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At least 523 records · Page 29

All sources NASA NTRS DOE OSTI

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 OSTI2026

Agentic workflow enables the recovery of critical materials from complex feedstocks via selective precipitation

We present a multi-agentic workflow for critical materials recovery that deploys a series of AI agents and automated instruments to recover critical materials from produced water and magnet leachates. This approach achieves selective precipitation from real-world feedstocks using simple chemicals, accelerating the development of efficient, adaptable, and scalable separations to a timeline of days, rather than months and years.

Ritchhart, Andrew J.↗

DOE OSTI2013

Enhanced heat transfer through filler-polymer interface by surface-coupling agent in heat-dissipation material: A non-equilibrium molecular dynamics study

Developing a composite material of polymers and micrometer-sized fillers with higher heat conductance is crucial to realize modular packaging of electronic components at higher densities. Enhancement mechanisms of the heat conductance of the polymer-filler interfaces by adding the surface-coupling agent in such a polymer composite material are investigated through the non-equilibrium molecular dynamics (MD) simulation. A simulation system is composed of α-alumina as the filler, bisphenol-A epoxy molecules as the polymers, and model molecules for the surface-coupling agent. The inter-atomic potential between the α-alumina and surface-coupling molecule, which is essential in the present MD simulation, is constructed to reproduce the calculated energies with the electronic density-functional theory. Through the non-equilibrium MD simulation runs, we find that the thermal resistance at the interface decreases significantly by increasing either number or lengths of the surface-coupling molecules and that the effective thermal conductivity of the system approaches to the theoretical value corresponding to zero thermal-resistance at the interface. Detailed analyses about the atomic configurations and local temperatures around the interface are performed to identify heat-transfer routes through the interface.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2016

Realization of consensus of multi-agent systems with stochastically mixed interactions

In this paper, we propose a new consensus model in which the interactions among agents stochastically switch between attraction and repulsion. Such a positive-and-negative mechanism is described by the white-noise-based coupling. Analytic criteria for the consensus and non-consensus in terms of the eigenvalues of the noise intensity matrix are derived, which provide a better understanding of the constructive roles of random interactions. Specifically, we discover a positive role of noise coupling that noise can accelerate the emergence of consensus. We find that the converging speed of the multi-agent network depends on the square of the second smallest eigenvalue of its graph Laplacian. The influence of network topologies on the consensus time is also investigated.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2017

Silicon nanoparticles as contrast agents in the methods of optical biomedical diagnostics

The efficiency of light scattering by nanoparticles formed using the method of picosecond laser ablation of silicon in water and by nanoparticles of mechanically grinded mesoporous silicon is compared. The ensembles of particles of both types possess the scattering coefficients sufficient to use them as contrast agents in optical coherence tomography (OCT), particularly in the range of wavelengths 700 – 1000 nm, where the absorption of both silicon and most biological and mimicking tissues is small. According to the Mie theory the main contribution to the scattering in this case is made by the particles having a relatively large size (150 – 300 nm). In the experiments on visualising the agar phantom surface by means of OCT, the contrast of the medium boundary, provided by nanoparticles amounted to 14 dB and 30 dB for the ablated particles and the porous silicon powder, respectively. The numerical simulation of OCT images of skin in the presence of nanoparticles, confirmed the efficiency of using them as a contrast agent. (nanoparticles)

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2025

Accelerating countermeasure candidate discovery for A-series chemical warfare agent exposure

The recent alleged use of A-series chemical warfare agents (CWAs) highlights the urgent need to better understand their inhibition of cholinesterase enzymes and the reported shortcomings of traditional oxime countermeasures. Here, using high-throughput (HT) mass spectrometry (MS) technologies, we characterized the largely unknown inhibition kinetics of A-series CWAs on human acetylcholinesterase (hAChE) and its reactivation by oximes, achieving label-free quantitation at rates of up to 7,000 reactions per hour. Our findings indicate i) A-series agents exhibit inhibitory potencies similar to traditional CWAs like sarin and VX, and ii) bipyridinium-based oximes can reactivate A-series-adducted hAChE in vitro, challenging prior reports on oxime efficacy. These results underscore the need for continued exploration of countermeasure candidates against A-series CWAs and demonstrate the potential of HT-MS for rapidly and safely characterizing emerging toxic chemicals.

acetylcholinesterase↗

DOE OSTI2023

Torrefaction of almond shell as a renewable reinforcing agent for plastics: techno-economic analyses and comparison to bioethanol process

Abstract In 2016, the US state of California alone produced nearly 3.5 billion kilograms of almonds, accounting for approximately 84% of the world’s almond production. This generated about 2.58 million metric tons (MTs) of almond residues. Almond shells are currently either burned to generate power or disposed of in landfill. Valorizing almond shells and hulls provides an opportunity to replace petroleum-derived products and divert organic material from landfill. Here we demonstrate a detailed techno-economic analysis (TEA) of an almond shell torrefaction process capable of utilizing the 520 000 MTs of almond shells produced annually in California. Our process also includes preprocessing the torrefied biomass to exploit it as a reinforcing agent for plastics. We further compared the revenue generated from the torrefied biomass and bioethanol derived from the same quantity of almond shells. We considered three different torrefaction facility scales to evaluate trade-offs between economies of scale at the facility and trucking costs to deliver almond shells. A facility that takes in 200 000 MT yr –1 of almond shells results in lower per-unit-output basis capital and operating cost relative to other smaller-scale torrefaction facilities, including 10 000 MT yr –1 and 50 000 MT yr –1 , considered for analysis in this study. The large-sale facility results in a minimum selling price (MSP) of the torrefied biomass of $311.4 MT –1 . An analogous TEA on converting almond residues into bioethanol is also investigated. The MSP of almond shell derived ethanol ($1.71 kg −1 ) is higher than that of corn ($0.48 kg −1 ) or cellulosic biomass ($0.88 kg −1 ) derived ethanol. Compared with the bioethanol route, the torrefied almond shells result in three times more revenue if utilized as a reinforcing agent for plastics.

Liu, Dupeng (ORCID:0000000269514064)↗

DOE OSTI2021

Does the Presence of the Biological Control Agent, Hypena opulenta (Lepidoptera: Erebidae) on Swallow-Worts Deter Monarch Oviposition?

Abstract Invasive black and pale swallow-worts (Vincetoxicum nigrum (L.) Moench, and Vincetoxicum rossicum Kelopow), which are related to milkweeds, can act as ecological traps for monarch butterflies (Danaus plexippus L. (Lepidoptera: Nymphalidae)) as they lay eggs on them that fail to develop. A recently approved biological control agent against swallow-worts, Hypena opulenta Christoph, occupies the same feeding guild on swallow-worts as monarch larvae and could be perceived as a competitor to monarchs. We tested how the presence of this defoliating moth on swallow-worts may influence monarch host selection. In a two-year field experiment, we placed pale swallow-wort plants that were either infested with H. opulenta or noninfested as well as common milkweed (Asclepias syriaca L.), into monarch habitats to assess oviposition rates. In the laboratory, monarchs were either given a choice or not between milkweeds and black swallow-worts with or without H. opulenta. While monarchs strongly preferred common milkweed in the field, up to 25% of the eggs we observed were laid on pale swallow-wort, without preference for swallow-wort with (10.7%) or without (14.3%) H. opulenta. In laboratory choice and no-choice tests, monarchs did not lay any eggs on black swallow-wort, likely because of the long-term laboratory rearing on common milkweeds. Our results confirm that pale swallow-wort may act as an oviposition sink to monarchs in Michigan as well. Since the biological control program is still in its infancy, the nature of interactions between monarchs and H. opulenta may change as the biocontrol agent becomes more widespread.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Remarkably High Internal Transcribed Spacer Haplotype Diversity of the Fungal Select Agent Coniothyrium glycines Discovered Throughout Its Range in Sub-Saharan Africa

Red leaf blotch of soybean, caused by the fungus Coniothyrium glycines, is a foliar disease characterized by blotching, necrosis, and defoliation that has only been reported from Africa. The species is listed as a Select Agent by the Federal Select Agent Program due to its potentially devastating impacts to soybean production should it spread to the United States. Despite its potential import, very few isolates are available for study. Herein, we obtained 96 new C. glycines isolates from six soybean-producing countries throughout sub-Saharan Africa. Along with 12 previously collected ones, we sequenced each at the internal transcribed spacer (ITS) region. Between all isolates, we identified a total of 28 single-nucleotide polymorphisms and 23 haplotypes. One hypothesis to explain the tremendous diversity uncovered at the ITS—which is generally conserved within a species—is that our current species concept of C. glycines is too broad and that there may be multiple species that cause red leaf blotch. Zambia contained the highest haplotype diversity, a significant fraction of which remains unsampled. Most haplotypes were specific to a single country, except for two, which were found in Zambia and either neighboring Mozambique or Zimbabwe. This geographic specificity indicates that the ITS region may be useful for identifying source populations or routes of transmission should this pathogen spread beyond Africa. The observed geographic partitioning of this pathogen is likely the result of millions of years of replication on little-studied native hosts, given that soybean has only been cultivated in Africa since the early 1900s.

Plant Sciences↗

DOE OSTI2026

Agentic artificial intelligence for multistage physics experiments at a large-scale user facility particle accelerator

We present a language-model-driven agentic artificial intelligence (AI) system to autonomously execute multistage physics experiments on a production synchrotron light source. Implemented at the Advanced Light Source particle accelerator, the system translates natural language user prompts into structured execution plans that combine archive data retrieval, control-system channel resolution, automated script generation, controlled machine interaction, and analysis. In a representative machine physics task, we show that preparation time was reduced by 2 orders of magnitude relative to manual scripting even for a system expert, while operator-standard safety constraints were strictly upheld. Core architectural features, plan-first orchestration, bounded tool access, and dynamic capability selection, enable transparent, auditable execution with fully reproducible artifacts. These results establish a blueprint for the safe integration of agentic AI into accelerator experiments and demanding machine physics studies, as well as routine operations, with direct portability across accelerators worldwide and, more broadly, to other large-scale scientific infrastructures.

Accelerator/storage ring control systems↗

DOE OSTI2025

Virtual Agents-Based Attack-Resilient Distributed Control for Islanded AC Microgrid

Due to its dependence on a communication network, distributed secondary control of microgrids is susceptible to denial-of-service (DoS) attacks in channel shutdown mode, which may negatively impact the network connectivity and thus deteriorate the coordination and power sharing among distributed generators (DGs). Honeypot is a common method for cyber deception by introducing fake targets. However, in the context of microgrid, the misleading information spread by honeypots will also impact the system performance. This paper proposes an attack-resilient distributed control for AC microgrids utilizing virtual agents (VAs) to counteract both DoS edge and node attacks. The VAs are designed to not impact the system’s steady state during normal operation but to share information among neighboring real agents and serve as dummy targets for DoS attacks. The control with VAs is implemented by a primal-dual gradient based distributed algorithm to efficiently obtain a practical solution for voltage/frequency regulation and power sharing. The simulation results on a 4-DG test system and a modified IEEE 34-bus system show that 1) VAs do not impact the normal functionality of the test system, and 2) deploying VAs can enhance the resilience of the microgrid control against DoS edge and node attacks.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Agent-Based Framework for Supporting Behind the Meter Transactive Power Electronic Systems

In this paper, the concept of a framework based on an agent-based interface for power stages in a power electronic system is presented. The presented concept or agent system is able to consider any number of different types of sources, types of converters, communication protocols, embedded decision making to support transactive, and hierarchy for large system integration. The concept is presented through several examples including the implementation on an actual physical system and demonstration of transactive type controls.

Starke, Michael↗

DOE OSTI2018

High performance Data Driven Agent-based Modeling Framework for Simulation of Commute Mode Choices in Metropolitan Area

Active transportation, human-powered transportation modes such as walking and bicycling, not only reduces the carbon footprint from the transportation sector but also promotes healthy living by offering opportunities for people to build physical activity into their daily routine. To encourage active transportation through urban planning and public campaigns, it is of significant importance to infer factors that substantially influence commuters in their transportation mode choice process. This necessitates a flexible and repeatable tool that can evaluate how a policy is perceived by individual commuters and convert their decisions into macro level understanding. This paper introduces one such effort that is specifically designed for studies of transportation mode choices in metropolitan areas. It provides results from a high-resolution data driven simulation based on high performance computing implementation of the agent-based model framework for home-to-work commute trips. The framework uses a graph-partition based technique that can leverage the interaction structure of agents within a geographic proximity and can boost the simulation execution time. Further, based on a flexible design, it can run ABM with different levels of computing resources-from multi core workstations to an HPC grid. The framework has been tested on the Titan Cray XK7 supercomputer of the Oak Ridge Leadership Computing Facility.

Park, Byung↗

DOE OSTI2021

Agent-Supervisor Coordination for Decentralized Event-Triggered Optimization

This letter proposes decentralized resource-aware coordination schemes for solving network optimization problems defined by objective functions that combine locally evaluable costs with network-wide coupling components. These methods are well suited for a group of supervised agents trying to solve an optimization problem under mild coordination requirements. Each agent has information on its local cost and coordinates with the network supervisor for information about the coupling term of the cost. The proposed approach is feedback-based and asynchronous by design, guarantees anytime feasibility, and ensures the asymptotic convergence of the network state to the desired optimizer. Numerical simulations on a power system example illustrate our results.

decentralized algorithms↗

DOE OSTI2019

Agent-Based System for Transactive Control of Smart Residential Neighborhoods

Buildings consume 74% of the total electricity produced in the United States. A significant portion of the building electric load includes heating ventilation and air-conditioning (HVAC) systems and water heating (WH) systems. Enabling flexibility in the operations can improve overall electric grid efficiency. This paper describes a multi-agent system for supporting integration, learning, optimization, and control of HVAC and WH in supporting a future smart grid. The architecture supports a transactive-based negotiation strategy between homeowners and a microgrid controller to adjust consumption behavior and reduce electricity costs. The framework is deployed in a neighborhood and preliminary testing is underway. The agent architecture design is discussed along with the preliminary optimization results from the demonstration site.

Starke, Michael↗

DOE OSTI2021

Transactive Electric Vehicle Agent: Design and Performance Evaluation

Transactive electric vehicle (TEV) agent enables the utilization of EVs’ flexible resources for the benefits of both utility and customer by active market participation. In this work, we propose a novel TEV agent optimization with a novel slider feature that models an individual customer’s willingness to participate in the transactive market. We characterize the customer comfort in EV’s context using a slider that provides flexibility to the customer to choose a trade-off between comfort and profit. Finally, the proposed optimization framework is used to investigate the comparative benefits of V2G technology compared to V1G.

day-ahead electricity market, electric vehicle, fl↗

DOE OSTI2023

Load Shedding for Voltage Regulation With Probabilistic Agent Compliance

With the increased observability and controllability of distribution systems, the share of behind-the-meter systems is trending upwards rapidly. As a consequence, the impact of human behaviors on system performance can no longer be ignored and should be reflected in the energy management system models. In this paper, we discuss the problem of distribution system voltage control by active power curtailment where the agent compliance of the load curtailment signal is probabilistic. We discuss the modeling of the optimal voltage control problem with probabilistic agent compliance as a chance-constrained optimization problem, its tractable safe approximation using convex restriction, and a scenario-based mixed-integer reformulation as well as the associated solution method based on augmented Lagrangian method. The numerical simulation on IEEE test system validates the effectiveness of the proposed approach in obtaining high-quality feasible load curtailment signal with low computational cost, which makes it a viable tool for real time decision making.

augmented Lagrangian method↗

DOE OSTI2023

Developing a Disaster-Ready Power Grid Agent Through Geophysically-Informed Fault Event Scenarios

Management of the nation’s power grid over the coming decades will need to factor multiple climate-driven threats to the power system that can be stressful or even detrimental to its operations. During disasters, grid operators suffer from cognitive overload where the electric grid is severely impacted by the weather, yet grid operators have limited awareness of these factors. Meanwhile, the electric grid is facing an explosion of data coming from a variety of sources which can enable the operator to evaluate the risks and develop mitigation strategies against hazardous events. In this work, we processed heterogeneous environmental and power grid data to learn and model grid behavior caused by extreme weather events. In this study, we focused on two weather-driven hazards, hurricanes and wildfires, which were analysed for the electric grid of Texas. We the used this data to train a Reinforcement Learning (RL) agent by analysing and predicting future behaviour of the grid during those hazard events. All these parts are incorporated in one framework to have a geophysically informed power simulators that can be used to train RL agents.

electic grid, reinforcement learning, climate adap↗