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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 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

DFF Layout Variations in CMOS SOI—Analysis of Hardening by Design Options

Four D flip-flop (DFF) layouts were created from the same schematic in Sandia National Laboratories’ CMOS7 silicon-on-insulator (SOI) process. Single-event upset (SEU) modeling and testing showed an improved response with the use of shallow (not fully bottomed) N-type metal-oxide-semiconductor field-effect transistors (NMOSFETs), extending the size of the drain implant and increasing the critical charge of the transmission gates in the circuit design and layout. This research also shows the importance of correctly modeling nodal capacitance, which is a major factor determining SEU critical charge. Accurate SEU models enable the understanding of the SEU vulnerabilities and how to make the design more robust.

42 ENGINEERING↗
DOE OSTI2023

Enhanced Magnetization in CoFe 2 O 4 Through Hydrogen Doping

Magnetic spinel oxides have attracted extensive research interest due to their rich physics and wide range of applications. However, these materials invariably suffer suppressed magnetization, due to structural imperfections (e.g., disorder, anti-site defects, etc.). Herein, a dramatic enhanced magnetization is obtained with an increasement of 5 µ B /u.c in CoFe 2 O 4 (CFO) through ionic liquid gating induced hydrogen doping. Further, the intercalated hydrogen ions lead to both distinct lattice expansion of ≈0.7% and notable Fe valence state reduction through electron doping, in which ≈17% Fe 3+ is reduced into Fe 2+ . These facts collectively trigger a site-specific spin-flip on tetrahedrally coordinated Co 2+ sites that enhances the net ferrimagnetic moment nearly to its theoretical maximum for perfect CFO.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Correlated conformational dynamics of the human GluN1-GluN2A type N-methyl-D-aspartate (NMDA) receptor

N-Methyl-D-aspartate receptors (NMDARs) are glutamate-gated ion channels found in the nerve cell membranes. As a result of overexcitation of NMDARs, neuronal death occurs and may lead to diseases such as epilepsy, stroke, Alzheimer’s disease, and Parkinson’s disease. In this study, human GluN1- GluN2A type NMDAR structure is modeled based on the X-ray structure of the Xenopus laevis template and missing loops are added by ab-initio loop modeling. The final structure is chosen according to two different model assessment scores. To be able to observe the structural changes upon ligand binding, glycine and glutamate molecules are docked into the corresponding binding sites of the receptor. Subsequently, molecular dynamics simulations of 1.3 μs are performed for both apo and ligand-bound structures. Structural parameters, which have been considered to show functionally important changes in previous NMDAR studies, are monitored as conformational rulers to understand the dynamics of the conformational changes. Moreover, principal component analysis (PCA) is performed for the equilibrated part of the simulations. Additionally, from these analyses, the differences in between apo and ligand-bound simulations can be summarized as the following: The girdle right at the beginning of the pore loop, which connects M2 and M3 helices of the ion channel, partially opens. Ligands act like an adhesive for the ligand-binding domain (LBD) by keeping the bi-lobed structure together and consequently this is reflected to the overall dynamics of the protein as an increased correlation of the LBD with especially the amino-terminal domain (ATD) of the protein.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Lax-Oleinik-Type Formulas and Efficient Algorithms for Certain High-Dimensional Optimal Control Problems

Two of the main challenges in optimal control are solving problems with state-dependent running costs and developing efficient numerical solvers that are computationally tractable in high dimension. In this paper, we provide analytical solutions to certain optimal control problems whose running cost depends on the state variable and with constraints on the control. We also provide Lax-Oleinik-type representation formulas for the corresponding Hamilton-Jacobi partial differential equations with state-dependent Hamiltonians. Additionally, we present an efficient, grid-free numerical solver based on our representation formulas, which is shown to scale linearly with the state dimension, and thus, to overcome the curse of dimensionality. Using existing optimization methods and the min-plus technique, we extend our numerical solvers to address more general classes of convex and nonconvex initial costs. We demonstrate the capabilities of our numerical solvers using implementations on a central processing unit (CPU) and a field-programmable gate array (FPGA). In several cases, our FPGA implementation obtains over a 10 times speedup compared to the CPU, which demonstrates the promising performance boosts FPGAs can achieve. Furthermore, our numerical results show that our solvers have the potential to serve as a building block for solving broader classes of high-dimensional optimal control problems in real-time.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Structural Basis of Functional Transitions in Mammalian NMDA Receptors

Excitatory neurotransmission meditated by glutamate receptors including N-methyl-D-aspartate receptors (NMDARs) is pivotal to brain development and function. NMDARs are heterotetramers composed of GluN1 and GluN2 subunits, which bind glycine and glutamate, respectively, to activate their ion channels. Despite importance in brain physiology, the precise mechanisms by which activation and inhibition occur via subunit-specific binding of agonists and antagonists remain largely unknown. Here, we show the detailed patterns of conformational changes and inter-subunit and -domain reorientation leading to agonist-gating and subunit-dependent competitive inhibition by providing multiple structures in distinct ligand states at 4 Å or better. The structures reveal that activation and competitive inhibition by both GluN1 and GluN2 antagonists occur by controlling the tension of the linker between the ligand-binding domain and the transmembrane ion channel of the GluN2 subunit. Our results provide detailed mechanistic insights into NMDAR pharmacology, activation, and inhibition, which are fundamental to the brain physiology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Data source authentication of synchrophasor measurement devices based on 1D-CNN and GRU

Synchrophasor measurement devices (SMDs) have been widely deployed to support real-time monitoring and control of power systems. In the meantime, data spoofing has emerged in recent years. Therefore, it is of great importance to study data authentication algorithms for detecting and defending the data spoofing effectively. Here, a one-dimensional convolutional neural network (1D-CNN) is utilized to extract temporal signatures hidden in frequency, voltage angle and amplitude data; then the gated recurrent unit (GRU) employs these temporal signatures for data source authentication. In case studies, the performances of different algorithms are tested in large-scale power systems with numerous SMDs for the first time, and comparisons among different algorithms show that the proposed algorithm can achieve a higher accuracy of data source authentication with a shorter time window.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Towards data-driven constitutive modelling for granular materials via micromechanics-informed deep learning

The analytical description of path-dependent elastic-plastic responses of a granular system is highly complicated because of continuously evolving microstructures and strain localisation within the system undergoing deformation. This study offers an alternative to the current analytical paradigm by developing micromechanics-informed machine-learning based constitutive modelling approaches for granular materials. A set of critical variables associated with the constitutive behaviour of granular materials are identified through an incremental stress-strain relationship analysis. Depending on the strategy to exploit the priori micromechanical knowledge, three different training strategies are explored. The first model uses only the measurable external variables to make stress predictions; the second model utilises a directed graph to link all the external strain sequences and internal microstructural evolution variables into a single prediction model comprised of a series of sub-mappings, and the third model explicitly integrates the physically important non-temporal properties with external strain paths into training through an enhanced Gated Recurrent Unit (GRU). These three models show satisfactory agreement with unseen test specimens based on multi-directional loading cases. The basic features and potential applications of each model are explained. Lastly, the key factors for constitutive training and limitations of the current work are also discussed in detail.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Innovative approaches to neutron beam optimization: A case study of FP14 at LANSCE

This paper describes an experimental method to acquire high resolution energy- and spatially- resolved neutron beam spots using the time-gated neutron imaging system with Teledyne Pi-MAX4 camera. These experimental data offer a unique opportunity for benchmarking beam spot simulations. High-quality simulations depend significantly on a high-fidelity geometry model, which can be challenging for legacy facilities. We informed our MCNPX geometry model by latest metrology survey employing Leica laser tracker ATS600. It gave us a high fidelity description of our facility geometry. Such a robust integration of novel tools and methods yields a previously unattainable level of accuracy in both predicting and capturing neutron beam spots, marking a notable advancement over traditional methods reliant on static image plates. Here, to demonstrate the practical application of these tools, we are showing a non-uniform beam spot challenge at our Flight Path 14 (FP14) at the Los Alamos Neutron Science Center (LANSCE). Our precise MCNPX prediction of beam spot shifting as function of neutron energy was confirmed by experimental beam spot measured with extremely high level of detail. Results of this research demonstrate a significant leap in neutron beam optimization at LANSCE and set a new benchmark in beam spot characterization. The advanced methods presented here have potential for adoption at similar research facilities worldwide, aiming at substantial improvement in neutron beam delivery for experiments.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

The modeling of risk perception in the use of structural health monitoring information for optimal maintenance decisions

This paper proposes an approach to select a maintenance strategy from a predefined set of choices considering the decision maker’s behavioral risk profile. It is assumed that the damage state is characterized by a continuous state parameter probabilistically inferred from observable sensor data. This work applies an engineering application of consequence-based decision-making incorporating the acceptable risk intensity of the decision-maker, i.e., the decision-maker’s (individual or an organization) valuation of the outcome of a decision, using a risk profile model. The utility of a decision-maker is subjective, and this paper considers the fact that different decision-makers mentally assign a different importance factor (the utility) to the seriousness or urgency to take necessary actions with the increasing intensity of structural damage. The approach herein incorporates a layer of human psychology on selecting appropriate maintenance strategies that not only depend on the posterior distribution of unmeasurable damage state but also consider the behavioral risk profile of the decision-maker. Further, the collective decision-making of an organization consisting of many individuals is also investigated. The approach is exemplified in a case study involving life cycle monitoring of a miter gate, part of a lock system enabling navigation of inland waterways.

42 ENGINEERING↗
DOE OSTI2020

Imaging Andreev Reflection in Graphene

Coherent charge transport along ballistic paths can be introduced into graphene by Andreev reflection, for which an electron reflects from a superconducting contact as a hole, while a Cooper pair is transmitted. We use here a liquid-helium cooled scanning gate microscope (SGM) to image Andreev reflection in graphene in the magnetic focusing regime, where carriers move along cyclotron orbits between contacts. Images of flow are obtained by deflecting carrier paths and displaying the resulting change in conductance. When electrons enter the the superconductor, Andreev-reflected holes leave for the collecting contact. To test the findings, we destroy Andreev reflection with a large current and by heating above the critical temperature. In both cases, the reflected carriers change from holes to electrons.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Resistive Switching of Spinel Li 4 Ti 5 O 12 Lithium-Ion Battery Material for Neuromorphic Computing

The rapid rise of AI has exposed significant limitations in conventional Von Neumann computing architecture, particularly in regard to speed and energy efficiency. To address these challenges, researchers are exploring a brain-inspired neuromorphic architecture that mimics biological neural networks, enabling massive parallel processing with reduced power consumption for complex AI computational demands. Recent interest has focused on utilizing battery electrodes and solid electrolyte materials for their resistive switching properties in developing a neuromorphic architecture. These properties are precisely tuned through local- and bulk-level chemical composition modifications via voltage bias stimuli. In this study, we demonstrate fabricating a three-terminal lithium-ion electrochemical transistor based on lithium titanium oxide (Li 4 Ti 5 O 12 ), a popular lithium-ion battery anode material. We deposited and characterized LTO thin films using RF sputtering, demonstrating a 6 orders of magnitude increase in electronic conductivity upon lithiation, with conductivity plateauing after 20% lithiation. Density functional theory calculations revealed transformation from the insulating to conducting state, supported by experimental characterization through X-Ray Photoelectron Spectroscopy (XPS) and Direct Current (DC) polarization analyses. The fabricated transistor consisted of LTO as the channel layer, gold as source/drain terminals, lithium phosphorus oxynitride (LiPON) as the lithium-ion conductor, and copper as the gate terminal. The device exhibited clear hysteresis in transfer characteristics due to lithium insertion/extraction processes. Long-term potentiation (LTP) and long-term depression (LTD) measurements showed an asymmetric ratio of 1.425 and maximum/minimum conductance ratio of 7.83. When implemented in a deep neural network (DNN) for MNIST handwritten digit recognition, the device achieved 92.03% accuracy over 20 training epochs. Detailed transport mechanism analysis revealed the crucial role of oxygen vacancies and interface effects in device operation. Our preliminary findings establish LTO-based lithium-ion electrochemical transistors as promising candidates for energy-efficient neuromorphic computing applications, offering potential solutions to traditional Von Neumann architecture limitations.

25 ENERGY STORAGE↗
DOE OSTI2025

Three-Dimensional Bubble Fluidics in Architected Porous Media

Gas bubble flows in porous media often exhibit complex and seemingly unpredictable behaviors that are difficult to control. This lack of control limits the ability to design effective devices which manage multiphase flows. Here, we show how the design of 3D printed pores can deterministically control the flow path of an injected gas stream. Open cell structures can be designed to shape the gas/liquid interface with fidelity to control how the two phases are distributed throughout a porous material. The distributed gas volume is free to interact physically and chemically with the surrounding liquid phase, an effect we exploit to create a logical control gate to redirect flows within a lattice. This also allows us to design architectures for reactive capture and aerating bioreactors, resulting in patterned boundaries which can make more effective use of the liquid and gas reagents.

3D microfluidics↗
DOE OSTI2022

Molecular-Level Control over Ionic Conduction and Ionic Current Direction by Designing Macrocycle-Based Ionomers

Poor ionic conductivity of the catalyst-binding, submicrometer- thick ionomer layers in energy conversion and storage devices is a huge challenge. However, ionomers are rarely designed keeping in mind the specific issues associated with nanoconfinement. Here, we designed nature-inspired ionomers (calix-2) having hollow, macrocyclic, calix[4]arene-based repeat units with precise, sub-nanometer diameter. In ≤100 nm-thick films, the in-plane proton conductivity of calix-2 was up to 8 times higher than the current benchmark ionomer Nafion at 85% relative humidity (RH), while it was 1-2 orders of magnitude higher than Nafion at 20-25% RH. Confocal laser scanning microscopy and other synthetic techniques allowed us to demonstrate the role of macrocyclic cavities in boosting the proton conductivity. The systematic self-assembly of calix-2 chains into ellipsoids in thin films was evidenced from atomic force microscopy and grazing incidence small-angle X-ray scattering measurements. Moreover, the likelihood of alignment and stacking of macrocyclic units, the presence of one-dimensional water wires across this macrocycle stacks, and thus the formation of long-range proton conduction pathways were suggested by atomistic simulations. We not only did see an unprecedented improvement in thin-film proton conductivity but also saw an improvement in proton conductivity of bulk membranes when calix-2 was added to the Nafion matrices. Nafion-calix-2 composite membranes also took advantage of the asymmetric charge distribution across calix[4]arene repeat units collectively and exhibited voltage-gating behavior. The inclusion of molecular macrocyclic cavities into the ionomer chemical structure can thus emerge as a promising design concept for highly efficient ion-conducting and ion-permselective materials for sustainable energy applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Structural interplay of anesthetics and paralytics on muscle nicotinic receptors

General anesthetics and neuromuscular blockers are used together during surgery to stabilize patients in an unconscious state. Anesthetics act mainly by potentiating inhibitory ion channels and inhibiting excitatory ion channels, with the net effect of dampening nervous system excitability. Neuromuscular blockers act by antagonizing nicotinic acetylcholine receptors at the motor endplate; these excitatory ligand-gated ion channels are also inhibited by general anesthetics. The mechanisms by which anesthetics and neuromuscular blockers inhibit nicotinic receptors are poorly understood but underlie safe and effective surgeries. Here we took a direct structural approach to define how a commonly used anesthetic and two neuromuscular blockers act on a muscle-type nicotinic receptor. We discover that the intravenous anesthetic etomidate binds at an intrasubunit site in the transmembrane domain and stabilizes a non-conducting, desensitized-like state of the channel. The depolarizing neuromuscular blocker succinylcholine also stabilizes a desensitized channel but does so through binding to the classical neurotransmitter site. Rocuronium binds in this same neurotransmitter site but locks the receptor in a resting, non-conducting state. Together, this study reveals a structural mechanism for how general anesthetics work on excitatory nicotinic receptors and further rationalizes clinical observations in how general anesthetics and neuromuscular blockers interact.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Nanosecond anomaly detection with decision trees and real-time application to exotic Higgs decays

Abstract We present an interpretable implementation of the autoencoding algorithm, used as an anomaly detector, built with a forest of deep decision trees on FPGA, field programmable gate arrays. Scenarios at the Large Hadron Collider at CERN are considered, for which the autoencoder is trained using known physical processes of the Standard Model. The design is then deployed in real-time trigger systems for anomaly detection of unknown physical processes, such as the detection of rare exotic decays of the Higgs boson. The inference is made with a latency value of 30 ns at percent-level resource usage using the Xilinx Virtex UltraScale+ VU9P FPGA. Our method offers anomaly detection at low latency values for edge AI users with resource constraints.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Laser-induced fluorescence measurements of ion fluctuations in electron and ion presheaths

Electrostatic flow-driven instabilities have been predicted in the presheath region of low-temperature plasmas for both ion and electron rich sheaths. The ion-acoustic fluctuations that arise from these instabilities can influence transport through an enhanced collision rate. In this work, ion fluctuation spectra were measured using laser-induced fluorescence (LIF) in the presheath region for both sheath polarities. Furthermore, the non-invasive nature of LIF compared to that of probes is particularly valuable for these measurements because the sheath and presheath around a probe may generate their own flow-driven instabilities, which obscure the measurement. Measurements were made using a recently implemented field programmable gate array-based system able to measure ion fluctuation spectra up to 1 MHz using a two-point correlation function technique. Narrow bandwidth ion fluctuations were observed near 0:46 f pi (460 kHz) for both sheath polarities, where f pi is the ion plasma frequency. The observed fluctuations were significantly stronger in the electron sheath case and were observed over a larger volume of plasma. Fluctuations were measured in the ion sheath case at locations far enough from the sheath that linear theory predicts stability, suggesting that ion-acoustic instabilities generated in the relatively small unstable region near the boundary reflect from the sheath and perturb a much larger volume of the plasma. This is expected to affect probes with both ion and electron rich sheaths, meaning any dc biased probe may effectively act as an ion-acoustic wave antenna. These measurements are consistent with the recent theory and particle-in-cell results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

DR-RINS: Digital real-time relative intensity noise suppressor for pump–probe spectroscopy and microscopy

Relative intensity noise (RIN) inherent in fiber lasers poses a serious obstacle to their use in pump–probe spectroscopy and imaging. RIN can be removed through an analog balanced detector, or, as we have previously shown, software adaptive noise cancellation (ANC) on digitized signals. One major drawback to software ANC is the added time required for digitizing and post-processing. In this article, we describe a design for ANC on a field-programmable gate array (FPGA), making use of high-level synthesis tools and fixed-point arithmetic to achieve real-time laser RIN suppression at 25 MHz sample rates. Unlike the software-ANC approach, the FPGA-ANC device can serve as a dedicated drop-in denoiser, placed between the detectors and a commercial lock-in amplifier. We demonstrate its application to transient absorption spectroscopy and microscopy, lowering the noise floor to ~17 dB above the shot noise limit. Furthermore, we demonstrate a dramatic improvement in data acquisition time from ~6 h to ~5 min in a real-time imaging scenario.

47 OTHER INSTRUMENTATION↗