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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

Using Piezoelectric Devices to Transmit Power through Walls

A method denoted wireless acoustic-electric feed-through (WAEF) has been conceived for transmitting power and/or data signals through walls or other solid objects made of a variety of elastic materials that could be electrically conductive or nonconductive. WAEF would make it unnecessary to use wires, optical fibers, tubes, or other discrete wall-penetrating signal-transmitting components, thereby eliminating the potential for structural weakening or leakage at such penetrations. Avoidance of such penetrations could be essential in some applications in which maintenance of pressure, vacuum, or chemical or biological isolation is required. In a basic WAEF setup, a transmitting piezoelectric transducer on one side of a wall would be driven at resonance to excite ultrasonic vibrations in the wall. A receiving piezoelectric transducer on the opposite side of the wall would convert the vibrations back to an ultrasonic AC electric signal, which would then be detected and otherwise processed in a manner that would depend on the modulation (if any) applied to the signal and whether the signal was used to transmit power, data, or both. An electromechanical-network model has been derived as a computationally efficient means of analyzing and designing a WAEF system. This model is a variant of a prior model, known in the piezoelectric-transducer art as Mason's equivalent-circuit model, in which the electrical and mechanical dynamics, including electromechanical couplings, are expressed as electrical circuit elements that can include inductors, capacitors, and lumped-parameter complex impedances. The real parts of the complex impedances are used to account for dielectric, mechanical, and coupling losses in all components (including all piezoelectric-transducer, wall, and intermediate material layers). In an application to a three-layer piezoelectric structure, this model was shown to yield the same results as do solutions of the wave equations of piezoelectricity and acoustic propagation in their full complexity.

Sherrit, Stewart↗
DOE OSTI2024

Smart Charge Management and Vehicle Grid Integration Deep Dive

The U.S. Department of Energy (DOE) Electric Vehicles at Scale Laboratory Consortium (EVs@Scale Lab Consortium) is accelerating research to support the establishment of a secure and scalable national network of charging infrastructure. Critical to this effort is an understanding of the potential grid impacts of EV charging and possible smart charge management (SCM) or vehicle-grid integration (VGI) capabilities that could mitigate these impacts. The EVs@Scale SCM/VGI Pillar is analyzing the impacts of EV charging and developing and demonstrating the capabilities of both SCM and VGI with many different vehicle use cases and grid scenarios. This deep dive discussion of the project encompasses the progress and future plans for the analysis components of the FUSE (Flexible charging to Unify the grid and transportation Sectors for Evs at scale) project.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Analytic Neural Network Gaussian Process Enabled Chance-Constrained Voltage Regulation for Active Distribution Systems with PVs, Batteries and EVs

This paper proposes an analytic neural network Gaussian process (NNGP)-based chance-constrained real-time voltage regulation method for active distribution systems with photovoltaics (PVs), batteries, and electric vehicles (EVs). NNGP can utilize historical measurement data to achieve real-time probabilistic node voltage estimation through Bayesian inference. Then, NNGP is fully analytically embedded into the optimal power flow model to perform voltage regulation and adapt to various topological changes. The uncertainties of voltage estimations are easily considered via the chance constraint, and it has been shown that the adoption of this chance constraint can significantly improve the reliability of voltage regulation under various scenarios. The comparison results with other methods, carried out on a real 759-node distribution system located in western Colorado, U.S., show that the proposed method can achieve accurate voltage estimation across different topologies and reliably perform voltage regulation considering PVs, batteries, and EVs.

active distribution systems↗
DOE OSTI2025

High-quality composite Pati-Salam axion

We present a composite QCD axion model where the Peccei-Quinn symmetry emerges as a high-quality, accidental symmetry. The axion potential is only modified by eight-fermion, dimension-12 operators, which if present at the Planck scale, allow for axion dark matter from misalignment while solving the strong 𝐶⁢𝑃 problem. The model is an SU⁡(𝑁 𝑐 ) gauge theory with ten flavors where the Pati-Salam unified subgroup SO⁡(6) × SO⁡(4) ⊂ SU⁢(10)𝐿 and Sp⁡(10) ⊂ SU⁢(10) 𝑅 are weakly gauged. The dynamics breaks SU⁢(10) 𝐿 × SU⁢(10) 𝑅 → SU⁢(10) 𝑉 and the weakly gauged groups to U⁡(3) × U⁡(2) ⊃ SU⁢(3) 𝑐 × SU⁢(2) 𝐿 × U⁡(1) 𝑌 , with the QCD axion identified as one of the Nambu-Goldstone bosons. This axion has a relatively large coupling to photons while a residual $\bar{𝜃}$ eff may be just below the current limit on the neutron electric dipole moment. If the dimension-12 operators are present near the grand unified theory scale, they can cause domain wall networks to decay, allowing for axion dark matter even for the postinflationary scenario.

Gherghetta, Tony [University of Minnesota, Minneap↗
DOE OSTI2024

7-8 GHz Point-to-Point Testing

Wireless spectrum is a limiting resource for continued economic growth in the United States. As discussed in the recent National Spectrum Strategy (NSS), wireless spectrum underpins several aspects of the U.S. economy and the demand for additional spectrum is driving the need for realizing spectrum sharing to enable continued development. At the same time, wireless spectrum is an essential foundation of critical energy infrastructure, including electric, oil, and natural gas resources. In particular, wireless point-to-point (P2P) links are the backbone of vast infrastructure networks that enable the flow of sensor and control information needed to manage critical energy sector infrastructure in the United States. These links will only become more important as the energy sector incorporates more diverse sensing and more efficient control mechanisms, which increases system complexity and data volume requiring more resilient communications. Therefore, the continued economic development of the U.S. depends on determining novel approaches to spectrum management that balance both broad access for advanced wireless technologies and resilience for critical infrastructure.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1980

A simple stripline design for uneven power split

A technique for the design of stripline or microstrip power dividers for unequal, but in-phase, power split is described. The output power ratio is determined by selecting the location of the input port in a manner analogous to the tap point for an electric power transformer. The technique yields a usable bandwidth of 7 to 8 percent and is attractive for tapered amplitude distribution networks for narrow band phased arrays.

Bailey, M. C.↗
NASA NTRS2010

Diagnosing Intermittent and Persistent Faults using Static Bayesian Networks

Both intermittent and persistent faults may occur in a wide range of systems. We present in this paper the introduction of intermittent fault handling techniques into ProDiagnose, an algorithm that previously only handled persistent faults. We discuss novel algorithmic techniques as well as how our static Bayesian networks help diagnose, in an integrated manner, a range of intermittent and persistent faults. Through experiments with data from the ADAPT electrical power system test bed, generated as part of the Second International Diagnostic Competition (DXC-10), we show that this novel variant of ProDiagnose diagnoses intermittent faults accurately and quickly, while maintaining strong performance on persistent faults.

Megshoel, Ole Jakob↗
NASA NTRSDate not supplied

Understanding Thermal Transport in Polymer –Silver Nanowire Composites

Understanding thermal transport across filler-polymer interfaces and filler-filler contacts within polymer composites is of great importance for better thermal design of the composites that are widely used in high-performance heat exchangers, energy storage devices, and flexible electronics. Over the past several decades, considerable progress has been made in improving the thermal conductivity of polymer composites, but several key questions concerning the influence of interfacial thermal resistance, or Kapitza resistance, still remain. Firstly, the thermal properties of these composites are highly dependent on thermal transport through the filler network and its contacts. For metallic nanofillers, the thermal conductivity is often estimated using the Wiedemann-Franz law based on electrical conductivity; however, it remains a question whether the Wiedemann-Franz law still holds at nanoscale contacts. Through investigation of silver nanowires of varying sizes, we were able to demonstrate that the Lorenz number for silver nanowire increases with decreasing nanowire diameter. Examination of the corresponding electrical and thermal conductivities indicate that these changes are due to that the relative contribution of phonons becomes more significant as a result of elastic stiffening. Furthermore, we show that for silver nanowires, the contact thermal resistance is ~8 times lower than that of multi-walled carbon nanotube (MWCNT) of similar diameters. Additionally, through systematic studies of electrospun polymer-silver nanowire composite nanofibers, we investigated the impact of interface morphology on the thermal conductivity enhancement of the composite system and probed the value of the Kapitza resistance for individual polymer-filler interfaces. For polymer nanofibers containing continuous, single silver nanowires, the thermal conductivity increases linearly with increasing volume fraction of silver, which is consistent with the prediction of percolation theory for samples above the percolation limit. By comparing this linear trend to the measured thermal conductivities of composite nanofibers with more complex structures, we were able to determine the resistance associated with any additional polymer-filler boundaries. In doing so we find that the thermal boundary resistance for polyvinylpyrrolidone (PVP)–silver interfaces is significantly lower than that of comparable polymer-MWCNT composite systems.Together our studies provide new insights into thermal transport in polymer nanocomposites and should help facilitate the design of high performance polymeric thermal interface material.

Thermal transport↗
NASA NTRSDate not supplied

Understanding Thermal Transport in Polymer - Silver Nanowire Composites

Understanding thermal transport across filler-polymer interfaces and filler-filler contacts within polymer composites is of great importance for better thermal design of the composites that are widely used in high-performance heat exchangers, energy storage devices, and flexible electronics. Over the past several decades, considerable progress has been made in improving the thermal conductivity of polymer composites, but several key questions concerning the influence of interfacial thermal resistance, or Kapitza resistance, still remain. Firstly, the thermal properties of these composites are highly dependent on thermal transport through the filler network and its contacts. For metallic nanofillers, the thermal conductivity is often estimated using the Wiedemann-Franz law based on electrical conductivity; however, it remains a question whether the Wiedemann-Franz law still holds at nanoscale contacts. Through investigation of silver nanowires of varying sizes, we were able to demonstrate that the Lorenz number for silver nanowire increases with decreasing nanowire diameter. Examination of the corresponding electrical and thermal conductivities indicate that these changes are due to that the relative contribution of phonons becomes more significant as a result of elastic stiffening. Furthermore, we show that for silver nanowires, the contact thermal resistance is ~8 times lower than that of multi-walled carbon nanotube (MWCNT) of similar diameters. Additionally, through systematic studies of electrospun polymer-silver nanowire composite nanofibers, we investigated the impact of interface morphology on the thermal conductivity enhancement of the composite system and probed the value of the Kapitza resistance for individual polymer-filler interfaces. For polymer nanofibers containing continuous, single silver nanowires, the thermal conductivity increases linearly with increasing volume fraction of silver, which is consistent with the prediction of percolation theory for samples above the percolation limit. By comparing this linear trend to the measured thermal conductivities of composite nanofibers with more complex structures, we were able to determine the resistance associated with any additional polymer-filler boundaries. In doing so we find that the thermal boundary resistance for polyvinylpyrrolidone (PVP)–silver interfaces is significantly lower than that of comparable polymer-MWCNT composite systems. Together our studies provide new insights into thermal transport in polymer nanocomposites and should help facilitate the design of high performance polymeric thermal interface material.

Matthew L. Fitzgerald↗
DOE OSTI2025

Wide‐Field Bond Quality Evaluation Using Frequency Domain Thermoreflectance with Deep Neural Network Feature Reconstruction

Heterogeneous integration of microelectronic components provides a pathway to improve circuit/component performance; however, this comes with assembly challenges, in particular due to complex interfaces via subsurface bump bonds. The ability of these bonds to transmit electrical signals and conduct heat to the carrier substrate limits component performance. In this work, hyperspectral frequency‐domain thermoreflectance (FDTR) imaging is demonstrated as a robust technique for evaluating the quality of subsurface indium bump bonds in a surrogate microelectronic sample. By performing microscale FDTR imaging with coarse motion image stitching, thermal phase maps that cover a 4 mm by 4 mm field‐of‐view with subsurface feature sensitivity at depths greater than 50 µm are obtained. The resulting FDTR hyperspectral data contains more than three million pixels and reveal the quality of subsurface microbump arrays. Wide‐field analysis of bonded versus gap regions is enabled by deep neural network feature reconstruction, that after training, rapidly provides an interpretable representation of bond quality. Utility of noisy higher frequency FDTR phase maps, i.e., near the computationally predicted sensing depth limit, results in an average prediction error of 11%. Taken together, FDTR with neural network‐based analysis demonstrates subsurface bond monitoring at length scales relevant for heterogeneously integrated microelectronics.

FDTR↗
DOE OSTI2024

Comparison of machine learning and electrical resistivity arrays to inverse modeling for locating and characterizing subsurface targets

Here, this study evaluates the performance of multiple machine learning (ML) algorithms and electrical resistivity (ER) arrays for inversion with comparison to a conventional Gauss-Newton numerical inversion method. Four different ML models and four arrays were used for the estimation of only six variables for locating and characterizing hypothetical subsurface targets. The combination of dipole-dipole with Multilayer Perceptron Neural Network (MLP-NN) had the highest accuracy. Evaluation showed that both MLP-NN and Gauss-Newton methods performed well for estimating the matrix resistivity while target resistivity accuracy was lower, and MLP-NN produced sharper contrast at target boundaries for the field and hypothetical data. Both methods exhibited comparable target characterization performance, whereas MLP-NN had increased accuracy compared to Gauss-Newton in prediction of target width and height, which was attributed to numerical smoothing present in the Gauss-Newton approach. MLP-NN was also applied to a field dataset acquired at U.S. DOE Hanford site.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Electrical design of the flexible imaging diffraction diagnostic for laser experiments (FIDDLE) at the National Ignition Facility (NIF)—Requirements, design, and performance

The Flexible Imaging Diffraction Diagnostic for Laser Experiments (FIDDLE) is a newly developed diagnostic for imaging time resolved diffraction in experiments at the National Ignition Facility (NIF). It builds on the successes of its predecessor, the Gated Diffraction Development Diagnostic (G3D). The FIDDLE was designed to support eight Daedalus version 2 sensors (six more hCMOS sensors than any other hCMOS-based diagnostic in NIF to date) and an integrated streak camera. We will review the electrical requirements, design, and performance of the electrical subsystems that were created to support this large number of cameras in the FIDDLE. The analysis of the data that the FIDDLE is intended to collect relies heavily on the accurate and well-understood timing of each sensor. We report camera-to-camera timing jitter of less than 100 ps rms and sensor integration times of 2.2 ns FWHM in 2-2 timing mode. Additionally, diffraction experiments on the NIF produce electric fields (EMI) on the order of 1 kV/m, which have been observed to negatively impact the performance of some electrical components of the FIDDLE. We report on the results of testing hCMOS camera electronics in a similar EMI environment generated in an offline lab. In addition, we also summarize the use of a novel approach to using a vector network analyzer as an EMI leak detector to understand and reduce the negative impacts of EMI on the FIDDLE.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Mechanisms enabling reconfigurability and long-term retention in vanadium oxide electrochemical memory

Phase coexistence in nanoscale electrochemical random-access memory (ECRAM) has recently been demonstrated to enable both information storage and extraordinary reconfigurability. These proof-of-principle demonstrations have left the mechanistic details of such a process unresolved. Particularly, the mechanisms that stabilize the multiple phases, and the underlying processes behind sustained memory retention, remain unclear, and are necessary to design such devices. Here we report microscale ECRAM devices composed of V⁢O𝑥, which enables us to directly probe the active region in an operando fashion using optical techniques. Using Raman mapping, we show the phase coexistence driven by the electrochemical injection of O vacancies to be spatially uniform (i.e., with no filaments). The stability was observed to be unusually long, with 1% loss over 14 years in ambient conditions. First-principles calculations of the oxygen vacancy formation energies in V⁢O 𝑥 further support the thermodynamic coexistence of multiple V⁢O 𝑥 phases and clarify the origin of the observed long-term retention in the ECRAM devices. Further, we demonstrate single devices that can be voltage programmed to exhibit synaptic, neuronal, and reconfigurable logic gate functionalities. Furthermore, we not only uncover the phase coexistence mechanism that may help device design, but also demonstrate the circuit-level applications of reconfigurability.

Electrical conductivity↗
DOE OSTI2026

Shuttling Majorana zero modes in disordered and noisy topological superconductors

The braiding of Majorana zero modes (MZMs) forms the fundamental building block for topological quantum computation. Braiding protocols which involve the physical exchange of MZMs are typically envisioned on a network of topological superconducting wires. An important component of these protocols is the transport of MZMs, which can be performed by using electric gates to locally tune sections of the wire between topologically trivial and nontrivial phases. In this work, we numerically simulate this transport by tuning a single section of a superconducting wire which contains either disorder (uncorrelated and correlated) or noise. We focus on the impact of these additional effects on the diabatic error, which describes unwanted transitions between the ground state and excited states. We show that the behavior of the average diabatic error is predominantly controlled by the statistics of the minimum bulk energy gap which is suppressed in the presence of disorder. The increase in diabatic error can be several orders of magnitude and is most deleterious when the disorder correlation length is a finite fraction of the transport distance and negligible when these lengths are far apart. In the presence of noise, the diabatic error is significantly enhanced due to optical transitions which depend on the minimum bulk energy gap as well as the frequency modes present in the noise. The results presented here serve to further characterize the diabatic error in disordered and noisy settings, which are important considerations in practical implementations of physical braiding schemes.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Digital Twin User Guide for Chelan County Public Utility District

This user manual offers a comprehensive guide for developing a Digital twin (DT) of a Kaplan turbine at Chelan County Public Utility District (Chelan PUD) using neural networks. As variable renewable generation expands, hydropower units must operate with optimal efficiency and stability. For Kaplan machines, this flexibility is achieved through coordinated control of guide vane (wicket gates) opening and runner blade pitch, which amplifies the plant’s inherent nonlinear behavior and challenges traditional physics-only modeling. The efficiency of the Kaplan turbine varies with different combinations of the guide vans (wicket gate) opening and the blade angle. Each guide van opening and blade angle has a corresponding highest efficiency point, forming a cam relationship that represents the optimal combination.The discharge of a hydraulic turbine is controlled by the opening angle of the guide vans. Therefore, for each value of head, there is a certain guide van opening and blade angle that corresponds to the highest efficiency. For a given head, different combinations of the guide van opening and blade angle have different efficiencies. Therefore, coordinate cam curves are used to describe the relationship between the wicket gate opening and blade angle with different water head. To address these challenges, the manual details a data-driven modeling and learning workflow centered on structured neural networks. The approach is designed to forecast critical operational variables—discharge flow, net head, penstock (or scroll-case) pressure, and generator electrical outputs—by leveraging real-time inputs such as the generator power control setpoint, exciter field current and field voltage, together with hydromechanical commands (e.g., gate position and, when available, runner blade-pitch angle). The neural models are trained and validated on operational data from a Kaplan unit operated by Chelan PUD, demonstrating that the structured NN architecture can learn the coupled gate–blade–electrical dynamics. The result is a robust DT that improves situational awareness and supports data-informed decision-making for Chelan PUD’s Kaplan turbine operations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1979

Further development and application of polycrystalline metal whiskers

High strength metal whiskers have a larger versatile field of application than monocrystalline whiskers. Although polycrystalline metal whiskers can be used for composites, preferably by extrusion in thermoplastics or by infiltration of resins or metals into whisker networks, the chief application at present may be the production and various use of whisker networks. Such networks can be produced up to high degrees of porosity and besides high mechanical strength, they have high inside surfaces and high electric conductivity. There are for instance, applications concerning construction of electrodes for batteries and fuel cells, catalysts and also new heat-exchanger material, capable of preparing fuel oil and gasoline in order to assist a high-efficiency combustion. The technical application of polycrystalline metal whiskers require their modification as well as the construction of a pilot production unit.

Schladitz, H. J.↗
NASA NTRS2009

Microwell Arrays for Studying Many Individual Cells

"Laboratory-on-a-chip" devices that enable the simultaneous culturing and interrogation of many individual living cells have been invented. Each such device includes a silicon nitride-coated silicon chip containing an array of micromachined wells sized so that each well can contain one cell in contact or proximity with a patch clamp or other suitable single-cell-interrogating device. At the bottom of each well is a hole, typically 0.5 m wide, that connects the well with one of many channels in a microfluidic network formed in a layer of poly(dimethylsiloxane) on the underside of the chip. The microfluidic network makes it possible to address wells (and, thus, cells) individually to supply them with selected biochemicals. The microfluidic channels also provide electrical contact to the bottoms of the wells.

Folch, Albert↗
NASA NTRS2018

An Overview of Science Challenges Pertaining to our Understanding of Extreme Geomagnetically Induced Currents

Vulnerability of man-made infrastructure to Earth-directed space weather events is a serious concern for today's technology-dependent society. Space weather-driven geomagnetically induced currents (GICs) can disrupt operation of extended electrically conducting technological systems. The threat of adverse impacts on critical technological infrastructure, like power grids, oil and gas pipelines, and communication networks, has sparked renewed interest in extreme space weather. Because extreme space weather events have low occurrence rate but potentially high impact, this presents a major challenge for our understanding of extreme GIC activity. In this chapter, we discuss some of the key science challenges pertaining to our understanding of extreme events. In addition, we present an overview of GICs including highlights of severe impacts over the last 80 years and recent U.S. Federal actions relevant to this community.

Ngwira, Chigomezyo M.↗