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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 OSTI2023

HCOO - aq Degradation in Droplets by OH aq in an Atmospheric Pressure Glow Discharge

Plasmas in contact with liquids can degrade organic molecules in solution, as reactive oxygen and nitrogen species produced in the plasma solvate into the liquid. Immersing small droplets (tens of microns in diameter) in the plasma can more rapidly activate the liquid compared to treating a large volume of liquid with a smaller surface-to-volume ratio. The interactions between a radio frequency glow discharge sustained in He/H 2 O and a water droplet containing formate (HCOO - aq ) immersed in and flowing through the plasma were modeled using a 0-dimensional global plasma chemistry model to investigate these activation processes. HCOO - aq interacts with OH aq , produced from solvation of OH from the gas phase. HCOO - aq concentrations were benchmarked with previously reported experimental measurements. The diameter of the droplet, initial HCOO - aq concentration, and gas flow rate affect only the HCOO - aq concentration and OH aq density, leaving the OH density in the gas phase unaffected. Power deposition and gas mixture (e.g., percentage of H 2 O) change both the gas and liquid phase chemistry. A general trend was observed – during the first portion of droplet exposure to the plasma, OH aq primarily consumes HCOO - aq . However, O2 - aq , a byproduct of HCOO - aq consumption, consumes OH aq once O2 - aq reaches a critically large density. Using HCOO - aq as a surrogate for OH aq sensitive contaminants, combinations of residence time, droplet diameter, water vapor density, and power will determine the optimum remediation strategy.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Improving ICARUS track reconstruction algorithms

The ICARUS experiment is part of the Short-Baseline Neutrino program at Fermilab. Its primary objective is to explore the possible existence of sterile neutrinos in the O(1 eV) mass range and to clarify the anomalies observed in the Liquid Scintillator Neutrino Detector and MiniBooNE experiments. The ICARUS-T600 detector is a Liquid Argon Time Projection Chamber, capable of producing high-resolution 3D images and precise calorimetric measurements of ionizing particles. This technology allows for a detailed study of neutrino interactions across a broad energy range, from a few keV to several hundred GeV. The track reconstruction is achieved through a software framework that applies a series of pattern recognition algorithms, transforming raw detector signals into fully reconstructed event topologies. This process involves identifying interaction vertices, particle tracks, and electromagnetic showers within the TPC. However, in certain cases, these algorithms may mistakenly break a single particle track into several shorter segments, interpreting each as a distinct particle. Since track length is used to estimate the particle's energy, such fragmentation can result in an energy underestimation of several hundred MeV. Furthermore, when a track is split into multiple segments, the particle identification (which relies on analyzing the energy loss as a function of the residual range) may fail, potentially leading to the loss of the entire event. To mitigate this problem, we have developed a dedicated algorithm designed to identify and reconnect (“stitch”) the tracks that were erroneously divided into multiple segments.

Ricci, Alessandro Maria [Pisa U.; INFN, Pisa] (ORC↗
DOE OSTI2023

A review of transport models in charged porous electrodes

There is increased interest in many different processes based upon interactions between a charged solid surface and a liquid electrolyte. Energy storage in capacitive porous materials, ionic membranes, capacitive deionization (CDI) for water desalination, capacitive energy generation, removal of heavy ions from wastewater streams, and geophysical applications are some examples of these processes. Process development is driven by the production of porous materials with increasing surface area. Understanding of the physical phenomena occurring at the charged solid-electrolyte interface will significantly improve the design and development of more effective applied processes. The goal of this work is to critically review the current knowledge in the field. The focus is on concepts behind different models. We start by briefly presenting the classical electrical double layer (EDL) models in flat surfaces. Then, we discuss models for porous materials containing macro-, meso-, and micro-pores. Some of the current models for systems comprising two different pore sizes are also included. Finally, we discuss the concepts behind the most common models used for ionic transport and Faradaic processes in porous media. The latter models are used for simulation of electrosorption processes in porous media.

42 ENGINEERING↗
DOE OSTI2020

Elucidating the Role of Hydrogen Bond Donor and Acceptor on Solvation in Deep Eutectic Solvents Formed by Ammonium/Phosphonium Salts and Carboxylic Acids

Deep eutectic solvents (DESs) constitute a rapidly emerging class of sustainable liquids that have been widely studied and employed in chemical separations, catalysis, and electrochemistry. The unique physicochemical and solvation properties of DESs can be highly tailored by choosing the appropriate hydrogen bond acceptor (HBA) and hydrogen bond donor (HBD). Understanding the role of the HBA and HBD on the multiple solvation interactions in DESs is important to enable their judicious selection for particular applications. As such, this work constitutes the first study to exploit chromatography to measure solute–solvent interactions of DESs using a wide array of known probe molecules. The constituent components of 20 DESs, formed by ammonium and phosphonium-based salts and carboxylic acids, are systematically modulated to delineate the contribution of the HBA and HBD toward individual solvation properties. Solute–solvent interactions measured in this study are used to interpret and explain the performance of DESs in desulfurization of fuels and extraction of natural products. The results from this study can be used to predict and understand the performance of DESs in various chemical processes where solvation interactions heavily influence outcomes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

On the efficacy of post-build thermomechanical treatments to improve properties of Zirconium fabricated using ultrasonic additive manufacturing

Here, hot-isostatic pressing has been applied to Zirconium plate fabricated using the ultrasonic additive manufacturing (UAM) technique to enhance interfacial bond quality. Specimens heated to 800 C for 1 h at 100 MPa pressure showed grain growth across many prior foil-to-foil interfaces, thereby increasing foil adhesion. In addition to the material softening induced by a loss of Hall-Petch strengthening, premature failure of specimens loaded parallel to the build direction was observed. Premature specimen failure was attributed to the local delamination at prior foil-to-foil boundaries where grain growth was pinned by Ti impurities introduced during the UAM process via the interaction between a Ti-alloy buffer foil and the welded Zr-foils underneath. In addition, the presence of Ti along select foil interfaces resulted in the nucleation and growth of secondary (Zr,Ti)(Fe,Cr) laves phases during higher-temperature thermomechanical processing. Using a combination of micro-scale X-ray computed tomography, fractography, and in-situ digital image correlation, the effect of defects along prior foil-to-foil boundaries was revealed as delamination-assisted plasticity accelerated specimen failure in preferred tensile orientations. These findings underscore the importance of impurity control when optimizing weld quality of higher-strength material systems using ultrasonic welding.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Evolution of highly multimodal Rayleigh–Taylor instabilities

Rayleigh–Taylor (RT) instabilities are important fluid instabilities that arise in inertial confinement fusion (ICF) capsule implosions, and many other contexts. Multi-mode coupling is observed in experiments and plays a substantial role in material mix from RT instabilities. In this work, we study the evolution of highly multimodal perturbations (power law distribution) that approximate those found at manufactured material interfaces. We use simulations of over 2000 different perturbations in the LANL code xRAGE to identify distinct phases in the processes of bubble growth and bubble merger which can be visualized in a 2D phase portrait with clear regimes of mode growth and decay. Our results show that the dynamic evolution of the instability strongly depends on the mode of the perturbations and mode interactions. The merger process accelerates bubble growth. A non-Markovian region and a transition of the instability from: (1) initial exponential growth to (2) linear growth and to (3) quadratic growth and asymptotic behavior, are clearly captured in the phase space. We have developed a quantitative model of bubble growth that reproduces the dynamic behavior of ensembles of perturbations. Implications for ICF capsules designed for robustness against instabilities are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Exploring Multiscale Earth System and Human-Earth System Dynamics in the Puget Sound Region

With its mountain-to-coast hydroclimate, strong influence of Pacific Ocean weather systems and climate patterns, and unique land use history with strong rural-to-urban gradients, the Puget Sound region is a natural laboratory for studying a number of complex processes in, and interactions among, different Earth and human systems. A 1-year scoping study was initiated by the Earth and Environmental Systems Modeling program of the Department of Energy’s Office of Science Biological and Environmental Research. It was intended to elucidate and highlight the rich opportunities Puget Sound offers to advance our understanding of and ability to simulate Earth system changes and human-Earth system interactions. A literature review, multi-day community workshop, and external input were used to develop this scoping study report. The report first summarizes scientific understanding and knowledge gaps associated with major regional systems, including atmosphere and climate, the land surface, coastal and marine processes, and human systems, as well as how these systems are changing over time. It then highlights some of the most notable extreme events in the region, including heat waves, atmospheric rivers, droughts, and wildfires. Finally, key research opportunities for Earth and environmental systems modeling in, above, and around Puget Sound are highlighted.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

First Differential Measurement of the Single 𝜋 + Production Cross Section in Neutrino Neutral-Current Scattering

Since its first observation in the 1970s, neutrino-induced neutral-current single positive pion production (NC⁢1⁢𝜋 + ) has remained an elusive and poorly understood interaction channel. This process is a significant background in neutrino oscillation experiments and studying it further is critical for the physics program of next-generation accelerator-based neutrino oscillation experiments. In this Letter, we present the first double-differential cross-section measurement of NC⁢1⁢𝜋 + interactions using data from the ND280 detector of the T2K experiment collected in 𝜈-beam mode. The measured flux-averaged integrated cross section is 𝜎 = (6.07 ± 1.22) × 10 −41 cm 2 /nucleon. We compare the results on a hydrocarbon target to the predictions of several neutrino interaction generators and final-state-interaction models. While model predictions agree with the differential results, the data show a weak preference for a cross-section normalization approximately 30% higher than predicted by most models studied in this Letter.

Neutrino detection↗
DOE OSTI2022

Carbonate Minerals and Dissimilatory Iron-Reducing Organisms Trigger Synergistic Abiotic and Biotic Chain Reactions under Elevated CO 2 Concentration

Increasing CO 2 emission has resulted in pressing climate and environmental issues. While abiotic and biotic processes mediating the fate of CO 2 have been studied separately, their interactions and combined effects have been poorly understood. To explore this knowledge gap, an iron-reducing organism, Orenia metallireducens, was cultured under 18 conditions that systematically varied in headspace CO 2 concentrations, ferric oxide loading, and dolomite (CaMg(CO 3 ) 2 ) availability. The results showed that abiotic and biotic processes interactively mediate CO 2 acidification and sequestration through "chain reactions", with pH being the dominant variable. Specifically, dolomite alleviated CO 2 stress on microbial activity, possibly via pH control that transforms the inhibitory CO 2 to the more benign bicarbonate species. The microbial iron reduction further impacted pH via the competition between proton (H + ) consumption during iron reduction and H + generation from oxidization of the organic substrate. Under Fe(III)-rich conditions, microbial iron reduction increased pH, driving dissolved CO 2 to form bicarbonate. Spectroscopic and microscopic analyses showed enhanced formation of siderite (FeCO 3 ) under elevated CO 2 , supporting its incorporation into solids. In conclusion, the results of these CO 2 -microbe-mineral experiments provide insights into the synergistic abiotic and biotic processes that alleviate CO 2 acidification and favor its sequestration, which can be instructive for practical applications (e.g., acidification remediation, CO 2 sequestration, and modeling of carbon flux).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Progress toward double-differential cross-section measurements of single charged-pion production in charged current muon neutrino interactions on argon with SBND

Resonant neutrino–nucleus processes constitute a significant portion of neutrino interactions in the few-GeV energy region. Charged-current interactions with a muon and one single charged pion in the final state (CC1$\pi$) are primarily sensitive to resonant processes, while also receiving contributions from non-resonant processes and being strongly affected by nuclear effects and final-state interactions. A precise understanding of this channel is essential for improving neutrino interaction models and reducing systematic uncertainties in oscillation measurements. The Short-Baseline Near Detector (SBND) at Fermilab has collected the largest neutrino–argon dataset to date, providing an excellent opportunity to study CC1$\pi$ interactions on argon. This analysis aims to improve existing single-differential cross-section measurements by reporting results in a variety of kinematic variables and to perform the first double-differential CC1$\pi$ cross-section measurement on argon, using novel techniques for pion energy reconstruction.

Pelegrina-Gutiérrez, Luis [Granada U.] (ORCID:0000↗
DOE OSTI2024

Operando XPS for Plasma Process Monitoring: A Case Study on the Hydrogenation of Copper Oxide Confined under h-BN

Here, we demonstrate that ambient pressure x-ray photoelectron spectroscopy (APXPS) can be used for in situ studies of dynamic changes in surface chemistry in a plasma environment. This opens a new and vast application space for XPS and greatly complements modern spectroscopy techniques to probe plasma-solid/liquid interactions relevant to process monitoring in the semiconductor industry, bio-medical plasma applications and plasma remediation technologies. Hexagonal boron nitride (h-BN) grown on Cu was used in this study as a well-defined model system for plasma process monitoring and because of its unique chemical, optical and electrical properties that make it a prospective material for advanced electronics. To better understand the stability and surface chemistry of h-BN during plasma assisted processing, we track in real time the plasma-induced chemical state changes of B, N and the underlying Cu substrate using APXPS equipped with an AC discharge plasma source operating at 13 Pa. Residual gas analysis (RGA) mass-spectra were concurrently collected during plasma-XPS to track reaction products formed during plasma exposure. A clear reduction of Cu x O is seen, while an h-BN layer remains intact, suggesting hydrogen radical (H • ) species can attack the exposed and h-BN covered Cu oxide patches and partially reduce the underlying substrate without significantly damaging the overlaying h-BN, which is of practical importance for development of h-BN encapsulated devices and interfaces. In addition to demonstration of plasma-XPS capabilities we discuss the observed challenges (e.g., parasitic plasma-chamber walls reactions and charging effects) and propose potential solutions.

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

A Novel use of Direct Simulation Monte-Carlo to Model Dynamics of COVID-19 Pandemic Spread

In this report, we evaluate a novel method for modeling the spread of COVID-19 pandemic. In this new approach we leverage methods and algorithms developed for fully-kinetic plasma physics simulations using Particle-In-Cell (PIC) Direct Simulation Monte-Carlo (DSMC) models. This approach then leverages Sandia-unique simulation capabilities, and High-Performance Computer (HPC) resources and expertise in particle-particle interactions using stochastic processes. Our hypothesis is that this approach would provide a more efficient platform with assumptions based on physical data that would then enable the user to assess the impact of mitigation strategies and forecast different phases of infection. This work addresses key scientific questions related to the assumptions this new approach must make to model the interactions of people using algorithms typically used for modeling particle interactions in physics codes (kinetic plasma, gas dynamics). The model developed uses rational/physical inputs while also providing critical insight; the results could serve as inputs to, or alternatives for, existing models. The model work presented was developed over a four-week time frame, thus far showing promising results and many ways in which this model/approach could be improved. This work is aimed at providing a proof-of-concept for this new pandemic modeling approach, which could have an immediate impact on the COVID-19 pandemic modeling, while laying a basis to model future pandemic scenarios in a manner that is timely and efficient. Additionally, this new approach provides new visualization tools to help epidemiologists comprehend and articulate the spread of this and other pandemics as well as a more general tool to determine key parameters needed in order to better predict pandemic modeling in the future. In the report we describe our model for pandemic modeling, apply this model to COVID-19 data for New York City (NYC), assess model sensitivities to different inputs and parameters and , finally, propagate the model forward under different conditions to assess the effects of mitigation and associated timing. Finally, our approach will help understand the role of asymptomatic cases, and could be extended to elucidate the role of recovered individuals in the second round of the infection, which is currently being ignored.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Accurate assessment of land–atmosphere coupling in climate models requires high-frequency data output

Land–atmosphere (L–A) interactions are important for understanding convective processes, climate feedbacks, the development and perpetuation of droughts, heatwaves, pluvials, and other land-centered climate anomalies. Local L–A coupling (LoCo) metrics capture relevant L–A processes, highlighting the impact of soil and vegetation states on surface flux partitioning and the impact of surface fluxes on boundary layer (BL) growth and development and the entrainment of air above the BL. A primary goal of the Climate Process Team in the Coupling Land and Atmospheric Subgrid Parameterizations (CLASP) project is parameterizing and characterizing the impact of subgrid heterogeneity in global and regional Earth system models (ESMs) to improve the connection between land and atmospheric states and processes. A critical step in achieving that aim is the incorporation of L–A metrics, especially LoCo metrics, into climate model diagnostic process streams. However, because land–atmosphere interactions span timescales of minutes (e.g., turbulent fluxes), hours (e.g., BL growth and decay), days (e.g., soil moisture memory), and seasons (e.g., variability in behavioral regimes between soil moisture and latent heat flux), with multiple processes of interest happening in different geographic regions at different times of year, there is not a single metric that captures all the modes, means, and methods of interaction between the land and the atmosphere. And while monthly means of most of the LoCo-relevant variables are routinely saved from ESM simulations, data storage constraints typically preclude routine archival of the hourly data that would enable the calculation of all LoCo metrics. Here, we outline a reasonable data request that would allow for adequate characterization of sub-daily coupling processes between the land and the atmosphere, preserving enough sub-daily output to describe, analyze, and better understand L–A coupling in modern climate models. A secondary request involves embedding calculations within the models to determine mean properties in and above the BL to further improve characterization of model behavior. Higher-frequency model output will (i) allow for more direct comparison with observational field campaigns on process-relevant timescales, (ii) enable demonstration of inter-model spread in L–A coupling processes, and (iii) aid in targeted identification of sources of deficiencies and opportunities for improvement of the models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

On the Formalization of Development and Assessment Process for Digital Twins in the Nearly Autonomous Management and Control System

In recent years, the autonomous control system has been encouraged in advanced reactors for restoring economic viability, simplifying the operation and maintenance, and enabling remote-site power generations [1]. Since the reactor is expected to be operated for a long period of time with a limited number of individuals onsite, it is recommended that the autonomous control system should have access to very realistic models of the state of processes in the whole lifecycle, together with these process behaviors in interaction with their environment in the real world. As a result, digital twin (DT) technology is suggested in autonomous control systems. DT is defined as a digital representation of a physical object or system, which contains a record for the histories of loads, operation and maintenance status, predictions for the near-term transient of important state variables, and decision-making process [2]. Since machine learning (ML) can recognize patterns within a complex system in real-time applications, it has been used to build DTs in the autonomous control systems for advanced reactors. Meanwhile, due to the rareness of operation data in accident scenarios, the development and assessment of DTs is expected to be mainly driven by simulations. Although the capability and feasibility of ML-based DTs are recognized in improving the safety and efficiency of reactor control, a major concern from the regulatory commission and the nuclear industry is whether the information from a DT is developed and assessed in accordance with expectation and requirements by the target decision. Such concerns not only affect the acceptance criteria for DTs, but also values that can be extracted from DTs and autonomous control system during operations. Inspired by the success of formal methods in improving the reliability and robustness of computer programming and software development, it is suggested that the development and assessment process (DAP) for both separate DTs and integral control system should be formalized in a transparent, consistent, and improvable manner. In this study, a digital-twin development and assessment process (DT-DAP) is proposed by adapting the evaluation model development and assessment process (EMDAP) [3] to requirements by the autonomous control system, ML algorithms, and DT technology. To demonstrate the framework, a baseline nearly autonomous management and control (NAMAC) system with ML-based DTs for diagnosis and prognosis is developed and assessed based on the framework. It is found that with selected testing methods and techniques, the DT-DAP can help identify errors in DTs and NAMAC which would otherwise be left unverified. Meanwhile, it is found that the DT-DAP can improve the DTs and NAMAC by continuously learning and iterating through different elements.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Characterization of Organosulfates and Organonitrates in Vertically Resolved Aerosols over the Southern Great Plains Field Campaign Report

Aerosol is the largest individual source of uncertainty in assessing the Earth’s radiative balance due to poorly understood aerosol processes and aerosol-cloud interactions. Thus, to constrain aerosol’s climate impacts, it is critical to understand aerosol compositions at high elevations. Organic material accounts for about 20-80% of total aerosol mass in the atmosphere and is known to play a key role in aerosol processes and cloud formation. In prior research, characterization of aerosol molecular composition has been mostly carried out at ground level. In these ground-level measurements, total speciated organosulfates and organonitrates may contribute significantly to organic aerosol mass on the order of 10-40%, most of which are from abundant biogenic volatile organic compounds such as isoprene and monoterpenes. Organosulfates and organonitrates have also been shown to be present in substantial amounts in cloud water, suggesting that they can be transported and/or directly formed at high elevations. On the other hand, the less common and more expensive aircraft studies have performed high-altitude measurements, but were often limited in the number of different altitudes sampled and in sample collection under consistent conditions. Therefore, the vertical distributions of key aerosol components such as organosulfates and organonitrates are not well understood and have not been extensively studied. Nevertheless, it is important to understand how organosulfates and organonitrates in aerosols are distributed, transformed, participate in aqueous-phase processes, and interact with high-altitude clouds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Dipole-Phonon Quantum Logic with Trapped Polar Molecular Ions

The interaction between the electric dipole moment of a trapped molecular ion and the phonon modes of the confined Coulomb crystal couples the orientation of the molecule to its motion. We consider the practical feasibility of harnessing this interaction to initialize, process, and read out quantum information encoded in molecular ion qubits without ever optically illuminating the molecules. We present two schemes wherein a molecular ion can be entangled with a cotrapped atomic ion qubit, providing, among other things, a means for molecular state preparation and measurement. Here, we also show that virtual phonon exchange can significantly boost the range of the intermolecular dipole-dipole interaction, allowing strong coupling between widely separated molecular ion qubits.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Transforming Cyber Education thru Open to All Accessible Pathways

Boise State University’s (BSU) Cyber Operations and Resilience CORe program was intentionally designed so that any student, especially non-traditional and non-technical students, with an interest in cybersecurity could have an education and training pathway to enter the cyber workforce. The CORe curriculum focuses on teaching students how to design, apply, and improve cybersecurity through the interaction of people, processes, and technology. CORe is a stackable curriculum with elective credit hours and options for various academic and industry certificates and certifications that enable students to customize their unique career pathway. The CORe program guides students to think about the system being managed, the risks presented, and the dynamic intersection of system elements when considering how to incorporate resilience frameworks in achieving a resilient system. By developing systems thinking, the students gain an understanding of the interdependencies interacting with the operational system. Further, the CORe program encourages students to integrate cybersecurity knowledge with models and frameworks found in other academic disciplines through a unifying systems approach. CORe is designed around the realities of today’s broad cyber landscape: that breaches will occur in any system over time and proactive design of resilience into systems to detect, respond, and recover in a timely and orderly manner is critical. Students are taught to think holistically about cybersecurity focusing on all system elements. CORe is not a traditional cybersecurity degree. CORe is distinguished by the non-traditional engineering, computer science approach to cybersecurity education with the singular focus on infusing resilience operations and transdisciplinary systems thinking principles throughout the curriculum.

99 GENERAL AND MISCELLANEOUS↗