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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 OSTI2024

Agent-based modeling to evaluate the effects of harvesting biomass and hunting on ring-necked pheasant ( Phasianus colchicus ) populations

As the US strives to divest from fossil fuels, dedicated energy crops have increased in popularity because of their potential to serve as a renewable source of transportation fuel and biomass-generated electricity. Whereas the impacts of crop agriculture on biodiversity have been well-documented, less is known about the potential impacts that growing bioenergy crops could have on wildlife. Here we look specifically at the ring-necked pheasant (Phasianus colchicus) and how pheasant populations may be influenced by growing and harvesting bioenergy crops. We explored effects of temporal harvest strategies at the field scale on biomass yield and pheasant population size. To investigate, we developed an agent-based model (ABM) that simulates ring-necked pheasants, tractors, hunters, and vegetation classes. One such vegetation class is land that is enrolled in a Conservation Reserve Program (CRP) plan specifically targeting pheasant conservation. Using this ABM, we assessed four different landscapes—corn-dominated, CRP-dominated, grassland-dominated, and mixed landscape—under strategies that varied the time of harvest. We also used ecological valuation to compare scenario outcomes from an economic perspective. We determined that biomass yield and pheasant population size were sensitive to harvesting times. Our scenarios totaled between ~$931,000 (minimum) and $3.8 million (maximum) over all landscapes, though on average harvesting in late spring generated the most value ($2.45 million) and harvesting in fall was a close second in terms of profitability ($2.39 million).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Agentic framework for programmatic crystal structure generation using a fine-tuned worker–supervisor large language model

Platinum group metals (PGMs) underpin many catalytic technologies but face severe supply constraints, motivating the search for alternative materials and computational methods to accelerate discovery. While atomistic simulation tools such as Pymatgen and ASE have streamlined structure manipulation, they require detailed inputs, limiting accessibility for experimentalists and slowing early-stage exploration. Here, in this study, we present an AI-driven agentic framework that orchestrates worker–supervisor large language models (LLMs). The worker translates natural-language prompts of varying abstraction into valid crystallographic structures using a compact LLM fine-tuned with low-rank adaptation on a curated text–code–CIF dataset, emphasizing energy-efficient training. Benchmarking against the baseline CodeGen-350M-mono model shows that fine-tuning reduces hallucination rates from 100% to as low as 5% and improves structural match accuracy to up to 82% for fully specified inputs. Accuracy declines with decreasing prompt detail but remains nontrivial even when only stoichiometry and space group are provided, underscoring the LLM’s capacity for crystallographic inference. The supervisor Claude LLM evaluates the outputs and triggers iterative refinement through the worker’s built-in structure manipulation capabilities (e.g., supercell scaling, strain, vacancy, and substitution operations). We further demonstrate use cases for technologically relevant catalysts, including IrO 2 , pyrochlore Pb 2 Ir 2 O 7 , Ni 2 FeO 4 , and Ni 3 Mo, where the framework generates physically consistent structures that can be refined via geometry optimization. This work introduces a low-energy, language-driven pathway for integrating human and machine intelligence in materials design, paving the way for AI-assisted synthesis planning and high-throughput screening of complex oxides.

AI agent↗
DOE OSTI2021

A multi-agent approach to distribution system fault section estimation in smart grid environment

We report that Multi-Agent Systems (MAS) are seen from different areas as one of the paramount trends for the next generation of power systems. Numerous published studies about MAS discuss its utilization in power distribution networks but none focuses on the prior step to restoration and self-healing that is fault section estimation. This paper aims to show how MAS can improve the utilities’ reliability indexes and consumer satisfaction by overcoming the multiple fault section estimation problem. In order to do this, the authors considered using MAS as a means of communication between smart meters. The purpose of smart meters usage is to employ devices that are already present in smart grids, mainly because of their reading and saving data capacity. The proposed method was tested on a radial feeder generated by the authors. The network was built on HYPERSIM, a software platform of OPAL-RT Technologies. The simulation results show that this MAS provides speed, efficiency, and automation for the process of fault section estimation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Assessment of two benzylation strategies for the analysis of nerve-agent derived ethyl- and pinacolyl methyl phosphonic acids in sandy loam soil by GC–MS

Despite their prohibition by the Chemical Weapons Convention, nerve agents (NAs) remain in use against military and civilian targets. Due to their high reactivity, NAs readily degrade to phosphonic acids, making them important markers in the inspection of areas of presumed NA use. In this work, we assess the use of benzylation to modify ethyl- and pinacolyl methylphosphonic acids, degradation products of VX and Soman respectively, for their efficient detection in a soil matrix at ~10 and ~1 μg/g using GC–MS. The soil matrix, Sandy Loam (SL), was chosen for its ubiquitous nature, complex composition with silica particles embedded in clay, and low organic content. In this study, we demonstrate that benzylation via benzyl bromide yields a LOD = 25.6 ng/mL for benzylated-EMPA and LOD = 30.1 ng/mL for benzylated-PMPA. This is superior to the use of p-methoxybenzyl trichloroacetimidate in providing stable phosphonic acid ester derivatives for analysis. A base-modified procedure for p-methoxybenzylation was explored in this study yielding a LOD = 29.1 ng/mL for p-methoxybenzylated-EMPA and LOD = 39.8 ng/mL for p-methoxybenzylated-PMPA. Both benzylation pathways (benzyl bromide and p-methoxybenzyl trichloroacetimidate) can be used to yield phosphonic acid derivatives that provide further confirmation of these Soman and VX degradation products in soil samples in investigative scenarios. The work herein represents the first application of benzylation methods for the analysis of these NA markers in the acidic, silicon-based SL soil.

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

Simulating policy interventions in the interfirm diffusion of low-carbon technologies: An agent-based evolutionary game model

Policy interventions are frequently used by authorities around the world to mitigate carbon emissions. However, economic systems are essentially complex adaptive systems, which often exhibit unexpected responses to exogenous interventions and leave intervenors in a dilemma, even if the interventions are elaborately designed. To explore the behaviors of the diffusion system regarding low-carbon technologies, this study builds an agent-based model (ABM) to simulate enterprises' reactions to multiple policy interventions aimed at spurring low-carbon technology diffusion. The simulated enterprises are in a complex network where they play evolutionary games with their neighbors, which enables the model to possess two critical features of economic systems: adaptiveness and equilibrium. The model reveals a dilemma of policy interventions: intuitively, carbon taxes, asymmetric penalties (only imposed on un-low-carbon enterprises) and subsidies can improve the diffusion, which is consistent with previous research; counter-intuitively, all these policies turn out to be inefficient or even harmful to low-carbon enterprises because of the diffusion system's high adaptiveness. Specifically, when carbon taxes and penalties increase, both the low-carbon and un-low-carbon enterprises end up with the equilibrium of equivalent but lower profits. In contrast, all the enterprises earn equivalent but more profits even though subsidies are only given to the low-carbon enterprises, which implies that the un-low-carbon enterprises (indirectly) grab a portion of the subsidies and accordingly weaken the incentive effect of subsidies. These system behaviors are summarized as "equalizing effect" because the system tends to equalize the impact of both positive and negative interventions among all enterprises even though the policy interventions are asymmetrically imposed on one type of the enterprises. The findings also indicate that policies implemented to enlarge green market sizes can help policymakers bypass the dilemma.

Agent-based modeling↗
DOE OSTI2020

Agent-based modeling of supply disruptions in the global rare earths market

Several independent assessments have identified rare earth elements (REEs) as critical materials, notably neodymium (Nd), praseodymium (Pr), and dysprosium (Dy) used in permanent magnets. Factors affecting their criticality include expected growth in demand arising from their unique performance-enhancing properties in consumer, energy, and military applications and the supply risk associated with China's dominance in their production. We demonstrate the use of Argonne's Global Critical Materials (GCMat) agent-based model to explore the possible consequences to REE market dynamics of different types of regional supply disruptions including a temporary loss of production, shutdown of capacity, and diversion of supply. Results suggest that supply disruptions may foster earlier and more REE mine starts outside of China, although some of these mines may not be able to sustain operations post disruption. Further, price and associated market responses such as production, capacity, and demand tended to extend beyond the disruption period. Such market impacts in the magnet supply chain could affect the costs and availability of a number of emerging clean energy technology applications such as electric vehicles and wind turbines. In the future, GCMat could be used to evaluate the effectiveness of mitigation strategies - including recycling, conservation, product substitution, and diversification of supplies - on reducing the severity of disruptions in REE markets.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Improved chemical synthesis, identification and evaluation of prospective centrally active oxime antidotes for the treatment of nerve agent exposure

In this study, an improved method for the synthesis of hydroxyiminoacetamide-based oximes, compounds rhat hold great promise as centrally-active nerve agent antidotes, is described. The method involves the coupling of hydroxyiminoacetic acid to various amines in the presence of HOBT or HATU and diisopropylcarbodiimide. The optimized protocol was found to work effectively for the coupling with amines to the activated form of the hydroxyiminoacetic acid with yields ranging between 84 and 90% for primary amines, 65–75% for α-substituted and cyclic amines, while producing decent 41–48% yields for the sterically hindered α,α-substituted amines, that can not be obtained using the previously established method.

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

Linking transportation agent-based model ($\mathrm{ABM}$) outputs with micro-urban social types ($\mathrm{MUSTs}$) via typology transfer for improved community relevance

The human relationship with transportation is shaped by social, economic, demographic, and urban form variables, or socio-spatial factors. The spatial dynamics of these are key to generating and interpreting outputs of transportation models that are most relevant for a community and the diverse mobility needs of its members. Here we present a typology transfer framework, grounded in socio-spatial dynamics shaping people's mobility, to take transportation-themed regional mobility model outcomes, in this case from two agent-based models (ABMs), and extrapolate them to other cities, with less time and resource intensity than new ABM development. The typology transfer process first identifies micro-urban social types (MUSTs) using socio-spatial factors, then defines city types based on spatial patterns of MUSTs to assess across which cities transfer results are likely to best hold. Lastly, a typology transfer multiplier matrix extrapolates a given variable, in our case the Mobility Energy Productivity (MEP) metric, to another city. The full process demonstration uses ABM results from Chicago (POLARIS model) and San Francisco (BEAM model), applying them to New York City. We discuss how MEP or other outputs can be appropriately estimated and used for integrated, human-centered mobility analysis. Key findings include that this MUST framework of user-defined dependent and independent variables allows tailoring ABM results and interpretations to specific community needs and data availability. Findings clarify that positive outcomes can be targeted towards user groups, based on sociospatial characteristics, using a typology approach, such as inclusive access to mobility choices, transportation affordability, and greater efficiency in resource use.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Laponite-Incorporated UiO-66-NH2-Polyethylene Oxide Composite Membranes for Protection against Chemical Warfare Agent Simulants

A strategy is developed to enhance the barrier protection of polyethylene oxide (PEO)-metal–organic framework (MOF) composite films against chemical warfare agent simulants. To achieve enhanced protection, an impermeable high-aspect-ratio filler in the form of Laponite RD (LRD) clay platelets was incorporated into a composite PEO film containing MOF UiO-66-NH 2 . The inclusion of the platelets aids in mitigating permeation of inert hydrocarbons (octane) and toxic chemicals (2-chloroethyl ethyl sulfide, 2-CEES) of dimensions/chemistry similar to prominent vesicant threats while still maintaining high water vapor transport rates (WVTR). By utilizing small-angle neutron scattering, small-angle X-ray scattering, and wide-angle X-ray scattering, the LRD platelet alignment of the films was determined, and the structure of the films was correlated with performance as a barrier material. Performance of the membranes against toxic chemical threats was assessed using permeation testing of octane and 2-CEES, a common simulant for the vesicant mustard gas, and breathability of the membranes was assessed using WVTR measurements. To assess their robustness, chemical exposure (in situ diffuse reflectance infrared Fourier transform spectroscopy) and mechanical (tensile strength) measurements were also performed. It was demonstrated that the barrier performance of the film upon inclusion of the LRD platelets exceeds that of other MOF-polymer composites found in the literature and that this approach establishes a new path for improving permselective materials for chemical protection applications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Paramagnetic Mn 8 Fe 4 -co-Polystyrene Nanobeads as a Potential T 1 –T 2 Multimodal Magnetic Resonance Imaging Contrast Agent with In Vivo Studies

In developing a cluster-nanocarrier design, as a magnetic resonance imaging contrast agent, we have investigated the enhanced relaxivity of a manganese and iron-oxo cluster grafted within a porous polystyrene nanobead with increased relaxivity due to a higher surface area. The synthesis of the cluster-nanocarrier for the cluster Mn 8 Fe 4 O 12 (O 2 CC 6 H 4 CH=CH 2 ) 16 (H 2 O) 4 , cross-linked with polystyrene (the nano-carrier), under miniemulsion conditions is described. By including a branched hydrophobe, iso-octane, the resulting nanobeads are porous and similar to 70 nm in diameter. The increased surface area of the nanobeads compared to nonporous nanobeads leads to an enhancement in relaxivity; r 1 increases from 3.8 to 5.2 ± 0.1 mM -1 s -1 , and r 2 increases from 11.9 to 50.1 ± 4.8 mM -1 s -1 , at 9.4 teslas, strengthening the potential for T 1 and T 2 imaging. Several metrics were used to assess stability, and the porosity produced no reduction in metal stability. Synchrotron X-ray fluorescence microscopy was used to demonstrate that the nanobeads remain intact in vivo . In depth, physicochemical characteristics were determined, including extensive pharmacokinetics, in vivo imaging, and systemic biodistribution analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Controlled Placement of Trivalent Heteroatoms in MFI Zeolite Frameworks Using Structure-Directing Agents

MFI zeolites contain distinct confining pore environments, either smaller (∼0.55 nm) channels or larger (∼0.70 nm) intersections. The substitution of trivalent heteroatoms generates Brønsted acid sites of varying acid strength, which, together with their location within different pore environments, dictates the stability of transition states via electrostatic (ion-pair) and van der Waals interactions. Here, we report that structure-directing agents (SDAs) that control Al 3+ substitutional patterns during MFI crystallization analogously position other trivalent heteroatoms (Ga 3+ , Fe 3+ , B 3+ ), altering the distribution of acid sites between channels and intersections, as probed by low-temperature (403 K) toluene methylation kinetics. Heteroatom-substituted MFI crystallized with tetrapropylammonium result in low selectivity toward p-xylene (<30%), while those crystallized using (co-)SDAs containing peripheral hydrogen-bonding groups (e.g., ethylenediamine) show high p-xylene selectivity (∼80%). These selectivities are consistent with DFT-calculated Gibbs free energy barriers for intersection-dominant and channel-dominant active site distributions, respectively. Transition states to form each xylene isomer are similar in size and charge; thus, their rate constants decrease with acid strength similarly, causing isomer selectivity to depend strongly on confinement but not on acid strength. These generalizable synthetic strategies enable independently controlling acid site strength and location in MFI zeolites and, in turn, catalytic rates and selectivities.

36 MATERIALS SCIENCE↗
DOE OSTI2023

High reactivity of mesoporous CeO 2 to dissociate chemical warfare agent sarin

We perform spectroscopic surface characterization on mesoporous ceria (CeO 2 ) under exposure of sarin gas, also known as GB. We find mesoporous CeO 2 displays extraordinary reactivity towards GB dissociation under high vacuum. The spectroscopic results combined with density functional theory (DFT) calculations suggest that the cleavage of the P–F and P–OR bonds are both possible pathways for GB to dissociate on the CeO 2 surfaces. The modeling reveals differences in dissociation pathways of GB on the crystallographic (111)- and (110)-surfaces of ceria. Here we also report some dissociation of GB on mesoporous CeO 2 under ambient conditions. The finding that mesoporous CeO 2 can degrade GB under mild conditions is encouraging and implies the strong potential of ceria-based materials to be applied in combating chemical warfare agents related to the GB series.

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

Non-solvents as physical blowing agents in printable silicone foams

Silicone foams were produced by dispersing an incompatible liquid phase (i.e. a non-solvent) into an uncured, liquid silicone. The formulation and processing parameters were varied to see the effect on porosity and pore morphology. Specifically, two fluorosilanes were added to stabilize the inclusion of fluorinated solvents as blowing agents. As the floruosilane content increased, the void content increased up to about 44 vol. % when the fluorosilane comprised 18 wt. % of the initial formulation. Fumed silica that was treated with a fluorinated silane was also used to try to stabilize the dispersed liquid. While the fumed silica content did not have a strong effect on the total void content, the morphology changed when silica content changed. Various fluorinated solvents with distinct chemical structures were used as the non-solvent and then removed after curing of the silicone. The interaction of the internal non-solvent phase and the silicone phase was expected to influence the porosity. These insights highlight how the manipulation of formulation and processing parameters, focusing on the inclusion of fluorosilanes and fluorinated solvents, contributes to the understanding of how incompatible liquid phases interact with silicone matrices to control porosity and pore morphology. Additionally, these interactions also influenced processability, leading to formulations that could be printed. Higher content of non-solvent inclusions could increase the yield stress and storage modulus of an uncured formulation, leading to the ability to tune intrastrand porosity while a 3D printed architecture could be modified to introduce porosity between the strands. Furthermore, in addition to fluorinated solvents, we also considered non-fluorinated solvents since these may be more industrially relevant in the future. Overall, this approach provides an alternative route to producing porous foams that can be 3D printed, which could be useful for applications like cushioning and protective gear.

physical blowing agent↗
DOE OSTI2025

Generative diffusion model surrogates for mechanistic agent-based biological models

Mechanistic, multicellular, agent-based models are commonly used to investigate tissue, organ, and organism-scale biology at single-cell resolution. The Cellular-Potts Model (CPM) is a powerful and popular framework for developing and interrogating these models. CPMs become computationally expensive at large space- and time- scales making application and investigation of developed models difficult. Surrogate models may allow for the accelerated evaluation of CPMs of complex biological systems. However, the stochastic nature of these models means each set of parameters may give rise to different model configurations, complicating surrogate model development. In this work, we leverage denoising diffusion probabilistic models (DDPMs) to train a generative AI surrogate of a CPM used to investigate in vitro vasculogenesis. We describe the use of an image classifier to learn the characteristics that define unique areas of a 2-dimensional parameter space. We then apply this classifier to aid in surrogate model selection and verification. Our CPM model surrogate generates model configurations 20,000 timesteps ahead of a reference configuration and demonstrates approximately a 22x reduction in computational time as compared to native code execution. Our work represents a step towards the implementation of DDPMs to develop digital twins of stochastic biological systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Agentic AI and the Cyber Arms Race

Here, in this article, we examine the implications for cyberwarfare and global politics as agentic artificial intelligence becomes more powerful and enables the broad proliferation of capabilities only available to the most well-resourced actors today.

Cybersecurity↗
DOE OSTI2021

Exploring Social Dynamics of Hard-Disk Drives Circularity with an Agent-Based Approach

By 2025, it is estimated that installed data storage in the U.S. will be 2.2 Zettabytes, generating about 50 million units of end-of-life hard-disk drives (HDDs) per year. The circular economy (CE) tackles waste issues by maximizing value retention in the economy, for instance, through reuse and recycling. However, the reuse of hard disk drives is hindered by the lack of trust organizations have toward other means of data removal than physically destroying HDDs. Here, an agent-based approach explores how organizations' decisions to adopt other data removal means affect HDDs' circularity. The model applies the theory of planned behavior to model the decisions of HDDs end-users. Results demonstrate that the attitude (which is affected by trust) of end-users toward data-wiping technologies acts as a barrier to reuse. Moreover, social pressure can play a significant role as organizations that adopt CE behaviors can set an example for others.

28 EE - Advanced Manufacturing Office (EE-5A)↗
DOE OSTI2023

A Review on Simulation Platforms for Agent-Based Modeling in Electrified Transportation

As the use of combustion engine vehicles plays a deciding role in global warming, we can observe a trend to replace them with electric vehicles (EV) driven by new environmentally conscious policies and increasing technological capabilities. With improvements in driving range and reduction in prices come new challenges that may hamper the progress towards complete battery driven transportation. A major challenge for the increasing EV adoption is the planning of extensions to existing infrastructure or the inclusion of new infrastructure components in the planning process. This demands increasingly complex planning tools that can simulate the interplay between different stakeholders in modern transportation scenarios such as EVs, charging stations, energy providers, and general transportation participants. Simulation platforms for agent-based modeling in transportation have been developed as effective interactive tools that allow planners to explore different trade-offs across different scenarios with the ability to simulate the impact of policy or infrastructure decisions on the different stakeholders in the simulation. This article surveys several of the major simulation platforms that include modern EV-based forms of transportation and allow the simulation of relevant infrastructure components alongside the well established transportation simulations. These tools allow researchers to analyze expected traffic flow, identify possible charging station locations based on area demand, predict electrical grid demand, and more. Here this survey intends to make it easier for researchers to identify and apply a simulation platform in the context of supporting the increasing electrification of the transportation sector, enabling more efficient simulation and planning capabilities in this domain.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Practical benzylation of N,N -substituted ethanolamines related to chemical warfare agents for analysis and detection by Electron Ionization Gas Chromatography-Mass Spectrometry

The benzylation of three, low-molecular weight N,N-disubstituted ethanolamines related to chemical warfare agents (CWAs) to furnish derivatives with improved Gas Chromatography-Mass Spectrometry (GC-MS) profiles is described. Due to their low molecular weight and polar nature, N,N-disubstituted ethanolamines are notoriously difficult to detect by routine GC-MS analyses during Organisation for the Prohibition of Chemical Weapons (OPCW) proficiency tests (PTs), particularly in scenarios when they are present at low levels (~1-10 ppm) amidst more abundant interferences. Our studies revealed that the optimal derivatization conditions involved the treatment of the ethanolamine with benzyl bromide in the presence of an inorganic base (e.g., Na 2 CO 3 ) in dichloromethane at 55 °C for 2 hours. This optimized set of conditions were then successfully applied to the derivatization of N,N-dimethylethanolamine, N,N-diethylethanolamine and N,N-diisopropylethanolamine present separately at 1 and 10 μg/mL concentrations in a glycerol-rich matrix sample featured in the 48 th OPCW PT. The benzylated derivatives of the three ethanolamines possessed retention times long enough to clear the massive glycerol-containing matrix interferences. In conclusion, the protocol herein is introduced as an alternative method for derivatization of these CWA and pharmaceutically important species and should find broad applicability in laboratories where their routine forensic analysis is carried out.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗