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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Consensus Weighting of a Multi-Agent System for Load Shedding

An agent-based scheme is proposed for distributed underfrequency load shedding (UFLS). The key concept is a consensus weighting protocol (CWP) for agents to reach an agreement. Unlike the well adopted average-consensus protocol (ACP), the proposed CWP enables each agent to converge to its weighted portion of the sum of all initial values. Thus, the proposed CWP is more suitable for the UFLS application, as it allows load buses with a higher level of loading to shed more, rather than reducing by the same average value over all load buses as required by the ACP. Proof of convergence for the proposed CWP is derived and presented in this paper, together with the constraints. For implementation of the multi-agent system (MAS), the monitoring, estimation, and distribution steps are developed. Two study cases and the simulation results are provided to validate the performance of the proposed agent-based UFLS scheme.

Xie, Jing↗
DOE OSTI2021

Manipulation of amorphous precursors to enhance zeolite nucleation

Crystallization in media comprised of amorphous precursors is becoming a more common phenomenon for numerous synthetic, biological, and natural materials that grow by a combination of classical and nonclassical pathways. Amorphous phases can exhibit a wide range of physicochemical properties that may evolve during the course of nucleation and crystal growth. This creates challenges for establishing causal relationships between amorphous precursor properties and their effect(s) on the selection of mechanistic pathways of crystallization and ultimately the properties of the crystalline product. In this study, we examine ways to manipulate the composition and colloidal stability of amorphous (alumino)silicate precursors that are prevalent in nanoporous zeolite syntheses. Changes in the amorphous precursor properties are evaluated on the basis of their ability to enhance rates of crystal formation. Here, we use fumed silica as the primary silicon source and examine the effects of infusing the source or growth medium with additional alkali metal, which serves as an inorganic structure-directing agent to facilitate the formation of porous crystal structures. We also assess the impact of adding a polymer additive, which reduces the colloidal stability of precursors, wherein we posit that the confined pockets of solution within the interstitial spaces of the precursor aggregates play an important role in regulating the rate of zeolite crystallization. Three commercially relevant zeolites (mordenite, SSZ-13, and ZSM-5) were selected for this study based on their diverse frameworks and methods of preparation. Here our findings reveal that alkali infusion significantly reduces the crystallization times for mordenite and SSZ-13, but has little impact on ZSM-5 synthesis. Conversely, we find that polymer addition markedly enhanced the rates of crystallization among all three zeolites, suggesting that this method may be a general approach to reduce zeolite synthesis times. Given the relatively high costs associated with commercial zeolite production, identifying new methods to improve the efficiency of hydrothermal syntheses can have significant practical implications beyond the fundamental benefits of developing new routes to tailor nonclassical crystallization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Blockchain for Fault-Tolerant Grid Operations Version 2.0

This report explores the potential of distributed ledger technology (DLT) as a transformative tool to enhance fault-tolerant operations in electrical distribution systems. Leveraging DLT's core attributes, including an immutable decentralized ledger, distributed consensus mechanisms, and state replication capabilities, this study focuses on three critical use cases. A central aspect of this research centers on the utilization of a consensus-driven ledger, providing actors within the system, such as distributed resources, with access to a reliable data repository. This empowers these actors to collaborate effectively and make informed decisions, all securely recorded on the blockchain. The first use case concentrates on data configuration, utilizing mathematical criteria---particularly, the chi-squared test for gross error detection---to identify trustworthy sensors for advanced decision-making. Building upon this foundation of trust, the second use case, topology identification, accurately determines circuit breaker states, unveiling the distribution network's topology. Ultimately, the third use case leverages this trust to execute switching actions, reconfiguring feeders and restoring power to disconnected customers after fault events. The concept of trust serves as a cornerstone in this approach, marking a departure from traditional fault location, isolation, and service restoration (FLISR) methods. Additionally, the blockchain-based architecture introduces decentralization, empowering disconnected areas to make autonomous decisions, even when communication with a central control center is disrupted. The primary contributions of this report are twofold: (1) a novel approach for evaluating distribution system voltage areas while preserving data ownership and (2) the implementation of interactions between distribution network areas using the actor model. Unlike the previous sequential approach for evaluating the area connection voltages, which required a radial network topology, this study's area model reduction enables a more versatile approach. The area model reduction addresses issues of prolonged data waiting times and multiple points of failure within the previous approach. Notably, the presented evaluation for the reduced network model area connection reveals a significant increase in the differences in voltage magnitudes. Simulation and evaluation of area agents across four distinct cases elucidate the area-level interaction behavior during a fault event. Simulations demonstrate that the proposed distributed FLISR (DFLISR) approach can successfully restore service to an affected area. Varying message delays and message loss probabilities in each simulation case underscore their impacts on restoration times, ranging from 3 min and 32 s to 6 min and 19 s. In contrast, power is not restored in an area in one of our simulation cases.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Commissioning of Dedicated Furnace for Nb3Sn Coatings of 2.6 GHz Single Cell Cavities

We present the results of commissioning a dedicated furnace for Nb3Sn coatings of 2.6 GHz single cell cavities. Nb3Sn is a desired coating due to its high critical temperature and smaller surface resistance compared to bulk Nb. Usage of Nb3Sn coated cavities will greatly reduce operating costs due to decreased dependance on cryo cooling. Tin is deposited by use of a tin chloride nucleation agent and tin vapor diffusion. Analysis of the resultant coating was performed using SEM/EDS to verify successful formation of Nb3Sn. Witness samples in line of sight of the source were used in order to understand the coating efficacy.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Privacy-Preserving Average Consensus With Beaver Triple and Communication Obfuscation

A privacy-preserving average consensus algorithm is proposed that synergizes the Beaver triple in secret sharing theory and noise obfuscation. The algorithm safeguards the initial values of agents against passive adversaries in a multiagent system. It is proved that the proposed algorithm can concurrently ensure average consensus and privacy, while also reducing the online computation and communication overhead compared to encryption-based ones. In addition, it imposes a less stringent condition for privacy preservation compared to certain noise-obfuscation techniques.

Beaver triple↗
DOE OSTI2023

Commissioning of dedicated furnace for Nb3Sn coatings of 2.6GHz single cell cavities

We present the results of commissioning a dedicated fur- nace for Nb3Sn coatings of 2.6 GHz single cell cavities. Nb3Sn is a desired coating due to its high critical temper- ature and smaller surface resistance compared to bulk Nb. Usage of Nb3Sn coated cavities will greatly reduce operat- ing costs due to decreased dependance on cryo cooling. Tin is deposited by use of a tin chloride nucleation agent and tin vapor diffusion. Analysis of the resultant coating was performed using SEM/EDS to verify successful formation of Nb3Sn. Witness samples in line of sight of the source were used in order to understand the coating efficacy.

Kulyavtsev, P. A.↗
DOE OSTI2026

Desorption Electrospray Ionization–Mass Spectrometry Imaging Provides Spatiochemical Information on Potential Biocontrol Agents against Phytophthora capsici Infection in Tomato Plants

Biological control agents can offer an eco-friendly and more sustainable alternative to conventional chemical pesticides, providing protection against destructive pathogens, such as Phytophthora capsici, while reducing potential environmental harm associated with synthetic pesticide use in agricultural systems. This work evaluates the biocontrol effectiveness of Bacillus vallismortis, Bacillus amyloliquefaciens, Bacillus thuringiensis, and Bacillus subtilis, against the widespread plant pathogen Phytophthora capsici. Our studies showed that Bacillus thuringiensis and Bacillus subtilis promote plant growth and provide protection against Phytophthora capsici in both in vitro and in vivo greenhouse studies, while Bacillus vallismortis and Bacillus amyloliquefaciens were effective in vitro but not in vivo. Specifically, Bacillus thuringiensis was observed to both hinder the growth of Phytophthora capsici and enhance plant resilience to this pathogen, with B. thuringiensis-treated, pathogen-exposed plants displaying a 94.4% increase in root length and a 74.0% increase in shoot height compared to plants with only oomycete exposure. To probe the molecular interactions between the biocontrol agent and pathogen, a dual culture of Bacillus thuringiensis and Phytophthora capsici was analyzed in situ using a desorption electrospray ionization–mass spectrometry imaging (DESI-MSI) workflow. This approach interrogated the spatially oriented biochemical interactions that may serve as the molecular foundation for the effectiveness of these biological control agents in crop protection, identifying seven unique phenotypic regions within the dual culture. Herein, we demonstrate the benefits of biological control agent application in tomato cultivation and showcase the strengths of desorption electrospray ionization–mass spectrometry imaging when applied to the spatially resolved molecular characterization of agriculturally relevant microorganisms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Highly efficient synthesis of zeolite chabazite using cooperative hydration-mismatched inorganic structure-directing agents

Chabazite (CHA type) zeolite is notoriously difficult to synthesize in the absence of organic structure-directing agents owing to long synthesis times and/or impurity formation. The ability to tailor organic-free syntheses of zeolites is additionally challenging due to the lack of molecular level understanding of zeolite nucleation and growth pathways, particularly the role of inorganic cations. In this study, we reveal that zeolite CHA can be synthesized using six different combinations of inorganic cations, including the first reported seed- and organic-free synthesis without the presence of potassium. We show that lithium, when present in small quantities, is an effective accelerant of CHA crystallization; and that ion pairings can markedly reduce synthesis times and temperatures, while expanding the design space of zeolite CHA formation in comparison to conventional methods utilizing potassium as the sole structure-directing agent. Herein, we posit the effects of cation pairings on zeolite CHA crystallization are related to their hydrated ionic radii. We also emphasize the broader implications for considering the solvated structure and cooperative role of inorganic cations in zeolite synthesis within the context of the reported findings for chabazite.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Elemental zoning enhances mass transport in zeolite catalysts for methanol to hydrocarbons

Mass transport limitations in zeolite catalysts pose major hurdles for their optimal performance in diverse chemical reactions. Most approaches to reduce these restrictions focus on the synthesis of either hierarchical or nanosized zeolites. Here we demonstrate that the existence of a siliceous, catalytically inactive exterior rim on ZSM-5 particles dramatically reduces the diffusion limitations, which leads to an enhanced catalyst lifetime for the methanol-to-hydrocarbon reaction. In this study, our findings reveal that binary inorganic and organic structure-directing agents enable a one-pot synthesis of Si-zoned ZSM-5 catalysts with diffusion properties that are characteristic of particles with a much smaller size. Operando ultraviolet–visible light diffuse reflectance spectroscopy reveals a marked reduction in external coking among Si-zoned samples. Molecular dynamics simulations to assess the diffusion of methanol and benzene in siliceous pores and in those with Brønsted acids reveal substantially reduced transport limitations in zoned regions, consistent with the improved catalyst activity of Si-zoned zeolites relative to that of ZSM-5 with a homogeneous acid-site distribution.

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

A new approach of reduction of carbon dioxide emission and optimal use of carbon and hydrogen content for the desired syngas production from coal

We report this research is designed to make progress in overcoming the challenges through the development of a two-stage coal processing. Specifically, a two-stage process was used to maximize the use of the carbon in coal or increase the carbon monoxide yield or lower carbon dioxide and methane yields. Carbon dioxide-char gasification in the absence of water can generate carbon monoxide with near-zero methane, which is desired to produce high-carbon and low-hydrogen chemicals such as oxalic acid through catalytic carbon monoxide coupling and hydrolysis. The technology is applicable to any coal, although Power River Basin (PRB) coal is used as an example feedstock in this research Also, the sodium-iron catalyst can accelerate not only the reaction kinetics in both stages but also increase the hydrogen/carbon monoxide ratio in the syngas produced in the second stage. In other words, the catalyst is a multifunctional agent, which can not only intensify the overall coal process efficiency but also improve the qualities of the desired syngas products and reduce carbon dioxide emission. Thus, In the 1st stage, the catalysts can significantly reduce the CO 2 -char gasification by as high as 75.00%. In the 2nd stage, the H 2 /CO ratio of ideal syngas is ~2:1 with near-0 CH 4 generation and the CH4 production can be reduced as high as 61.29% for the CO 2 –H 2 O-Char coal gasification. The activation energy for the 2nd stage is reduced by as high as 35.43% than that of raw coal without use Na–Fe catalyst. The overall carbon footprint reduction for the study is reduced by 87.33% in the 1st stage and 96.77% compared to the direct coal combustion.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2021

Chlamydomonas as a model for reactive oxygen species signaling and thiol redox regulation in the green lineage

While the maintenance of redox balance is important for all organisms, the energy balance in the chloroplast is particularly tightly linked to the overall cellular redox status in photosynthetic organisms. Excess light can cause overreduction of the photosynthetic electron transport chain, which, when unchecked, results in the generation of reactive oxygen species (ROS) that can oxidize cellular components including nucleic acids, proteins, and lipids (Li et al., 2009). A photosynthetic cell possesses multiple layers of defense against oxidative stress, such as antioxidant enzymes (Foyer and Noctor, 2005) and alternative electron transfer pathways (Alric and Johnson, 2017). At the same time, ROS can function as important signals that mediate responses to biotic and abiotic stresses (Apel and Hirt, 2004). Reversibly oxidizable small molecules and proteins can serve as ROS sinks and signals and are re-reduced by multiple mechanisms. For example, the ascorbate–glutathione (GSH) cycle is central in controlling ROS levels and regenerating/reducing oxidized cellular redox agents (Figure 1A; reviewed by Foyer and Noctor, 2011). The functions of many proteins can be regulated by the redox state of cysteine residues, such as the formation or reduction of disulfides by thioredoxins (TRX) (Buchanan, 1991) and glutaredoxins (Michelet et al., 2013b; Figure 1, B and C).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Role of Cation Ordering on Device Performance in (Ag,Cu)InSe 2 Solar Cells with KF Post-Deposition Treatment

CuInSe 2 (CIS) has been proposed as an attractive bottom cell candidate in tandem solar cells. However, to justify the coupling with high-performance top cells (e.g., perovskites, GaAs), significant work on improving the efficiency is required. To this extent, several authors have demonstrated the benefits of alkali post-deposition treatments (PDT) to increase device open-circuit voltage (V oc ) in CIS and how Ag alloying - (Ag,Cu)InSe 2 (ACIS) - reduces defect density and enhances current collection in devices. Herein, we present a detailed study of the role that KF-PDT plays on CIS and ACIS absorber composition and structure, and propose an explanation for the decreased V oc observed when silver and potassium coexist in the system (ACIS + KF). Through a suite of synchrotron-based techniques, we investigate the nanoscale chemical distribution of the films and the formation of secondary phases. Through photoluminescence imaging, we observed a high degree of passivation with the addition of KF, and synchrotron-based X-ray diffraction confirmed the absence of a KInSe 2 surface layer usually considered to be a passivating agent. Raman spectroscopy and synchrotron X-ray fluorescence show the increased presence of Cu- and Se-poor clusters in ACIS + KF, which are correlated to significantly reduced X-ray beam-induced current (XBIC). An increase in the intensity of the E/B 2 stretching mode of CIS is attributed to cation ordering near the junction and is found to track inversely to bulk V oc measurements. The cation ordering is hypothesized to arise from the formation and redistribution of defects that normally occur near the surfaces of CIS as a consequence of its polar character. Here, these defects compensate each other, and the overall inhomogeneity of the charge distribution generates electrostatic potential fluctuations that greatly increase the saturation current and hence reduce the open-circuit voltage of the device.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Multi-agent voltage control in distribution systems using GAN-DRL-based approach

Active distribution grids can experience voltage fluctuations and violations due to the high penetration of variable distributed energy resources (DERs). These problems might occur because of the uncertain and variable generation natures of these resources, especially solar photovoltaic resources, during panel shadowing scenarios. Volt-VAR control (VVC) is an efficient method that controls the reactive power set-points of the inverters to regulate the voltage of distribution grids. Although several VVC approaches have been proposed recently, the performance of these approaches degrades significantly if behind-the-meter solar generation data are unobservable/missing. Therefore, it is necessary to impute missing/unobservable PV data accurately to be utilized in VVC approaches. Further, this paper proposes a model-free, data-driven, centrally trained, and decentrally executed multi-agent deep reinforcement learning-based VVC architecture to regulate the voltage of distribution networks. A generative adversarial network (GAN) is incorporated to impute the unobservable PV data accurately, which improves the performance of the proposed control architecture. The proposed multi-agent-soft-actor–critic algorithm (MASAC)-based VVC technique utilizes the actual PV dataset as well as the imputed dataset from the GAN framework to learn the optimal coordinated control policy for controlling the optimal reactive power set-points of PV inverters. The effectiveness of the proposed approach is analyzed on a modified IEEE 34-bus test case with added PV inverters. The results are compared and analyzed with a base case model with no VVC and VVC with a local droop control approach, genetic algorithm optimization, and a centralized soft actor–critic-based approach. Moreover, the performance of the proposed approach is compared with that of a multi-agent VVC framework without using the PV generation data and load information as the system state. The results illustrate that the proposed method with more state input improves the voltage profile and reduces the power loss of the network across various loading and PV generation scenarios.

14 SOLAR ENERGY↗
DOE OSTI2026

Smart Charging of Fleet and Personal Electric Vehicles through Joint Vehicle-to-Grid Optimization

As electric vehicle (EV) adoption accelerates, vehicle-to-grid (V2G) strategies offer advantages over unmanaged charging (V0G) by enhancing grid stability, reducing fleet operation costs, and supporting integration of variable generation resources. This research develops a day-ahead optimization framework linked with agent-based simulations to evaluate coordinated V2G participation by fleet and personal EVs under 5 energy-pricing settings in Austin, Texas. Three scenarios (V0G, fleet-only V2G, and joint-V2G) are examined, considering real-time price and grid profiles, health-damage costs, and operational constraints for both fleet and personal EVs. Results show how V2G scenarios shift fleet EV charging to mid-day while enabling strategic battery-discharge during evening peaks, mitigating grid stress and lowering EV energy costs. V2G delivers close to 80% energy-cost savings for a 2000-EV fleet in Austin on grid-stressed days, with 55% lower charging pollutant outputs. Joint-V2G amplifies system-level benefits by complementing fleet discharge, but smart-charging equipment costs can offset those benefits.

Electric vehicle↗
DOE OSTI2021

Next Generation Chemical Agent Detection Architecture [Poster]

Sandia National Labs (SNL)-designed, portable chemical warfare agent (CWA) detection systems consist of three-stages: collection, separation, and detection. We use microfabrication technologies to miniaturize these stages and to reduce the overall size, weight, power, and (potentially) cost of the final system. Our newest system consists of a multi-dimensional separation stage and an miniature ion mobility spectrometer (IMS) detector for unprecedented system sensitivity, selectivity, and depth of target list.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2023

Online transfer learning strategy for enhancing the scalability and deployment of deep reinforcement learning control in smart buildings

In recent years, advanced control strategies based on Deep Reinforcement Learning (DRL) proved to be effective in optimizing the management of integrated energy systems in buildings, reducing energy costs and improving indoor comfort conditions when compared to traditional reactive controllers. However, the scalability and implementation of DRL controllers are still limited since they require a considerable amount of time before converging to a near-optimal solution. This issue is currently addressed in literature through the offline pre-training of the DRL agent. However this solution results in two main critical issues: (1) the need to develop a building surrogate model to perform the training task, and (2) the need to perform a fine-tuning process over several training episodes to obtain a near-optimal control policy. In this context, this paper introduces an Online Transfer Learning (OTL) strategy that exploits two knowledge-sharing techniques, weight-initialization and imitation learning, to transfer a DRL control policy from a source office building to various target buildings in a simulation environment coupling EnergyPlus and Python. A DRL controller based on discrete Soft Actor–Critic (SAC) is trained on the source building to manage the operation of a cooling system consisting of a chiller and a thermal storage. Several target buildings are defined to benchmark the performance of the OTL strategy with that of a Rule-Based Controller (RBC) and two DRL-based control strategies, deployed in offline and online fashion. The strategy adopted for OTL emulates the real world implementation with a simulation process by implementing the transferred DRL agent for a single episode in the target buildings. Target buildings have the same geometrical features and are served by the same energy system as the source building, but differ in terms of weather conditions, electricity price schedules, occupancy patterns, and building envelope efficiency levels. The results show that the OTL strategy can reduce the cumulated sum of temperature violations on average by 50% and 80% respectively when compared to RBC and online DRL while enhancing the energy system operation with electricity cost savings ranging between 20% and 40%. Furthermore, the OTL agent performs slightly worse than the offline DRL controller but it does not require any modeling effort and can be implemented directly on target buildings emulating a real-world implementation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Ultrasonic Characterization of Ethylene Vinyl Acetate (EVA) Crosslinking for Quality Assurance and Lamination Process Control (US-Xlink)

Module makers strive to cut lamination processing times to enhance production throughput and reduce costs. If overdone, this might lead to poor EVA quality due to incomplete EVA crosslinking and a large concentration of potentially harmful reactants. Those deficiencies are frequently missed during production quality testing as initially their impact on power output is small. Additionally, the crosslinking agent is frequently inhomogeneously dispersed across the EVA foils such that local destructive characterization procedures such as differential scanning calorimetry (DSC), Soxhlet extraction, swelling methods, or mechanical tests provide only a limited amount of information. However, these defects and inhomogeneities can become considerably more important during field operation, dramatically reducing long-term power yield, and increasing LCOE. Examples of typical long-term module degradation modes relating to poor lamination process conditions include cell breakage, corrosion of the metallization, delamination, and local quality deficiencies. To provide reliable material characterization in a manufacturing setting, we devised a non-destructive technology that uses ultrasound to evaluate the quality of interface adhesion and the degree of crosslinking. As a calibration reference, DSC measurements were employed. Although the potential of ultrasonic approaches for this purpose has already been noted, those previous methods were generally limited to local qualitative measurements. Furthermore, variations in EVA thickness and temperature had a substantial impact on them. The solution we propose solves these limitations by employing ultrasonic absorption rather than relying solely on sound velocity data.

14 SOLAR ENERGY↗