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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Utah FORGE: Seismic Velocity Models, February 2021

This dataset contains a map, showing the Utah FORGE seismic stations, and seismic velocity model data. There are 61 1-D velocity models which are in a compressed TAR file. A paper is referenced at the end of this description which discusses the use of these data in 3D modelling. The paper summary follows: We expand the application of spatial autocorrelation (SPAC) from typical 1-D Vs profiles to quasi-3-D imaging via Bayesian Monte Carlo inversion (BMCI) using a dense nodal array (49 nodes) located at the Utah Frontier Observatory for Research in Geothermal Energy (FORGE) site. Combinations of 4 and 9 geophones in subarrays provide for 36 and 25 1-D Vs profiles, respectively. Profiles with error bars are determined by calculating coherency functions that fit observations in a frequency range of 0.2-5 Hz. Thus, a high-resolution quasi-3-D Vs model from the surface to 2.0 km depth is derived and shows that surface-parallel sedimentary strata deepen to the west, consistent with a 3-D seismic reflection survey. Moreover, the resulting Vs profile is consistent with a Vs profile derived from distributed acoustic sensing (DAS) data located in a borehole at the FORGE site. The quasi-3-D velocity model shows that the base of the basin dips ~22 degrees to the west and topography on the basement interface coincident with the Mag Lee Wash suggests that the bedrock interface is an unconformity. Reference: Zhang, H. and K. L. Pankow (2021). High-resolution Bayesian spatial auto-correlation (SPAC) pseudo-3D Vs model of Utah FORGE site with a dense geophone array, Geophys. Res. Int, https://doi.org/10.1093/gji/ggab049

15 GEOTHERMAL ENERGY↗
DOE OSTI2019

Slot waveguide with structural modulation

Apparatuses for communication or sensing are disclosed, the apparatuses comprising a substrate; a bottom cladding disposed on the substrate; a device layer disposed on the bottom cladding, wherein the device layer comprises: two substantially parallel rails extending from an input side to an output side of the device layer and configured to form a slot between the two substantially parallel rails, wherein each of the two substantially parallel rails comprises an inner edge adjacent to the slot and an outer edge opposite the slot; and one or more teeth coupled to each of the two substantially parallel rails; and a top cladding disposed onto the device layer and bottom cladding; wherein the bottom cladding, the device layer, and the top cladding are configured to support at least one optical guided mode. Other embodiments are described and claimed.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

Three paths toward the quantum angle operator

We examine mathematical questions around angle (or phase) operator associated with a number operator through a short list of basic requirements. We implement three methods of construction of quantum angle. The first one is based on operator theory and parallels the definition of angle for the upper half-circle through its cosine and completed by a sign inversion. The two other methods are integral quantization generalizing in a certain sense the Berezin–Klauder approaches. One method pertains to Weyl–Heisenberg integral quantization of the plane viewed as the phase space of the motion on the line. It depends on a family of “weight” functions on the plane. The third method rests upon coherent state quantization of the cylinder viewed as the phase space of the motion on the circle. The construction of these coherent states depends on a family of probability distributions on the line.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Multifunctional nanopore electrode array method for characterizing and manipulating single entities in attoliter-volume enclosures

Structurally regular nanopore arrays fabricated to contain independently controllable annular electrodes represent a new kind of architecture capable of electrochemically addressing small collections of matter—down to the single entity (molecule, particle, and biological cell) level. Furthermore, these nanopore electrode arrays (NEAs) can also be interrogated optically to achieve single entity spectroelectrochemistry. Larger entities such as nanoparticles and single bacterial cells are investigated by dark-field scattering and potential-controlled single-cell luminescence experiments, respectively, while NEA-confined molecules are probed by single molecule luminescence. By carrying out these experiments in arrays of identically constructed nanopores, massively parallel collections of single entities can be investigated simultaneously. The multilayer metal–insulator design of the NEAs enables highly efficient redox cycling experiments with large increases in analytical sensitivity for chemical sensing applications. NEAs may also be augmented with an additional orthogonally designed nanopore layer, such as a structured block copolymer, to achieve hierarchically organized multilayer structures with multiple stimulus-responsive transport control mechanisms. Finally, NEAs constructed with a transparent bottom layer permit optical access to the interior of the nanopore, which can result in the cutoff of far-field mode propagation, effectively trapping radiation in an ultrasmall volume inside the nanopore. Furthermore, the bottom metal layer may be used as both a working electrode and an optical cladding layer, thus, producing bifunctional electrochemical zero-mode waveguide architectures capable of carrying out spectroelectrochemical investigations down to the single molecule level.

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

Decentralized Carrier Phase Shifting for Optimal Harmonic Minimization in Asymmetric Parallel-Connected Inverters

This paper presents a carrier phase shifting technique for minimizing the aggregate harmonics in networks of asymmetric parallel-connected inverters for distributed power generation system applications. The proposed technique is: 1) implemented in a decentralized manner, relying only on local voltage and current measurements, and 2) optimal in the sense that it minimizes a cost function representing the carrier-frequency current harmonics. The analysis indicates that the proposed optimal carrier phase shifting technique can enable order-of-magnitude reductions in harmonic power, and also universal improvements compared to symmetric carrier interleaving for asymmetric inverter networks. Moreover, compared to existing methods that require either centralized communication or information exchange between inverters to coordinate carriers, the proposed technique is completely decentralized, which provides important practical benefits for implementation, including improved robustness and reduced cost. The technique is experimentally validated on a network of three single-phase 2-kW inverters and demonstrates a 36.5% reduction in the weighted total harmonic distortion factor of the aggregate inverter current, and the ability to converge to the optimal carrier phase spacing dynamically in less than one line frequency cycle (16.7 ms) in steady state and transient operating conditions.

42 ENGINEERING↗
DOE OSTI2015

Algebraic multigrid domain and range decomposition (AMG-DD / AMG-RD)*

In modern large-scale supercomputing applications, algebraic multigrid (AMG) is a leading choice for solving matrix equations. However, the high cost of communication relative to that of computation is a concern for the scalability of traditional implementations of AMG on emerging architectures. This paper introduces two new algebraic multilevel algorithms, algebraic multigrid domain decomposition (AMG-DD) and algebraic multigrid range decomposition (AMG-RD), that replace traditional AMG V-cycles with a fully overlapping domain decomposition approach. While the methods introduced here are similar in spirit to the geometric methods developed by Brandt and Diskin [Multigrid solvers on decomposed domains, in Domain Decomposition Methods in Science and Engineering, Contemp. Math. 157, AMS, Providence, RI, 1994, pp. 135--155], Mitchell [Electron. Trans. Numer. Anal., 6 (1997), pp. 224--233], and Bank and Holst [SIAM J. Sci. Comput., 22 (2000), pp. 1411--1443], they differ primarily in that they are purely algebraic: AMG-RD and AMG-DD trade communication for computation by forming global composite “grids” based only on the matrix, not the geometry. (As is the usual AMG convention, “grids” here should be taken only in the algebraic sense, regardless of whether or not it corresponds to any geometry.) Another important distinguishing feature of AMG-RD and AMG-DD is their novel residual communication process that enables effective parallel computation on composite grids, avoiding the all-to-all communication costs of the geometric methods. The main purpose of this paper is to study the potential of these two algebraic methods as possible alternatives to existing AMG approaches for future parallel machines. As a result, this paper develops some theoretical properties of these methods and reports on serial numerical tests of their convergence properties over a spectrum of problem parameters.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Low-Power Deep Learning Inference using the SpiNNaker Neuromorphic Platform

n this presentation we will discuss recent results on using the SpiNNaker neuromorphic platform (48-chip model) for deep learning neural network inference. We use the Sandia Labs developed Whet stone spiking deep learning library to train deep multi-layer perceptrons and convolutional neural networks suitable for the spiking substrate on the neural hardware architecture. By using the massively parallel nature of SpiNNaker, we are able to achieve, under certain network topologies, substantial network tiling and consequentially impressive inference throughput. Such high-throughput systems may have eventual application in remote sensing applications where large images need to be chipped, scanned, and processed quickly. Additionally, we explore complex topologies that push the limits of the SpiNNaker routing hardware and investigate how that impacts mapping software-implemented networks to on-hardware instantiations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Rapid discovery and evolution of nanosensors containing fluorogenic amino acids

Binding-activated optical sensors are powerful tools for imaging, diagnostics, and biomolecular sensing. However, biosensor discovery is slow and requires tedious steps in rational design, screening, and characterization. Here we report on a platform that streamlines biosensor discovery and unlocks directed nanosensor evolution through genetically encodable fluorogenic amino acids (FgAAs). Building on the classical knowledge-based semisynthetic approach, we engineer ~15 kDa nanosensors that recognize specific proteins, peptides, and small molecules with up to 100-fold fluorescence increases and subsecond kinetics, allowing real-time and wash-free target sensing and live-cell bioimaging. An optimized genetic code expansion chemistry with FgAAs further enables rapid (~3 h) ribosomal nanosensor discovery via the cell-free translation of hundreds of candidates in parallel and directed nanosensor evolution with improved variant-specific sensitivities (up to ~250-fold) for SARS-CoV-2 antigens. Altogether, this platform could accelerate the discovery of fluorogenic nanosensors and pave the way to modify proteins with other non-standard functionalities for diverse applications.

Biosensors↗
DOE OSTI2016

MULTI-SPACECRAFT OBSERVATIONS AND TRANSPORT MODELING OF ENERGETIC ELECTRONS FOR A SERIES OF SOLAR PARTICLE EVENTS IN AUGUST 2010

During 2010 August a series of solar particle events was observed by the two STEREO spacecraft as well as near-Earth spacecraft. The events, occurring on August 7, 14, and 18, originated from active regions 11093 and 11099. We combine in situ and remote-sensing observations with predictions from our model of three-dimensional anisotropic particle propagation in order to investigate the physical processes that caused the large angular spreads of energetic electrons during these events. In particular, we address the effects of the lateral transport of the electrons in the solar corona that is due to diffusion perpendicular to the average magnetic field in the interplanetary medium. We also study the influence of two coronal mass ejections and associated shock waves on the electron propagation, and a possible time variation of the transport conditions during the above period. For the August 18 event we also utilize electron observations from the MESSENGER spacecraft at a distance of 0.31 au from the Sun for an attempt to separate between radial and longitudinal dependencies in the transport process. Our modelings show that the parallel and perpendicular diffusion mean free paths of electrons can vary significantly not only as a function of the radial distance, but also of the heliospheric longitude. Normalized to a distance of 1 au, we derive values of λ {sub ∥} in the range of 0.15–0.6 au, and values of λ {sub ⊥} in the range of 0.005–0.01 au. We discuss how our results relate to various theoretical models for perpendicular diffusion, and whether there might be a functional relationship between the perpendicular and the parallel mean free path.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Enhancement-mode two-channel triple quantum dot from an undoped Si/Si 0.8 Ge 0.2 quantum well hetero-structure

Here, we demonstrate coupled triple dot operation and charge sensing capability for the recently introduced quantum dot technology employing undoped Si/Si 0.8 Ge 0.2 hetero-structures which also incorporate a single metal-gate layer to simplify fabrication. Si/SiGe hetero-structures with a Ge concentration of 20% rather than the more usual 30% typically encountered offer higher electron mobility. The devices consist of two in-plane parallel electron channels that host a double dot in one channel and a single dot in the other channel. In a device where the channels are sufficiently close a triple dot in a triangular configuration is induced leading to regions in the charge stability diagram where three charge-addition lines of different slope approach each other and anti-cross. In a device where the channels are further apart, the single dot charge-senses the double dot with relative change of ~2% in the sensor current.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Fully Inkjet‐Printed, 2D Materials‐Based Field‐Effect Transistor for Water Sensing

Abstract Despite significant progress in solution‐processing of 2D materials, it remains challenging to reliably print high‐performance semiconducting channels that can be efficiently modulated in a field‐effect transistor (FET). Herein, electrochemically exfoliated MoS 2 nanosheets are inkjet‐printed into ultrathin semiconducting channels, resulting in high on/off current ratios up to 10 3 . The reported printing strategy is reliable and general for thin film channel fabrication even in the presence of the ubiquitous coffee‐ring effect. Statistical modeling analysis on the printed pattern profiles suggests that a spaced parallel printing approach can overcome the coffee‐ring effect during inkjet printing, resulting in uniform 2D flake percolation networks. The uniformity of the printed features allows the MoS 2 channel to be hundreds of micrometers long, which easily accommodates the typical inkjet printing resolution of tens of micrometers, thereby enabling fully printed FETs. As a proof of concept, FET water sensors are demonstrated using printed MoS 2 as the FET channel, and printed graphene as the electrodes and the sensing area. After functionalization of the sensing area, the printed water sensor shows a selective response to Pb 2+ in water down to 2 ppb. This work paves the way for additive nanomanufacturing of FET‐based sensors and related devices using 2D nanomaterials.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Ground motion response to an ML 4.3 earthquake using co-located distributed acoustic sensing and seismometer arrays

The PoroTomo research team deployed two arrays of seismic sensors in a natural laboratory at Brady Hot Springs, Nevada in March 2016. The 1500 m (length) by 500 m (width) by 400 m (depth) volume of the laboratory overlies a geothermal reservoir. The surface Distributed Acoustic Sensing (DAS) array consisted of 8700 m of fiber-optic cable in a shallow trench, including 340 m in a well. The conventional seismometer array consisted of 238 three- component geophones. The DAS cable was laid out in three parallel zig-zag lines with line segments approximately 100 meters in length and geophones were spaced at approximately 60- meter intervals. Both DAS and conventional geophones recorded continuously over 15 days during which a moderate-sized earthquake with a local magnitude of 4.3 was recorded on March 21, 2016. Its epicenter was approximately 150-km south-southeast of the laboratory. Several DAS line segments with co-located geophone stations were used to compare signal-to-noise (SNR) ratios in both time and frequency domains and to test relationships between DAS and geophone data. The ratios were typically within a factor of five of each other with DAS SNR often greater for P-wave but smaller for S-wave relative to geophone SNR. The SNRs measured for an earthquake can be better than for active sources, because the earthquake signal contains more low frequency energy and the noise level is also lower at those lower frequencies. Amplitudes of the sum of several DAS strain-rate waveforms matched the finite difference of two geophone waveforms reasonably well, as did the amplitudes of DAS strain waveforms with particle-velocity waveforms recorded by geophones. Similar agreement was found between DAS and geophone observations and synthetic strain seismograms. In conclusion, the combination of good SNR in the seismic frequency band, high-spatial density, large N, and highly accurate time control among individual sensors suggests that DAS arrays have potential to assume a role in earthquake seismology.

60 signal-to-noise ratio↗
DOE OSTI2016

Heating and acceleration of solar wind ions by turbulent wave spectrum in inhomogeneous expanding plasma

Near the Sun (< 10R{sub s}) the acceleration, heating, and propagation of the solar wind are likely affected by the background inhomogeneities of the magnetized plasma. The heating and the acceleration of the solar wind ions by turbulent wave spectrum in inhomogeneous plasma is studied using a 2.5D hybrid model. The hybrid model describes the kinetics of the ions, while the electrons are modeled as massless neutralizing fluid in an expanding box approach. Turbulent magnetic fluctuations dominated by power-law frequency spectra, which are evident from in-situ as well as remote sensing measurements, are used in our models. The effects of background density inhomogeneity across the magnetic field on the resonant ion heating are studied. The effect of super-Alfvénic ion drift on the ion heating is investigated. It is found that the turbulent wave spectrum of initially parallel propagating waves cascades to oblique modes, and leads to enhanced resonant ion heating due to the inhomogeneity. The acceleration of the solar wind ions is achieved by the parametric instability of large amplitude waves in the spectrum, and is also affected by the inhomogeneity. The results of the study provide the ion temperature anisotropy and drift velocity temporal evolution due to relaxation of the instability. The non-Maxwellian velocity distribution functions (VDFs) of the ions are modeled in the inhomogeneous solar wind plasma in the acceleration region close to the Sun.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

All-Ceramic Passive Wireless Temperature Sensor Realized by Tin-Doped Indium Oxide (ITO) Electrodes for Harsh Environment Applications

In this work, an all-ceramic passive wireless inductor–capacitor (LC) resonator was presented for stable temperature sensing up to 1200 °C in air. Instead of using conventional metallic electrodes, the LC resonators are modeled and fabricated with thermally stable and highly electroconductive ceramic oxide. The LC resonator was modeled in ANSYS HFSS to operate in a low-frequency region (50 MHz) within 50 × 50 mm geometry using the actual material properties of the circuit elements. The LC resonator was composed of a parallel plate capacitor coupled with a planar inductor deposited on an Al2O3 substrate using screen-printing, and the ceramic pattern was sintered at 1250 °C for 4 h in an ambient atmosphere. The sensitivity (average change in resonant frequency with respect to temperature) from 200–1200 °C was ~170 kHz/°C. The temperature-dependent electrical conductivity of the tin-doped indium oxide (ITO, 10% SnO2 doping) on the quality factor showed an increase of Qf from 36 to 43 between 200 °C and 1200 °C. The proposed ITO electrodes displayed improved sensitivity and quality factor at elevated temperatures, proving them to be an excellent candidate for temperature sensing in harsh environments. The microstructural analysis of the co-sintered LC resonator was performed using a scanning electron microscope (SEM) which showed that there are no cross-sectional and topographical defects after several thermal treatments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Real-Time GPU-Accelerated OFDR With an Integrated Auxiliary Interferometer

A GPU-accelerated optical frequency domain reflectometry (OFDR) system with an improved integrated auxiliary interferometer is proposed. Unlike conventional approaches that require separate auxiliary interferometers and multiple detection channels, the proposed OFDR system embeds this functionality directly into the signal via an intentional beat component. This enables self-calibration of laser nonlinearity while maintaining a cost-effective hardware configuration. Building on this simplified configuration, the system leverages GPU acceleration with an NVIDIA RTX 4070 Ti to achieve real-time performance, delivering high-throughput signal processing for continuous OFDR interrogation. The signal processing pipeline comprises signal capture, resampling for nonlinearity compensation, and frequency shift computation, all optimized for parallel execution. Hardware benchmarking demonstrates substantial acceleration over CPU implementations, achieving up to a 45× speedup for resampling and frequency shift computations and enabling processing latencies below 30 ms. Thermal response validation is conducted under two complementary scenarios: localized heating using a water bath and cryogenic-temperature conditions using liquid nitrogen. Under localized heating, the system achieves an accuracy of 0.249 °C with a thermal sensitivity of 5.971 GHz/°C, while cryogenic-temperature validation demonstrates a frequency shift response with a sensitivity of 2.383 GHz/°C and an accuracy of 2.04 °C. The high acceleration of the proposed GPU-accelerated OFDR system and its accuracy are achieved by exploiting CUDA-based stride indexing, enabling efficient parallel segmentation and processing of large datasets without additional memory copies. The benchmarking results confirm the robustness, accuracy, and deployability of the proposed OFDR system across a wide temperature range, establishing it as a practical platform for real-time distributed fiber sensing in structurally dynamic environments.

Harb, Salah [Lawrence Berkeley National Laboratory↗
DOE OSTI2018

Effect of curvature in the magnetic shear profile on micro-tearing modes in the tokamak pedestal

The pedestal region of a tokamak plasma differs from the core in several respects. This work emphasizes the magnetic shear profile in the pedestal which is distinctive for two reasons: the pedestal is close to a magnetic-field separatrix so that the q-profile is intrinsically steep, and the steep pedestal gradients cause a peak in the bootstrap current with obvious effects on q(r). In fact, the pedestal q-profile has a complicated structure yielding a curved magnetic shear profile. Global linear simulations suggest that such a q-profile could substantially affect the nature of micro-instabilities. Here, this paper analytically investigates this special feature of the pedestal, after appropriately modifying the slab-model field equations to allow for more complicated variation of the parallel wave vector. Surprisingly, the departure from a locally linear q profile (flat magnetic shear), even when small, supports a qualitatively novel mode whose width is fixed by curvature in the profile. The mode is unstable; its substantial growth rate is robust in the sense of persisting even when the q-profile modification is assumed to be small. However, this mode, originating from details of the q-profile, will not be found in a typical local ballooning gyrokinetic simulation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Computable and Operationally Meaningful Multipartite Entanglement Measures

Multipartite entanglement is an essential resource for quantum communication, quantum computing, quantum sensing, and quantum networks. The utility of a quantum state |ψ$\rangle$ for these applications is often directly related to the degree or type of entanglement present in |ψ$\rangle$. Therefore, efficiently quantifying and characterizing multipartite entanglement is of paramount importance. Here, in this work, we introduce a family of multipartite entanglement measures, called concentratable entanglements. Several well-known entanglement measures are recovered as special cases of our family of measures, and hence we provide a general framework for quantifying multipartite entanglement. We prove that the entire family does not increase, on average, under local operations and classical communications. We also provide an operational meaning for these measures in terms of probabilistic concentration of entanglement into Bell pairs. Finally, we show that these quantities can be efficiently estimated on a quantum computer by implementing a parallelized SWAP test, opening up a research direction for measuring multipartite entanglement on quantum devices.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Convolutional networks for vehicle track segmentation

Existing methods to detect vehicle tracks in coherent change detection images, a product of combining two synthetic aperture radar images taken at different times of the same scene, rely on simple, fast models to label track pixels. These models, however, are unable to capture natural track features such as continuity and parallelism. More powerful, but computationally expensive models can be used in offline settings. We present an approach that uses dilated convolutional networks consisting of a series of 3-by-3 convolutions to segment vehicle tracks. The design of our networks considers the fact that remote sensing applications tend to operate in low power and have limited training data. As a result, we aim for small, efficient networks that can be trained end-to-end to learn natural track features entirely from limited training data. We demonstrate that our 6-layer network, trained on just 90 images, is computationally efficient and improves the F-score on a standard dataset to 0.992, up from 0.959 obtained by the current state-of-the-art method.

47 OTHER INSTRUMENTATION↗