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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Molecular-scale insights into the electrical double layer at oxide-electrolyte interfaces

The electrical double layer (EDL) at metal oxide-electrolyte interfaces critically affects fundamental processes in water splitting, batteries, and corrosion. However, limitations in the microscopic-level understanding of the EDL have been a major bottleneck in controlling these interfacial processes. Herein, we use ab initio-based machine learning potential simulations incorporating long-range electrostatics to unravel the molecular-scale picture of the EDL at the prototypical anatase TiO 2 -electrolyte interface under various pH conditions. Our large-scale simulations, capable of capturing interfacial water dissociation/recombination reactions and electrolytic proton transport, provide unprecedented insights into the detailed structure of the EDL. Moreover, the larger capacitance of the EDL under basic relative to acidic conditions, originating from the higher affinity of the cations for the oxide surface, is found to give rise to distinct charging mechanisms on negative and positive surfaces. Our results are validated by the agreement between the computed EDL capacitance and experimental data.

Chemical physics↗
DOE OSTI2025

A generative artificial intelligence framework for long-time plasma turbulence simulations

Generative deep learning techniques are employed in a novel framework for the construction of surrogate models capturing the spatiotemporal dynamics of 2D plasma turbulence. The proposed Generative Artificial Intelligence Turbulence (GAIT) framework enables the acceleration of turbulence simulations for long-time transport studies. GAIT leverages a convolutional variational auto-encoder and a recurrent neural network to generate new turbulence data from existing simulations, extending the time horizon of transport studies with minimal computational cost. The application of the GAIT framework to plasma turbulence using the Hasegawa–Wakatani (HW) model is presented, evaluating its performance via various analyses. Very good agreement is found between the GAIT and the HW models in the spatiotemporal Fourier and Proper Orthogonal Decomposition spectra, the flow topology characterized by the Okubo–Weiss parameter, and the time autocorrelation function of turbulent fluctuations. Excellent agreement has also been obtained in the probability distribution function of particle displacements and the effective turbulent diffusivity. In-depth analyses of the latent space of turbulent states, choice of hyperparameters and alternative deep learning models for the time prediction are presented. Our results highlight the potential of Artificial Intelligence-based surrogate models to overcome the computational challenges in turbulence simulation, which can be extended to other situations such as geophysical fluid dynamics.

Artificial intelligence↗
DOE OSTI2020

High Energy ERLs for Electron Cooling

Future electron-ion colliders such as the recently approved eRHIC collide high-intensity ion beams with high current electron beams. The electron beams take advantage of synchrotron radiation to damp emittances but the ion beams must be cooled via some beam-cooling mechanism, including electron cooling. The ion energies are typically a few hundreds of GeV per nucleon. At this energy, a DC cooler powered by an electrostatic accelerator, the preferred cooling approach on existing machines, is not feasible. An ERL, in principle, can provide the high current and brightness to cool these high-brightness ion beams. The beam quality requirements are much different from previous ERLs designs used for FELs. The cooling bunch must be very long to match the ion beam and the relative energy spread must be very small. Incoherent cooling can be enhanced with magnetized beams, but the magnetization must be maintained throughout the ERL. An alternate cooling mechanism, the so-called Coherent Electron Cooling, is, in principle, stronger and can be done with non-magnetized beams. We will present two applications of an ERL to high energy electron cooling and describe some of the technical challenges that must be overcome to operate such an ERL

Benson, Stephen↗
NASA NTRS1986

A laboratory study of collisional electrostatic ion cyclotron waves

The effects of neutral-particle collisions on electrostatic ion cyclotron instability are analyzed. Experiments were conducted in the Q machine of Motley (1975) with a cesium plasma in which the neutral gas pressure in the main chamber varied from about 5 microtorr-10 mtorr. The relation between electrostatic ion cyclotron wave amplitude and frequency and neutral argon pressure is examined. It is observed that over the full range of neutral pressure the frequency changes by less than 10 percent and the ion cyclotron waves continue to be excited and reach amplitudes of at least several percent at values of the neutral pressure where the ion-neutral collision frequency/ion gyrofrequency is about 0.3.

Suszcynsky, D. M.↗
DOE OSTI2020

Image Processing Algorithms for Tuning Quantum Devices and Nitrogen-Vacancy Imaging

Semiconductor quantum dot devices can be challenging to configure into a regime where they are suitable for qubit operation. This challenge arises from variations in gate control of quantum dot electron occupation and tunnel coupling between quantum dots on a single device or across several devices. Furthermore, a single control gate usually has capacitive coupling to multiple quantum dots and tunnel barriers between dots. If the device operator, be it human or machine, has quantitative knowledge of how gates control the electrostatic and dynamic properties of multiqubit devices, the operator can more quickly and easily navigate the multidimensional gate space to find a qubit operating regime. We have developed and applied image analysis techniques to quantitatively detect where charge offsets from different quantum dots intersect, so called anticrossings. In this document we outline the details of our algorithm for detecting single anticrossings, which has been used to fine-tune the inter-dot tunnel rates for a three quantum dot system. Additionally, we show that our algorithm can detect multiple anticrossings in the same dataset, which can aid in the coarse tuning the electron occupation of multiple quantum dots. We also include an application of cross correlation to the imaging of magnetic fields using nitrogen vacancies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1986

A laboratory study of ion energization by EIC waves and subsequent upstreaming along diverging magnetic field lines

A laboratory study related to energetic upstreaming ions in the ionosphere-magnetosphere system is described. The experiment was carried out in a cesium Q machine plasma with a region of nonuniform magnetic field. Electrostatic ion cyclotron waves were excited by drawing an electron current to a small biased exciter electrode. In the presence of the instability, ions are heated in the direction perpendicular to B. Using a gridded retarding potential ion energy analyzer, the evolution of the ion velocity distribution was followed as the ions passed through the heating region and subsequently flowed out along the diverging B field lines. As expected, the heated ions transfer their energy from perpendicular to parallel motion as they move through the region of diverging B field. Both their parallel thermal energy and the parallel drift energy increase at the expense of the perpendicular energy.

Cartier, S. L.↗
NASA NTRS1994

Evaluation of Some Slow-wave Vane Structures for Aminiature Traveling-wave Tube at 30 Ghz

The dispersion characteristics of six vane type slow wave structures were experimentally measured near 1 GHz to determine applicability in an electrostatically focused 30 GHz miniature traveling wave tube (TWT). From the measured results, the trapezoidal vane structure appeared to be the most promising exhibiting an interaction impedance equal to 337.9 ohms at beta(L)/pi equal to 0.3. A 30 GHz trapezoidal vane structure with coupling irises was fabricated using electrical discharge machining (EDM). This structure, however, was too lossy for a short electrostatically focused tube, but several of the structures are amenable to a tube with permanent magnetic focusing.

Kavanagh, Frank↗
DOE OSTI2024

Predicting Partial Atomic Charges in Metal–Organic Frameworks: An Extension to Ionic MOFs

Molecular simulation is an invaluable tool to predict and understand the usage of metal–organic frameworks (MOFs) for gas storage and separation applications. Accurate partial atomic charges, commonly obtained from density functional theory (DFT) calculations, are often required to model the electrostatic interactions between the MOF and adsorbates, especially when the adsorbates have dipole or quadrupole moments, such as water and CO 2 . Machine learning (ML) models have been previously employed to predict partial charges and avoid the computational cost associated with DFT calculations. However, previous ML models suffer from small training data sets, which limit their scope of application. In this work, we introduce two novel machine learning models, PACMOF2-neutral and PACMOF2-ionic, aimed at predicting the density-derived electrostatic and chemical (DDEC6) partial atomic charges for both neutral and ionic MOFs. These models not only yield DFT-level accuracy at a fraction of the computational cost but also demonstrate a remarkable improvement in prediction of adsorption, as validated with grand canonical Monte Carlo simulations. Furthermore, the robustness and fast computational time of the PACMOF2 models, along with their transferability to other porous materials such as covalent organic frameworks and zeolites, underscores their potential in high-throughput screening of MOFs for diverse applications.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Super-resolution and signal separation in contact Kelvin probe force microscopy of electrochemically active ferroelectric materials

In this work, imaging mechanisms in contact Kelvin probe force microscopy (cKPFM) are explored via information theory-based methods. Gaussian processes are used to achieve super-resolution in the cKPFM signal, effectively extrapolating across the spatial and parameter space. Tensor factorization is applied to reduce the multidimensional signal to the tensor convolution of the scalar functions that show a clear trending behavior with the imaging parameters. These methods establish a workflow for the analysis of the multidimensional datasets that can then be related to the relevant physical mechanisms. We also provide an interactive Google Colab notebook that goes through all the analyses discussed in the paper.

36 MATERIALS SCIENCE↗
NASA NTRS1988

Electrostatic ion-cyclotron waves in a two-ion component plasma

The excitation of electrostatic ion cyclotron (EIC) waves is studied in a single-ended Q machine in a two-ion component plasma (Ca+ and K+). Over a large range of relative concentrations of Cs+ and K+ ions, two modes are excited with frequencies greater than the respective cyclotron frequencies of the ions. The results are discussed in terms of a fluid theory of electrostatic ion cyclotron waves in a two-ion component plasma.

Suszcynsky, David M.↗
DOE OSTI2020

Predicting molecular dipole moments by combining atomic partial charges and atomic dipoles

The molecular dipole moment ( μ ) is a central quantity in chemistry. It is essential in predicting infrared and sum-frequency generation spectra as well as induction and long-range electrostatic interactions. Furthermore, it can be extracted directly—via the ground state electron density—from high-level quantum mechanical calculations, making it an ideal target for machine learning (ML). Here, we choose to represent this quantity with a physically inspired ML model that captures two distinct physical effects: local atomic polarization is captured within the symmetry-adapted Gaussian process regression framework which assigns a (vector) dipole moment to each atom, while the movement of charge across the entire molecule is captured by assigning a partial (scalar) charge to each atom. The resulting “MuML” models are fitted together to reproduce molecular μ computed using high-level coupled-cluster theory and density functional theory (DFT) on the QM7b dataset, achieving more accurate results due to the physics-based combination of these complementary terms. The combined model shows excellent transferability when applied to a showcase dataset of larger and more complex molecules, approaching the accuracy of DFT at a small fraction of the computational cost. We also demonstrate that the uncertainty in the predictions can be estimated reliably using a calibrated committee model. The ultimate performance of the models—and the optimal weighting of their combination—depends, however, on the details of the system at hand, with the scalar model being clearly superior when describing large molecules whose dipole is almost entirely generated by charge separation. These observations point to the importance of simultaneously accounting for the local and non-local effects that contribute to μ ; furthermore, they define a challenging task to benchmark future models, particularly those aimed at the description of condensed phases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2016

Modeling a Miniaturized Scanning Electron Microscope Focusing Column - Lessons Learned in Electron Optics Simulation

This presentation discusses work done to assess the design of a focusing column in a miniaturized Scanning Electron Microscope (SEM) developed at the NASA Marshall Space Flight Center (MSFC) for use in-situ on the Moon-in particular for mineralogical analysis. The MSFC beam column design uses purely electrostatic fields for focusing, because of the severe constraints on mass and electrical power consumption imposed by the goals of lunar exploration and of spaceflight in general. The resolution of an SEM ultimately depends on the size of the focused spot of the scanning beam probe, for which the stated goal here is a diameter of 10 nanometers. Optical aberrations are the main challenge to this performance goal, because they blur the ideal geometrical optical image of the electron source, effectively widening the ideal spot size of the beam probe. In the present work the optical aberrations of the mini SEM focusing column were assessed using direct tracing of non-paraxial rays, as opposed to mathematical estimates of aberrations based on paraxial ray-traces. The geometrical ray-tracing employed here is completely analogous to ray-tracing as conventionally understood in the realm of photon optics, with the major difference being that in electron optics the lens is simply a smoothly varying electric field in vacuum, formed by precisely machined electrodes. Ray-tracing in this context, therefore, relies upon a model of the electrostatic field inside the focusing column to provide the mathematical description of the "lens" being traced. This work relied fundamentally on the boundary element method (BEM) for this electric field model. In carrying out this research the authors discovered that higher accuracy in the field model was essential if aberrations were to be reliably assessed using direct ray-tracing. This led to some work in testing alternative techniques for modeling the electrostatic field. Ultimately, the necessary accuracy was attained using a BEM/Fourier series hybrid approach. The presentation will give background remarks about the MSFC mini Lunar SEM concept and electron optics modeling, followed by a description of the alternate field modeling techniques that were tried, along with their incorporation into a ray-trace simulation. Next, the validation of this simulation against commercially available software will be discussed using an example lens as a test case. Then, the efficacy of aberration assessment using direct ray-tracing will be demonstrated, using this same validation case. The discussion will include practical error checks of the field solution. Finally, the ray-trace assessment of the MSFC mini Lunar SEM concept will be shown and discussed. The authors believe this presentation will be of general interest to practitioners of modeling and simulation, as well as those with a general optics background. Because electron optics and photon optics share many basic concepts (e.g., lenses, images, aberrations, etc.), the appeal of this presentation need not be restricted to just those interested in charged particle optics.

Modeling Miniaturizing Scanning↗
NASA NTRS1989

SRM propellant, friction/ESD testing

Following the Pershing 2 incident in 1985 and the Peacekeeper ignition during core removal in 1987, it was found that propellant can be much more sensitive to Electrostatic Discharges (ESD) than ever before realized. As a result of the Peacekeeper motor near miss incident, a friction machine was designed and fabricated, and used to determine friction hazards during core removal. Friction testing with and electrical charge being applied across the friction plates resulted in propellant ignitions at low friction pressures and extremely low ESD levels. The objective of this test series was to determine the sensitivity of solid rocket propellant to combined friction pressure and electrostatic stimuli and to compare the sensitivity of the SRM propellant to Peacekeeper propellant. The tests are fully discussed, summarized and conclusions drawn.

Campbell, L. A.↗
DOE OSTI2022

Machine learning reveals key ion selectivity mechanisms in polymeric membranes with subnanometer pores

Designing single-species selective membranes for high-precision separations requires a fundamental understanding of the molecular interactions governing solute transport. Here, we comprehensively assess molecular-level features that influence the separation of 18 different anions by nanoporous cellulose acetate membranes. Our analysis identifies the limitations of bulk solvation characteristics to explain ion transport, highlighted by the poor correlation between hydration energy and the measured permselectivity (R 2 = 0.37). Entropy-enthalpy compensation, spanning 40 kilojoules per mole, leads to a free-energy barrier (ΔG‡) variation of only ~8 kilojoules per mole across all anions. We apply machine learning to elucidate descriptors for energetic barriers from a set of 126 collected features. Notably, electrostatic features account for 75% of the overall features used to describe ΔG‡, despite the relatively uncharged state of cellulose acetate. Our work presents an approach for studying ion transport across nanoporous membranes that could enable the design of ion-selective membranes.

36 MATERIALS SCIENCE↗
NASA NTRS1985

Plasma-depleted holes, waves, and energized particles from high-altitude explosive plasma perturbation experiments

The results of high-explosive shaped charge experiments King Crab and Bubble Machines I and II, intended to perturb the ambient plasma and magnetic field, are discussed. The instrumentation was flown above an altitude of 460 km in March 1980 and 1981 and comprised a single-axis dipole electric field detector, a fixed bias cylindrical Langmuir probe, a three-axis attitude magnetometer, and curved plated energetic ion and electron electrostatic analyzer. Among the effects of the explosion which are detailed, emphasis is placed on the creation of an ion-depleted dark hole during the Bubble Machine II experiment; mechanisms explaining the phenomenon are outlined. The auroral intensity ion beams with energies of up to 6.8 keV, observed following the explosion in the field-aligned ion electrostatic analyzer, are suggested to represent an existing ion conic population pitch angle scattered by the released barium into the view of the detector.

Wescott, E. M.↗
DOE OSTI2021

Fast and Accurate Machine Learning Strategy for Calculating Partial Atomic Charges in Metal–Organic Frameworks

Computational high-throughput screening using molecular simulations is a powerful tool for identifying top-performing metal–organic frameworks (MOFs) for gas storage and separation applications. Accurate partial atomic charges are often required to model the electrostatic interactions between the MOF and the adsorbate, especially when the adsorption involves molecules with dipole or quadrupole moments such as water and CO 2 . Although ab initio methods can be used to calculate accurate partial atomic charges, these methods are impractical for screening large material databases because of the high computational cost. We developed a random forest machine learning model to predict the partial atomic charges in MOFs using a small yet meaningful set of features that represent both the elemental properties and the local environment of each atom. The model was trained and tested on a collection of about 320 000 density-derived electrostatic and chemical (DDEC) atomic charges calculated on a subset of the Computation-Ready Experimental Metal–Organic Framework (CoRE MOF-2019) database and separately on charge model 5 (CM5) charges. The model predicts accurate atomic charges for MOFs at a fraction of the computational cost of periodic density functional theory (DFT) and is found to be transferable to other porous molecular crystals and zeolites. In conclusion, a strong correlation is observed between the partial atomic charge and the average electronegativity difference between the central atom and its bonded neighbors.

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

Methods for stabilizing biological and soft materials for atom probe tomography

Techniques are disclosed for stabilizing soft specimen traditionally considered too fragile for APT instruments. These specimens include biological samples, polymers and other fragile materials. For this purpose, a protective structure is disclosed that surrounds the sides of the specimen by supporting walls while only exposing the very end or terminus of the specimen to the electrostatic field of the APT instrument. The protective structure may take the form of a nanoscale conical grinder which continually machines the specimen to regenerate the terminus of the specimen in-situ. Alternately, the protective structure may take the form of a nanopipette in which the specimen is first frozen before undergoing field evaporation together with the tip of the nanopipette. Heretofore only routinely possible for rigid and hard materials, the design thus extends APT analysis to produce three-dimensional atomic-scale maps of soft specimens.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Application of machine learning for optical emission spectroscopy data in NAGDIS-II

In this study, we applied machine learning to optical emission spectroscopy (OES) data and device parameters from the linear plasma device NAGDIS-II to explore the potential application of machine learning for predicting electron density, $n$ e , and temperature, $T$ e . The covered ranges of $n$ e and $T$ e , which were measured by an electrostatic probe, are 3.6 × 10 17 –2.4 × 10 19 m -3 and 0.3–7.1 eV, respectively. A three hidden layer neural network (NN) is introduced to model the relationship between $n$ e /$T$ e and the combination of line intensities, radial position, and device parameters. It is shown that the errors in $n$ e and $T$ e become 18.0 and 18.8%, respectively, which were almost the same level for the electrostatic probe, using all available data. Lasso regression and greedy algorithm are used to select the necessary line emissions. In conclusion, it is shown that four- or five-line intensities are sufficient to obtain almost the same quality as the one with all the other lines.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗