming mission-critical to discover knowledge about unforeseen behavior. We have developed a method to quantitative image analysis framework to resolve these problems, in which machine learning and particle filter estimation are uniquely combined. The quantitative and automated measurement of the dislocation velocity in an Fe-31Mn-3Al-3Si autunitic steel subjected to the tensile deformation was performed to validate the framework, and an intermittent motion of the dislocations was quantitatively analyzed. The framework is successfully classifying, identifying and tracking nanoscale objects; these are not able to be accurately implemented by the conventional mean-path based analysis.

36 MATERIALS SCIENCE↗

Static and Dynamic Intensification of Water–Ethylene Glycol Separation Using a Dividing Wall Column

This paper makes several first-of-a-kind contributions toward “double intensification” (static/dynamic) of distillation systems, focusing in particular on the energy-intensive separation of a mixture of water and ethylene glycols. First, we demonstrate that a dividing wall column (DWC) can be an appropriate choice for separating wide-boiling zeotropic mixtures. Additionally, we show that the conventional DWC configuration where the wall is in the “middle” should be discarded in favor of a less frequently encountered “common-bottom” setup. For the mixture considered, choosing a DWC in lieu of a conventional two-column sequence can lead to over 6% energy cost savings and a 5% reduction in the number of stages compared to the conventional direct sequence two-column counterpart. The second part of this paper focuses on applying the previously introduced concept of dynamic process intensification to the DWC, the first time that such an effort is reported in the literature, to our knowledge. Here, we show that an additional 1.4% energy savings can be unlocked in this way, and confirm the stable operation of the column via dynamic simulation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Plasma flow reactor for steady state monitoring of physical and chemical processes at high temperatures

Here, we present the development of a steady state plasma flow reactor to investigate gas phase physical and chemical processes that occur at high temperature (1000 < T < 5000 K) and atmospheric pressure. The reactor consists of a glass tube that is attached to an inductively coupled argon plasma generator via an adaptor (ring flow injector). We have modeled the system using computational fluid dynamics simulations that are bounded by measured temperatures. In situ line-of-sight optical emission and absorption spectroscopy have been used to determine the structures and concentrations of molecules formed during rapid cooling of reactants after they pass through the plasma. Emission spectroscopy also enables us to determine the temperatures at which these dynamic processes occur. A sample collection probe inserted from the open end of the reactor is used to collect condensed materials and analyze them ex situ using electron microscopy. The preliminary results of two separate investigations involving the condensation of metal oxides and chemical kinetics of high-temperature gas reactions are discussed.

36 MATERIALS SCIENCE↗

Concurrent probing of electron-lattice dephasing induced by photoexcitation in 1 T -TaSeTe using ultrafast electron diffraction

It has been technically challenging to concurrently probe the electrons and the lattices in materials during nonequilibrium processes, allowing their correlations to be determined. Here, in a single set of ultrafast electron diffraction patterns taken on the charge-density-wave (CDW) material 1T-TaSeTe, we discover a temporal shift in the diffraction intensity measurements as a function of scattering angle. With the help of dynamic models and theoretical calculations, we show that the ultrafast electrons probe both the valence-electron and lattice dynamic processes, resulting in the temporal shift measurements. Our results demonstrate unambiguously that the CDW is not merely a result of the periodic lattice deformation ever present in 1T-TaSeTe but has significant electronic origin. This method demonstrates an approach for studying many quantum effects that arise from electron-lattice dephasing in molecules and crystals for next-generation devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Imaging Coherent Structural Dynamics with Ultrafast Electron Microscopy

Development of ultrafast electron and X-ray scattering methods has enabled direct routes to probing atomic-scale structural dynamics. This in turn has led to new insight into lattice responses to a variety of dynamic processes associated with phase transformations, electron-lattice correlations, and nanoscale mechanical motion, to name a few. Presently, the most wide-spread approaches involve using table-top, laser-driven electron-scattering chambers or femtosecond (fs) X-ray beamlines to probe dynamics in reciprocal space and, in many instances, over specimen regions that are large relative to unit-cell dimensions and discrete (atomic and nanoscale) structural and morphological defects (e.g., vacancies, line and screw dislocations, grain boundaries, interfaces, etc.). As a result, the transients monitored for relatively large-spot-size reciprocal-space measurements – typically some aspect of a Bragg reflection (intensity, position, width, shape) – may be comprised of a range of responses occurring within the probed region. To directly resolve the role of distinct morphologies and structural features on dynamics associated with the nucleation, emergence, evolution, and decay of coherent phenomena, one would ideally directly image the local, nanoscale behaviors and precisely correlate responses to the nature of the feature. Here, I will show how such effects can be directly probed with ultrafast electron microscopy (UEM). After a brief overview of the operating principles of UEM, I will discuss how we are using real-space imaging to directly visualize coherent structural dynamics in a variety of nanostructured and nanoscale materials.

47 OTHER INSTRUMENTATION↗

Quantitative comparison of adaptive sampling methods for protein dynamics

Adaptive sampling methods, often used in combination with Markov state models, are becoming increasingly popular for speeding up rare events in simulation such as molecular dynamics (MD) without biasing the system dynamics. Several adaptive sampling strategies have been proposed, but it is not clear which methods perform better for different physical systems. Here, we present a systematic evaluation of selected adaptive sampling strategies on a wide selection of fast folding proteins. The adaptive sampling strategies were emulated using models constructed on already existing MD trajectories. We provide theoretical limits for the sampling speed-up and compare the performance of different strategies with and without using some a priori knowledge of the system. The results show that for different goals, different adaptive sampling strategies are optimal. In order to sample slow dynamical processes such as protein folding without a priori knowledge of the system, a strategy based on the identification of a set of metastable regions is consistently the most efficient, while a strategy based on the identification of microstates performs better if the goal is to explore newer regions of the conformational space. Interestingly, the maximum speed-up achievable for the adaptive sampling of slow processes increases for proteins with longer folding times, encouraging the application of these methods for the characterization of slower processes, beyond the fast-folding proteins considered here.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

ZFSP Proposal: Understanding the Physics and Chemistry of Iron Alloys relevant to the Conditions of Planetary Cores

Recent research results by the deep-Earth geoscience and astronomy communities have revealed a wealth of interesting and outstanding fundamental science questions about the interiors of terrestrial planets and exoplanets including the origin of the magnetic field in the iron core and its impact on the evolution of life, the alloying of light elements on physics and chemistry of the planet’s dynamic processes, and the discovery of super-rotation and heterogeneous behavior of the inner core. Resolving these questions requires a first-hand experimental database at relevant pressure-temperature (P-T) conditions, but is technically challenging using static diamond anvil cell (DAC) and dynamic shock wave efforts alone, due to their limited P-T conditions and analytical capabilities. However, the recent advent of new capabilities of Sandia’s Z-Machine, coupled with our recent developments in in-situ ellipsometry at the UT Austin and Sandia National Laboratory and first-principles calculations and geodynamic modelling capabilities at UC Berkeley, motivates the joint collaborative effort presented here. In this collaborative research, we will use the capabilities of Sandia’s Z-Machine to investigate the elastic, thermal transport and melting properties of material relevant to both Earth and exoplanets at their relative P-T conditions. Our long-term research goal is to better understand the physics and dynamics of planetary interiors through interdisciplinary collaborations between physicists, mineral physicists, theorists, geodynamicists, and astrophysicists. The conditions in the Earth and super-Earth can range up to ~300-500 GPa and ~5000-8000 K. We will couple these experiments with a unique set of diagnostics, to include a new ellipsometry capability, in order to sensitively measure conductivity of these materials, and phase changes, including melting. Specifically, the newly demonstrated capability of Z to shock materials to a given P-T along the Hugoniot, and then to apply a pressure ramp taking the material along an isentrope, provides a unique opportunity to obtain P-T conditions not accessible by traditional DAC technology, or through shocks simply along the Hugoniot. Our physics team will perform experiments and analyze results to determine the physics underlying iron alloys as high-energy planetary impactors, classic transition metal alloys, and iron-bearing periclase relevant to the interiors of rocky planets, including exoplanets. The experimental results so analyzed will provide data that our collaborative team of mineral physicists, geodynamics, seismologists, and astrophysicists will apply toward obtaining a fundamental understanding of the physical and chemical states of the terrestrial planets and exoplanets, including their chemical compositions, thermal transport behavior, origin of magnetic fields, and dynamic evolution of the planet.

58 GEOSCIENCES↗

Marine ice sheet experiments with the Community Ice Sheet Model

Ice sheet models differ in their numerical treatment of dynamical processes. Simulations of marine-based ice are sensitive to the choice of Stokes flow approximation and basal friction law and to the treatment of stresses and melt rates near the grounding line. We study the effects of these numerical choices on marine ice sheet dynamics in the Community Ice Sheet Model (CISM). In the framework of the Marine Ice Sheet Model Intercomparison Project 3d (MISMIP3d), we show that a depth-integrated, higher-order solver gives results similar to a 3D (Blatter–Pattyn) solver. We confirm that using a grounding line parameterization to approximate stresses in the grounding zone leads to accurate representation of ice sheet flow with a resolution of ~2 km, as opposed to ~0.5 km without the parameterization. In the MISMIP+ experimental framework, we compare different treatments of sub-shelf melting near the grounding line. In contrast to recent studies arguing that melting should not be applied in partly grounded cells, it is usually beneficial in CISM simulations to apply some melting in these cells. This suggests that the optimal treatment of melting near the grounding line can depend on ice sheet geometry, forcing, or model numerics. In both experimental frameworks, ice flow is sensitive to the choice of basal friction law. To study this sensitivity, we evaluate friction laws that vary the connectivity between the basal hydrological system and the ocean near the grounding line. CISM yields accurate results in steady-state and perturbation experiments at a resolution of ~2 km (arguably 4 km) when the connectivity is low or moderate and ~1 km (arguably 2 km) when the connectivity is strong.

54 ENVIRONMENTAL SCIENCES↗