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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 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Collaborative: Fundamental studies of how water influences the synthesis and behavior of zeolite catalysts for reactions in the circular carbon economy (Final Technical Report)

This project established a computational framework to predict and interpret how synthesis conditions control active site location in MFI zeolites and how those site distributions influence catalytic reactivity. The Hibbitts Group led the theoretical effort, applying periodic DFT calculations to quantify (i) SDA–framework–heteroatom interactions during crystallization and (ii) the energetics and mechanisms of arene methylation reactions within distinct MFI environments.

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

Collaborative Approach to Identify Degradation Mechanisms and Validate Aging Protocols for a Diverse Set of DAC Materials (TCF Base Technology-Specific Final Report)

This work supports the mission of the U.S. Department of Energy to promote American energy leadership, technological innovation, and economic growth through the development of technologies for cost effective carbon capture. While capture technologies can provide carbon dioxide for enhanced oil recovery, many capture materials suffer from oxidative, hydrolytic and/or thermal degradation which leads to capacity loss and unwanted emissions such as ammonia. Short lifetimes increase operational costs and cost studies suffer from uncertainty because the true lifetimes of many capture materials are unknown. In this study, a suite of capture materials were studied to quantify their degradation, provide insight into the mechanisms that lead to their uptake loss and provide validated accelerated aging protocols for industry.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Collaborative Research: Enabling multi-scale studies of magnetic reconnection with interpretable data-driven models

The development of accurate reduced descriptions and improved closures for magnetic reconnection is an important and a long‐standing challenge in plasma physics. The four‐fluid approach, and associated closures, that were investigated have the potential to improve the accuracy of plasma fluid models, capturing physical effects which would otherwise require a kinetic description. If successful, this approach could have an important impact for the modeling of laboratory and space plasmas. The major goals of this project were to develop new machine learning (ML) tools based on sparse and symbolic regression techniques, and to extract interpretable and generalizable reduced models (e.g., in the form of partial differential equations - PDEs) from data generated by first principles plasma simulations. Preserving interpretability of such data‐driven models is key to addressing the long‐standing theoretical and numerical challenges. Prior proof‐of‐principle studies have demonstrated the enormous potential of this approach, by recovering the well‐established hierarchy of plasma equations (from Vlasov to MHD) from data produced by particle‐in‐cell (PIC) simulations. Our goal in this project was to extend and apply these new tools to construct better kinetic closures for magnetic reconnection; to derive better models of particle injection and acceleration by this fundamental plasma process; and to use this understanding to accelerate the development of multi‐scale plasma algorithms. While our immediate focus was on the problem of magnetic reconnection, the tools that were will developed are general and applicable to other areas of plasma physics, and more broadly to many‐body phenomena. We anticipate that the development of these multi‐scale models will have a significant impact across different areas of plasma science, from fusion to space and astrophysical plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

The first measurement of the muon anomalous magnetic moment from the Fermilab Muon g-2 collaboration

This paper will cover the physics and methods behind Fermilab’s Muon g-2 Experiment, along with the long-awaited results from Run-1. The experiment was undertaken to resolve the tension between the Standard Model and the previous measurement taken at Brookhaven National Laboratory. The measured value of the muon magnetic anomaly is a µ (FNAL) = 116592040(54) × 10 -11 . This result is in good agreement with Brookhaven’s previous measurement. The new world average, a µ (Exp) = 116592061(41) × 10 -11 , shows a difference from the theoretical value of the Standard Model (SM), a µ (SM) = 116591810(43) × 10 -11 , of 4.2 standard deviations, strongly hinting at physics beyond the Standard Model. The experiment requires the simultaneous measurement of the muon precession frequency, the magnetic field, and the muons’ distribution in the field. All three of these measurements will be discussed in context, along with the main systematic corrections and uncertainties.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Call for Participation: Collaborative Benchmarking of Functional-Structural Root Architecture Models. The Case of Root Water Uptake

Three-dimensional models of root growth, architecture and function are becoming important tools that aid the design of agricultural management schemes and the selection of beneficial root traits. However, while benchmarking is common in many disciplines that use numerical models, such as natural and engineering sciences, functional-structural root architecture models have never been systematically compared. The following reasons might induce disagreement between the simulation results of different models: different representation of root growth, sink term of root water and solute uptake and representation of the rhizosphere. Presently, the extent of discrepancies is unknown, and a framework for quantitatively comparing functional-structural root architecture models is required. We propose, in a first step, to define benchmarking scenarios that test individual components of complex models: root architecture, water flow in soil and water flow in roots. While the latter two will focus mainly on comparing numerical aspects, the root architectural models have to be compared at a conceptual level as they generally differ in process representation. Therefore, defining common inputs that allow recreating reference root systems in all models will be a key challenge. In a second step, benchmarking scenarios for the coupled problems are defined. We expect that the results of step 1 will enable us to better interpret differences found in step 2. This benchmarking will result in a better understanding of the different models and contribute toward improving them. Improved models will allow us to simulate various scenarios with greater confidence and avoid bugs, numerical errors or conceptual misunderstandings. This work will set a standard for future model development.

Plant Sciences↗
DOE OSTI2017

Editorial: Biological Engagement Programs: Reducing Threats and Strengthening Global Health Security Through Scientific Collaboration

It is often said about infectious diseases that a “threat anywhere is a threat everywhere,” and the recent outbreaks of Ebola in West Africa and Zika virus in South America have proven that pathogens know no borders. Not only are they transboundary, pathogens do not discriminate who they infect. In addition to the natural increase in emerging zoonotic infectious diseases worldwide due to changing environmental conditions and globalization, the use of infectious diseases as warfare agents is a threat in today’s world. Early detection remains one of the best ways to prevent small outbreaks becoming epidemics and pandemics. We find that an accurate diagnosis, detection, and reporting of diseases are important components of mitigating outbreaks, and biosurveillance remains the top tool in our toolbox. And while vaccines have been important for controlling more common infectious virus diseases, they are less feasible for less common diseases, emerging pathogens, and rapidly evolving microbes. Furthermore, due to globalization and increased travel, emigration, and migration, biosurveillance is critical throughout the world, not just in pockets of more developed regions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Neuroevolution Application to Collaborative and Heuristics-Based Connected and Autonomous Vehicle Cohort Simulation at Uncontrolled Intersection

Artificial intelligence is gaining tremendous attractiveness and showing great success in solving various problems, such as simplifying optimal control derivation. This work focuses on the application of Neuroevolution to the control of Connected and Autonomous Vehicle (CAV) cohorts operating at uncontrolled intersections. The proposed method implementation’s simplicity, thanks to the inclusion of heuristics and effective real-time performance are demonstrated. The resulting architecture achieves nearly ideal operating conditions in keeping the average speeds close to the speed limit. It achieves twice as high mean speed throughput as a controlled intersection, hence enabling lower travel time and mitigating energy inefficiencies from stop-and-go vehicle dynamics. Low deviation from the road speed limit is hence continuously sustained for cohorts of at most 50 m long. This limitation can be mitigated with additional lanes that the cohorts can split into. The concept also allows the testing and implementation of fast-turning lanes by simply replicating and reconnecting the control architecture at each new road crossing, enabling high scalability for complex road network analysis. The controller is also successfully validated within a high-fidelity vehicle dynamic environment, showing its potential for driverless vehicle control in addition to offering a new traffic control simulation model for future autonomous operation studies.

Jacquelin, Frederic (ORCID:0000000183154344)↗