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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 1,639 records · Page 91
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Nanomaterials for Sensor Applications

A large part of the advances in nanotechnology have been directed towards the development of highspeed electronics, more efficient catalysts, and sensors. This latter group of applications has great relevance and unprecedented development potential for the coming years. Some of the main objectives for the development of sensors have focused on making more sensitive, effective and specific sensing devices. The improvement of these systems and the increase of specificity are clearly associated with a decrease in size of the components, which can lead to obtaining more rapid action, almost in real time. Nanomaterials currently used in sensor development include a long list of nanostructured systems, as for example: Metal nanotubes, nanowires, nanofibers, nanocomposites, nanorods, nanoparticles, nanostructured polymers, and different allotropes of carbon as carbon nanotubes, graphene or fullerenes, among others [1]. These nanomaterials are characterized by having unique physicochemical properties, including high electrical and thermal conductivity, extremely high surface area/volume ratio, high mechanical strength and even excellent catalytic properties [1] [2]. These materials, may exhibit relevant physicochemical behavior, such as quantization or electronic confinement effects, which can be used in the development of all kinds of sensors [2]. So far, sensors have been developed for determination and quantification of gases, radiation, biomolecules, microorganisms, etc. [2] [3]. The sensors developed so far usually use the system lock and key, wherein the selective receptor (lock) is selectively anchored to the analyte of interest (or key). This system has great limitations when analyzing the analyte in the presence of other analytes, which can alter the sensitivity or specificity of the measure, as occurs in sensors used in biomedical applications [3] [4]. One possible solution is based on the development of sensor arrays, consisting of a combination of different and specific sensors, which may enable simultaneous measurements of one or more analytes in a less favorable environment [5] in these cases. These sensors are now a reality, although there is still a long way to go before the levels of precision and accuracy are reached. Future challenges for the development and commercialization of efficient sensors are mainly focused on improving the specificity, reproducibility, and the ability to detect trace levels. We hope that in the coming years nanotechnology and nanomaterials allow reaching previously unimaginable advances in the development of these systems.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Ginsparg-Wilson Hamiltonians with Improved Chiral Symmetry

We construct a family of Ginsparg-Wilson Hamiltonians with improved chiral properties, starting from a construction of Creutz-Horvath-Neuberger that provides a doubler-free Hamiltonian lattice regularization for Dirac fermions in even spacetime dimensions. We use a higher-order generalization of the Ginsparg-Wilson relation due to Fujikawa, which yields an order-$k$ Hamiltonian overlap operator for each integer $k \geq 0$, with an exactly conserved but nonquantized chiral charge that becomes quantized as $k \to \infty$. Our construction provides physical insight into how Fujikawa's higher-order Ginsparg-Wilson relation improves chiral symmetry while reproducing the anomaly, highlighting the trade-offs inherent in any Hamiltonian lattice realization of an anomalous chiral symmetry. This class of Hamiltonian lattice regularizations, with their tunable chiral symmetry properties, offers potential advantages for quantum and tensor-network simulations.

Singh, Hersh [Fermilab]↗
DOE OSTI2025

Fast Machine Learning for Quantum Control of Microwave Qudits on Edge Hardware

Quantum optimal control is a promising approach to improve the accuracy of quantum gates, but it relies on complex algorithms to determine the best control settings. CPU or GPU-based approaches often have delays that are too long to be applied in practice. It is paramount to have systems with extremely low delays to quickly and with high fidelity adjust quantum hardware settings, where fidelity is defined as overlap with a target quantum state. Here, we utilize machine learning (ML) models to determine control-pulse parameters for preparing Selective Number-dependent Arbitrary Phase (SNAP) gates in microwave cavity qudits, which are multi-level quantum systems that serve as elementary computation units for quantum computing. The methodology involves data generation using classical optimization techniques, ML model development, design space exploration, and quantization for hardware implementation. Our results demonstrate the efficacy of the proposed approach, with optimized models achieving low gate trace infidelity near $10^{-3}$ and efficient utilization of programmable logic resources.

Sanders, Flor [Columbia U.]↗
DOE OSTI2025

Rapid Inference of Logic Gate Neural Networks for Anomaly Detection in High Energy Physics

The increasing data rates and complexity of detectors at the Large Hadron Collider (LHC) necessitate fast and efficient machine learning models, particularly for rapid selection of what data to store, known as triggering. Building on recent work in differentiable logic gates, we present a public implementation of a Convolutional Differentiable Logic Gate Neural Network (CLGN). We apply this to detecting anomalies at the Level-1 Trigger at CMS using public data from the CICADA project. We demonstrate that the CLGN achieves physics performance on par with or superior to conventional quantized neural networks. We also synthesize an LGN for a Field-Programmable Gate Array (FPGA) and show highly promising FPGA characteristics, notably zero Digital Signal Processor (DSP) resource usage. This work highlights the potential of logic gate networks for high-speed, on-detector inference in High Energy Physics and beyond.

FOS: Physical sciences↗
DOE OSTI2021

Deformed waveshape of quantum oscillation in magnetocaloric effect for layered organic superconductor.

Magnetocaloric effect for a layered organic superconductor beta ''-(BEDT-TTF)(2)SF5CH2CF2SO3 has been investigated. At low magnetic fields, a sinusoidal quantum oscillation, arising from a closed Fermi surface, is observed. As the field increases, the waveshape of the oscillation is strongly deformed and then sharp peaks emerge. The total energy including the Landau quantized states and the elastic energy of the leads holding the sample is calculated as a function of field strength and angle, and the minimum total energy, which determines the sample angle, is obtained as a function of field. The calculated results clarify that the deformation of the quantum oscillation is ascribed to a tilting effect of the sample by the magnetic torque.

Sugiura, Shiori↗
DOE OSTI2022

Supercurrent-Induced Weyl Superconductivity

Here, we show that Weyl superconductivity can be induced by finite supercurrent in noncentrosymmetric spin–orbit-coupled superconductors with line nodes. We introduce a three-dimensional tight-binding model of a tetragonal superconductor in a D+p-wave pairing state with a finite center-of-mass momentum, and elucidate that a line-nodal to point-nodal spectral transition occurs by applying an infinitesimal supercurrent. We also clarify that the higher-order effect in spin–orbit coupling is particularly important for this phenomenon. The point nodes are protected by topologically nontrivial Weyl charges, and therefore gapless arc states appear on the surface of the superconductor. Furthermore, both the positions and the Weyl charges of the point nodes depend on the direction of the current. In addition, a quantized Berry phase defined on high-symmetry planes characterizes the Weyl nodes when the in-plane supercurrent is considered. Our proposition paves a new way for controlling the superconducting gap structures by using an external field.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Quantum Gravity and Laser Interferometry: Towards Observable Predictions

Understanding quantum gravity remains one of the deepest challenges in modern physics, as direct experimental access to Planck-scale effects is beyond current technological reach. However, recent theoretical advances indicate that quantum fluctuations of spacetime may produce measurable effects in precision experiments, particularly near causal horizons. This opens new avenues for testing quantum gravity phenomena through high-precision measurement techniques. This dissertation develops multiple theoretical models to characterize these effects and examines their potential observational signatures in future gravitational wave interferometers. We begin by investigating the role of quantum fluctuations in near-horizon geometries through the lens of the AdS/CFT correspondence, which provides a powerful framework for understanding the interplay between quantum field theory and general relativity via holographic principles. By modeling stochastic energy-momentum sources in Rindler-AdS spacetime, we demonstrate that vacuum fluctuations transform the Einstein equations into a Langevin-type stochastic differential equation, leading to potentially observable fluctuations in photon traversal times. Extending this approach to Minkowski spacetime, we establish a correspondence between gravitational shockwaves and fluid dynamics, showing that near-horizon perturbations satisfy an equation analogous to that governing incompressible fluids, thereby reinforcing the membrane paradigm and hydrodynamic analogies in the context of the fluid/gravity duality. Furthermore, we construct the covariant phase space of a spherically symmetric causal diamond in Minkowski spacetime, identifying two fundamental charges that govern its evolution. These results provide a foundation for quantizing causal horizons and understanding their microscopic degrees of freedom. Building upon these theoretical developments, we further examine a related stochastic phenomenon: the gravitational wave memory background arising from the cumulative memory steps produced by supermassive black hole mergers. After reviewing the standard stochastic gravitational wave background, gravitational memory effects, and BMS symmetries, we model the stochastic memory background using a Brownian motion framework. We show that while the cumulative memory background initially appears above the sensitivity curve of space-based interferometers like LISA, the realistic subtraction of individually resolvable merger events substantially suppresses the residual signal, making its detection more challenging. This highlights the critical importance of source subtraction when evaluating the detectability of gravitational memory effects. By bridging fundamental theory with experimental prospects, this dissertation contributes to the ongoing effort to uncover the quantum nature of spacetime through precision measurement techniques. Whether through detecting quantum spacetime fluctuations, gravitational memory backgrounds, or probing the symmetries of causal horizons, the pursuit of observable quantum gravity phenomena continues to expand the frontiers of both theory and experiment.

Zhang, Yiwen [Caltech] (ORCID:0000000323559416)↗
NASA NTRS1967

Picture coding.

Picture coding systems and selection of pre- and post-quantizing filters

PICTURE↗
NASA NTRS1966

Gravitation and light

Gravitation and light-gravitational deflection, effect of photon spin, gravitational red shift, Maxwell and Einstein theories, and quantization of coupled Maxwell Einstein field

Joseph Weber↗
NASA NTRS1969

VICAR-DIGITAL image processing system

Computer program corrects various photometic, geometric and frequency response distortions in pictures. The program converts pictures to a number of elements, with each elements optical density quantized to a numerical value. The translated picture is recorded on magnetic tape in digital form for subsequent processing and enhancement by computer.

Billingsley, F.↗