SEARCH · Search NASA

Results for “Guiding Principles”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

863 records · Page 48

All sources NASA NTRS DOE OSTI

NASA NTRS1998

Incompressible Turbulent Wing-Body Junction Flow

The overall objective of this study is to contribute to the optimized design of fan bypass systems in advanced turbofan engines. Increasing the engine bypass ratios have provided a major boost in engine performance improvement over the last fifty years. An engine with high bypass ratio (11-16:1) such as the Advanced Ducted Propulsion (ADP) is being developed and is expected to provide an additional 25% improvement in overall efficiency over the early turbofans. Such significant improvements in overall efficiency would reduce the cost per seat mile, which is a major government and Industry challenge for the 21th century. The research is part of the Advanced Subsonic Technology (AST) program that involves a NASA, U.S. Industry and FAA partnership with the goal of a safe and highly productive global air transportation system. The immediate objective of the study is to perform numerical simulation of duct-strut interactions to elucidate the loss mechanisms associated with this configuration that is typical of advanced turbofan engines such as ADP. However, at present experimental data for a duct-strut configuration are not available. Thus, as a first step a wing-body junction flow would be studied and is the specific objective of the present study. At the outset it is to be recognized that while duct-strut interaction flow is similar to that of wing-body junction flows, there are some differences owing to the presence of a wall at both ends of the strut. Likewise, some differences are due to the sheared inflow (as opposed to a uniform inflow) velocity profile. It is however expected that some features of a wing-body junction flow would persist. Next, some of the salient aspects of the complex flow near a wing-body junction, as revealed by various studies reported in the literature will be reviewed. One of the principle characteristics of the juncture flow, is the presence of the mean flow components in a plane perpendicular to the direction of the oncoming free-stream flow. The lateral curvature of the wing/strat causes the oncoming turbulent layer to skew about am axis (x-axis) parallel to the plane (xz-plane) of the mean shear. This is the principle mechanism for the generation of secondary flow. Such skew-induced secondary flows are slow to be attenuated by Reynolds stresses. Additional contribution to the generation of secondary flow comes from anisotropies in Reynolds stresses. Upstream of the strut, the mean-vorticity is directed span wise (along the y-direction). The presence of secondary flow in the vicinity of the strut causes the vorticity to stretch around the obstacle in a horse-shoe shape, with each leg having a vorticity of the opposite sense. The blockage effect of the strut imposes a severe adverse pressure gradient on the oncoming turbulent shear layer, causing boundary layer separation ahead of the leading edge, resulting in a vortex that rolls up and flows downstream into the juncture region. The separation vortices trailing in the wake of the wing can alter the lift or drag characteristics of the surfaces downstream of the wing-body juncture. Likewise, on submarines, the wake flow behind the appendage can degrade the performance of the propeller located downstream. The complex nature of this flow is caused by the presence of all six components of Reynolds stresses. Devenport and Simpson report that in the vicinity of the horse-shoe vortex there is intense recirculation with turbulent stresses being much larger than those normally observed in turbulent flows. These features contribute to making this flow a challenge to predict numerically. Some of the past studies provide useful insights into this flow that would guide our numerical efforts. In measurements reported by Shabaka and Bradshaw, the eddy viscosity tensor is seen to be non-isotropic and has negative components in certain regions. In an effort to evaluate the closure assumptions of various turbulence models, Devenport and Simpson used their own extensive measurements in juncture flows around the nose of a wing-body junction. Measured values of mean-velocity and/or turbulence kinetic energy was used to predict the magnitude of the shear stress vector. Algebraic stress models performed the best followed by Cebeci-Smith eddy viscosity model. The flow is reported to be dominated by a pressure field produced by the wing and the velocity field generated by the horseshoe vortex that is wrapped around the junction between the wing and wall. Kubendran et al. conclude from an experimental study that the shape of leading edge of the wing as characterized by its slenderness ratio is a major factor in determining the flow fields in the juncture region. The more thinner the leading edge of the juncture, the weaker the horseshoe vortex is. Also, with a slender leading edge, the secondary flow in the juncture would be due mainly to the cross-stream gradients of Reynolds stresses rather than due to a lateral skewing of the shear layer.

Krishnamurthy, R.↗

NASA NTRS2004

Changes in Hardware in Order to Accommodate Compliant Foil Air Bearings of a Larger Size

Compliant foil air bearings are at the forefront of the Oil-Free turbomachinery revolution of supporting gas turbine engines with air lubricated hydrodynamic bearings. Foil air bearings have existed for almost fifty years, yet their commercialization has been confined to relatively small, high-speed systems characterized by low temperatures and loads, such as in air cycle machines, turbocompressors and micro-turbines. Recent breakthroughs in foil air bearing design and solid lubricant coating technology, have caused a resurgence of research towards applying Oil-Free technology to more demanding applications on the scale of small and mid range aircraft gas turbine engines. In order to foster the transition of Oil-Free technology into gas turbine engines, in-house experiments need to be performed on foil air bearings to further the understanding of their complex operating principles. During my internship at NASA Glenn in the summer of 2003, a series of tests were performed to determine the internal temperature profile in a compliant bump- type foil journal air bearing operating at room temperature under various speeds and load conditions. From these tests, a temperature profile was compiled, indicating that the circumferential thermal gradients were negligible. The tests further indicated that both journal rotational speed and radial load are responsible for heat generation with speed playing a more significant role in the magnitude of the temperatures. As a result of the findings from the tests done during the summer of 2003, it was decided that further testing would need to be done, but with a bearing of a larger diameter. The bearing diameter would now be increased from two inches to three inches. All of the currently used testing apparatus was designed specifically for a bearing that was two inches in diameter. Thus, my project for the summer of 2004 was to focus specifically on the scatter shield put around the testing rig while running the bearings. Essentially I was to design a scatter shield that would be able to accommodate the three inch bearing and that would also meet all safety requirements. Furthermore, the new scatter shield also had to house a heater, used for high-speed and temperature testing. Using Solidworks, a computer aided modeling program, I was able to accomplish the task set out for me and designed the new scatter shield. Furthermore, I also guided the fabrication process. As a result of this containment shield being designed, the Oil-Free turbomachinery team now has the ability to test bearings of larger diameters. Finally, it is expected that these tests will provide information useful for the validation of future analytical modeling codes.

Zeszotek, Michelle↗

DOE OSTI2025

Dissipation Pathways in a Photosynthetic Complex

Determining how energy flows within and between molecules is crucial for understanding chemical reactions, material properties, and even vital processes such as photosynthesis. While the general principles of energy transfer are well established, elucidating the specific molecular pathways by which energy is funneled remains challenging, as it requires tracking energy flow in complex molecular environments. Here, we demonstrate how photon excitation energy is partially dissipated in the light-harvesting Fenna–Matthews–Olson (FMO) complex, mediating the excitation energy transfer from light-harvesting chlorosomes to the photosynthetic reaction center in green sulfur bacteria. Specifically, we isolate the contribution of the protein and specific vibrational modes of the pigment molecules to the energy dynamics. For this, we introduce an efficient computational implementation of a recently proposed theory of dissipation pathways for open quantum systems, based on second-order perturbation theory in the electronic couplings. Using it and a state-of-the-art FMO model with highly structured and chromophore-specific spectral densities, we demonstrate that energy dissipation is dominated by low-frequency modes (<800 cm –1 ) as their energy range is near-resonance with the energy gaps between electronic states of the pigments. We identify the most important modes for dissipation to be in-plane breathing modes (∼200 cm –1 ) of the bacteriochlorophylls in the complex. Conversely, far-detuned intramolecular vibrations with higher frequencies (>800 cm –1 ) play no role in dissipation. Interestingly, the FMO complex first needs to borrow energy from the environment to release excess photonic energy, indicating that the energy exchange between the system and thermal environment is not strictly unidirectional in time but involves a transient thermally activated step. Beyond their fundamental value, these insights can guide the development of artificial light-harvesting devices and, more broadly, engineer environments for chemical and quantum control tasks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

A unified understanding of minimum lattice thermal conductivity

Here, we propose a first-principles model of minimum lattice thermal conductivity ($κ^{min}_L$) based on a unified theoretical treatment of thermal transport in crystals and glasses. We apply this model to thousands of inorganic compounds and find a universal behavior of $κ^{min}_L$ in crystals in the high-temperature limit: The isotropically averaged $κ^{min}_L$ is independent of structural complexity and bounded within a range from ~0.1 to ~2.6 W/(m K), in striking contrast to the conventional phonon gas model which predicts no lower bound. We unveil the underlying physics by showing that for a given parent compound, $κ^{min}_L$ is bounded from below by a value that is approximately insensitive to disorder, but the relative importance of different heat transport channels (phonon gas versus diffuson) depends strongly on the degree of disorder. Moreover, we propose that the diffuson-dominated $κ^{min}_L$ in complex and disordered compounds might be effectively approximated by the phonon gas model for an ordered compound by averaging out disorder and applying phonon unfolding. With these insights, we further bridge the knowledge gap between our model and the well-known Cahill–Watson–Pohl (CWP) model, rationalizing the successes and limitations of the CWP model in the absence of heat transfer mediated by diffusons. Finally, we construct graph network and random forest machine learning models to extend our predictions to all compounds within the Inorganic Crystal Structure Database (ICSD), which were validated against thermoelectric materials possessing experimentally measured ultralow κ L . Our work offers a unified understanding of $κ^{min}_L$, which can guide the rational engineering of materials to achieve .

42 ENGINEERING↗

DOE OSTI2024

Non-Electricity Based Renewable Fuels: Theory and Computation for Solar Thermochemical Hydrogen

Dominated by photovoltaics and wind, current renewable energy sources generate mostly electricity, but 80% of the global final energy consumption occurs in form of fuels. Therefore, direct solar fuel generation would be a major breakthrough for the energy transition. Solar thermochemical hydrogen (STCH) is one of the very few potential routes towards scalable renewable fuels, but currently suffers from lack of an oxide working material that could optimally perform energy conversion within the thermodynamic boundary conditions. Theory and computation can contribute in two distinct ways, through materials search and discovery, but also by providing detailed mechanistic models for specific systems so to advance our understanding of possible design strategies. To enable high-throughput materials screening, we developed a defect graph neural network (dGNN) machine learning approach,[1] which accelerates the prediction of defect formation energies by replacing the tedious density functional theory (DFT) supercell calculations for all possible defect sites. This approach enables high-throughput database screening of oxides, which was integrated with thermodynamic modeling to extract the reduction entropies as additional selection criterion for STCH. Once potential candidate materials are identified, detailed models can guide materials design by predicting performance characteristics. One challenge is to quantitatively predict thermochemical equilibria at high concentrations when the redox active defects start to interact with each other, thereby impeding the formation of additional defects. Introducing a model for the free energy of defect interaction, parametrized on the basis of DFT data, we simulated the complete STCH redox cycle for (Sr,Ce)MnO3 alloys, achieving near-quantitative agreement with experimental data.[2] The analysis of these simulations reveals how defect interactions diminish the reduction entropy and H2 yield, suggesting to include these interactions in design considerations. Finally, we revisit the popular van't Hoff method for analyzing reduction enthalpies and entropies. This method is not ideal, as it involves a temperature-dependent convolution of gas-phase and solid-state entropies, causing uncertainties in the same order of magnitude as the physical quantities of interest. To avoid this problem, we suggest a simple alternative approach which can be applied to experimental and simulated data alike.

first-principles calculations↗

DOE OSTI2021

SAGE Intrusion Detection System: Sensitivity Analysis Guided Explainability for Machine Learning.

This report details the results of a three-fold investigation of sensitivity analysis (SA) for machine learning (ML) explainability (MLE): (1) the mathematical assessment of the fidelity of an explanation with respect to a learned ML model, (2) quantifying the trustworthiness of a prediction, and (3) the impact of MLE on the efficiency of end-users through multiple users studies. We focused on the cybersecurity domain as the data is inherently non-intuitive. As ML is being using in an increasing number of domains, including domains where being wrong can elicit high consequences, MLE has been proposed as a means of generating trust in a learned ML models by end users. However, little analysis has been performed to determine if the explanations accurately represent the target model and they themselves should be trusted beyond subjective inspection. Current state-of-the-art MLE techniques only provide a list of important features based on heuristic measures and/or make certain assumptions about the data and the model which are not representative of the real-world data and models. Further, most are designed without considering the usefulness by an end-user in a broader context. To address these issues, we present a notion of explanation fidelity based on Shapley values from cooperative game theory. We find that all of the investigated MLE explainability methods produce explanations that are incongruent with the ML model that is being explained. This is because they make critical assumptions about feature independence and linear feature interactions for computational reasons. We also find that in deployed, explanations are rarely used due to a variety of reason including that there are several other tools which are trusted more than the explanations and there is little incentive to use the explanations. In the cases when the explanations are used, we found that there is the danger that explanations persuade the end users to wrongly accept false positives and false negatives. However, ML model developers and maintainers find the explanations more useful to help ensure that the ML model does not have obvious biases. In light of these findings, we suggest a number of future directions including developing MLE methods that directly model non-linear model interactions and including design principles that take into account the usefulness of explanations to the end user. We also augment explanations with a set of trustworthiness measures that measure geometric aspects of the data to determine if the model output should be trusted.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Enhanced Selectivity for C 2 H 4 Production from C 2 H 6 on Partially Chlorinated IrO 2 (110) Surfaces

Modifying metal oxide surfaces to limit their oxidizing activity can provide a means of improving catalytic selectivity toward the partial oxidation of light alkanes. Here, in this study, we investigated the oxidation of C 2 H 6 on Cl-modified IrO 2 (110) surfaces using temperature-programmed reaction spectroscopy (TPRS) and first-principles microkinetic modeling. We find that substituting Cl for O in the IrO 2 (110) surface enhances the selectivity for C 2 H 6 conversion to C 2 H 4 during TPRS by suppressing extensive oxidation to CO x products, while also either enhancing C 2 H 4 production or altering it to a lesser extent, depending on the initial C 2 H 6 coverage. The C 2 H 4 selectivity increased with increasing C 2 H 6 and Cl coverage, but reached a limiting value below 50%. The Cl coverage changed negligibly during C 2 H 6 oxidation, and the surface reactivity decreased only marginally for Cl coverages up to 0.5 ML (monolayer). TPRS simulations using a microkinetic model predict C 2 H 4 and CO x product yields as a function of the Cl coverage that agree closely with the experimental results. According to the simulations, C 2 H 6 conversion to C 2 H 4 occurs on Cl-IrO 2 (110) by the hydrogenation of C 2 H 3 * species adsorbed in blocked states, in which neighboring sites are occupied only by unreactive HO and Cl species. The microkinetic modeling shows that H-hopping away from surface HO groups provides a relatively efficient route for C 2 H 3 * to escape blocked configurations and dehydrogenate, and that this process can limit the C 2 H 4 selectivity on Cl-IrO 2 (110) under the conditions studied. Overall, our results demonstrate that Cl-substitution into IrO 2 (110) enhances the selectivity for C 2 H 4 production from C 2 H 6 and provides insights into the reaction mechanism that can guide strategies to further improve the C 2 H 4 selectivity.

IrO2↗

DOE OSTI2021

Computational design and analysis of modular cells for large libraries of exchangeable product synthesis modules

Microbial metabolism can be harnessed to produce a large library of useful chemicals from renewable resources such as plant biomass. However, it is laborious and expensive to create microbial biocatalysts to produce each new product. To tackle this challenge, we have recently developed modular cell (ModCell) design principles that enable rapid generation of production strains by assembling a modular (chassis) cell with exchangeable production modules to achieve overproduction of target molecules. Previous computational ModCell design methods are limited to analyze small libraries of around 20 products. In this study, we developed a new computational method, named ModCell-HPC, that can design modular cells for large libraries with hundreds of products with a highly-parallel and multi-objective evolutionary algorithm and enable us to elucidate modular design properties. We demonstrated ModCell-HPC to design Escherichia coli modular cells towards a library of 161 endogenous production modules. From these simulations, we identified E. coli modular cells with few genetic manipulations that can produce dozens of molecules in a growth-coupled manner with different types of fermentable sugars. These designs revealed key genetic manipulations at the chassis and module levels to accomplish versatile modular cells, involving not only in the removal of major by-products but also modification of branch points in the central metabolism. We further found that the effect of various sugar degradation on redox metabolism results in lower compatibility between a modular cell and production modules for growth on pentoses than hexoses. To better characterize the degree of compatibility, we developed a method to calculate the minimal set cover, identifying that only three modular cells are all needed to couple with up 85 compatible production modules. By determining the unknown compatibility contribution metric, we further elucidated the design features that allow an existing modular cell to be re-purposed towards production of new molecules. Altogether, ModCell-HPC is a useful tool for understanding modularity of biological systems and guiding more efficient and generalizable design of modular cells that help reduce research and development cost in biocatalysis.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Phase Equilibria and Thermochemistry of Advanced Fuels: Modeling Burnup Behavior (Final Report)

Achieving the goal of developing advanced fuel concepts that meet the DOE objectives of being robust, demonstrating high performance, and are more tolerant of accident conditions than current fuel systems will require a thorough understanding of the thermophysical and thermochemical properties of the constituent materials. Non-oxide fuel systems are being explored under the Advanced Fuels Program that hold significant promise for improved performance and accident tolerance, including the uranium silicide-based system considered in the current work. Prospective cladding materials currently considered that contribute to improved accident tolerance include silicon carbide composites and ferritic alloys (Fe-Cr-Al base compositions). Thus, the effort developed thermochemical models and values, supported with targeted experiments, to evaluate the ferritic alloy and silicon carbide composite cladding systems in contrast to current zirconium alloy cladding. The developed detailed understanding will serve to aid in relatively early screening of candidate systems to avoid wasted effort, guide development of new fuel forms, and to provide a basis for predicting and modeling fuel performance. Major deliverables for the project included: Thermochemical assessment and models of phases in the U-Si and U-Si-N systems; thermochemical evaluation supported by experimental measurements of fuel-cladding interactions of silicide fuel with baseline zirconium, ceramic composite, and ferritic alloy cladding; thermochemical assessment and models of phases supported by experimental measurements for silicide fuel with key fission products provided in a dataset and reported in refereed publications. Within the project a significantly refined U-Si phase diagram was developed and reported that now includes homogeneity ranges for key phases, such at the U 3 Si 2 proposed fuel phase, and settles issues with regard to uncertainty in the stability of some phases. Computational efforts together with key experiments has determined phase formation in interactions between U 3 Si 2 and Zircaloy-4 cladding material, a ferritic FeCrAlY alloy of interest as an advanced cladding material, and silicon carbide, also of interest as a fiber-reinforced composite cladding. As expected, very significant reactions occur between U3Si2 and Zircaloy-4, with much less interaction at higher temperatures for the ferritic alloy, and finally interactions with SiC only in the region of contact. A potentially major issue is the stability of U 3 Si 2 fuel that has undergone significant burnup. The result is the loss of the uranium metal, liberating silicon, and the formation of concomitant fission product elements that either dissolve in the U 3 Si 2 phase or form independent, and possibly silicide phases. A combination of experimental determinations of phase formation of U 3 Si 2 reacted with representative fission products yttrium, gadolinium, cerium, zirconium, and molybdenum and first principles calculations has helped understand the fuel chemistry. The behavior of the U 3 Si 2 phase and the partitioning of silicon to possible fission product phases with burnup was thus determined, with significant dissolution in U 3 Si 2 of cerium, gadolinium, zirconium, and plutonium predicted along with independent phase formation of a U-Mo-Si ternary phase, yttrium silicide, and elemental selenium. It can be concluded that at significant burnup there will be a very minor amount of the U 3 Si 2 fuel phase that will decompose to a lower silicide or a uranium alloy as silicon preferentially forms a secondary phase.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

Data from: "A guide to using GitHub for developing and versioning data standards and reporting formats"

These data are the results of a systematic review that investigated how data standards and reporting formats are documented on the version control platform GitHub. Our systematic review identified 32 data standards in earth science, environmental science, and ecology that use GitHub for version control of data standard documents. In our analysis, we characterized the documents and content within each of the 32 GitHub repositories to identify common practices for groups that version control their documents on GitHub.In this data package, there are 8 CSV files that contain data that we characterized from each repository, according to the location within the repository. For example, in 'readme_pages.csv' we characterize the content that appears across the 32 GitHub repositories included in our systematic review. Each of the 8 CSV files has an associated data dictionary file (names appended with '_dd.csv' and here we describe each content category within CSV files.There is one file-level metadata file (flmd.csv) that provides a description of each file within the data package.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Abiotic proxies for predictive mapping of nearshore benthic assemblages: implications for marine spatial planning

Marine spatial planning (MSP) should assist managers in guiding human activities toward sustainable practices and in minimizing user conflicts in our oceans. A necessary first step is to quantify spatial patterns of marine assemblages in order to understand the ecosystem's structure, function, and services. However, the large spatial scale, high economic value, and density of human activities in nearshore habitats often makes quantifying this component of marine ecosystems especially daunting. To address this challenge, we developed an assessment method that employs abiotic proxies to rapidly characterize marine assemblages in nearshore benthic environments with relatively high resolution. We evaluated this assessment method along 300 km of the State of Maine's coastal shelf (<100 m depth), a zone where high densities of buoyed lobster traps typically preclude extensive surveys by towed sampling gear (i.e., otter trawls). During the summer months of 2010–2013, we implemented a stratified-random survey using a small remotely operated vehicle that allowed us to work around lobster buoys and to quantify all benthic megafauna to species. Stratifying by substrate, depth, and coastal water masses, we found that abiotic variables explained a significant portion of variance (37–59%) in benthic species composition, diversity, biomass, and economic value. Generally, the density, diversity, and biomass of assemblages significantly increased with the substrate complexity (i.e., from sand-mud to ledge). The diversity, biomass, and economic value of assemblages also decreased significantly with increasing depth. Last, demersal fish densities, sessile invertebrate densities, species diversity, and assemblage biomass increased from east to west, while the abundance of mobile invertebrates and economic value decreased, corresponding mainly to the contrasting water mass characteristics of the Maine Coastal Current system (i.e., summertime current direction, speed, and temperature). Integrating modeled predictions with existing GIS layers for abiotic conditions allowed us to scale up important assemblage attributes to define key foundational ecological principles of MSP and to find priority regions where some bottom-disturbing activities would have minimal impact to benthic assemblages. We conclude that abiotic proxies can be strong forcing functions for the assembly of marine communities and therefore useful tools for spatial extrapolations of marine assemblages in congested (heavily used) nearshore habitats.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Strain-concentration for fast, compact photonic modulation and non-volatile memory

A critical figure of merit (FoM) for electro-optic (EO) modulators is the transmission change per voltage, d T / d V . Conventional approaches in wave-guided modulators maximize d T / d V via a high EO coefficient or longer light-material interaction lengths but are ultimately limited by material losses and nonlinearities. Optical and RF resonances improve d T / d V at the cost of spectral non-uniformity, especially for high- Q optical cavity resonances. Here, we introduce an EO modulator based on piezo-strain-concentration of a photonic crystal cavity to address both trade-offs: (i) it eliminates the trade-off between d T / d V and waveguide loss—i.e., enhancement of the resonance tuning efficiency d v c / d V for the fixed EO coefficient, waveguide length, and cavity Q —and (ii) at high DC strains it exhibits a non-volatile (NV) cavity tuning Δ v c ,NV for passive memory and programming of multiple devices into resonance despite fabrication variations. The device is fabricated on a scalable silicon nitride-on-aluminum nitride platform. We measure d v c / d V =177±1MHz/V, corresponding to Δ v c =40±0.32GHz for a voltage spanning ±120V with an energy consumption of δ U /Δ v c =0.17nW/GHz. The modulation bandwidth is flat up to ω BW,3dB /2 π =3.2±0.07MHz for broadband DC-AC and 142±17MHz for resonant operation near a 2.8 GHz mechanical resonance. Optical extinction up to 25 dB is obtained via Fano-type interference. Strain-induced beam-buckling modes are programmable under a “read-write” protocol with a continuous, repeatable tuning range of 5±0.25GHz, allowing for storage and retrieval, which we quantify with mutual information of 2.4 bits and a maximum non-volatile excursion of 8 GHz. Using a full piezo-optical finite-element-model (FEM) we identify key design principles for optimizing strain-based modulators and chart a path towards achieving performance comparable to lithium niobate-based modulators and the study of high strain physics on-chip.

Wen, Y. Henry (ORCID:0009000685423628)↗

DOE OSTI2023

Accuracy of DFT computed oxygen-vacancy formation energies and high-throughput search of solar thermochemical water-splitting compounds

The enthalpy change involved in metal oxide reduction is a key quantity in various processes related to energy conversion and storage, and is of particular interest for computational prediction. Often this prediction involves the simulation of a high temperature reduction process with a 0K methodology like density functional theory (DFT), and it is not infrequent for the high temperature and 0K stable crystal structures to differ. This introduces a conundrum with regards to the choice of crystal structure to utilize in the computation, with approaches in the literature varying and experimental validation remaining scarce. In this work we address both the crystal structure conundrum and the experimental validation, and then apply the insights we gain to guide a high-throughput search for new materials for solar thermochemical water-splitting applications. By computing the DFT+U oxygen vacancy formation energy (ΔE vf ) of a selection of ABO 3 compounds and comparing different crystal structures for each composition, we highlight the issues that arise when the structure utilized in the computation is dynamically unstable at 0K, namely the presence of an artificial lowering of ΔE vf , and the lack of convergence of ΔE vf with cell size. We solve these limitations by identifying and employing a suitable surrogate dynamically stable structure. We then validate the predictive power of our calculations against appositely generated experimental measurements of reduction enthalpy for a series of Hubbard U values, finding an accuracy ranging between 0.2-0.6 eV/O. In light of such conclusions, we revise and expand a previous a high-throughput DFT study on ABO 3 perovskite oxides. As a result, we provide a list of candidate STCH materials, highlight trends with redox-active cation and structural distortion, and identify Mn 4+ , Mn 3+ and Co 3+ as the most promising redox-active cations.

08 HYDROGEN↗

DOE OSTI2018

First-Principles Investigation of Mechanical and Thermodynamic Properties of Nickel Silicides at Finite Temperature

First-principles calculations are performed to investigate lattice parameters, elastic constants and 3D directional Young’s modulus E of nickel silicides (i.e., β-Ni{sub 3}Si, δ-Ni{sub 2}Si, θ-Ni{sub 2}Si, ε-NiSi, and θ-Ni{sub 2}Si), and thermodynamic properties, such as the Debye temperature, heat capacity, volumetric thermal expansion coefficient, at finite temperature are also explored in combination with the quasi-harmonic Debye model. The calculated results are in a good agreement with available experimental and theoretical values. The five compounds demonstrate elastic anisotropy. The dependence on the direction of stiffness is the greatest for δ-Ni{sub 2}Si and θ-Ni{sub 2}Si, when the stress is applied, while that for β-Ni{sub 3}Si is minimal. The bulk modulus B reduces with increasing temperature, implying that the resistance to volume deformation will weaken with temperature, and the capacity gradually descend for the compound sequence of β-Ni{sub 3}Si > δ-Ni{sub 2}Si > θ-Ni{sub 2}Si > ε-NiSi > θ-Ni{sub 2}Si. The temperature dependence of the Debye temperature ΘD is related to the change of lattice parameters, and ΘD gradually decreases for the compound sequence of ε-NiSi > β-Ni{sub 3}Si > δ-Ni{sub 2}Si > θ-Ni{sub 2}Si > θ-Ni{sub 2}Si. The volumetric thermal expansion coefficient αV, isochoric heat capacity and isobaric heat capacity C{sub p} of nickel silicides are proportional to T{sup 3} at low temperature, subsequently, αV and C{sub p} show modest linear change at high temperature, whereas C{sub v} obeys the Dulong-Petit limit. In addition, β-Ni{sub 3}Si has the largest capability to store or release heat at high temperature. From the perspective of solid state physics, the thermodynamic properties at finite temperature can be used to guide further experimental works and design of novel nickel–silicon alloys.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2020

First Principle based Thermal Conductivity Modeling of Metal Alloys with Applications on Uranium Alloys

Thermal conductivity is an important materials property related to heat transport, which is essential to many applications, ranging from thermoelectrics to nuclear reactor materials. High- quality thermal conductivity data is critical to these materials and their associated technologies, including the nuclear fuel materials like traditional oxide fuels and metallic uranium (U) fuels, e.g. U-Zr and U-Mo alloys. And thermal conductivity modeling is widely used to interpolate or extrapolate experimental data, to obtain high-quality thermal conductivity data over wide temperature and composition range, and to understand the impacts of different factors including defects and microstructures. However, a general thermal conductivity model for metal alloys which can work regrading different phase components is still missing. Also, for U alloys, a thermal conductivity model working with different phases is needed. Therefore, in this work, we developed thermal conductivity models for metal alloys, based on ab-initio calculations, semi-classical physics rules, and limited experimental data. The goals of these models are to help obtain high- quality thermal conductivity data within a little experimental input as possible, have models that are extendable to varying microstructures, including different types of irradiation effects, and provide mechanistic understanding of heat transfer in the modeled alloys. In this work, our model solves several challenges in the development. The DFT-BTE approach is applied to decrease the reliance on experimental data and make the model extendable to composition changes and defects. A practical and efficient way to combine the DFT inputs with physics rules is pointed out in this work too. A staged approach, which starts from simple cases of elemental metals, then extends to solid solutions, different compound phases, and multi-phase mixtures, is presented to work with the metal alloys in different phase components. Our models are demonstrated respectively on aU for elemental metal model, on U-Zr and U-Mo alloys in aU temperature range for multi-phase mixture model, on high-temperature U-Zr, U-Nb, and U-Mo alloys in the body-centered cubic phase for concentrated solid solution model, and on irradiated U-Mo alloys for irradiated metal alloy model. All models show great agreement with experimental data. In these demonstrations, our model shows its advantages compared to previous empirical fitting model. Our model requires fewer experimental data, due to the inputs from DFT. The quantitative insights into the different physical factors are provided in our model, as it incorporates the electron and phonon scattering mechanisms. Our model also can be extended to incorporate the contributions of point defects, grain boundaries, and noble gas bubbles, to integrate their effects on heat transfer. This model can serve as both a foundation for understanding the more complex thermal conductivity of realistic U alloy fuels and a useful tool to guide further modeling of thermal conductivity to aid materials and device design.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2024

The Transactive Energy Network Template Metamodel

While transactive energy, which is defined as an allocation of electricity based on dynamically discovered values or prices, has been extensively studied, its uptake and use has been slow. This report describes a tool, the transactive network template, which should hasten the creation and uptake of transactive energy networks. Some basic principles of transactive energy are familiar from existing wholesale electricity markets. Locational prices are calculated today for zones within bulk electric transmission systems. Locational prices differ while accounting for the locational costs of electricity generation and the losses and constraints incurred when electricity is transmitted from generators and distributed to consumers. A transactive energy network might include these transmission zones. However, current research strives to apply transactive energy also in electricity distribution circuits, buildings, and even for individual generating and consuming devices. At the same time, researchers explore how to apply transactive energy in real time during increasingly shorter time intervals. Automated computational agents become necessary as transactive energy becomes applied to smaller circuit zones and at faster dynamic timescales. A transactive energy network is an example of a multi-agent system. Each zone in the network is represented by its transactive agent, which makes decisions for and acts on behalf of a business entity that is responsible for and manages one of the circuit regions. A transactive energy network is also an example of a decentralized, distributed control system. Control decisions and responsibilities are distributed among the network’s transactive agents. The transactive agents are independent; that is, there typically is no centralized authority or oversight function. Instead, transactive agents exchange transactive signals and thereby negotiate the prices and quantities of electricity that they will exchange. Initially, the circuit regions and responsibilities of transactive agents appear to be very dissimilar. Each circuit region may comprise transmission, distribution, or building-level circuits. Each has a unique position and electrical connectivity within the transactive energy network. Each possesses unique assets that either generate or consume electricity, and these (e.g., renewable energy generator, diesel generator, aggregate utility load, building load, space conditioning, refrigerator, etc.) may further differ in their price flexibility and in their strategies for responding to dynamic electricity prices. Given such diversity, an implementer’s first inclination might be to start from scratch to define all these devices and to engineer their seemingly unique interactions. Given that each implementer’s perspective may be narrow within a transactive energy network, it is unlikely that uniquely engineered systems would interact well. This is where the transactive network template is applicable. The transactive network template is a metamodel that has been developed to guide implementers as they configure their own transactive agent within a network of such agents. The object-oriented design of the transactive network template provides basic code object types that may be used and extended by implementers to represent each of the assets in their circuit region. These objects further facilitate the transactive agent’s necessary computations, which are divided among responsibilities to schedule power usage, balance electric supply and demand, and coordinate the exchange of electricity with the other transactive agents. This report addresses the conceptual transactive network template design. Implementers are directed to more formal design documents and reference implementations. A Python™-based1 reference implementation of the transactive network template has been coded, and three implementations have been configured to represent a national laboratory and two university campuses. Version 2 of the transactive node template generalizes the market class and its methods to facilitate multiple, and more diverse market coordination mechanisms than were facilitated by and demonstrated using Version 1. Version 3 includes new Appendix B, which addresses the designs of methods that would make dynamic prices track approved electricity rates. In the future, the author wishes to make the transactive network template more generally applicable to networks that require more accurate power flow. Development of the transactive network template is jointly funded by the U.S. Department of Energy (DOE) Energy Efficiency and Renewable Energy and the DOE Office of Electricity. In late 2015, one of the first projects to be funded by the DOE Grid Laboratory Modernization Laboratory Consortium was the Clean Energy and Transactive Campus project, led by Pacific Northwest National Laboratory. DOE funds were matched by an investment by the Washington Department of Commerce through its Clean Energy Fund. The transactive network template was developed to guide the implementation of transactive energy networks within this project’s scope.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2017

Scanning Quantum Cryogenic Atom Microscope

Microscopic imaging of local magnetic fields provides a window into the organizing principles of complex and technologically relevant condensed-matter materials. However, a wide variety of intriguing strongly correlated and topologically nontrivial materials exhibit poorly understood phenomena outside the detection capability of state-of-the-art high-sensitivity high-resolution scanning probe magnetometers. We introduce a quantum-noise-limited scanning probe magnetometer that can operate from room-to-cryogenic temperatures with unprecedented dc-field sensitivity and micron-scale resolution. The Scanning Quantum Cryogenic Atom Microscope (SQCRAMscope) employs a magnetically levitated atomic Bose-Einstein condensate (BEC), thereby providing immunity to conductive and blackbody radiative heating. The SQCRAMscope has a field sensitivity of 1.4 nT per resolution-limited point (approximately 2 μm) or 6 nT/√Hz per point at its duty cycle. Furthermore, compared to point-by-point sensors, the long length of the BEC provides a naturally parallel measurement, allowing one to measure nearly 100 points with an effective field sensitivity of 600 pT/√Hz for each point during the same time as a point-by-point scanner measures these points sequentially. Moreover, it has a noise floor of 300 pT and provides nearly 2 orders of magnitude improvement in magnetic flux sensitivity (down to 10 -6 Φ 0 /√Hz) over previous atomic probe magnetometers capable of scanning near samples. These capabilities are carefully benchmarked by imaging magnetic fields arising from microfabricated wire patterns in a system where samples may be scanned, cryogenically cooled, and easily exchanged. We anticipate the SQCRAMscope will provide charge-transport images at temperatures from room temperature to 4 K in unconventional superconductors and topologically nontrivial materials.

74 ATOMIC AND MOLECULAR PHYSICS↗