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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 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Dinuclear Complexes of Uranyl, Neptunyl, and Plutonyl: Structures and Oxidation States Revealed by Experiment and Theory

Dinuclear perchlorate complexes of uranium, neptunium, and plutonium were characterized by reactivity and DFT, with results revealing structures containing pentavalent, hexavalent, and heptavalent actinyls, and actinyl-actinyl interactions (AAIs). Electrospray ionization produced native complexes [(AnO 2 ) 2 (ClO 4 ) 3 ] - for An:An = U:U, Np:Np, Pu:Pu, and Np:Pu, which are intuitively formulated as actinyl(V) perchlorates. However, DFT identified lower-energy structures [(AnO 2 )(AnO 3 )(ClO 4 ) 2 (ClO 3 )] - comprising a perchlorate fragmented to ClO 3 , actinyl(VI) cation An VI O 2 2+ , and neutral AnO 3 . For U:U and Np:Np, and Np in Np:Pu, the coordinated AnO 3 is calculated as actinyl(VI) with an equatorial oxo, [O yl =An VI =O yl ][=O eq ], whereas for Pu:Pu, it is plutonyl(V) oxyl, [O yl =Pu V =O yl ][-O eq • ]. The implied lower stability of Pu VI versus Np VI indicates weaker Pu=O eq versus Np=O eq bonding. Adsorption of O 2 by the U:U complex suggests oxidation of U V to U VI , corroborating the assignment of perchlorate [(An V O 2 ) 2 (ClO 4 ) 3 ] - . DFT predicts the O 2 adducts are [(An VI O 2 )(O 2 )(An VI O 2 )(ClO 4 ) 3 ] - with actinyls oxidized from +V to +VI by bridging peroxide, O 2 2- . In accordance with reactivity, O 2- addition is computed as substantially exothermic for U:U and least favorable for Pu:Pu. Collision-induced dissociation of native complexes eliminated ClO 2 to yield [(AnO 2 )(O) 2 (AnO 2 )(ClO 4 ) 2 ] - , in which fragmented O atoms bridge as oxyl O -• and oxo O 2- to yield uranyl(VI) and plutonyl(VI), or as oxos O 2- to yield neptunyl(VII), [O yl =Np VII =O yl ] 3+ .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Frequency threshold determination for frequency-responsive load controllers

Systems, methods, and computer media for managing frequency response in a power grid are provided herein. Individual grid-connected electrical devices can be turned on and/or off by corresponding frequency-responsive load controllers when frequency deviations beyond a threshold are detected. Each controller selects, for the corresponding electrical device, a frequency threshold from available frequencies in a frequency range. If the selected frequency falls within a deadband frequency range, then the controller sets the frequency threshold to a frequency outside of the deadband (e.g., to a closest available frequency outside of the deadband). On a system-wide level, this approximates a uniform distribution of frequency thresholds over the entire frequency range, including the deadband, and achieves the proper power-to-frequency relationship for grid stability. A supervisory coordinator can determine the frequency range from which a frequency threshold is selected based on aggregated power information for devices and controllers throughout the grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Assessing the effect of regularization on the molecular properties predicted by SCAN and self-interaction corrected SCAN meta-GGA

Recent regularization of the SCAN meta-GGA functional (rSCAN) has simplified the numerical complexities of the SCAN functional, alleviating SCAN's stringent demand on the numerical integration grids to some extent. The regularization of rSCAN, however, results in the breaking of some constraints such as the uniform electron gas limit, the slowly varying density limit, and coordinate scaling of the iso-orbital indicator. Here, we assess the effects of regularization on the electronic, structural, vibrational, and magnetic properties of molecules by comparing the SCAN and rSCAN predictions. The properties studied include atomic energies, atomization energies, ionization potentials, electron affinities, barrier heights, infrared intensities, dissociation and reaction energies, spin moments of molecular magnets, and isomer ordering of water clusters. Our results show that rSCAN requires less dense numerical grids and gives very similar results to those of SCAN for all properties examined with the exception of atomization energies, which are worsened in rSCAN. We also examine the performance of self-interaction-corrected (SIC) rSCAN with respect to SIC-SCAN using the Perdew–Zunger (PZ) SIC method. The PZSIC method uses orbital densities to compute one-electron self-interaction errors and places an even more stringent demand on numerical grids. Our results show that SIC-rSCAN gives marginally better performance than SIC-SCAN for almost all properties studied in this work with numerical grids that are on average half or less as dense as that needed for SIC-SCAN.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Simulation and characterization of cation disorder in ZnGeP 2

New optoelectronic materials are needed for improving the efficiency and reliability of devices such as solar cells. Cation ordering presents one means of controlling optoelectronic properties while introducing potential to also diversify the mineral constituents of electronic devices; however, the mechanisms of ordering are not yet well understood. To better understand cation ordering in a system integratable with current devices, we assess short- and long-range order parameters of ZnGeP 2 , a material closely lattice matched to Si. Structures are simulated using cluster-based Monte Carlo and first-principles calculations to compare structural distortions, periodicity, and local coordination environments in ZnGeP 2 to experimental data both from the literature and presented here. Comparing order parameters, we relate the transition in order parameters of ZnGeP 2 to that of ZnGeP 2 , discuss the reduction of band gaps with disorder, and show that traditional structural characterization alone is insufficient for understanding order in ZnGeP 2 .

14 SOLAR ENERGY↗
DOE OSTI2022

High-Fidelity Measurements for Flattop-HEU Benchmark Reevaluation

Flattop was first built in the 1950’s at Los Alamos National Laboratory. Flattop-HEU is composed of a sphere of highly enriched uranium (HEU) surrounded by a thick spherical natural uranium (NU) reflector. The reflector is composed of three parts: a stationary hemisphere and two movable quarter spheres. For fine control of the reactivity of the system, there are three control rods of natural uranium located in voids in the stationary hemisphere. The final components that make Flattop a useful critical assembly are the glory hole and mass adjustment pieces. These pieces can be loaded in various configurations into the glory hole and the core pedestal to control the known worth of the system. The glory hole and mass adjustment pieces are mostly small pieces of HEU with some mass adjustment pieces fabricated from NU. This allows for the irradiation of samples to a specified level. To better document the system, Flattop was evaluated and included in the International Criticality Safety Benchmark Evaluation Project (ICSBEP) handbook. The original benchmark evaluation of Flattop-HEU was written in 1999 based on an experiment completed in the 1960’s. This original evaluation was written to provide a single diameter that defined critical mass; however, as computational capabilities have increased, the focus for benchmark evaluations has shifted to include detailed modelswith all physical dimensions. Thus, as Flattop is a lynchpin in critical experiment work, the benchmark is being reevaluated at current standards. This summary discusses some of the largest known uncertainties from the evaluation and the high-fidelity measurements taken to reduce these uncertainties.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Securing Solar for the Grid (S2G)

The first slide deck provides an overview of the goals and objectives of the DOE Grid Modernization Initiative's Project entitled "Assessment and Coordination of DER Cybersecurity Standards." It covers the project's ongoing efforts to create a library of standards related to the cybersecurity of DER. The presentation will review the progress of this effort to-date and solicit feedback from participants on future directions. The second slide deck summarizes NREL's accomplishments for last three years under S2G project in a 10-12 min presentation.

clean energy↗
DOE OSTI2022

Analysis of vibronic coupling in a 4f molecular magnet with FIRMS

Vibronic coupling, the interaction between molecular vibrations and electronic states, is a fundamental effect that profoundly affects chemical processes. In the case of molecular magnetic materials, vibronic, or spin-phonon, coupling leads to magnetic relaxation, which equates to loss of magnetic memory and loss of phase coherence in molecular magnets and qubits, respectively. The study of vibronic coupling is challenging, and most experimental evidence is indirect. Here we employ far-infrared magnetospectroscopy to directly probe vibronic transitions in [Yb(trensal)] (where H 3 trensal = 2,2,2-tris(salicylideneimino)trimethylamine). We find intense signals near electronic states, which we show arise due to an “envelope effect” in the vibronic coupling Hamiltonian, which we calculate fully ab initio to simulate the spectra. We subsequently show that vibronic coupling is strongest for vibrational modes that simultaneously distort the first coordination sphere and break the C 3 symmetry of the molecule. With this knowledge, vibrational modes could be identified and engineered to shift their energy towards or away from particular electronic states to alter their impact. Hence, these findings provide new insights towards developing general guidelines for the control of vibronic coupling in molecules.

36 MATERIALS SCIENCE↗
DOE OSTI2026

An efficient explicit implementation of a near-optimal quantum algorithm for simulating linear dissipative differential equations

We propose an efficient block-encoding technique for the implementation of the Linear Combination of Hamiltonian Simulations (LCHS) for simulating dissipative initial-value problems. This algorithm approximates a target nonunitary operator as a weighted sum of Hamiltonian evolutions, thereby emulating a dissipative problem by mixing various time scales. We introduce an efficient encoding of the LCHS into a quantum circuit based on a simple coordinate transformation that turns the dependence on the summation index into a trigonometric function. Classically, this method is equivalent to the use of a highly accurate Fejér-Clenshaw-Curtis quadrature formula. Quantumly, this significantly simplifies block-encoding of a dissipative problem and allows one to perform an exponential number of Hamiltonian simulations by a single Quantum Signal Processing (QSP) circuit. The resulting LCHS circuit has high success probability and the selector scales logarithmically with the number of terms in the LCHS sum and linearly with time. Careful analysis of error convergence proves that this method is more efficient than other LCHS circuits that have recently appeared in the literature. We verify the quantum circuit and its scaling by simulating it on a digital emulator of fault-tolerant quantum computers and, as a test problem, solve the advection-diffusion equation. The proposed algorithm can be used for simulating a wide class of nonunitary initial-value problems including the Liouville equation with added dissipation and linear embeddings of nonlinear systems, such as the Koopman-von Neumann and Carleman embeddings.

Novikau, I [Lawrence Livermore National Laboratory↗
DOE OSTI2022

Exploring Structure-Sensitive Relations for Small Species Adsorption Using Machine Learning

Accurate prediction of adsorption energies on heterogeneous catalyst surfaces is crucial to predicting reactivity and screening materials. Adsorption linear scaling relations have been developed extensively but often lack accuracy and apply to one adsorbate and a single binding site type at a time. These facts undermine their ability to predict structure sensitivity and optimal catalyst structure. Using machine learning on nearly 300 density functional theory calculations, we demonstrate that generalized coordination number scaling relations hold well for oxygen- and high-valency carbon-binding species but fail for others. Here we reveal that the valency and the electronic coupling of a species with the surface, along with the site type and its coordination environment, are critical for small species adsorption. The model simultaneously predicts the adsorption energy and preferred site and significantly outperforms linear scalings in accuracy. It can expose the structure sensitivity of chemical reactions and enable enhanced catalyst activity via engineering particle shape and facet defects. The generality of our methodology is validated by training the model with transition metal data and transferring it to predict adsorption energies on single-atom alloys.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Elucidating Gas Reduction Effects of Organosilicon Additives in Lithium-Ion Batteries

Lithium-ion batteries (LIBs) with nonaqueous liquid electrolytes are prone to gas generation at elevated voltages and temperatures, degrading battery performance and posing serious safety risks. Organosilicon (OS) additives are an emerging candidate solution for gassing problems in LIBs, but a detailed understanding of their functional mechanisms remains elusive. In this work, we present a combined computational and experimental study to elucidate the gasreducing effects of OS additives. Cell volume measurements and gas chromatography–mass spectrometry reveal that OS additives can substantially reduce gas evolution in LIBs, particularly CO 2 regardless of source. Through density functional theory calculations, we identify multiple plausible pathways for CO 2 evolution, including (1) nucleophile-induced ring-opening of ethylene carbonate (EC) and the subsequent electro-oxidation and (2) direct electro-oxidation of lithium carbonate (Li 2 CO 3 ). Correspondingly, we find that OS additives function via two primary mechanisms: (1) scavenging of nucleophiles such as superoxide (O 2 •– ), peroxide (O 2 2– ), and carbonate ion (CO 3 2– ); (2) oligomerization with ethylene carbonate oxide ion and ethylene dicarbonate ion. Moreover, we discover that OS additives possess strong lithium coordination affinity, which helps further reduce the nucleophilic reaction energies and hence increases their nucleophile-scavenging efficiency. Finally, we provide a mechanistic interpretation for the enhanced gasreduction effects observed with fluorinated OS compounds, corroborated by surface analysis results from X-ray photoelectron spectroscopy. Our study offers the first molecular-level insights into how OS additives contribute to reduced gas formation in LIBs, paving the way for improved safety and performance of LIBs.

25 ENERGY STORAGE↗
DOE OSTI2026

Constrained variational optimization of counting-time allocation in sequential scattering measurements: Application to Bonse–Hart USANS

Sequential scattering measurements are often performed under a fixed experimental-time budget, even though the expected count rate varies strongly across the measured coordinate. When the dwell time at each measurement position can be controlled independently, this variation creates a general resource-allocation problem: how should the available time be distributed to minimize the uncertainty of the reconstructed profile? We formulate this problem as a constrained variational optimization for measurements governed by Poisson counting statistics. When each measurement is treated independently, minimizing the averaged squared relative uncertainty yields an inverse-square-root intensity allocation. The formulation is then generalized to include correlations between neighboring measurements and an instrumental resolution operator, leading to an allocation criterion that equalizes the marginal reduction in posterior uncertainty per unit measurement time. Bonse–Hart ultra-small-angle neutron scattering (USANS), in which reciprocal space is sampled sequentially through analyzer-angle stepping, provides an experimentally grounded application. Computational benchmarking shows that the optimized allocation outperforms uniform-time and constant-relative-error strategies, while application to an experimentally measured graphite USANS profile from the Spallation Neutron Source, using Poisson resampling under alternative schedules, demonstrates how counting time should be redistributed toward weak-intensity regions under an identical total duration. The resulting framework applies to sequential scattering and related scanning measurements whenever local dwell times are adjustable and directly determine the measurement uncertainties, and when the relevant correlation and instrumental-response models are available.

Tung, Chi-Huan [ORNL] (ORCID:0000000221972074)↗
DOE OSTI2023

Next-Generation Marine Energy Software Needs Assessment

The U.S. Department of Energy (DOE) Water Power Technologies Office’s (WPTO) initial investment in marine energy software was driven by needs identified over a decade ago. WPTO-funded research was first launched because of a U.S. congressional mandate that called for the DOE to officially research marine energy technologies, which also established the DOE WPTO in 2008. A congressional mandate requested the WPTO to evaluate a variety of marine energy devices, establish baseline levelized cost of energy estimates, and provide an overall report to Congress. This congressional mandate led to the Reference Model Project (RMP), for which WPTO funded a national multi-laboratory team to develop these reference models, based on state-of-the-art designs of six marine energy converter archetypes that consisted of three current energy converters and three wave energy converters (WEC). Each device was designed to operate for a specific marine resource, thus allowing the devices to serve as reference models for future studies. The RMP congressional report cited the need for improved marine energy software to handle a variety of device designs, as well as a need to standardize performance outputs. Without validated software packages and established metrics, information presented to the WPTO by technology developers could be incorrect or inaccurate and result in misleading conclusions. The recommendation to coordinate WPTO investment in software for numerical modeling and analysis was given a high priority because it would directly fill needs at the time, and focused funding would amplify impact. By sponsoring software development, WPTO would provide industry developers, university researchers, and national laboratories software that could be used, customized, and advanced, thus supporting the overall advancement of marine energy.

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

Deep Reinforcement Learning From Demonstrations to Assist Service Restoration in Islanded Microgrids

Microgrids can be operated in island mode during utility grid outages to support service restoration and improve system resilience. To schedule and dispatch distributed energy resources (DERs) in an islanded microgrid, conventional model-based methods rely on accurate distribution network models and lack generalization and adaptability. Data-driven methods are promising for DER coordination but face practical challenges such as potential hazards to microgrids during online training and insufficient online training opportunities due to low outage rates. This paper presents a novel two-stage learning framework that builds on the deep deterministic policy gradient from demonstrations to identify an optimal restoration strategy. At the pre-training stage, imitation learning is applied to equip the control agent with expert experiences to guarantee acceptable initial performance. At the online training stage, action clipping, reward shaping, and expert demonstrations are leveraged to ensure safe exploration while accelerating the training process. In conclusion, the proposed method is illustrated using the IEEE 123-node system and compared with a representative model-based method and the standard deep deterministic policy gradient method to prove solution accuracy and demonstrate increased computational efficiency.

Du, Yan↗
DOE OSTI2022

Access of named data elements in coordination namespace

An approach is described that provides access to a named data element in a Coordination Namespace that is stored in a memory that is distributed amongst a set of nodes. A request of a name corresponding to the named data element is received from a requesting process and the approach responsively searches for the name in the Coordination Namespace. In response to determining an absence of data corresponding to the named data element, a pending state is indicated to the requesting process. In response to determining that the data corresponding to the named data element exists, a successful state is returned to the requesting process. In one embodiment, the successful state also includes providing the requesting process with access to the data corresponding to the named data element.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Simulations of future particle accelerators: issues and mitigations

The ever increasing demands placed upon machine performance have resulted in the need for more comprehensive particle accelerator modeling. Computer simulations are key to the success of particle accelerators. Many aspects of particle accelerators rely on computer modeling at some point, sometimes requiring complex simulation tools and massively parallel supercomputing. Examples include the modeling of beams at extreme intensities and densities (toward the quantum degeneracy limit), and with ultra-fine control (down to the level of individual particles). In the future, adaptively tuned models might also be relied upon to provide beam measurements beyond the resolution of existing diagnostics. Much time and effort has been put into creating accelerator software tools, some of which are highly successful. However, there are also shortcomings such as the general inability of existing software to be easily modified to meet changing simulation needs. In this paper possible mitigating strategies are discussed for issues faced by the accelerator community as it endeavors to produce better and more comprehensive modeling tools. This includes lack of coordination between code developers, lack of standards to make codes portable and/or reusable, lack of documentation, among others.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Large-scale frictionless jamming with power-law particle size distributions

Due to significant computational expense, discrete element method simulations of jammed packings of size-dispersed spheres with size ratios greater than 1:10 have remained elusive, limiting the correspondence between simulations and real-world granular materials with large size dispersity. Here, invoking a recently developed neighbor binning algorithm, we generate mechanically stable jammed packings of frictionless spheres with power-law size distributions containing up to nearly 4 000 000 particles with size ratios up to 1:100. By systematically varying the width and exponent of the underlying power laws, we analyze the role of particle size distributions on the structure of jammed packings. The densest packings are obtained for size distributions that balance the relative abundance of large-large and small-small particle contacts. Although the proportion of rattler particles and mean coordination number strongly depend on the size distribution, the mean coordination of nonrattler particles attains the frictionless isostatic value of six in all cases. The size distribution of nonrattler particles that participate in the load-bearing network exhibits no dependence on the width of the total particle size distribution beyond a critical particle size for low-magnitude exponent power laws. This signifies that only particles with sizes greater than the critical particle size contribute to the mechanical stability. However, for high-magnitude exponent power laws, all particle sizes participate in the mechanical stability of the packing.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Steady-State Analysis of Microgrid Distributed Control Under Denial of Service Attacks

Distributed control is an effective method to coordinate multiple components in a microgrid. It usually has mandatory requirements for communication graph topology; changing the topology unexpectedly could disrupt the operation of a distributed controller. A denial of service (DoS) attack blocks communication channels to cause variations in communication graph. Unforeseen topology changes render a controller to receive incomplete system information. Control decisions made based on incorrect information can lead to significantly reduced grid supporting capability. As a result, the vital power balance between generation and load may be challenged. Determining power balance requires steady-state power flow analysis; however, the cyber-induced steady-state analysis is not well studied in the literature. Here, in this article, we show that a cyber–physical microgrid with unknown DoS attacks has augmented uncertain power flow equations, whose special structure creates new computational issue to determining power balance. To deal with the issue, we develop a novel cyber-induced microgrid model: the cyber–physical system is transformed into a pure physical model, where the disruption effects of DoS in the cyber layer are shown to be equivalent to the variations of the physical model parameters. With the transformed system, we develop a sufficient condition to ascertain the system power balance under unknown DoS attacks. In addition, practical insights for resilient distributed control design are shown as well.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Universally Accessible Structural Data on Macromolecular Conformation, Assembly, and Dynamics by Small Angle X-Ray Scattering for DNA Repair Insights.

Structures provide a critical breakthrough step for biological analyses, and small angle X-ray scattering (SAXS) is a powerful structural technique to study dynamic DNA repair proteins. As toxic and mutagenic repair intermediates need to be prevented from inadvertently harming the cell, DNA repair proteins often chaperone these intermediates through dynamic conformations, coordinated assemblies, and allosteric regulation. By measuring structural conformations in solution for both proteins, DNA, RNA, and their complexes, SAXS provides insight into initial DNA damage recognition, mechanisms for validation of their substrate, and pathway regulation. Here, we describe exemplary SAXS analyses of a DNA damage response protein spanning from what can be derived directly from the data to obtaining super resolution through the use of SAXS selection of atomic models. We outline strategies and tactics for practical SAXS data collection and analysis. Making these structural experiments in reach of any basic and clinical researchers who have protein, SAXS data can readily be collected at government-funded synchrotrons, typically at no cost for academic researchers. In addition to discussing how SAXS complements and enhances cryo-electron microscopy, X-ray crystallography, NMR, and computational modeling, we furthermore discuss taking advantage of recent advances in protein structure prediction in combination with SAXS analysis.

Chinnam, Naga Babu↗