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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 991 records · Page 55

Imaging Strain-Localized Single-Photon Emitters in Layered GaSe below the Diffraction Limit

Nanoscale strain control of exciton funneling is an increasingly critical tool for the scalable production of single photon emitters (SPEs) in two-dimensional materials. However, conventional far-field optical microscopies remain constrained in spatial resolution by the diffraction limit and thus can provide only a limited description of nanoscale strain localization of SPEs. Here, we quantify the effects of nanoscale heterogeneous strain on the energy and brightness of GaSe SPEs on nanopillars with correlative cathodoluminescence, photoluminescence, and atomic force microscopy, supported by density functional theory simulations. We report the strain-localized SPEs have a broad range of emission wavelengths from 620 to 900 nm. We reveal substantial strain-controlled SPE wavelength tunability over a ~100 nm spectral range and 2 orders of magnitude enhancement in the SPE brightness at the pillar center due to Type-I exciton funneling. In addition, we show that radiative biexciton cascade processes contribute to observed CL photon superbunching. Also, the GaSe SPEs show excellent stability, where their properties remain unchanged after electron beam exposure. Importantly, we anticipate that this comprehensive study on the nanoscale strain control of two-dimensional SPEs will provide key insights to guide the development of truly deterministic quantum photonics.

2D materials↗

Tracking Active Phase Behavior on Boron Nitride during the Oxidative Dehydrogenation of Propane Using Operando X-ray Raman Spectroscopy

Hexagonal boron nitride (hBN) is a highly selective catalyst for the oxidative dehydrogenation of propane (ODHP) to propylene. Using a variety of ex situ characterization techniques, the activity of the catalyst has been attributed to the formation of an amorphous boron oxyhydroxide surface layer. The ODHP reaction mechanism proceeds via a combination of surface mediated and gas phase propagated radical reactions with the relative importance of both depending on the surface-to-void-volume ratio. Here we demonstrate the unique capability of operando X-ray Raman spectroscopy (XRS) to investigate the oxyfunctionalization of the catalyst under reaction conditions (1 mm outer diameter reactor, 500 to 550 °C, P = 30 kPa C 3 H 8 , 15 kPa O 2 , 56 kPa He). We probe the effect of a water cofeed on the surface of the activated catalyst and find that water removes boron oxyhydroxide from the surface, resulting in a lower reaction rate when the surface reaction dominates and an enhanced reaction rate when the gas phase contribution dominates. Computational description of the surface transformations at an atomic-level combined with high precision XRS spectra simulations with the OCEAN code rationalize the experimental observations. Finally, this work establishes XRS as a powerful technique for the investigation of light element-containing catalysts under working conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Dynamic mode decomposition of nonequilibrium electron-phonon dynamics: accelerating the first-principles real-time Boltzmann equation

Abstract Nonequilibrium dynamics governed by electron–phonon ( e -ph) interactions plays a key role in electronic devices and spectroscopies and is central to understanding electronic excitations in materials. The real-time Boltzmann transport equation (rt-BTE) with collision processes computed from first principles can describe the coupled dynamics of electrons and atomic vibrations (phonons). Yet, a bottleneck of these simulations is the calculation of e –ph scattering integrals on dense momentum grids at each time step. Here we show a data-driven approach based on dynamic mode decomposition (DMD) that can accelerate the time propagation of the rt-BTE and identify dominant electronic processes. We apply this approach to two case studies, high-field charge transport and ultrafast excited electron relaxation. In both cases, simulating only a short time window of ~10% of the dynamics suffices to predict the dynamics from initial excitation to steady state using DMD extrapolation. Analysis of the momentum-space modes extracted from DMD sheds light on the microscopic mechanisms governing electron relaxation to a steady state or equilibrium. The combination of accuracy and efficiency makes our DMD-based method a valuable tool for investigating ultrafast dynamics in a wide range of materials.

36 MATERIALS SCIENCE↗

Bayesian blacksmithing: discovering thermomechanical properties and deformation mechanisms in high-entropy refractory alloys

Finding alloys with specific design properties is challenging due to the large number of possible compositions and the complex interactions between elements. This study introduces a multi-objective Bayesian optimization approach guiding molecular dynamics simulations for discovering high-performance refractory alloys with both targeted intrinsic static thermomechanical properties and also deformation mechanisms occurring during dynamic loading. The objective functions are aiming for excellent thermomechanical stability via a high bulk modulus, a low thermal expansion, a high heat capacity, and for a resilient deformation mechanism maximizing the retention of the BCC phase after shock loading. Contrasting two optimization procedures, we show that the Pareto-optimal solutions are confined to a small performance space when the property objectives display a cooperative relationship. Conversely, the Pareto front is much broader in the performance space when these properties have antagonistic relationships. Density functional theory simulations validate these findings and unveil underlying atomic-bond changes driving property improvements.

36 MATERIALS SCIENCE↗

Development of interatomic potential for Al–Tb alloys using a deep neural network learning method

An interatomic potential for the Al–Tb alloy around the composition of Al 90 Tb 10 is developed using the deep neural network (DNN) learning method. The atomic configurations and the corresponding total potential energies and forces on each atom obtained from ab initio molecular dynamics (AIMD) simulations are collected to train a DNN model to construct the interatomic potential for the Al–Tb alloy. Here we show that the obtained DNN model can well reproduce the energies and forces calculated by AIMD simulations. Molecular dynamics (MD) simulations using the DNN interatomic potential also accurately describe the structural properties of the Al 90 Tb 10 liquid, such as partial pair correlation functions (PPCFs) and bond angle distributions, in comparison with the results from AIMD simulations. Furthermore, the developed DNN interatomic potential predicts the formation energies of the crystalline phases of the Al–Tb system with an accuracy comparable to ab initio calculations. The structure factors of the Al 90 Tb 10 metallic liquid and glass obtained by MD simulations using the developed DNN interatomic potential are also in good agreement with the experimental X-ray diffraction data. The development of short-range order (SRO) in the Al 90 Tb 10 liquid and the undercooled liquid is also analyzed and three dominant SROs, i.e., Al-centered distorted icosahedron (DISICO) and Tb-centered ‘3661’ and ‘15551’ clusters, respectively, are identified.

36 MATERIALS SCIENCE↗

Mechanical properties of freestanding few-layer graphene/boron nitride/polymer heterostacks investigated with local and non-local techniques

van der Waals two-dimensional materials and heterostructures combined with polymer films continue to attract research attention to elucidate their functionality and potential applications. This study presents the fabrication and mechanical testing of 2D material heterostacks, consisting of few-layer boron nitride and graphene heterostructures synthesized via chemical vapor deposition, capped with a polymethyl methacrylate layer and suspended across ∼200 μm wide trenches using a combined wet–dry transfer method. The mechanical characterization of the heterostacks was performed using two independent approaches: (a) non-local testing with a custom-built tensile testing platform and (b) local load–displacement testing employing atomic force microscopy probes, complemented by finite element simulations. Both approaches provided new results, which are in good agreement with each other. Overall, our findings offer new insights into a combined load capacity in complex multi-material two-dimensional systems, and can contribute to advancing micro and nano-scale device designs and implementations.

Lespasio, Marcus↗

Gaussian approximation potential for amorphous Si : H

Hydrogenation of amorphous silicon (a–Si : H) is critical for reducing defect densities, passivating midgap states and surfaces, and improving photoconductivity in silicon-based electro-optical devices. Modeling the atomic-scale structure of this material is critical to understanding these processes, which in turn is needed to describe c–Si/a–Si : H heterojunctions that are at the heart of modern solar cells with world-record efficiency. Density functional theory (DFT) studies achieve the required high accuracy but are limited to moderate system sizes of 100 atoms or so by their high computational cost. Simulations of amorphous materials have been hindered by this high cost because large structural models are required to capture the medium-range order that is characteristic of such materials. Empirical potential models are much faster, but their accuracy is not sufficient to correctly describe the frustrated local structure. Data-driven, machine-learned interatomic potentials have broken this impasse and have been highly successful in describing a variety of amorphous materials in their elemental phase. Here, we extend the Gaussian approximation potential (GAP) for silicon by incorporating the interaction with hydrogen, thereby significantly improving the degree of realism with which amorphous silicon can be modeled. We show that our Si : H GAP enables the simulation of hydrogenated silicon with an accuracy very close to DFT but with computational expense and run times reduced by several orders of magnitude for large structures. Here, we demonstrate the capabilities of the Si : H GAP by creating models of hydrogenated liquid and amorphous silicon and showing that their energies, forces, and stresses are in excellent agreement with DFT results, and their structure as captured by bond and angle distributions are in agreement with both DFT and experiments.

36 MATERIALS SCIENCE↗

Program Repository for Tools for Heliophysics Science (Theseus)

This software is being developed to support data analysis and simulation for the growing field of outer heliosphere physics. In particular, this software will allow data analysis, inference, and simulation of physical mechanisms describing how energetic neutral atoms behave that originate from the solar system's boundary with the interstellar medium.

Weaver, Brian↗

Software for Heliospheric Science

This software is being developed to support data analysis, modeling, and simulation for the growing field of heliosphere physics. In particular, this software will implement data analysis, modeling, inference, and simulation of physical mechanisms describing how energetic neutral atoms behave within the Earth’s heliosphere and in the interstellar medium beyond.

VanDervort, Lauren↗

Two-dimensional quantum gas with real time control of complete Hamiltonian (Final Report)

We developed a novel quantum platform with the complete capability to control individual atoms and their mutual interactions in real time. Ultracold atoms are employed since they have the lowest temperature and decoherence. This system is the ultimate dream of quantum physicists where the Hamiltonian of every single atom, including its kinetic energy, potential energy, and interactions, can be independently programmed in real time. We also initiated a new theoretical collaboration to explore its full potential.

74 ATOMIC AND MOLECULAR PHYSICS↗

Development of a Pronghorn Model of the High Temperature Engineering Test Reactor: Preliminary Results from Loss of Forced Cooling #3 [Slides]

This presentation contains results from a Pronghorn model of the High Temperature Engineering Test Reactor (HTTR) operated by the Japan Atomic Energy Agency. The model was used to simulate a loss of forced cooling (LOFC) experiment. This presentation contains preliminary results from a standalone thermal hydraulics model of this LOFC test and some discussion of the results compared to data

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

Statistical Mechanics on Lattices (smol) v0.0.1

smol is a Python implementation of the Cluster Expansion Method and extensions of this methodology; which is used to fit applied lattice models from first principle calculations for subsequent use in Monte Carlo simulations for computing thermodynamic and statistical properties of atomic configuration. smol has a several notable advantages over other similar software packages. The first being its Python implementation which makes it easy to use even for users with little software and coding skills. Despite being implemented in Python, essential Monte Carlo routines are implemented in Cython such that performance is not compromised and is competitive even to similar software implemented in C/C++. Furthermore, the package has specific functionality for handling complex ionic materials (such as cathodes and electrolytes) that is not readily available in other packages. Lastly, the software has a flexible and modular design with the intention of making it fast and efficient to develop and extend the methodology.

Barroso-Luque, Luis↗

Characterization of a 5-eV neutral atomic oxygen beam facility

An experimental effort to characterize an existing 5-eV neutral atomic oxygen beam facility being developed at Princeton Plasma Physics Laboratory is described. This characterization effort includes atomic oxygen flux and flux distribution measurements using a catalytic probe, energy determination using a commercially designed quadrupole mass spectrometer (QMS), and the exposure of oxygen-sensitive materials in this beam facility. Also, comparisons were drawn between the reaction efficiencies of materials exposed in plasma ashers, and the reaction efficiencies previously estimated from space flight experiments. The results of this study show that the beam facility is capable of producing a directional beam of neutral atomic oxygen atoms with the needed flux and energy to simulate low Earth orbit (LEO) conditions for real time accelerated testing. The flux distribution in this facility is uniform to +/- 6 percent of the peak flux over a beam diameter of 6 cm.

Vaughn, J. A.↗

Flow Characteristics of UHV Nitrogen Arcjet

Flow characteristics in the nozzle of a nitrogen arcjet have been simulated by a model. Electrons, ions, and neutral atoms and molecules are represented as separate species. Dissociation, ionization, and recombination are treated as separate reactions. Thermal non-equilibrium is represented by a two-temperature model. Energy input to plasma from the arc is modeled as a source determined by local current and electrical conductivity. Momentum and energy losses and recombinations at the nozzle wall are included as source/sink determined by fluxes to the wall. The results show essentially frozen gas-phase reactions and thermal nonequilibrium due to Joule heating of electrons and in the expansion part of the nozzle. Wall interactions have strong effects on the results, indicating that they play important roles in the flow due to very high surface area relative to the volume of the plasma. For example, plasma velocity decreases from 6000 m per s without wall interactions to 3000 m per s with modest amount of wall interactions. These results also show reasonable agreement with optical emission measurements, which confirms that the arcjet plasma is far from LTE. The spectra suggest nitrogen dissociation levels of 0.3% - 9%, depending on nitrogen flow rate and arc plasma current, which also determine the relative amounts of excited atomic and molecular nitrogen. Langmuir probe studies of the source show that electron and ion fluxes increase with increasing power, and that the ion energy distribution shifts to lower energies. Typical ion fluxes were on the order of 4E-9 A/cm**2 with a maximum ion kinetic energy of 3.5eV. The median electron energy was 1eV, with a maximum of less than 4eV.

Chang, C. H.↗

Empirical Modeling of the Storm Time Innermost Magnetosphere Using Van Allen Probes and THEMIS Data: Eastward and Banana Currents

The structure of storm time currents in the inner magnetosphere, including its innermost region inside 4R(sub E), is studied for the first time using a modification of the empirical geomagnetic field model TS07D and new data from Van Allen Probes and Time History of Events and Macroscale Interactions during Substorms missions. It is shown that the model, which uses basis-function expansions instead of ad hoc current modules to approximate the magnetic field, consistently improves its resolution and magnetic field reconstruction with the increase of the number of basis functions and resolves the spatial structure and evolution of the innermost eastward current. This includes a connection between the westward ring current flowing largely at R > or approx. 3R(sub E) and the eastward ring current concentrated at R < or approx. 3R(sub E) resulting in a vortex current pattern. A similar pattern coined 'banana current' was previously inferred from the pressure distributions based on the energetic neutral atom imaging and first-principles ring current simulations. The morphology of the equatorial currents is dependent on storm phase. During the main phase, it is complex, with several asymmetries forming banana currents. Near SYM-H minimum, the banana current is strongest, is localized in the evening-midnight sector, and is more structured compared to the main phase. It then weakens during the recovery phase resulting in the equatorial currents to become mostly azimuthally symmetric.

Stephens, G. K.↗

Cyber Resiliency and the Implementation of a Host-Based Intrusion Detection System in an Urban Air Mobility Environment

With the growth in Urban Air Mobility systems and the increasing reliance on interconnected technologies, ensuring the security of these complex components has become critical. As cities evolve into smart urban centers, the vulnerability to cyber threats escalates, possibly endangering citizens safety and the efficiency of transportation networks.In response to these challenges, this paper presents a study on the need for cyber resilient techniques within future air traffic environments. It will pay specific attention to the implementation of a Host-Based Intrusion Detection System (HIDS) utilizing Atomic OSSEC software, tailored specifically to a NASA simulation of an UrbanAirMobility environments’ unique demands. Further, this study seeks to outline the rational for NASA’s recommendation for a HIDS in such environments. It explores the design, development, and deployment of the proposed HIDS, focusing on its adaptability to monitor the hybrid nature of the Urban Air Mobility environment. Leveraging machine learning algorithms and anomaly detection techniques, the HIDS is equipped to continuously monitor and analyze the behavior of individual host systems, vehicles, and devices, thereby providing a proactive approach to threat detection. Implementing a HIDS is a pivotal strategy for enhancing cyber resiliency, as it gives an organization granular visibility into internal system activities, enables rapid detection and response to anomalous behavior and cyber threats, and fortifies the organizations overall cybersecurity posture. Finally, this study aims to provide recommendations and include learned takeaways that the Urban Air Mobility industry should consider. In brief, this paper highlights the significance of host-based intrusion detection in UrbanAirMobility environments and underscores the necessity of tailored security solutions to safeguard against emerging cyber threats.

UAM↗

Decoherence Noise on the Superconducting Qubits Training Program

Quantum computing is a growing field with promising applications in a variety of fields such as healthcare, energy consumption, and cryptography. Quantum computing leverages the principles of quantum mechanics - superposition and entanglement. Yet, in the Noisy Intermediate Scale Quantum (NISQ) Era - quantum systems face the major challenge of decoherence due to noise. This era is characterized by low amounts of qubits and high gate error. Decoherence leads to the loss of the quantum information stored in the qubit. Noise occurs with any quantum system that is exposed to the environment. It should also be noted that quantum information can be stored in the cavity - Fermilab specializes in coupling transmons to ultrahigh-Q SRF cavities. The Superconducting Qubits Training Program (SQTP) provides a visualization for beginners in quantum computing. The open quantum system simulated is a superconducting qubit (two-level atom) coupled to a microwave cavity whose excitations are photons. The Rotating Wave Approximation of the Jaynes-Cumming Hamiltonian is used. SQTP utilizes open-source Python-based libraries scQubits, NumPy, and QuTiP alongside the Master Lindblad equation. In this project, we study the different decay behaviors of qubits and cavities with collapse operators.

Lopez, Sara↗