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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 433 records · Page 24

A computational study of diffusion in a glass-forming metallic liquid

In this study, liquid phase diffusion plays a critical role in phase transformations (e.g. glass transformation and devitrification) observed in marginal glass forming systems such as Al-Sm. Controlling transformation pathways in such cases requires a comprehensive description of diffusivity, including the associated composition and temperature dependencies. In our computational study, we examine atomic diffusion in Al-Sm liquids using ab initio molecular dynamics (AIMD) and determine the diffusivities of Al and Sm for selected alloy compositions. Non-Arrhenius diffusion behavior is observed in the undercooled liquids with an enhanced local structural ordering. Through assessment of our AIMD result, we construct a general formulation for Al-Sm liquid, involving a diffusion mobility database that includes composition and temperature dependence. A Volmer-Fulcher-Tammann (VFT) equation is adopted for describing the non-Arrhenius behavior observed in the undercooled liquid. Furthermore, the composition dependence of diffusivity is found quite strong, even for the Al-rich region contrary to the sole previous report on this binary system. The model is used in combination with the available thermodynamic database to predict specific diffusivities and compares well with reported experimental data for 0.6 at.% and 5.6 at.% Sm in Al-Sm alloys.

36 MATERIALS SCIENCE↗

COMPUTER-AIDED LATTICE DESIGN AND ADVANCED MODELING FOR THE DEVELOPMENT OF LIGHTWEIGHT STRUCTURAL MATERIALS

The notion of a “fission battery” conveys a vision focused on realizing very simple “plug-and-play” nuclear systems that can be integrated into a variety of applications requiring affordable, reliable energy in the form of electricity and/or heat and function without operations and maintenance staff. Fission batteries require lightweight structural materials to increase their mobility, and the lightweight materials must demonstrate structural resilience under various conditions. The objective of this work is to develop lattice structured lightweight structural material featuring a good combination of mechanical properties using advanced modeling and simulation together with an advanced additive manufacturing technique such as laser powder bed fusion. The preliminary results show that different lattice structures and types can be successfully meshed using nTopology software, and the lattice structure data can be successfully transformed to Multiphysics Object-Oriented Simulation (MOOSE) Environment input. Finite Element Analysis (FEA) displays that, at macro/engineering scale simulation, the weight saving design has an obvious effect on tensile behavior such as effective elastic modulus and yield stress. The novel approaches of this work are (1) development of lattice structures for improved mechanical properties using advanced simulation and modeling techniques; and (2) model predictions of the mechanical properties (e.g., strength and stress distribution) of macroscopic materials in order to preliminarily select a lattice structure for additive manufacturing.

36 MATERIALS SCIENCE↗

Experimental and Computational Mechanistic Studies Guiding the Rational Design of Molecular Electrocatalysts for Production and Oxidation of Hydrogen

Understanding how to control the movement of protons and electrons is crucial to the design of fast, efficient electrocatalysts for hydrogen production and oxidation based on earth-abundant metals. Our work seeks to elucidate fundamental questions about proton movement. We have demonstrated that incorporating a pendant amine functioning as a proton relay in the second coordination sphere of a metal complex helps proton mobility, resulting in faster and more energy efficient catalysts. Proton transfer reactions are often rate limiting, and are influenced by several factors, such as pKa values, steric effects, hydrogen bonding, and solvation/desolvation of the exogenous base and acid employed. The presence of multiple protonation sites introduces branching points along the catalytic cycle, making less productive pathways accessible, or leading to the formation of stable off-cycle species. Using ligands with only one pendant amine mitigates this problem and results in catalysts with high rates for production of H2. For H2 oxidation catalysts, iron complexes with a high H2 binding affinity were developed. However, the improvement of H2 binding enthalpy resulted in a pKa mismatch between the protonated metal center and the protonated pendant amine, and consequently to rate-limiting intramolecular proton movement. Taken altogether, our results demonstrate the necessity of optimizing the entire catalytic cycle, as the optimization of a specific catalytic step can negatively influence another step, and not necessarily lead to better catalytic performance. We discuss a general procedure, based on thermodynamic arguments, which allows the simultaneous minimization of the free energy change of each catalytic step, yielding a nearly flat free energy surface, with no large barriers due to energy mismatches from either high- or low-energy intermediates. This research was supported as part of the Center for Molecular Electrocatalysis, an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences. Pacific Northwest National Laboratory is operated by Battelle for DOE.

hydrogen, catalysis, quantum chemistry, proton tra↗

High resolution viscous fingering simulation in miscible displacement using a p-adaptive discontinuous Galerkin method with algebraic multigrid preconditioner

High resolution simulation of viscous fingering can offer an accurate and detailed prediction for subsurface engineering processes involving fingering phenomena. The fully implicit discontinuous Galerkin (DG) method has been shown to be an accurate and stable method to model viscous fingering with high Peclet number and mobility ratio. In this study, we present two techniques to speedup large scale simulations of this kind. The first technique relies on a simple p-adaptive scheme in which high order basis functions are employed only in elements near the finger fronts where the concentration has a sharp change. As a result, the number of degrees of freedom is significantly reduced and the simulation yields almost identical results to the more expensive simulation with uniform high order elements throughout the mesh. The second technique for speedup involves improving the solver efficiency. We present an algebraic multigrid (AMG) preconditioner which allows the DG matrix to leverage the robust AMG preconditioner designed for the continuous Galerkin (CG) finite element method. The resulting preconditioner works effectively for fixed order DG as well as p-adaptive DG problems. Finally, with the improvements provided by the p-adaptivity and AMG preconditioning, we can perform high resolution three-dimensional viscous fingering simulations required for miscible displacement with high Peclet number and mobility ratio in greater detail than before for well injection problems.

97 MATHEMATICS AND COMPUTING↗

Algorithms and file structures to enhance software workflows for ion mobility mass spectrometry (IM-MS)

Support customizations of algorithms and raw data file structures to enhance software workflows for liquid chromatography (LC), mass spectrometry (MS) and ion mobility mass spectrometry (IM-MS)-based metabolite characterization. Evaluate and improve the integration of ion mobility to existing MS analysis methods of the Mass Profiler Professional workflow (Mass Profiler, ID Browser and Mass Profiler Professional).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Polarization-controlled volatile ferroelectric and capacitive switching in Sn 2 P 2 S 6

Abstract Smart electronic circuits that support neuromorphic computing on the hardware level necessitate materials with memristive, memcapacitive, and neuromorphic- like functional properties; in short, the electronic response must depend on the voltage history, thus enabling learning algorithms. Here we demonstrate volatile ferroelectric switching of Sn 2 P 2 S 6 at room temperature and see that initial polarization orientation strongly determines the properties of polarization switching. In particular, polarization switching hysteresis is strongly imprinted by the original polarization state, shifting the regions of non-linearity toward zero-bias. As a corollary, polarization switching also enables effective capacitive switching, approaching the sought-after regime of memcapacitance. Landau–Ginzburg–Devonshire simulations demonstrate that one mechanism by which polarization can control the shape of the hysteresis loop is the existence of charged domain walls (DWs) decorating the periphery of the repolarization nucleus. These walls oppose the growth of the switched domain and favor back-switching, thus creating a scenario of controlled volatile ferroelectric switching. Although the measurements were carried out with single crystals, prospectively volatile polarization switching can be tuned by tailoring sample thickness, DW mobility and electric fields, paving way to non-linear dielectric properties for smart electronic circuits.

97 MATHEMATICS AND COMPUTING↗

Crystallization and Thermoelectric Transport in Semiconductor Micro- and Nanostructures Under Extreme Conditions

This project focused on thermoelectric transport in semiconductor micro and nanostructures where moderate and typical operating voltages and currents lead to extreme thermal gradients and current densities. Models that describe behavior of semiconducting materials typically assume an equilibrium condition or slight deviations from it. In these cases the generation-recombination processes are assumed to have reached a local equilibrium for a given temperature. Hence, free carrier concentrations and their mobilities, band-gap, thermal conductivity, thermoelectric properties, mobility of atoms and mechanical properties of the material, can be described as a function of temperature. In the case of PN junctions under electrical bias, carrier concentrations can change up to ~ 1020 cm-3 and a drift-diffusion approximation is typically used to obtain the carrier concentrations while assuming that the material properties do not change. In non-equilibrium conditions, the assumption that the material properties remain the same may not be valid. While the increased conduction-band electron concentration may not have a drastic effect on the material, large hole concentration is expected to soften the material as ‘a hole’ comes into existence as a broken bond in the lattice. As the hole density approaches 1022 cm-3, the number of bonds holding the lattice together is significantly reduced, making it easier to break additional bonds, reduce band-gap and inhibit phonon transport. As these holes move away from where they were generated, local properties are expected to deviate significantly from the equilibrium case. Hence, temperature alone is not sufficient to describe the behavior of the material. The behavior of the solid material close to a molten region (liquid-solid interfaces) is also expected to deviate from the equilibrium case as a function of hole injection rate, which can be drastically increased or decreased in the presence of an electric field. In the past years we have investigated the possible thermoelectric explanation of asymmetric melting of self-heated Si micro-structures using equilibrium materials’ properties that exist in the literature. We have analyzed the contribution of the electrons and the holes and identified the generation-transport-recombination of minority carriers (GTR) as the reason for an extreme change in the thermal profile in presence of strong generation and electric field. A more complete analysis required construction of models that capture the individual generation and recombination processes to understand the thermal profile as well as the possibility of electronic softening and non-equilibrium melting of the structure below melting temperature. The possibility of melting a material at a lower temperature breaks the correlation between the atomic mobility and the kinetic energy in the system for a given temperature and may allow alternative growth processes. This may also be the mechanism behind ‘amorphization-without-melting in layered structures heated with laser pulses’ that has been reported earlier. The conventional models for semiconductors are constructed for low temperature operation and their projections to higher temperatures do not yield reasonable carrier concentrations. Using these models, the free hole concentrations are calculated to be on the order of 1019 cm-3 at melting, which also do not correlate well with the latent heat of fusion. The melt is expected to correspond to broken bond concentrations on the order of the atomic density (~5x1022 cm-3 for Silicon). Hence, using conventional models the thermoelectric contribution expected from the GTR process is estimated to be much smaller than it likely is. Our work focused on improving the computational models and electrical characterization of materials and devices to better understand thermoelectric trabsport under extremen thermal gradients and current densities. Specifically, during this project, we have - Expanded our computational models to include self-consistent solution of Poisson charge equation (together with current and heat equations currently solved) for improved accuracy of role of bipolar conduction, - Developed a crystallization model incorporating experimentally determined nucleation rates and growth velocities to enable simulation of grain growth, growth-from-melt, filament formation and retention, - Performed high-temperature characterization of relevant materials (including metal contacts, interfacial and insulation layers); electrical and thermal conductivities, Seebeck coefficient, carrier mobility and concentration, - Performed High-speed device-level characterization of metastable amorphous and crystalline phases, crystallization and amorphization dynamics, melting and crystalline growth-from-melt, - Observed and characterized formation of microplasmas in electrically stressed ZnO nanoforests.

36 MATERIALS SCIENCE↗

Best of both worlds: Enforcing detailed balance in machine learning models of transition rates

The slow microstructural evolution of materials often plays a key role in determining material properties. When the unit steps of the evolution process are slow, direct simulation approaches such as molecular dynamics become prohibitive and Kinetic Monte-Carlo (kMC) algorithms, where the state-to-state evolution of the system is represented in terms of a continuous-time Markov chain, are instead frequently relied upon to efficiently predict long-time evolution. The accuracy of kMC simulations however relies on the complete and accurate knowledge of reaction pathways and corresponding kinetics. This requirement becomes extremely stringent in complex systems such as concentrated alloys where the astronomical number of local atomic configurations makes the a priori tabulation of all possible transitions impractical. Machine learning models of transition kinetics have been used to mitigate this problem by enabling the efficient on-the-fly prediction of kinetic parameters. While conventional KMC methods based on transition state theory naturally yield reversible dynamics that exactly obey the detailed balance criterion, providing strong guarantees on the properties of the stationary distribution, many recently-proposed ML-based approaches to barrier predictions provide no such guarantees. In this study, we derive conditions under which physics-informed ML architectures exactly enforce the detailed balance condition by construction, even when relying on non-extensive descriptions of states in terms of local environments around mobile defects. In conclusion, using the diffusion of a vacancy in a concentrated alloy as an example, we show that such ML architectures also exhibit superior performance in terms of prediction accuracy, demonstrating that the imposition of physical constraints can facilitate the accurate learning of barriers at no increase in computational cost.

36 MATERIALS SCIENCE↗

Quantifying uncertainty in the process-structure relationship for Al–Cu solidification

Phase field method (PFM) is a simulation tool to predict microstructural evolution during solidification and is helpful to establish the process-structure relationship for alloys. The robustness of the relationship however is affected by model-form and parameter uncertainties in PFM. In this paper, the uncertainty associated with the thermodynamic and process parameters of PFM is studied and quantified. Surrogate modeling is used to interpolate four quantities of interests (QoIs), including dendritic perimeter, area, primary arm length, and solute segregation, as functions of thermodynamic and process parameters. A sparse grid approach is applied to mitigate the curse-of-dimensionality computational burden in uncertainty quantification. Polynomial chaos expansion is employed to obtain the probability density functions of the QoIs. The effect of parameter uncertainty on the Al–Cu dendritic growth during solidification simulation are investigated. Here, the results show that the dendritic morphology varies significantly with respect to the interface mobility and the initial temperature.

36 MATERIALS SCIENCE↗

Oak Ridge National Laboratory's Strategic Research and Development Insights for Digital Twins

Oak Ridge National Laboratory (ORNL) is pleased to provide our response to the NITRD RFI on Digital Twins Research and Development. Digital twins are virtual representations of physical systems, leveraging real-time data to simulate and predict behaviors. ORNL is advancing digital twin technology across various disciplines, including neutron scattering, networking, science ecosystems, supercomputing, secure facilities, mobility technologies, materials design and discovery, power systems, fusion reactors, biological sciences, and earth observation. These efforts aim to enhance scientific research, operational efficiency, and decision-making processes. ORNL facilities, such as the High Flux Isotope Reactor (HFIR), Grid-C, Spallation Neutron Source (SNS), and Oak Ridge Leadership Computing Facility (OLCF), provide the infrastructure to develop and demonstrate these digital twin technologies. In this document, we lay out key challenges, research gaps, and future opportunities based on our experience with digital twins that aim to serve as useful contributions towards a National Digital Twins R&D Strategic Plan. In the remaining document, we address nine of the thirteen topic areas specified in the RFI.

97 MATHEMATICS AND COMPUTING↗

SU-F-J-77: Variations in the Displacement Vector Fields Calculated by Different Deformable Image Registration Algorithms Used in Helical, Axial and Cone-Beam CT Images of a Mobile

Purpose: To investigate quantitatively the displacement-vector-fields (DVF) obtained from different deformable image registration algorithms (DIR) in helical (HCT), axial (ACT) and cone-beam CT (CBCT) to register CT images of a mobile phantom and its correlation with motion amplitudes and frequencies. Methods: HCT, ACT and CBCT are used to image a mobile phantom which includes three targets with different sizes that are manufactured from water-equivalent material and embedded in low density foam. The phantom is moved with controlled motion patterns where a range of motion amplitudes (0–40mm) and frequencies (0.125–0.5Hz) are used. The CT images obtained from scanning of the mobile phantom are registered with the stationary CT-images using four deformable image registration algorithms including demons, fast-demons, Horn-Schunk and Locas-Kanade from DIRART software. Results: The DVF calculated by the different algorithms correlate well with the motion amplitudes that are applied on the mobile phantom where maximal DVF increase linearly with the motion amplitudes of the mobile phantom in CBCT. Similarly in HCT, DVF increase linearly with motion amplitude, however, its correlation is weaker than CBCT. In ACT, the DVF’s do not correlate well with the motion amplitudes where motion induces strong image artifacts and DIR algorithms are not able to deform the ACT image of the mobile targets to the stationary targets. Three DIR-algorithms produce comparable values and patterns of the DVF for certain CT imaging modality. However, DVF from fast-demons deviated strongly from other algorithms at large motion amplitudes. Conclusion: In CBCT and HCT, the DVF correlate well with the motion amplitude of the mobile phantom. However, in ACT, DVF do not correlate with motion amplitudes. Correlations of DVF with motion amplitude as in CBCT and HCT imaging techniques can provide information about unknown motion parameters of the mobile organs in real patients as demonstrated in this phantom visibility study.

60 APPLIED LIFE SCIENCES↗

High Fidelity Simulations of Large-Scale Wireless Networks

The worldwide proliferation of wireless connected devices continues to accelerate. There are 10s of billions of wireless links across the planet with an additional explosion of new wireless usage anticipated as the Internet of Things develops. Wireless technologies do not only provide convenience for mobile applications, but are also extremely cost-effective to deploy. Thus, this trend towards wireless connectivity will only continue and Sandia must develop the necessary simulation technology to proactively analyze the associated emerging vulnerabilities. Wireless networks are marked by mobility and proximity-based connectivity. The de facto standard for exploratory studies of wireless networks is discrete event simulations (DES). However, the simulation of large-scale wireless networks is extremely difficult due to prohibitively large turnaround time. A path forward is to expedite simulations with parallel discrete event simulation (PDES) techniques. The mobility and distance-based connectivity associated with wireless simulations, however, typically doom PDES and fail to scale (e.g., OPNET and ns-3 simulators). We propose a PDES-based tool aimed at reducing the communication overhead between processors. The proposed solution will use light-weight processes to dynamically distribute computation workload while mitigating communication overhead associated with synchronizations. This work is vital to the analytics and validation capabilities of simulation and emulation at Sandia. We have years of experience in Sandia’s simulation and emulation projects (e.g., MINIMEGA and FIREWHEEL). Sandia’s current highly-regarded capabilities in large-scale emulations have focused on wired networks, where two assumptions prevent scalable wireless studies: (a) the connections between objects are mostly static and (b) the nodes have fixed locations.

Onunkwo, Uzoma↗

Multi-modal Energy-optimal Trip Scheduling in Real-time (METS-R) for Transportation Hubs (Final Report)

This report summarizes the work performed under the award number EE0008524. The project develops the Multi-modal Energy-optimal Trip Scheduling in Real-time (METS-R) platform as the next-generation transportation solution based on autonomous electric vehicles (AEV) serving passenger trips from and to urban transportation hubs, to substantially reduce transportation energy consumption. Extensive data collection and analyses were first conducted to understand the demand patterns and energy consumption of hub-based on-road trips. Then, a data-driven framework that consists of an analytical module and a simulation module was proposed. For the analytical module, five planning + operation tools were developed to support the planning and energy-efficient operations of urban AEV services: the charging station planning that robotically allocates charging supplies based on the stationary charging demand distribution; the transit planning and demand adaptive scheduling model that efficiently generates\ candidate transit routes from hubs to other places and dynamically adjusts the transit time table to fit the current demand; the online energy-efficient routing that learns the energy-optimal paths from observations of link-level energy consumption in real-time; the hub-based ridesharing that matches trip requests together with account for the uncertainty of future trip demand and vehicle supply; and finally, the integrated demand prediction and anomaly detection pipeline that leverages the flight/train time table and support other planning/operation tools. To demonstrate the performance of these tools, a scalable high-performance agent-based simulator was built. We divided the urban space into multiple service zones where each zone was considered as an agent for passenger generation and vehicle charging. Two types of AEV agents were coded to model two types of mobility services: AEV taxi and AEV transit. For the AEV taxi, the team implemented the functions of pickup/drop-off passengers, energy-efficient routing, ridesharing, fleet rebalancing, and recharging. For the AEV bus, the team implemented the functions of demand-adaptive route scheduling, passenger boarding, and recharging. A high-performance computing framework was introduced to receive various profiling information (such as link energy updates, vehicle speed) from the simulator instances and communicate the operational commands back to the instances. The numerical experiments show that each of the proposed operational algorithms can reduce energy consumption and improve system efficiency. Furthermore, there exists the need to collectively consider multiple planning + operational strategies as multiple strategies can influence each other in terms of performance impacts. Recommendations for future work related to AEV planning and simulation are discussed.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Secure LoRa Firmware Update with Adaptive Data Rate Techniques

Internet of Things (IoT) devices rely upon remote firmware updates to fix bugs, update embedded algorithms, and make security enhancements. Remote firmware updates are a significant burden to wireless IoT devices that operate using low-power wide-area network (LPWAN) technologies due to slow data rates. One LPWAN technology, Long Range (LoRa), has the ability to increase the data rate at the expense of range and noise immunity. The optimization of communications for maximum speed is known as adaptive data rate (ADR) techniques, which can be applied to accelerate the firmware update process for any LoRa-enabled IoT device. In this paper, we investigate ADR techniques in an application that provides remote monitoring of cattle using small, battery-powered devices that transmit data on cattle location and health using LoRa. In addition to issues related to firmware update speed, there are significant concerns regarding reliability and security when updating firmware on mobile, energy-constrained devices. A malicious actor could attempt to steal the firmware to gain access to embedded algorithms or enable faulty behavior by injecting their own code into the device. A firmware update could be subverted due to cattle moving out of the LPWAN range or the device battery not being sufficiently charged to complete the update process. To address these concerns, we propose a secure and reliable firmware update process using ADR techniques that is applicable to any mobile or energy-constrained LoRa device. The proposed system is simulated and then implemented to evaluate its performance and security properties.

97 MATHEMATICS AND COMPUTING↗

Relationship between Surface Self-Diffusion and Bubble Mobility in Solids: Theory and Atomistic Simulation

Diffusion processes in solids are characterized by complex mechanisms occurring at the atomistic level. The relevant theoretical concepts are sufficiently developed in the case of the diffusion of point defects. At the same time, the diffusion of objects such as clusters of vacancies or nanometer-size cavities in the crystal lattice is described only in terms of continuous-medium approximation. This paper attempts to link the existing theory of diffusion of bubbles in a crystalline matrix with the atomistic description of the process on the basis of the molecular dynamics method. For simplicity, the diffusion of cavities in a two-dimensional Lennard-Jones lattice is considered. A controlled molecular dynamics method is proposed to speed up the direct computation of the diffusion rate of bubbles. Based on the results of simulation, a practical interpretation is given to a parameter of the continuum theory such as the rate of surface self-diffusion. The applicability range of the continuum theory is demonstrated, and principles for the refinement of the theory in the case of minimum-size bubbles are formulated.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

A simple primary amide for the selective recovery of gold from secondary resources

Waste electrical and electronic equipment (WEEE) such as mobile phones contains a plethora of metals of which gold is by far the most valuable. Herein a simple primary amide is described that achieves the selective separation of gold from a mixture of metals typically found in mobile phones by extraction into toluene from an aqueous HCl solution; unlike current processes, reverse phase transfer is achieved simply using water. Phase transfer occurs by dynamic assembly of protonated and neutral amides with [AuCl 4 ]– ions through hydrogen bonding in the organic phase, as shown by EXAFS, mass spectrometry measurements, and computational calculations, and supported by distribution coefficient analysis. In conclusion, the fundamental chemical understanding gained herein should be integral to the development of metal-recovery processes, in particular through the use of dynamic assembly processes to build complexity from simplicity.

36 MATERIALS SCIENCE↗

Homological Invariants of Pauli Stabilizer Codes

Abstract We study translationally invariant Pauli stabilizer codes with qudits of arbitrary, not necessarily uniform, dimensions. Using homological methods, we define a series of invariants called charge modules. We describe their properties and physical meaning. The most complete results are obtained for codes whose charge modules have Krull dimension zero. This condition is interpreted as mobility of excitations. We show that it is always satisfied for translation invariant 2D codes with unique ground state in infinite volume, which was previously known only in the case of uniform, prime qudit dimension. For codes all of whose excitations are mobile we construct a p-dimensional excitation and a $$(D-p-1)$$ ( D - p - 1 ) -form symmetry for every element of thep-th charge module. Moreover, we define a braiding pairing between charge modules in complementary degrees. We discuss examples which illustrate how charge modules and braiding can be computed in practice.

Physics↗