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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Ion-temperature determination with a baffled Langmuir probe

An electrostatic Langmuir probe for real-time measurements of parameters in magnetized plasma is tested in fully ionized, barium, Q-machine plasma. The small-diameter, long-length, tungsten wire sensor, i.e., the probe tip, oriented with its cylindrical axis perpendicular to the magnetic field (B), is partially shielded by ceramic baffles, or masks, that form sensor-access slots between the baffles. Adjusting the azimuthal orientation of the slots, by rotating the probe about its cylindrical axis, changes the fraction of proximity gyro-orbiting electrons, relative to the fraction of proximity gyro-orbiting ions, that can access the recessed sensor along the magnetic field. Thus, the ratio between the electron and ion saturation currents, $I^{sat}_e$ and $I^{sat}_i$, can be adjusted without having affected the probe bias voltage V b . When optimally shielded ($I^{sat}_e/I^{sat}_i$=1), accurate, real-time measurements of space potential Vs can be acquired. When maximally shielded ($I^{sat}_e/I^{sat}_i$ << 1), accurate, real-time measurements of ion temperature T i can be acquired. Subtracting the floating potential V f of an optimally shielded baffled probe from V f of a maximally shielded baffled probe yields T i (and its fluctuation phase) in real time.

47 OTHER INSTRUMENTATION↗
NASA NTRS1994

The hypervelocity impact facilities at the University of Kent at Canterbury, UK

The University of Kent at Canterbury facilities for production of hypervelocity impacts are discussed. Meteoroids are simulated by electrostatic acceleration of small (10(exp -12) - 10(exp -17) kg) particles using a 2-MV Van de Graaff accelerator. This machine has been operational for many years; both the machine and experimental area are currently being upgraded. Larger particles (10(exp -10) - 10(exp -14) kg) are accelerated using a more recently installed light gas gun. The status of all hardware (including experimental areas) is given, along with brief details of recent, current, and future projects making use of them.

Burchell, Mark J.↗
NASA NTRS2011

Evaluation of Tribocharged Electrostatic Beneficiation of Lunar Simulant in Lunar Gravity

The lunar regolith has high concentrations of aluminum, silicon, calcium, iron, sodium, and titanium oxides. Liberation of these metals would provide necessary materials for structural and building material fabrication, spare part, machine and tool production, and construction and site preparation in-situ on the moon or other extraterrestrial body (Rao et al 1979). Ilmenite (FeTi03) is a mineral of interest on the moon as a source of iron, titanium, and oxygen (Cameron 1992, Zhao and Shadman 1993) and therefore enrichment of this mineral in the feedstock before processing would be a considerable advantage in reducing energy requirements to process regolith. Not only for construction materials, but shipping oxygen and water from earth is weight prohibitive, and so investigations into the potential production of oxygen from the oxides of lunar regolith are a major research initiative by NASA (Sibille et al. 2009, Moscatello et al. 2009). In this paper, the results of electrostatic beneficiation of two sets of lunar simulants on two different reduced gravity flight series are presented.

Quinn, Jacqueline W.↗
NASA NTRS1978

Nuclear quadrupole resonance studies project

The participation of undergraduates in nuclear quadrupole resonance research at Grambling University was made possible by NASA grants. Expanded laboratory capabilities include (1) facilities for high and low temperature generation and measurement; (2) facilities for radio frequency generation and measurement with the modern spectrum analyzers, precision frequency counters and standard signal generators; (3) vacuum and glass blowing facilities; and (4) miscellaneous electronic and machine shop facilities. Experiments carried out over a five year period are described and their results analyzed. Theoretical studies on solid state crystalline electrostatic fields, field gradients, and antishielding factors are included.

Murty, A. N.↗
DOE OSTI2020

iPNHOT: a knowledge-based approach for identifying protein-nucleic acid interaction hot spots

The interaction between proteins and nucleic acids plays pivotal roles in various biological processes such as transcription, translation, and gene regulation. Hot spots are a small set of residues that contribute most to the binding affinity of a protein-nucleic acid interaction. Compared to the extensive studies of the hot spots on protein-protein interfaces, the hot spot residues within protein-nucleic acids interfaces remain less well-studied, in part because mutagenesis data for protein-nucleic acids interaction are not as abundant as that for protein-protein interactions. In this study, we built a new computational model, iPNHOT, to effectively predict hot spot residues on protein-nucleic acids interfaces. One training data set and an independent test set were collected from dbAMEPNI and some recent literature, respectively. To build our model, we generated 97 different sequential and structural features and used a two-step strategy to select the relevant features. The final model was built based only on 7 features using a support vector machine (SVM). The features include two unique features such as ΔSASsa 1/2 and esp3, which are newly proposed in this study. Based on the cross validation results, our model gave F1 score and AUROC as 0.725 and 0.807 on the subset collected from ProNIT, respectively, compared to 0.407 and 0.670 of mCSM-NA, a state-of-the art model to predict the thermodynamic effects of protein-nucleic acid interaction. The iPNHOT model was further tested on the independent test set, which showed that our model outperformed other methods. Here, by collecting data from a recently published database dbAMEPNI, we proposed a new model, iPNHOT, to predict hotspots on both protein-DNA and protein-RNA interfaces. The results show that our model outperforms the existing state-of-art models. Our model is available for users through a webserver: http://zhulab.ahu.edu.cn/iPNHOT/.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2009

Advances in Non-contact Measurement of Creep Properties

Our team has developed a novel approach to measuring creep at extremely high temperatures using electrostatic levitation (ESL). This method has been demonstrated on niobium up to 2300 C, while ESL has melted tungsten (3400 C). High-precision machined spheres of the sample are levitated in the NASA MSFC ESL, a national user facility, and heated with a laser. The laser is aligned off-center so that the absorbed photons transfer their momentum to the sample, causing it to rotate at up to 250,000+ RPM. The rapid rotation loads the sample through centripetal acceleration, causing it to deform. The deformation of the sample is captured on high-speed video, which is analyzed by machine-vision software from the University of Massachusetts. The deformations are compared to finite element models to determine the constitutive constants in the creep relation. Furthermore, the noncontact method exploits stress gradients within the sample to determine the stress exponent in a single test. This method was validated in collaboration with the University of Tennessee for niobium at 1985 C, with agreement within the uncertainty of the conventional measurements. A similar method is being employed on Ultra-High-Temperature ZrB2- SiC composites, which may see application in rocket nozzles and sharp leading edges for hypersonic vehicles.

Hyers, Robert W.↗
NASA NTRS2003

MEMS-Based Piezoelectric/Electrostatic Inchworm Actuator

A proposed inchworm actuator, to be designed and fabricated according to the principles of microelectromechanical systems (MEMS), would effect linear motion characterized by steps as small as nanometers and an overall range of travel of hundreds of microns. Potential applications for actuators like this one include precise positioning of optical components and active suppression of noise and vibration in scientific instruments, conveyance of wafers in the semiconductor industry, precise positioning for machine tools, and positioning and actuation of micro-surgical instruments. The inchworm motion would be generated by a combination of piezoelectric driving and electrostatic clamping. The actuator (see figure), would include a pair of holders (used for electrostatic clamping), a slider (the part that would engage in the desired linear motion), a driver, a piezoelectric stack under the driver, and a pair of polymer beams centrally clamped to the flexure beam via a T bar. The holders would be held stationary. One end of the piezoelectric stack would be held stationary; the other end would be connected to the bottom of the driver, which would be free to move up and down. All of these components except the piezoelectric stack and the polymer beams would be micromachined from a 500- m-thick silicon wafer by deep reactive-ion etching. The inchworm motion would be perpendicular to the broad faces of the wafer (perpendicular to the plane of the figure). The combination of the polymer beams and the centrally clamped flexure beam would spring-bias the slider into a position such that, in the absence of electrostatic clamping, the gap between the slider on the one hand and both the driver and the holder on the other hand would be no more than a few microns. This arrangement would make it possible to electrostatically pull the slider into contact with either the holders or the driver at a clamping force of the order of 1 N by applying a reasonably small voltage (of the order of 100 V).

Yang, Eui-Hyeok↗
NASA NTRS2004

Electrostatically clean solar array

Provided are methods of manufacturing an electrostatically clean solar array panel and the products resulting from the practice of these methods. The preferred method uses an array of solar cells, each with a coverglass where the method includes machining apertures into a flat, electrically conductive sheet so that each aperture is aligned with and undersized with respect to its matched coverglass sheet and thereby fashion a front side shield with apertures (FSA). The undersized portion about each aperture of the bottom side of the FSA shield is bonded to the topside portions nearest the edges of each aperture's matched coverglass. Edge clips are attached to the front side aperture shield edges with the edge clips electrically and mechanically connecting the tops of the coverglasses to the solar panel substrate. The FSA shield, edge clips and substrate edges are bonded so as to produce a conductively grounded electrostatically clean solar array panel.

Stern, Theodore Garry↗
DOE OSTI2022

Extracting forces from noisy dynamics in dusty plasmas

Extracting environmental forces from noisy data is a common yet challenging task in complex physical systems. Machine learning (ML) represents a robust approach to this problem, yet is mostly tested on simulated data with known parameters. Here we use supervised ML to extract the electrostatic, dissipative, and stochastic forces acting on micron-sized charged particles levitated in an argon plasma (dusty plasma). By tracking the sub-pixel motion of particles in subsequent images, we successfully estimated these forces from their random motion. The experiments contained important sources of non-Gaussian noise, such as drift and pixel-locking, representing a data mismatch from methods used to analyze simulated data with purely Gaussian noise. Our model was trained on simulated particle trajectories that included all of these artifacts, and used more than 100 dynamical and statistical features, resulting in a prediction with 50\% better accuracy than conventional methods. Lastly, in systems with two interacting particles, the model provided non-contact measurements of the particle charge and Debye length in the plasma environment.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

DS-TIDE: Harnessing Dynamical Systems for Efficient Time-Independent Differential Equation Solving

Time-Independent Differential Equations (TIDEs) are central to modeling equilibrium behavior across a wide range of scientific and engineering domains, from electrostatics to porous media flow. Conventional numerical solvers offer reliable solutions but incur significant computational costs due to fine-grained discretization and iterative procedures. Machine learning-based approaches address this by replacing iterative solving processes with one-time inference; however, their sophisticated models require extensive training resources that often exceed those of traditional solvers. Consequently, designing a TIDE solver that achieves high accuracy, broad applicability, and exceptional computational efficiency remains a fundamental challenge. In this paper, we propose DS-TIDE, a novel hardware solver that is inspired by, and subsequently leverages, the intrinsic connection between Dynamical Systems (DS) and Differential Equations (DEs) to efficiently and accurately solve TIDEs. DS-TIDE employs a CMOS-compatible DS-based processor, whose physical states evolve under carefully designed DE-driven dynamics and naturally converge to equilibrium -- the solution of the target TIDE -- within ~1µs on a ~1-watt DS-TIDE processor. To enhance expressivity, DS-TIDE incorporates Heterogeneous Dynamics with Temporal Layering (HDTL), which solves TIDEs through a three-stage DS evolution -- conditioning, solving, and decoding -- each governed by specialized dynamics. The entire evolution process is analogous to an infinitely deep neural network temporally unrolled, offering the system the capability of representing complex equations. Furthermore, DS-TIDE is equipped with an on-device DS-DE Auto-Alignment mechanism that dynamically adapts intrinsic hardware dynamics within milliseconds, effectively aligning the system’s dynamics to diverse target DEs. Experimental results across TIDEs from a wide range of scientific and engineering domains demonstrate that DS-TIDE achieves ~10^3× speedup, ~10^5× energy savings, and competitive or superior accuracy compared to state-of-the-art numerical and ML-based solvers.

Liu, Chuan↗
DOE OSTI2023

Electronic structure theory on modeling short-range noncovalent interactions between amino acids

While short-range noncovalent interactions (NCIs) are proving to be of importance in many chemical and biological systems, these atypical bindings happen within the so-called van der Waals envelope and pose an enormous challenge for current computational methods. We introduce SNCIAA, a database of 723 benchmark interaction energies of short-range noncovalent interactions between neutral/charged amino acids originated from protein x-ray crystal structures at the “gold standard” coupled-cluster with singles, doubles, and perturbative triples/complete basis set [CCSD(T)/CBS] level of theory with a mean absolute binding uncertainty less than 0.1 kcal/mol. Subsequently, a systematic assessment of commonly used computational methods, such as the second-order Møller−Plesset theory (MP2), density functional theory (DFT), symmetry-adapted perturbation theory (SAPT), composite electronic-structure methods, semiempirical approaches, and the physical-based potentials with machine learning (IPML) on SNCIAA is carried out. It is shown that the inclusion of dispersion corrections is essential even though these dimers are dominated by electrostatics, such as hydrogen bondings and salt bridges. Overall, MP2, ωB97M-V, and B3LYP+D4 turned out to be the most reliable methods for the description of short-range NCIs even in strongly attractive/repulsive complexes. SAPT is also recommended in describing short-range NCIs only if the δMP2 correction has been included. The good performance of IPML for dimers at close-equilibrium and long-range conditions is not transferable to the short-range. We expect that SNCIAA will assist the development/improvement/validation of computational methods, such as DFT, force-fields, and ML models, in describing NCIs across entire potential energy surfaces (short-, intermediate-, and long-range NCIs) on the same footing.

Chemistry↗
DOE OSTI2025

Periodic GFN1-xTB Tight Binding: A Generalized Ewald Partitioning Scheme for the Klopman–Ohno Function

A novel formulation is presented for the treatment of electrostatics in the periodic GFN1-xTB tight-binding model. Periodic GFN1-xTB is hindered by the functional form of the second-order electrostatics, which only recovers Coulombic behavior at large interatomic distances and lacks a closed-form solution for its Fourier transform. We address this by introducing a binomial expansion of the Klopman–Ohno function to partition short- and long-range interactions, enabling the use of a generalized Ewald summation for the solution of the electrostatic energy. This approach is general and is applicable to any damped potential of the form |R n + c| –m . Benchmarks on the X23 molecular crystal dataset and a range of prototypical bulk semiconductors demonstrate that this systematic treatment of the electrostatics eliminates unphysical behavior in the equation of state curves. In the bulk systems studied, we observe a mean absolute error in total energy of 35 meV/atom, comparable to the machine-learned universal force field, M3GNet, and sufficiently precise for structure relaxation. These results highlight the promising potential of GFN1-xTB as a universal tight-binding parametrization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Polarization-driven band topology evolution in twisted MoTe 2 and WSe 2

Motivated by recent experimental observations of opposite Chern numbers in R-type twisted MoTe 2 and WSe 2 homobilayers, we perform large-scale density-functional-theory calculations with machine learning force fields to investigate moiré band topology across a range of twist angles in both materials. We find that the Chern numbers of the moiré frontier bands change sign as a function of twist angle, and this change is driven by the competition between moiré ferroelectricity and piezoelectricity. Our large-scale calculations, enabled by machine learning methods, reveal crucial insights into interactions across different scales in twisted bilayer systems. The interplay between atomic-level relaxation effects and moiré-scale electrostatic potential variation opens new avenues for the design of intertwined topological and correlated states, including the possibility of mimicking higher Landau level physics in the absence of magnetic field.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Constructing a new predictive scaling formula for ITER's divertor heat-load width informed by a simulation-anchored machine learning

Understanding and predicting divertor heat-load width λq is a critically important problem for an easier and more robust operation of ITER with high fusion gain. Previous predictive simulation data for λ q using the extreme-scale edge gyrokinetic code XGC1 [S. Ku et al., Phys. Plasmas 25, 056107 (2018)] in the electrostatic limit under attached divertor plasma conditions in three major US tokamaks [C. S. Chang et al., Nucl. Fusion 57, 116023 (2017)] reproduced the Eich and Goldston attached-divertor formula results [formula #14 in T. Eich et al., Nucl. Fusion 53, 093031 (2013) and R. J. Goldston, Nucl. Fusion 52, 013009 (2012)] and furthermore predicted over six times wider λ q than the maximal Eich and Goldston formula predictions on a full-power (Q = 10) scenario ITER plasma. After adding data from further predictive simulations on a highest current JET and highest-current Alcator C-Mod, a machine learning program is used to identify a new scaling formula for λ q as a simple modification to the Eich formula #14, which reproduces the Eich scaling formula for the present tokamaks and which embraces the wide λ q XGC for the full-current Q = 10 ITER plasma. Additionally, the new formula is then successfully tested on three more ITER plasmas: two corresponding to long burning scenarios with Q = 5 and one at low plasma current to be explored in the initial phases of ITER operation. The new physics that gives rise to the wider λ q XGC is identified to be the weakly collisional, trapped-electron-mode turbulence across the magnetic separatrix, which is known to be an efficient transporter of the electron heat and mass. Electromagnetic turbulence and high-collisionality effects on the new formula are the next study topics for XGC1.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Electrostatic powder spreading for metal powder bed fusion applications

Typical powder bed fusion processes spread each layer of powder by pushing it across the build area with a spreader bar or roller. While simple, these methods require good flowing powder and do not have the ability to place more than one powder type per layer. This naturally limits the ability to incorporate more than one material onto each powder layer in powder bed additive manufacturing processes. Here we demonstrate electrostatic powder spreading, a method to deposit a powder layer without mechanical contact with the previous layers. Electrostatic powder spreading (ESPS) uses an electric field formed between a powder container and a counter electrode to move powder particles from the container to the powder bed. We show that the rate at which powder is deposited can be controlled by adjusting the strength of the electric field. Correspondingly, the deposited layer thickness is controlled by the strength of the electric field and the recoating speed. To demonstrate the feasibility of ESPS for laser powder bed fusion powder spreading, nearly fully dense (> 99.8%) coupons were built in a commercial L-PBF machine using the ESPS setup. Finally, we achieve 2D patterning of a single layer by using an array of electrodes and switching the applied electric field on and off. ESPS represents a method to produce an arbitrary patterned multi-material powder bed without complicated powder removal steps and easy implementation into existing L-PBF machines. Furthermore, ESPS presents an opportunity to build parts with 3D gradients in material properties.

36 MATERIALS SCIENCE↗
NASA NTRS1995

Surface Micro-Machining: Progress Towards Micro-Electro Mechanical Systems

Surface micromachining is a technique for building electromechanical systems in silicon. A number of electromechanical systems have been implemented in miniature using the fundamental structural building blocks of tensile and non-tensile springs, differential capacitance sensing cells, and electrostatic drive. The integration of complicated mechanical structures and electrical circuits onto a single chip is expected to improve reliability and testability of systems. Reduction in interconnect wiring, the increased use of automation, and the inherent reliability of integrated circuits will all contribute to increased reliability of systems.

Doscher, James↗
DOE OSTI2022

Gaussian approximation of dispersion potentials for efficient featurization and machine-learning predictions of metal–organic frameworks

Energy-related descriptors in machine learning are a promising strategy to predict adsorption properties of metal–organic frameworks (MOFs) in the low-pressure regime. Interactions between hosts and guests in these systems are typically expressed as a sum of dispersion and electrostatic potentials. The energy landscape of dispersion potentials plays a crucial role in defining Henry’s constants for simple probe molecules in MOFs. To incorporate more information about this energy landscape, we introduce the Gaussian-approximated Lennard-Jones (GALJ) potential, which fits pairwise Lennard-Jones potentials with multiple Gaussians by varying their heights and widths. The GALJ approach is capable of replicating information that can be obtained from the original LJ potentials and enables efficient development of Gaussian integral (GI) descriptors that account for spatial correlations in the dispersion energy environment. GI descriptors would be computationally inconvenient to compute using the usual direct evaluation of the dispersion potential energy surface. Here, we show that these new GI descriptors lead to improvement in ML predictions of Henry’s constants for a diverse set of adsorbates in MOFs compared to previous approaches to this task.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗