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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

EMIS Agent Simulation Model (Electricity Markets Investment Suite) [SWR-19-56]

The Electricity Markets Investment Suite Agent-based Simulation (EMIS-AS) model is an agent-based model developed at NREL for simulating annual investment and retirement decisions of heterogeneous investors in the electricity sector. EMIS-AS is designed to capture the evolution of the electricity generation portfolio resulting from the interactions of heterogeneous investors under different policy and market designs. EMIS-AS not only allows end-users to customize market products and rules, but also to capture investors' heterogeneous financing parameters, technology preferences, beliefs about the future (forecasts), ability to update those forecasts, and risk preferences under uncertainty.

Anwar, Mahammad Bashar↗
DOE OSTI2020

CE ABM (Circular Economy Agent-Based Model) [SWR 20-113]

The CE ABM framework aims to evaluate the techno-economic, market, and social conditions that maximize the value retention and minimize raw material inputs of different circular economy (CE) strategies. Several types of agents are defined in the model, such as asset owners, service providers, recyclers, and manufacturers and modeled CE strategies are design-for-circularity, products and components reuse, and recycling. In addition to techno-economic relations, the CE ABM framework accounts for behavioral factors such as social norms and trust. (Title previously known as "ABSiCE (Agent-Based Simulations of the Circular Economy)". Updated Oct 27, 2023)

Walzberg, Julien↗
DOE OSTI2013

Tricyclic GyrB/ParE (TriBE) Inhibitors. A new class of broad-spectrum dual-targeting antibacterial agents

Increasing resistance to every major class of antibiotics and a dearth of novel classes of antibacterial agents in development pipelines has created a dwindling reservoir of treatment options for serious bacterial infections. The bacterial type IIA topoisomerases, DNA gyrase and topoisomerase IV, are validated antibacterial drug targets with multiple prospective drug binding sites, including the catalytic site targeted by the fluoroquinolone antibiotics. Growing resistance to fluoroquinolones, frequently mediated by mutations in the drug-binding site, is increasingly limiting the utility of this antibiotic class, prompting the search for other inhibitor classes that target different sites on the topoisomerase complexes. The highly conserved ATP-binding subunits of DNA gyrase (GyrB) and topoisomerase IV (ParE) have long been recognized as excellent candidates for the development of dual-targeting antibacterial agents with broad-spectrum potential. However, to date, no natural product or small molecule inhibitors targeting these sites have succeeded in the clinic, and no inhibitors of these enzymes have yet been reported with broad-spectrum antibacterial activity encompassing the majority of Gram-negative pathogens. Using structure-based drug design (SBDD), we have created a novel dual-targeting pyrimidoindole inhibitor series with exquisite potency against GyrB and ParE enzymes from a broad range of clinically important pathogens. Inhibitors from this series demonstrate potent, broad-spectrum antibacterial activity against Gram-positive and Gram-negative pathogens of clinical importance, including fluoroquinolone resistant and multidrug resistant strains. Moreover, lead compounds have been discovered with clinical potential; they are well tolerated in animals, and efficacious in Gram-negative infection models.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Geophysical Monitoring with Seismic Metamaterial Contrast Agents

Acoustic impedance tube and forced-oscillation seismic core test measurements were conducted to examine the low-frequency properties of acoustic metamaterial contrast agents. Water-stable suspensions of metal-organic framework (MOF) nanoparticles increased sound transmission loss (100-1250 Hz) and seismic attenuation (10-70 Hz), and reduced Young’s modulus of nanofluid-saturated Berea Sandstone cores. Preliminary measurements were used to parameterize a seismic wave velocity model. These results indicate that injectable MOF nanofluid contrast agents have potential to enhance seismic delineation of subsurface fluids and structures.

Miller, Quin RS↗
DOE OSTI2011

Technical Report (Final): Development of Solid State Reagents for Preparing Radiolabeled Imaging Agents

The goal of this research was on the development of new, rapid, and efficient synthetic methods for incorporating short-lived radionuclides into agents of use in measuring dynamic processes. The initial project period (Year 1) was focused on the preparation of stable, solid state precursors that could be used to efficiently incorporate short-lived radioisotopes into small molecules of use in biological applications (environmental, plant, and animal). The investigation included development and evaluation of new methods for preparing carbon-carbon and carbon-halogen bonds for use in constructing the substrates to be radiolabeled. The second phase (Year 2) was focused on developing isotope incorporation techniques using the stable, boronated polymeric precursors. The final phase (Year 3), was focused on the preparation of specific radiolabeled agents and evaluation of their biodistribution using micro-PET and micro-SPECT. In addition, we began the development of a new series of polymeric borane reagents based on polyethylene glycol backbones.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Validating agent based models through virtual worlds.

As the US continues its vigilance against distributed, embedded threats, understanding the political and social structure of these groups becomes paramount for predicting and dis- rupting their attacks. Agent-based models (ABMs) serve as a powerful tool to study these groups. While the popularity of social network tools (e.g., Facebook, Twitter) has provided extensive communication data, there is a lack of ne-grained behavioral data with which to inform and validate existing ABMs. Virtual worlds, in particular massively multiplayer online games (MMOG), where large numbers of people interact within a complex environ- ment for long periods of time provide an alternative source of data. These environments provide a rich social environment where players engage in a variety of activities observed between real-world groups: collaborating and/or competing with other groups, conducting battles for scarce resources, and trading in a market economy. Strategies employed by player groups surprisingly re ect those seen in present-day con icts, where players use diplomacy or espionage as their means for accomplishing their goals. In this project, we propose to address the need for ne-grained behavioral data by acquiring and analyzing game data a commercial MMOG, referred to within this report as Game X. The goals of this research were: (1) devising toolsets for analyzing virtual world data to better inform the rules that govern a social ABM and (2) exploring how virtual worlds could serve as a source of data to validate ABMs established for analogous real-world phenomena. During this research, we studied certain patterns of group behavior to compliment social modeling e orts where a signi cant lack of detailed examples of observed phenomena exists. This report outlines our work examining group behaviors that underly what we have termed the Expression-To-Action (E2A) problem: determining the changes in social contact that lead individuals/groups to engage in a particular behavior. Results from our work indicate that virtual worlds have the potential for serving as a proxy in allocating and populating behaviors that would be used within further agent-based modeling studies.

Lakkaraju, Kiran↗
DOE OSTI2017

An Information Theoretic Framework and Self-organizing Agent- based Sensor Network Architecture for Power Plant Condition Monitoring

A central goal of the work was to enable both the extraction of all relevant information from sensor data, and the application of information gained from appropriate processing and fusion at the system level to operational control and decision-making at various levels of the control hierarchy through: 1. Exploiting the deep connection between information theory and the thermodynamic formalism, 2. Deployment using distributed intelligent agents with testing and validation in a hardware-in-the loop simulation environment. Enterprise architectures are the organizing logic for key business processes and IT infrastructure and, while the generality of current definitions provides sufficient flexibility, the current architecture frameworks do not inherently provide the appropriate structure. Of particular concern is that existing architecture frameworks often do not make a distinction between ``data'' and ``information.'' This work defines an enterprise architecture for health and condition monitoring of power plant equipment and further provides the appropriate foundation for addressing shortcomings in current architecture definition frameworks through the discovery of the information connectivity between the elements of a power generation plant. That is, to identify the correlative structure between available observations streams using informational measures. The principle focus here is on the implementation and testing of an emergent, agent-based, algorithm based on the foraging behavior of ants for eliciting this structure and on measures for characterizing differences between communication topologies. The elicitation algorithms are applied to data streams produced by a detailed numerical simulation of Alstom’s 1000 MW ultra-super-critical boiler and steam plant. The elicitation algorithm and topology characterization can be based on different informational metrics for detecting connectivity, e.g. mutual information and linear correlation.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2020

Argonne’s global critical materials agent-based model (GCMat)

Several studies have identified rare earths as critical materials. Although reasonably abundant in the Earth’s crust, rare earths typically occur in low concentrations of mined ores. Processes for recovering rare earth concentrates from these ores are complex and capital intensive. Further, lead times for deposit development, licensing, and construction are long, with reports of 10- 15 years. China is a major player in the rare earths supply chain, both in production capacity and technology innovation. In 2017, China supplied more than 80% of global rare earth oxide demand. Rare earth elements (REEs) have unique magnetic, catalytic, and phosphorescent properties that significantly improve performance of a wide range of technologies. These technologies span aerospace, energy, telecommunications, electronics, transportation, defense, and other diverse applications. Consequently, disruptions in rare earth supply can have a significant societal impact. Estimating that impact requires understanding of the dynamics across the supply chain, from rare earth oxide extraction to end use application. This report documents Argonne’s Global Critical Materials model (GCMat), first described by Riddle et al. 2015. GCMat provides capabilities to explore supply chain dynamics and uncertainty under scenarios of demand growth or shrinkage, technology adoption, supply disruptions, and trade policies and mitigation strategies of new supply sources, product substitution, consumer thrifting, and stockpiling. Supply chain participants from rare earth mining through final demand are modeled as interacting agents who make market decisions independently as time progresses. Since the version documented in Riddle et al. 2015, GCMat has been expanded to cover additional REEs, derived products and supply chains that use these REEs, and includes new agent behaviors and modeling capabilities. Section 2 provides a summary of the GCMat model design, including the structure of the model and key assumptions, section 3 summarizes methods used for model calibration and sensitivity analysis, and section 4 provides examples of model results.

36 MATERIALS SCIENCE↗
DOE OSTI2024

SEDONA and ERDE: Portable Detection of Chemical Agents by Low Magnetic Field Nuclear Magnetic Resonance [Slides]

Two spectrometer systems have been developed at LANL for hazardous and/or toxic chemical agent detection and forensic analysis: SpEctroscopic Detection Of Nerve Agents (SEDONA) is a portable bottle scanner; and Earth’s field Resonance Detection and Evaluation (ERDE) Devices are fieldable J-coupled Earth’s Field - NMR (EF-NMR) spectrometers.

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

Agent-Based, Bottom-Up Medium- and Heavy-duty Electric Vehicle Economics, Operation, Charging and Adoption (Research Performance Final Report)

This is the research performance final report for the project entitled: Agent-Based, Bottom-Up Medium- and Heavy-duty Electric Vehicle Economics, Operation, Charging and Adoption This project was able to achieve the DOE’s goals of developing new modeling tools to understand MDHD vehicle operation and adoption. The first modeling tool is a fleet-level techno-economic analysis model capable of estimating energy use and associated environmental and cost impacts for electrified and conventional vehicles of any MDHD vocation, using real-world cost and operations data, including approaches to optimizing schedules for charging and/or vehicle dispatch. The second modeling tool is a system-level, bottom-up, agent-based adoption model capable of generating geographically-resolved estimates of market projections for MDHD vehicles and charging infrastructure. These tools will be developed and published to serve dual purposes as analysis tools for researchers, and decision-support tools for decision makers within the MDHD system.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Accelerating lattice gauge theory studies with Agentic AI

Lattice gauge theory research, with its computationally intensive simulations and complex multi‑stage workflows, is well positioned to benefit from agentic AI systems. We demonstrate how such tools can support key components of lattice gauge theory research, including novel simulation code development using standard LQCD frameworks, HPC job orchestration, simulation data analysis, and expert‑guided tuning of algorithmic parameters such as Hasenbusch mass preconditioning and multigrid solvers. Our results show that agentic AI can reduce manual effort, improve productivity, and accelerate the research cycle while maintaining essential human oversight.

Ayyar, Venkitesh [Fermilab]↗
DOE OSTI2021

Shotgun Immunoproteomic Approach for the Discovery of Linear B-Cell Epitopes in Biothreat Agents Francisella tularensis and Burkholderia pseudomallei

Peptide-based subunit vaccines are coming to the forefront of current vaccine approaches, with safety and cost-effective production among their top advantages. Peptide vaccine formulations consist of multiple synthetic linear epitopes that together trigger desired immune responses that can result in robust immune memory. The advantages of linear compared to conformational epitopes are their simple structure, ease of synthesis, and ability to stimulate immune responses by means that do not require complex 3D conformation. Prediction of linear epitopes through use of computational tools is fast and cost-effective, but typically of low accuracy, necessitating extensive experimentation to verify results. On the other hand, identification of linear epitopes through experimental screening has been an inefficient process that requires thorough characterization of previously identified full-length protein antigens, or laborious techniques involving genetic manipulation of organisms. In this study, we apply a newly developed generalizable screening method that enables efficient identification of B-cell epitopes in the proteomes of pathogenic bacteria. As a test case, we used this method to identify epitopes in the proteome of Francisella tularensis (Ft), a Select Agent with a well-characterized immunoproteome. Our screen identified many peptides that map to known antigens, including verified and predicted outer membrane proteins and extracellular proteins, validating the utility of this approach. We then used the method to identify seroreactive peptides in the less characterized immunoproteome of Select Agent Burkholderia pseudomallei (Bp). This screen revealed known Bp antigens as well as proteins that have not been previously identified as antigens. Although B-cell epitope prediction tools Bepipred 2.0 and iBCE-EL classified many of our seroreactive peptides as epitopes, they did not score them significantly higher than the non-reactive tryptic peptides in our study, nor did they assign higher scores to seroreactive peptides from known Ft or Bp antigens, highlighting the need for experimental data instead of relying on computational epitope predictions alone. The present workflow is easily adaptable to detecting peptide targets relevant to the immune systems of other mammalian species, including humans (depending upon the availability of convalescent sera from patients), and could aid in accelerating the discovery of B-cell epitopes and development of vaccines to counter emerging biological threats.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Identification of Colletotrichum aenigma as the new causal agent of leaf blight disease on Aucuba japonica Thunb., and screenings of effective fungicides for its sustainable management

Aucuba japonica Thunb is an evergreen woody ornamental plant with significant economic and ecological values. It also produces aucubin, showing a variety of biological activities. It is widely planted in the southwest region of China, including karst landscape areas in Guizhou Province. In January 2022, a serious leaf blight disease was observed on the leaves of A. japonica in the outdoor gardens of Guizhou University, Guiyang, Guizhou, China. The causal agent was identified as Colletotrichum aenigma through amplification and sequencing of the internal transcribed spacer (ITS) region, translation of the chitin synthase ( CHS ) and actin ( ACT ) genes, and morphological characterizations. Koch’s postulates were confirmed by its pathogenicity on healthy leaves, including re-isolation and identification. To our knowledge, this is the first report of C. aenigma causing leaf blight on A. japonica worldwide. To identify pathogen characteristics that could be utilized for future disease management, the effects of temperature and light on mycelial growth, conidia production, and conidial germination, and the effects of humidity on conidial germination were studied. Optimal temperatures for mycelial growth of C. aenigma BY827 were 25–30°C, while 15°C and 35°C were favorable for conidia production. Concurrently, alternating 10-h light and 14-h dark, proved to be beneficial for mycelial growth and conidial germination. Additionally, conidial germination was enhanced at 90% humidity. In vitro screenings of ten chemical pesticides to assess their efficacy in suppressing C. aenigma representative strain BY827. Among them, difenoconazole showed the best inhibition rate, with an EC 50 (concentration for 50% of maximal effect) value of 0.0148 μg/ml. Subsequently, field experiment results showed that difenoconazole had the highest control efficiency on A. japonica leaf blight (the decreasing rate of disease incidence and decreasing rate of disease index were 44.60 and 47.75%, respectively). Interestingly, we discovered that C. aenigma BY827 may develop resistance to mancozeb, which is not reported yet among Colletotrichum spp. strains. In conclusion, our study provided new insights into the causal agent of A. japonica leaf blight, and the effective fungicides evaluated provided an important basis and potential resource for the sustainable control of A. japonica leaf blight caused by C. aenigma in the field.

Fan, Ruidong↗
DOE OSTI2020

PET Imaging Agents (FES, FFNP, and FDHT) for Estrogen, Androgen, and Progesterone Receptors to Improve Management of Breast and Prostate Cancers by Functional Imaging

Many breast and prostate cancers are driven by the action of steroid hormones on their cognate receptors in primary tumors and in metastases, and endocrine therapies that inhibit hormone production or block the action of these receptors provide clinical benefit to many but not all of these cancer patients. Because it is difficult to predict which individuals will be helped by endocrine therapies and which will not, positron emission tomography (PET) imaging of estrogen receptor (ER) and progesterone receptor (PgR) in breast cancer, and androgen receptor (AR) in prostate cancer can provide useful, often functional, information on the likelihood of endocrine therapy response in individual patients. This review covers our development of three PET imaging agents, 16α-[ 18 F]fluoroestradiol (FES) for ER, 21-[ 18 F]fluoro-furanyl-nor-progesterone (FFNP) for PgR, and 16β-[ 18 F]fluoro-5α-dihydrotestosterone (FDHT) for AR, and the evolution of their clinical use. For these agents, the pathway from concept through development tracks with an emerging understanding of critical performance criteria that is needed for successful PET imaging of these low-abundance receptor targets. Progress in the ongoing evaluation of what they can add to the clinical management of breast and prostate cancers reflects our increased understanding of these diseases and of optimal strategies for predicting the success of clinical endocrine therapies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Design and Gas Separation Performance of Imidazolium Poly(ILs) Containing Multivalent Imidazolium Fillers and Crosslinking Agents

This work introduces a series of vinyl-imidazolium-based polyelectrolyte composites, which were structurally modified via impregnation with multivalent imidazolium-benzene ionic liquids (ILs) or crosslinked with novel cationic crosslinkers which possess internal imidazolium cations and vinylimidazolium cations at the periphery. A set of eight [C4vim][Tf2N]-based membranes were prepared via UV-initiated free radical polymerization, including four composites containing di-, tri-, tetra-, and hexa-imidazolium benzene ILs and four crosslinked derivatives which utilized tri- and tetra- vinylimidazolium benzene crosslinking agents. Structural and functional characterizations were performed, and pure gas permeation data were collected to better understand the effects of “free” ILs dispersed in the polymeric matrix versus integrated ionic crosslinks on the transport behaviors of these thin films. These imidazolium PIL:IL composites exhibited moderately high CO2 permeabilities (~20–40 Barrer), a 4–7× increase relative to corresponding neat PIL, with excellent selectivities against N2 or CH4. The addition of imidazolium-benzene fillers with increased imidazolium content were shown to correspondingly enhance CO2 solubility (di- < tri- < tetra- < hexa-), with the [C4vim][Tf2N]: [Hexa(Im+)Benz ][Tf2N] composite showing the highest CO2 permeability (PCO2 = 38.4 Barrer), while maintaining modest selectivities (αCO2/CH4 = 20.2, αCO2/N2 = 23.6). Additionally, these metrics were similarly improved with the integration of more ionic content bonded to the polymeric matrix; increased PCO2 with increased wt% of the tri- and tetra-vinylimidazolium benzene crosslinking agent was observed. This study demonstrates the intriguing interactions and effects of ionic additives or crosslinkers within a PIL matrix, revealing the potential for the tuning of the properties and transport behaviors of ionic polymers using ionic liquid-inspired small molecules.

36 MATERIALS SCIENCE↗
NASA NTRS1975

Effects of multifunctional crosslinking agents on the thermomechanical properties of polyimide films

The potential of high temperature resistant polymers such as polyimides (PI) and polyphenylquinoxalines (PPQ) as matrix resins in fiber-reinforced composites has not been fully realized to date. One of the problems associated with these resins is that they exhibit creep, or thermoplastic yielding under load at temperatures approaching 316 C (600 F). The purpose of this investigation was to further reduce thermoplastic behavior of polyimide resins by substituting a controlled amount of the diamine monomer with crosslinking agents having a higher amine functionality. The knowledge gained from a study of the thermomechanical properties of the crosslinked resins would then be used in the fabrication of fiber-reinforced polyimide composites. This report describes the synthesis and characterization of three new polyfunctional amines. Polyimide films containing varying amounts of the cross-linking agents were prepared, and their properties compared with those of control samples prepared with difunctional amines. The effect of crosslink density on isothermal weight loss, polymer softening, and glass transition temperatures is discussed.

Delvigs, P.↗
NASA NTRS1976

Exploratory study on the effects of novel diamine curing agents and isocyanate precursors on the properties of new epoxy and urethane adhesives

The effects of novel aromatic diamine structures on the adhesive properties of epoxy and polyurethane adhesives were studied. Aromatic diamines based on benzophenone and diphenyl-methane isomers were evaluated as curing agents for epoxy resins and benzophenone and diphenyl-methane based diamine isomers were evaluated as curing agents for polyurethane adhesives. Polyurethane adhesives were prepared based on m, m prime-diisocyanato-diphenyl-methane and m, m prime-diisocyanato-benzophenone. The m, m prime-diisocayanato-diphenyl-methane based adhesive had properties comparable to state-of-the-art adhesives. The m, m prime-diisocyanato-benzophenone based adhesive was extremely reactive.

Glasgow, D. G.↗