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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 1,153 records · Page 64
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Regulation of Lignin Biosynthesis and Its Role in Growth-Defense Tradeoffs

Plant growth-defense tradeoffs are fundamental for optimizing plant performance and fitness in a changing biotic/abiotic environment. This process is thought to involve readjusting resource allocation to different pathways. It has been frequently observed that among secondary cell wall components, alteration in lignin biosynthesis results in changes in both growth and defense. How this process is regulated, leading to growth or defense, remains largely elusive. In this article, we review the canonical lignin biosynthesis pathway, the recently discovered tyrosine shortcut pathway, and the biosynthesis of unconventional C-lignin. We summarize the current model of the hierarchical transcriptional regulation of lignin biosynthesis. Moreover, the interface between recently identified transcription factors and the hierarchical model are also discussed. We propose the existence of a transcriptional co-regulation mechanism coordinating energy allowance among growth, defense and lignin biosynthesis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Deep red emitting Mg2La2SnO7:Mn4+ phosphor: Synthesis and luminescence properties

Highlights: • Novel Mg{sub 2}La{sub 2}SnO{sub 7}:Mn{sup 4+} deep-red-emitting phosphor is synthesized in air. • Emission band peaking at ∼ 706 nm is observed in the range of 640–780 nm. • The thermal stability and luminous mechanism is explained. - Abstract: Mg{sub 2}La{sub 2}SnO{sub 7}:Mn{sup 4+} phosphor is synthesized by the solid-state reaction method in air. Monitored at 706 nm, excitation spectrum of Mg{sub 2}La{sub 2}SnO{sub 7}:Mn{sup 4+} phosphor including peaks at ∼ 300, 333, 395, and 516 nm can be observed in the range of 220–600 nm. With excitation at 333 nm, emission band of Mg{sub 2}La{sub 2}SnO{sub 7}:Mn{sup 4+} phosphor is shown in the range of 640–780 nm owing to the {sup 2}E → {sup 4}A{sub 2} transitions of Mn{sup 4+} ion. The optimal Mn{sup 4+} ion concentration is ∼ 0.3 mol% in Mg{sub 2}La{sub 2}SnO{sub 7}:Mn{sup 4+} phosphor. The lifetime decreases from 1.23 to 0.83 ms with the increase of Mn{sup 4+} concentration from 0.1 to 1.2 mol%. There is only one luminescence center (Mn{sup 4+}) in Mg{sub 2}La{sub 2}SnO{sub 7}:Mn{sup 4+} phosphor, which is confirmed by the luminescence properties, decay curves, and time-resolved emission spectra. Mg{sub 2}La{sub 2}SnO{sub 7}:Mn{sup 4+} phosphor has good thermal stability. Luminous mechanism is explained by energy level diagram of Mn{sup 4+} ion and the thermal quenching phenomenon is analyzed by the configuration coordinate diagram of Mn{sup 4+} ion.

36 MATERIALS SCIENCE↗
DOE OSTI2026

NASA analysis of space mission options for the 2025 planetary defense conference hypothetical asteroid impact threat scenario

The 2025 Planetary Defense Conference (PDC) hypothetical asteroid impact threat exercise is being conducted in coordination with the United Nations-endorsed Space Mission Planning Advisory Group (SMPAG), exercising SMPAG's processes for assessing space mission options and communicating to decision makers. Here, in this paper, we describe the work performed by our NASA-led team and present the results we contributed to the SMPAG effort for the exercise. Our NASA-led team assessed mission options for asteroid reconnaissance (flyby and rendezvous), deflection, and robust disruption using several viable techniques: kinetic impactors, ion beam deflection, and nuclear explosive devices. Our simulations and analyses considered how much change-in-velocity an asteroid can tolerate before fragmentation onset, and we worked towards establishing requirements for robustly disrupting an asteroid. Heuristics informed by the simulation results are incorporated into optimization of deflection and disruption mission campaign options. Finally, we make some observations about useful generalizations from these results with potential applicability to any planetary defense scenario.

Asteroid deflection↗
DOE OSTI2025

Videos, photos, and AI-derived grain size data associated with “High-throughput AI Video Surveys Enable Reproducible Multiscale Sediment Size Mapping, with Implications for Hydrobiogeochemical Parameterization”

NOTE: The manuscript associated with this data package is currently in review. The data may be revised based on reviewer feedback. Upon manuscript acceptance, this data package will be updated with the final dataset and additional metadata. This data package is associated with the manuscript “High-throughput AI Video Surveys Enable Reproducible Multiscale Sediment Size Mapping, with Implications for Hydrobiogeochemical Parameterization” under review. This data package includes five data types: 1) raw photos and videos from drone survey and walking smartphone surveys; 2) images derived from raw videos; 3) manual labeling of reference scales; 4) metadata for all images and photo resolution derived from artificial intelligence (AI) models or manual labels, 5) grain size data obtained from AI models for all photos, 6) metadata and grain size data after quality control, 7) summaries of sample efficiency for all data, and 8) computational fluid dynamics (CFD) data used to support hydro-biogeochemical (HBGC) parameter estimation. Such data is used to 1) demonstrate significant improvements in accuracy, efficiency, and quality control for grain size data collection with the help of AI models, 2) study the spatial heterogeneity of grain size and observation reproducibility based on tens of thousands of data points generated by the AI models, and 3) evaluate the impacts of grain size heterogeneity on key HBGC parameters across sediment-to-reach and hourly-to-yearly scales. In particular, the data package contains 116 folders and 179696 files. The files include 41 videos in .mov format, 64047 photos in .jpg format, 13541 video-derived photos in .png format, 12747 segmentation mask data in .tif format, 12747 segmentation data in .json format, 24771 .csv files that with metadata and grain size for each individual photo as well as water depth and velocity data from CFD and observation, 51791 .txt files of raw AI predicted labels, and 11 flight record data in .srt format. The summary for all metadata and grain size statistics information is included in “Scales_V3_NG.csv” and “Statistics_V3_NG.csv”. The summary for data that pass data quality control (QC) level 0-2 is included in “QCStatistics_V3_NG.csv”. The QC level 0 represents photos whose photo resolution is positive, excluding photos that miss reference scale. The QC level 1 means reference scale circularity uncertainty is less than 5% for smartphone images while representing photo resolution is larger than 0.44 mm/pixel for drone images. The QC level 2 means excluding photos whose grain number is less than 100, a minimum number of grains recommended by classic literature. The summary for each video’s name, length, frame rates, survey area, grain number, survey efficiency, etc. can be found in “QCSummary_V3_NG.csv”. The summary for site name, GPS coordinates, and number of images at each site can be found in “SitesSummary_V3_*.csv” files. Overall computational efficiency summary is reported in Table 4 of accompanying manuscript. Additionally, the nitrate concentration data used in this work was downloaded from an existing dataset published on ESS-DIVE (Boat-Dragged Sensor Hanford Reach.csv; Conner A. et al., 2020). We thank the United States Forest Service, Washington Department of Fish and Wildlife, Washington Department of Natural Resources, Cowiche Canyon Conservatory, Port of Benton, and the Confederated Tribes and Bands of the Yakama Nation for access to field locations where the data were collected. We also thank the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate data collection and optimization of data usage according to their values and worldview.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Structures and Stabilities of (MgO) n Nanoclusters

Global minima for (MgO) n structures were optimized using a tree growth–hybrid genetic algorithm in conjunction with MNDO/MNDO/d semiempirical molecular orbital calculations followed by density functional theory geometry optimizations with the B3LYP functional. New lowest energy isomers were found for a number of (MgO) n clusters. The most stable isomers for (MgO) n (n > 3) are 3-dimensional. For n < 20, hexagonal tubular (MgO)n structures are more favored in energy than the cubic structures. The cubic structures and their variations dominate after n = 20. For the cubic isomers, increasing the size of the cluster in any dimension improves the stability. The effectiveness of increasing the size of the cluster in a specific dimension to improve stability diminishes as the size in that dimension increases. For cubic structures of the same size, the most compact cubic structure is expected to be the more stable cubic structure. The average Mg–O bond distance and coordination number both increase as n increases. The calculated average Mg–O bond distance is 2.055 Å at n = 40, slightly smaller than the bulk value of 2.104 Å. The average coordination number is predicted to be 4.6 for the lowest energy (MgO) 40 as compared to the bulk value of 6. As n increases, the normalized clustering energy ΔE(n) for the (MgO) n increases and the slope of the ΔE(n) vs n curve decreases. The value of ΔE(40) is predicted to be 150 kcal/mol, as compared to the bulk value ΔE(∞) = 176 kcal/mol. Finally, the electronic properties of the clusters are presented and the reactive sites are predicted to be at the corners.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2022

Improved Particle Swarm Algorithm Using Rubik’s Cube Topology for Bilevel Building Energy Transaction

Following the rapid growth of distributed energy resources (e.g., renewables, battery), localized peer-to-peer energy transactions are receiving more attention for multiple benefits, such as reducing power loss and stabilizing the main power grid. To promote distributed renewables locally, the local trading price is usually set to be within the external energy purchasing and selling price range. Consequently, building prosumers are motivated to trade energy through a local transaction center. This local energy transaction is modeled in bilevel optimization game. A selfish upper level agent is assumed with the privilege to set the internal energy transaction price with an objective of maximizing its arbitrage profit. Meanwhile, the building prosumers at the lower level will response to this transaction price and make decisions on electricity transaction amount. Therefore, this non-cooperative leader-follower trading game is seeking for equilibrium solutions on the energy transaction amount and prices. Additionally, a uniform local transaction price structure (purchase price equals selling price) is considered here. Aiming at reducing the computational burden from classical Karush–Kuhn–Tucker (KKT) transformation and protecting the private information of each stakeholder (e.g., building), swarm intelligence-based solution approach is employed for upper level agent to generate trading price and coordinate the transactive operations. On one hand, to decrease the chance of premature convergence in global-best topology, Rubik’s Cube topology is proposed in this study based on further improvement of a two-dimensional square lattice model (i.e., one local-best topology-Von Neumann topology). Rotating operation of the cube is introduced to dynamically changing the neighborhood and enhancing information flow at the later searching state. Several groups of experiments are designed to evaluate the performance of proposed Rubik’s Cube topology-based particle swarm algorithm. The results have validated the effectiveness of proposed topology and operators comparing with global-best version PSO and Von Neumann topology-based PSO and its scalability on larger scale applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Analysis of Control-Oriented Wake Modeling Tools Using Lidar Field Results

Wind turbines in a wind farm operate individually to maximize their own performance regardless of the impact of aerodynamic interactions on neighboring turbines. Wind farm controls can be used to increase power production or reduce overall structural loads by properly coordinating turbines. One wind farm control strategy that is addressed in literature is known as wake steering, wherein upstream turbines operate in yaw misaligned conditions to redirect their wakes away from downstream turbines. The National Renewable Energy Laboratory (NREL) in Golden, CO conducted a demonstration of wake steering on a single utility-scale turbine. In this campaign, the turbine was operated at various yaw misalignment setpoints while a lidar mounted on the nacelle scanned five downstream distances. The lidar measurements were combined with turbine data, as well as measurements of the inflow made by a highly instrumented meteorological mast upstream. The full-scale measurements are used to validate controls-oriented tools, including wind turbine wake models, used for wind farm controls and optimization. This paper presents a quantitative comparison of the lidar data and controls-oriented wake models under different atmospheric conditions and turbine operation. The results show good agreement between the lidar data and the models under these different conditions.

17 WIND ENERGY↗
DOE OSTI2018

A Hierarchical VLSM-Based Demand Response Strategy for Coordinative Voltage Control between Transmission and Distribution Systems

This paper presents a two-stage hierarchical voltage-load sensitivity matrix (VLSM)-based demand response (DR) algorithm for regulating the voltage at distribution feeders while fulfilling the transmission system DR requests. This allows distributed energy resources be aggregated to provide transmission-level services without causing operational issues in the distribution grids. At the beginning of each operation interval, a transmission system controller will issue DR commands to distribution system controllers. In the first stage, the distribution system controller uses a VLSM-based dispatch algorithm to dispatch the available DR resources on the distribution feeder with an objective to minimize the total voltage deviations at the lowest cost. Then, power flow studies are conducted assuming that the DR commands have been executed. If voltage violations are detected, a second-stage VLSM-based DR dispatch will be performed to remove those violations. After that, the upper and lower DR limits calculated for the next operation interval are sent back to the transmission system controller so the transmission optimization algorithm can use them as operational constraints to make subsequent decisions. The DR resources include smart photovoltaic (PV) inverters that can curtail real power and provide reactive power support, controllable loads and capacitor banks. In conclusion, the IEEE 123-bus test system with 5-minute PV and load data is used to evaluate the performance of the algorithm. In conclusion, simulation results show that the proposed algorithm can fulfill the transmission-level DR requests while maintaining the voltage in the distribution system within limits.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Hollow-structured Ni-N-C catalysts for highly selective CO 2 electroreduction

Atomically dispersed single-atom catalysts have emerged as promising non-precious catalyst alternatives to expensive Ag and Au catalysts for electrochemical CO 2 reduction reaction (CO 2 RR). In particular, nickel-nitrogen-carbon (Ni-N-C) catalysts have demonstrated a high faradaic efficiency (FE) toward CO formation at low overpotentials. Nonetheless, the exact nature of Ni active sites under CO 2 RR remains elusive and conventional Ni-N-C catalysts are limited by microporosity and low density of Ni single atoms, hindering performance in CO 2 electrolyzers. Here, we report the synthesis of hollow-structured Ni-N-C ( hs -Ni-N-C) catalysts via a post-synthesis modification (PSM) strategy using partial ligand exchange of 2-methylimidazole with 3-amino-1,2,4-triazole. This approach enables the formation of a hollow structure, resulting in more than a twofold increase in Ni atom density compared to regular Ni-N-C (r-Ni-N-C). In a zero-gap CO 2 electrolyzer, the optimized hs -Ni-N-C allows for achieving an FE CO of 97% at a current density of > 100 mA cm⁻ 2 , while maintaining high CO selectivity with stable performance over 100 h at 2.5 V. hs-Ni-N-C shows a more than sevenfold increase in the CO partial current density relative to r-Ni-N-C resulting from the combined effects of a higher density of Ni single-atom sites, improved kinetics, and lower transport resistance under the operating conditions, as indicated by electrochemical impedance spectra and distribution of relaxation times analysis. Operando high energy-resolution X-ray absorption spectroscopy (XAS) reveals that atop-bonded CO on Ni single sites induces dynamic transformations of the Ni–N coordination environment, leading to a symmetric coordination structure of hs -Ni-N-C. Under CO 2 RR, the catalysts undergo a more pronounced structural change and form a minor fraction of Ni nanoparticles. Density functional theory calculations are consistent with the XAS results and provide molecular insights showing that the interplay between protonation and CO adsorption leads to adsorbate-induced restructuring of the Ni single atom. This work demonstrates the synergistic role of hollow structure and high-density Ni atoms in governing CO 2 RR selectivity and provides mechanistic insights into the structural dynamics of single-atom catalysts under operating conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Rubik’s Cube Topology Based Particle Swarm Algorithm for Bilevel Building Energy Transaction

Following the rapid growth of distributed energy resources (e.g. renewables, battery), localized peer-to-peer energy transactions are receiving more attention for multiple benefits, such as, reducing power loss, stabilizing the main power grid, etc. To promote distributed renewables locally, the local trading price is usually set to be within the external energy purchasing and selling price range. Consequently, building prosumers are motivated to trade energy through a local transaction center. This local energy transaction is modeled in bilevel optimization game. A selfish upper level agent is assumed with the privilege to set the internal energy transaction price with an objective of maximizing its arbitrage profit. Meanwhile, the building prosumers at the lower level will response to this transaction price and make decisions on electricity transaction amount. Therefore, this non-cooperative leader-follower trading game is seeking for equilibrium solutions on the energy transaction amount and prices. In addition, a uniform local transaction price structure (purchase price equals selling price) is considered here. Aiming at reducing the computational burden from classical Karush-Kuhn-Tucker (KKT) transformation and protecting the private information of each stakeholder (e.g., building), swarm intelligence based solution approach is employed for upper level agent to generate trading price and coordinate the transactive operations. On one hand, to decrease the chance of premature convergence in global-best topology, Rubiks Cube topology is proposed in this study based on further improvement of a two-dimensional square lattice model (i.e., one local-best topology-Von Neumann topology). Rotating operation of the cube is introduced to dynamically changing the neighborhood and enhancing information flow at the later searching state. Several groups of experiments are designed to evaluate the performance of proposed Rubiks Cube topology based particle swarm algorithm. The results have validated the effectiveness of proposed topology and operators comparing with global-best version PSO and Von Neumann topology based PSO and its scalability on larger scale applications.

Feng, Xiaochun↗
DOE OSTI2025

Evaluating the Origins of Aerobic Oxidation Catalysis with TAM-3, a MOF with Accessible Co(II) Sites and Large Pores

Metal-organic frameworks (MOFs) are attractive platforms that merge concepts of homogeneous and heterogeneous catalysis. Catalyst design and optimization are enabled by an array of synthetic methods that offer independent control over the local chemical structure of lattice-embedded metal ions (i.e., ligand identity and geometry) and the long-range materials properties (i.e., porosity). Establishing the origin of catalytic activity in MOF-promoted reactions remains a significant challenge: The relative rates of catalyst turnover and substrate diffusion dictate the extent to which interstitial sites are accessible and operational in catalysis. To minimize the contributions of surface sites in catalysis, materials with large pore dimensions are often sought, however, the impact of pore expansion on the origins of catalytic activity is similarly challenging to establish. Here, we describe TAM-3, a Co(II) based MOF with accessible metal sites supported by a facially coordinating tris-tetrazole ligand set. TAM-3 features large channel-like pores (17 × 23 Å) and promotes aerobic C−H oxidation and olefin epoxidation. Using a set of simple kinetics experiments, based on the analysis of kinetic isotope effects and olefin oxidation diastereoselectivities, we demonstrate that despite the large pores, interstitial metal ions do not significantly contribute to the observed substrate oxidation. This study highlights the importance of conducting kinetic experiments to assess the origin of apparent catalytic activity with MOFs and the challenge of harnessing reactive oxidants with microporous catalyst materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

SQMS Nanofabrication Taskforce: Towards Fabrication of High Coherence Superconducting Qubits

SQMS Nanofabrication Taskforce, which brings together experts in nanofabrication and materials science at the SQMS Center, has been launched to implement novel materials, substrates, and fabrication techniques for high coherence superconducting quantum devices. In a first coordinated effort, the Nanofabrication Taskforce developed fabrication processes to eliminate the lossy materials at surfaces and interfaces of superconducting qubits to enhance qubit coherence. The initial results of this study demonstrated T1 enhancement by almost an order of magnitude with best T1 s reaching ~ 600 $\mu$s. [1] We attribute this improvement to the replacement of lossy native Nb oxide layer with native Ta oxide, which is thinner and less disordered. we are now currently working on strategies with an aim towards moving qubit coherence times to millisecond timescales and beyond. The results of a systematic study will be presented to address substrate preparation, alternative materials as low loss platforms (Nb, Ta, and Re), novel non-oxide forming low loss capping layers such as proximitized Au, optimized qubit designs, and optimized Josephson junction materials, processing, and design.

Bal, Mustafa↗
DOE OSTI2022

Multiscale simulation of integrated energy system and electricity market interactions

Accelerating the deep decarbonization of the world's electric grids requires the coordination of complex energy systems and infrastructures across timescales from seconds to decades. Here, we present a new multiscale simulation framework that integrates process- and grid-centric modeling paradigms to better design, operate, and control integrated energy systems (IESs), which combine multiple technologies, in wholesale energy markets. Traditionally, IESs are analyzed with a process-centric paradigm such as levelized cost of electricity (LCOE) or annualized net revenue, ignoring important interactions with electricity markets. This framework explicitly models the complex interactions between an IES's bidding, scheduling, and control decisions and the energy market's clearing and settlement processes, while incorporating operational uncertainties. Through two case studies, we show the importance of understanding and quantifying complex resource-grid interactions. In case study 1, we demonstrate that optimized bidding from one resource shifts the profit distribution for all energy systems in the market. This result suggests new and more flexible IES technologies can disrupt the economics of all market participants, possibly leading to accelerated retirements of less flexible resources. Interestingly, the optimized bidding has little impact on grid-level aggregate statistics, such as total generation costs and renewable penetration rate. While aggregate modeling strategies may remain valid under some IES adoption scenarios for analysis focused on regional outcomes, direct comparisons of IES technologies at specific locations without considering these interactions may lead to misleading or incorrect conclusions. In case study 2, we consider the design and flexible operation of IESs that hybridize conventional generators with energy storage. Through a sensitivity analysis, we find that as the size of the storage system increases, the total number of start-ups for coal- and natural gas-based IESs reduced by 25% and 33.6%, and the total thermal generator ramping (i.e., mileage) reduced by 86.5% and 62.5%, respectively. This shows the primary benefit of storage may not be reduced operational costs (which do not change significantly) but fewer start-ups and less ramping, which may greatly simplify the design, operation, and control of carbon capture systems. The new modeling and optimization capabilities from this work enable the coupling of rigorous, dynamic process models with grid-level production cost models to quantitatively identify the nuanced interdependencies across these vast timescales that must be addressed to realize clean, safe, and secure energy production. Moreover, the proposed general multiscale simulation framework is applicable to all IES technologies and can be easily extended to consider other energy carriers (e.g., hydrogen, ammonia) and energy infrastructures (e.g., natural gas pipelines).

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2015

Branch-and-Bound algorithm applied to uncertainty quantification of a Boiling Water Reactor Station Blackout

Evaluation of the impacts of uncertainty and sensitivity in modeling presents a significant set of challenges in particular to high fidelity modeling. Computational costs and validation of models creates a need for cost effective decision making with regards to experiment design. Experiments designed to validate computation models can be used to reduce uncertainty in the physical model. In some cases, large uncertainty in a particular aspect of the model may or may not have a large impact on the final results. For example, modeling of a relief valve may result in large uncertainty, however, the actual effects on final peak clad temperature in a reactor transient may be small and the large uncertainty with respect to valve modeling may be considered acceptable. Additionally, the ability to determine the adequacy of a model and the validation supporting it should be considered within a risk informed framework. Low fidelity modeling with large uncertainty may be considered adequate if the uncertainty is considered acceptable with respect to risk. In other words, models that are used to evaluate the probability of failure should be evaluated more rigorously with the intent of increasing safety margin. Probabilistic risk assessment (PRA) techniques have traditionally been used to identify accident conditions and transients. Traditional classical event tree methods utilize analysts’ knowledge and experience to identify the important timing of events in coordination with thermal-hydraulic modeling. These methods lack the capability to evaluate complex dynamic systems. In these systems, time and energy scales associated with transient events may vary as a function of transition times and energies to arrive at a different physical state. Dynamic PRA (DPRA) methods provide a more rigorous analysis of complex dynamic systems. Unfortunately DPRA methods introduce issues associated with combinatorial explosion of states. This study presents a methodology to address combinatorial explosion using a Branch-and-Bound algorithm applied to Dynamic Event Trees (DET), which utilize LENDIT (L – Length, E – Energy, N – Number, D – Distribution, I – Information, and T – Time) as well as a set theory to describe system, state, resource, and response (S2R2) sets to create bounding functions for the DET. The optimization of the DET in identifying high probability failure branches is extended to create a Phenomenological Identification and Ranking Table (PIRT) methodology to evaluate modeling parameters important to safety of those failure branches that have a high probability of failure. The PIRT can then be used as a tool to identify and evaluate the need for experimental validation of models that have the potential to reduce risk. Finally, in order to demonstrate this methodology, a Boiling Water Reactor (BWR) Station Blackout (SBO) case study is presented.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2015

Measuring and monitoring KIPT Neutron Source Facility Reactivity

Argonne National Laboratory (ANL) of USA and Kharkov Institute of Physics and Technology (KIPT) of Ukraine have been collaborating on developing and constructing a neutron source facility at Kharkov, Ukraine. The facility consists of an accelerator-driven subcritical system. The accelerator has a 100 kW electron beam using 100 MeV electrons. The subcritical assembly has k eff less than 0.98. To ensure the safe operation of this neutron source facility, the reactivity of the subcritical core has to be accurately determined and continuously monitored. A technique which combines the area-ratio method and the flux-to-current ratio method is purposed to determine the reactivity of the KIPT subcritical assembly at various conditions. In particular, the area-ratio method can determine the absolute reactivity of the subcritical assembly in units of dollars by performing pulsed-neutron experiments. It provides reference reactivities for the flux-to-current ratio method to track and monitor the reactivity deviations from the reference state while the facility is at other operation modes. Monte Carlo simulations are performed to simulate both methods using the numerical model of the KIPT subcritical assembly. It is found that the reactivities obtained from both the area-ratio method and the flux-to-current ratio method are spatially dependent on the neutron detector locations and types. Numerical simulations also suggest optimal neutron detector locations to minimize the spatial effects in the flux-to-current ratio method. The spatial correction factors are calculated using Monte Carlo methods for both measuring methods at the selected neutron detector locations. Monte Carlo simulations are also performed to verify the accuracy of the flux-to-current ratio method in monitoring the reactivity swing during a fuel burnup cycle.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Collaborative Research and Development Program on Explosive Detection Technology

In September 2013, at the 6th Permanent Coordinating Group Meeting between the U.S Department of Energy (DOE) and the French Institut de Radioprotection et de Sureté Nucléaire (IRSN), France expressed an interest in bilateral cooperation with the United States because its newly revised regulations that require enhanced explosives detection capabilities at nuclear and radiological facilities. In the ensuing years, PNNL (DOE/NNSA) and IRSN sought to identify an area of collaboration within explosives detection that would leverage the specific technical strengths of each organization. Based upon awareness of each other’s technical acumen gleaned from the scientific literature on explosives detection, it was clear that specific organizations within each nation could provide the needed expertise to enable enhancement of explosives detection through a collaborative development effort. The French lnstitut Saint-Louis was determined to be an optimal partner for IRSN to develop a collaboration with DOE/NNSA using PNNL’s detection team in this effort. Thus, the dialog was started between the technical experts at each organization to define where complementary expertise in explosives detection could be best leveraged. The technical plans and objectives of this project were sound with promising results. In the end, the joint action sheet was not implemented. The challenge with executing the project was in the complexity of getting a signed agreement between DOE, IRSN and ISL. Most of the obstacles surrounded the ability to protect intellectual property and obtain an agreement which included all of the parties. At a high level, this report documents the interactions and attempt to develop a cooperative framework for explosives detection development from FY 2014 through FY 2020.

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

Solvent-Mediated Synthesis of Amorphous Li 3 PS 4 /Polyethylene Oxide Composite Solid Electrolytes with High Li + Conductivity

Solvent-mediated routes have emerged as an effective, scalable, and low-temperature method to fabricate sulfide-based solid-state electrolytes. However, tuning the synthesis conditions to optimize the electrolyte’s morphology, structure, and electrochemical properties is still underexplored. Here, we report a new class of composite solid electrolytes (SEs) containing amorphous Li 3 PS 4 synthesized in situ with a poly(ethylene oxide) (PEO) binder using a one-pot, solvent-mediated route. The solvent and thermal processing conditions have a dramatic impact on the Li 3 PS 4 structure. Conducting the synthesis in tetrahydrofuran resulted in crystalline β-Li 3 PS 4 whereas acetonitrile led to amorphous Li 3 PS 4 . Annealing at 140 °C increased the Li + conductivity of an amorphous composite (Li 3 PS 4 + 1 wt % PEO) by 3 orders of magnitude (e.g., from 4.5 × 10 –9 to 8.4 × 10 –6 S/cm at room temperature) because of: (i) removal of coordinated solvent and (ii) rearrangement of the polyanionic network to form P 2 S 7 4– and PS 4 3– moieties. The PEO content in these composites should be limited to 1–5 wt % to ensure reasonable Li+ conductivity (e.g., up to 1.1 × 10 –4 S/cm at 80 °C) while providing enough binder to facilitate scalable processing. Here, the results of this study highlight a new strategy to suppress crystallization in sulfide-based SEs, which has important implications for solid-state batteries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗