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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
NASA NTRS1979

On the Performance of the Martin Digital Filter for High- and Low-pass Applications

A nonrecursive numerical filter is described in which the weighting sequence is optimized by minimizing the excursion from the ideal rectangular filter in a least squares sense over the entire domain of normalized frequency. Additional corrections to the weights in order to reduce overshoot oscillations (Gibbs phenomenon) and to insure unity gain at zero frequency for the low pass filter are incorporated. The filter is characterized by a zero phase shift for all frequencies (due to a symmetric weighting sequence), a finite memory and stability, and it may readily be transformed to a high pass filter. Equations for the filter weights and the frequency response function are presented, and applications to high and low pass filtering are examined. A discussion of optimization of high pass filter parameters for a rather stringent response requirement is given in an application to the removal of aircraft low frequency oscillations superimposed on remotely sensed ocean surface profiles. Several frequency response functions are displayed, both in normalized frequency space and in period space. A comparison of the performance of the Martin filter with some other commonly used low pass digital filters is provided in an application to oceanographic data.

Mcclain, C. R.↗
DOE OSTI2023

Recent Advancements in Reconfigurable mmWave Devices Based on Phase-Change and Metal Insulator Transition Materials

Chalcogenide Phase Change Materials (PCM) and metal insulator transition (MIT) materials are a group of materials that are capable of switching between low resistance and high resistance states. These emerging materials have been widely used in optical storage media and memory devices. Over the past recent years, there have been interests in exploiting the PCM and MIT materials, especially germanium antimony telluride (GST) alloys and vanadium dioxide (VO 2 ), for radio frequency (RF) applications. The PCM and MIT-based RF devices are expected to bridge the gap between semiconductor switches and microelectromechanical system (MEMS) switches as they combine the low insertion loss performance of MEMS technology and the small size and reliability performance of semiconductor technology. This article presents an overview of the PCM and MIT materials for RF circuits and discusses the recent advancements in reconfigurable millimeter-wave (mmWave) devices based on PCM and MIT materials in depth.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Hybrid stochastic synapses enabled by scaled ferroelectric field-effect transistors

Achieving brain-like density and performance in neuromorphic computers necessitates scaling down the size of nanodevices emulating neuro-synaptic functionalities. However, scaling nanodevices results in reduction of programming resolution and emergence of stochastic non-idealities. While prior work has mainly focused on binary transitions, in this work, we leverage the stochastic switching of a three-state ferroelectric field-effect transistor to implement a long-term and short-term two-tier stochastic synaptic memory with a single device. Experimental measurements are performed on a scaled 28 nm high-k metal gate technology-based device to develop a probabilistic model of the hybrid stochastic synapse. In addition to the advantage of ultra-low programming energies afforded by scaling, our hardware–algorithm co-design analysis reveals the efficacy of the two-tier memory in comparison to binary stochastic synapses in on-chip learning tasks—paving the way for algorithms exploiting multi-state devices with probabilistic transitions beyond deterministic ones.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2018

Highly scalable distributed-memory sparse triangular solution algorithms.

This paper presents a highly efficient distributed-memory parallel sparse triangular solver. The triangular solution phase is often performed following factorization phase in the sparse linear solvers and has become increasingly computa­tionally expensive for direct solvers with many right hand sides (RHSs) or preconditioned iterative solvers. However, the low arithmetic intensity and sequential nature of the triangular solve algorithm pose performance challenges for its large-scale distributed-memory parallelization. In this work, we propose several strategies to enhance scalability of an algorithm with 2D block cyclic process layout. First, an asynchronous binary-tree-based communication scheme implemented via non-blocking MPI functions is leveraged to broadcast partial solutions and reduce partial updates among a subset of processes for each block column and row of the triangular matrix, respectively. This scheme reduces message latency, improves communication load balance and significantly accelerates asynchronous execution of the triangular solve. In addition, efficient BLAS operations and threading implementations are exploited to accelerate local computations and further reduce process idle time. The proposed strategies are implemented in SuperLU_DIST and numerical experiments show up to 4.4x improvement with one right-hand side and up to 6.1x improvement with 50 right- hand sides on 4096 processes, compared to the current release. This is the first time that sparse triangular solution is demonstrated strong scaling on more than 4000 cores.

Liu, Yang↗
DOE OSTI2022

Towards Superior Software Portability with SHAD and HPX C++ Libraries

As hardware architectures and software stacks complexity grows, development productivity, performance and software portability, quickly evolve from desirable features to actual needs. SHAD, the Scalable High-performance Algorithms and Data-structures C++ library is designed to mitigate these issues: it provides general purpose building blocks as well as high-level custom utilities, and offers a shared-memory programming abstraction which facilitates the programming of complex systems, scaling up to High Performance Computing clusters. SHAD’s portability is achieved through an abstract runtime interface, which decouples the upper layers of the library and hides the low level details of the underlying architecture. This layer enables SHAD to interface with different runtime/threading systems, e.g. Intel TBB and Global Memory and Threading (GMT). However, current backends targeting distributed systems, rely on a centralized controller which may possibly limit scalability up to hundreds of nodes and creates a network hot spot due to all to one communication for synchronization, and possibly resulting in degraded performance at high process counts. In this research, we explore HPX, the C++ standard library for parallelism and concurrency, as an additional backend in support of the SHAD library, and present the methodologies in support of local and remote task executions in SHAD with respect to HPX. Finally, we evaluate the proposed system by comparing against existing backends of SHAD and analyzing their performance on C++ Standard Template Library algorithms.

Wu, Nanmiao↗
DOE OSTI2024

Strain Fluctuations Unlock Ferroelectricity in Wurtzites

Ferroelectrics are of practical interest for non-volatile data storage due to their reorientable, crystallographically defined polarization. Yet efforts to integrate conventional ferroelectrics into ultrathin memories have been frustrated by film-thickness limitations, which impede polarization reversal under low applied voltage. Wurtzite materials, including magnesium-substituted zinc oxide (Zn,Mg)O, have been shown to exhibit scalable ferroelectricity as thin films. In this work, the origins of ferroelectricity in (Zn,Mg)O are explained, showing that large strain fluctuations emerge locally in (Zn,Mg)O and can reduce local barriers to ferroelectric switching by more than 40%. Concurrent experimental and computational evidence of these effects are provided by demonstrating polarization switching in ZnO/(Zn,Mg)O/ZnO heterostructures featuring built-in interfacial strain gradients. These results open up an avenue to develop scalable ferroelectrics by controlling strain fluctuations atomistically.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Prefrontal white matter pathology in air pollution exposed Mexico City young urbanites and their potential impact on neurovascular unit dysfunction and the development of Alzheimer's disease

Millions of urban children are chronically exposed to high concentrations of air pollutants, i.e., fine particulate matter (PM{sub 2.5}) and ozone, associated with increased risk for Alzheimer's disease. Compared with children living with clear air those in Mexico City (MC) exhibit systemic, brain and intrathecal inflammation, low CSF Aβ{sub 42,} breakdown of the BBB, attention and short-term memory deficits, prefrontal white matter hyperintensities, damage to epithelial and endothelial barriers, tight junction and neural autoantibodies, and Alzheimer and Parkinson's hallmarks. The prefrontal white matter is a target of air pollution. We examined by light and electron microscopy the prefrontal white matter of MC dogs (n: 15, age 3.17±0.74 years), children and teens (n: 34, age: 12.64±4.2 years) versus controls. Major findings in MC residents included leaking capillaries and small arterioles with extravascular lipids and erythrocytes, lipofuscin in pericytes, smooth muscle and endothelial cells (EC), thickening of cerebrovascular basement membranes with small deposits of amyloid, patchy absence of the perivascular glial sheet, enlarged Virchow–Robin spaces and nanosize particles (20–48 nm) in EC, basement membranes, axons and dendrites. Tight junctions, a key component of the neurovascular unit (NVU) were abnormal in MC versus control dogs (χ{sup 2}<0.0001), and white matter perivascular damage was significantly worse in MC dogs (p=0.002). The integrity of the NVU, an interactive network of vascular, glial and neuronal cells is compromised in MC young residents. Characterizing the early NVU damage and identifying biomarkers of neurovascular dysfunction may provide a fresh insight into Alzheimer pathogenesis and open opportunities for pediatric neuroprotection. - Highlights: • The prefrontal white matter is a target of air pollution. • Tight junctions, key neurovascular unit elements, are abnormal in young urbanites. • Identifying neurovascular dysfunction biomarkers is key for pediatric neuroprotection. • Early characterization of NVU damage may provide a fresh insight into AD pathogenesis.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

A Preprocessing Tool for Enhanced Ion Mobility–Mass Spectrometry-Based Omics Workflows

The ability to improve the data quality of ion mobility–mass spectrometry (IM-MS) measurements is of great importance for enabling modular and efficient computational workflows and gaining better qualitative and quantitative insights from complex biological and environmental samples. We developed the PNNL PreProcessor, a standalone and user-friendly software housing various algorithmic implementations to generate new MS-files with enhanced signal quality and in the same instrument format. Different experimental approaches are supported for IM-MS based on Drift-Tube (DT) and Structures for Lossless Ion Manipulations (SLIM), including liquid chromatography (LC) and infusion analyses. The algorithms extend the dynamic range of the detection system, while reducing file sizes for faster and memory-efficient downstream processing. Specifically, multidimensional smoothing improves peak shapes of poorly defined low-abundance signals, and saturation repair reconstructs the intensity profile of high-abundance peaks from various analyte types. Further, other functionalities are data compression and interpolation, IM demultiplexing, noise filtering by low intensity threshold and spike removal, and exporting of acquisition metadata. Several advantages of the tool are illustrated, including an increase of 19.4% in lipid annotations and a two-times faster processing of LC-DT IM-MS data-independent acquisition spectra from a complex lipid extract of a standard human plasma sample. The software is freely available at https://omics.pnl.gov/software/pnnl-preprocessor.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Revealing the structure and electronic characteristics of Te-rich threshold switching materials for high-density integration

Ovonic threshold switching (OTS) selectors play an important role in the integration of advanced three-dimensional memory. Selectors based on tellurium (Te)-containing materials exhibit significant promise due to their low threshold voltages and superior consistency. Here we have theoretically studied the structure and electronic properties of a typical OTS material, amorphous GeTe 6 , to explore the switching mechanisms using ab initio molecular dynamics simulations. The results indicate that Ge atoms tend to bond with Te atoms, forming stable chemical bonds. The Te-centered clusters are predominantly in the form of distorted octahedrons, while the Ge-centered clusters are in the form of both octahedrons and tetrahedrons. Notably, the proportion of tetrahedrons within the 4-coordinated Ge-centered clusters reaches an impressive 66.9%. These tetrahedrons are randomly dispersed throughout the simulated cell, leading to a stable amorphous configuration. The mid-gap state observed in the mobility bandgap originates from the atomic chain composed of both over-coordinated Ge and Te atoms. It is the inherent stability of the chemical environment within amorphous GeTe 6 that enables it to maintain its amorphous phase under a repeated threshold voltage, a characteristic that distinguishes it from non-OTS materials, such as amorphous tellurium. Furthermore, our findings provide an in-depth understanding of the structure and electronic characteristics of amorphous GeTe 6 , which can promote the design and application of the Te-rich threshold switching materials.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Threshold-voltage modulated phase change heterojunction for application of high density memory

Phase change random access memory is one of the most important candidates for the next generation non-volatile memory technology. However, the ability to reduce its memory size is compromised by the fundamental limitations inherent in the CMOS technology. While 0T1R configuration without any additional access transistor shows great advantages in improving the storage density, the leakage current and small operation window limit its application in large-scale arrays. In this work, phase change heterojunction based on GeTe and n-Si is fabricated to address those problems. The relationship between threshold voltage and doping concentration is investigated, and energy band diagrams and X-ray photoelectron spectroscopy measurements are provided to explain the results. The threshold voltage is modulated to provide a large operational window based on this relationship. The switching performance of the heterojunction is also tested, showing a good reverse characteristic, which could effectively decrease the leakage current. Furthermore, a reliable read-write-erase function is achieved during the tests. Phase change heterojunction is proposed for high-density memory, showing some notable advantages, such as modulated threshold voltage, large operational window, and low leakage current.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Implementation of a Binary Neural Network on a Passive Array of Magnetic Tunnel Junctions

The increasing scale of neural networks and their growing application space have produced demand for more energy- and memory-efficient artificial-intelligence-specific hardware. Avenues to mitigate the main issue, the von Neumann bottleneck, include in-memory and near-memory architectures, as well as algorithmic approaches. In this report we leverage the low-power and the inherently binary operation of magnetic tunnel junctions (MTJs) to demonstrate neural network hardware inference based on passive arrays of MTJs. In general, transferring a trained network model to hardware for inference is confronted by degradation in performance due to device-to-device variations, write errors, parasitic resistance, and nonidealities in the substrate. To quantify the effect of these hardware realities, we benchmark 300 unique weight matrix solutions of a two-layer perceptron to classify the Wine dataset for both classification accuracy and write fidelity. Despite device imperfections, we achieve software-equivalent accuracy of up to 95.3% with proper tuning of network parameters in 15 x 15 MTJ arrays having a range of device sizes. The success of this tuning process shows that new metrics are needed to characterize the performance and quality of networks reproduced in mixed signal hardware.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Real-time data analysis for medical diagnosis using FPGA-accelerated neural networks

Real-time analysis of patient data during medical procedures can provide vital diagnostic feedback that significantly improves chances of success. With sensors becoming increasingly fast, frameworks such as Deep Neural Networks are required to perform calculations within the strict timing constraints for real-time operation. However, traditional computing platforms responsible for running these algorithms incur a large overhead due to communication protocols, memory accesses, and static (often generic) architectures. In this work, we implement a low-latency Multi-Layer Perceptron (MLP) processor using Field Programmable Gate Arrays (FPGAs). Unlike CPUs and Graphics Processing Units (GPUs), our FPGA-based design can directly interface sensors, storage devices, display devices and even actuators, thus reducing the delays of data movement between ports and compute pipelines. Moreover, the compute pipelines themselves are tailored specifically to the application, improving resource utilization and reducing idle cycles. We demonstrate the effectiveness of our approach using mass-spectrometry data sets for real-time cancer detection. We demonstrate that correct parameter sizing, based on the application, can reduce latency by 20% on average. Furthermore, we show that in an application with tightly coupled data-path and latency constraints, having a large amount of computing resources can actually reduce performance. Using mass-spectrometry benchmarks, we show that our proposed FPGA design outperforms both CPU and GPU implementations, with an average speedup of 144x and 21x, respectively. In our work, we demonstrate the importance of application-specific optimizations in order to minimize latency and maximize resource utilization for MLP inference. By directly interfacing and processing sensor data with ultra-low latency, FPGAs can perform real-time analysis during procedures and provide diagnostic feedback that can be critical to achieving higher percentages of successful patient outcomes.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

A Synoptic VLBI Technique for Localizing Nonrepeating Fast Radio Bursts with CHIME/FRB

We demonstrate the blind interferometric detection and localization of two fast radio bursts (FRBs) with subarcminute precision on the 400 m baseline between the Canadian Hydrogen Intensity Mapping Experiment (CHIME) and the CHIME Pathfinder. In the same spirit as Very Long Baseline Interferometry (VLBI), the telescopes were synchronized to separate clocks, and the channelized voltage (herein referred to as baseband) data were saved to a disk with correlation performed offline. The simultaneous wide field of view and high sensitivity required for blind FRB searches implies a high data rate—6.5 terabits per second (Tb/s) for CHIME and 0.8 Tb s{sup −1} for the Pathfinder. Since such high data rates cannot be continuously saved, we buffer data from both telescopes locally in memory for ≈40 s, and write to the disk upon receipt of a low-latency trigger from the CHIME Fast Radio Burst Instrument (CHIME/FRB). The ≈200 deg{sup 2} field of view of the two telescopes allows us to use in-field calibrators to synchronize the two telescopes without needing either separate calibrator observations or an atomic timing standard. In addition to our FRB observations, we analyze bright single pulses from the pulsars B0329+54 and B0355+54 to characterize systematic localization errors. Our results demonstrate the successful implementation of key software, triggering, and calibration challenges for CHIME/FRB Outriggers: cylindrical VLBI outrigger telescopes which, along with the CHIME telescope, will localize thousands of single FRB events with sufficient precision to unambiguously associate a host galaxy with each burst.

47 OTHER INSTRUMENTATION↗
NASA NTRS1985

Advanced detectors and signal processing for bubble memories

The feasibility of combining silicon and magnetic bubble technologies is demonstrated. Results of bubble film annealing indicate that a low temperature silicon on garnet technology is the most likely one to succeed commercially. Annealing ambients are also shown to have a major effect on the magnetic properties of bubble films. Functional MOSFETs were fabricated on bubble films coated with thick (approximately 1 micron) SiO2 layers. The two main problems with these silicon on garnet MOSFETs are low electron mobilities and large gate leakage currents. Results indicate that the laser recrystallized silicon and gate oxide (SiO2) layers are contaminated. The data suggest that part of the contaminating ions originate in the sputtered oxide spacer layer and part originates in the bubble film itself. A diffusion barrier, such as silicon nitride, placed between the bubble film and the silicon layer should eliminate the contamination induced problem.

Kryder, M. H.↗
NASA NTRS2008

Improved Linear Algebra Methods for Redshift Computation from Limited Spectrum Data - II

Given photometric broadband measurements of a galaxy, Gaussian processes may be used with a training set to solve the regression problem of approximating the redshift of this galaxy. However, in practice solving the traditional Gaussian processes equation is too slow and requires too much memory. We employed several methods to avoid this difficulty using algebraic manipulation and low-rank approximation, and were able to quickly approximate the redshifts in our testing data within 17 percent of the known true values using limited computational resources. The accuracy of one method, the V Formulation, is comparable to the accuracy of the best methods currently used for this problem.

Foster, Leslie↗
NASA NTRS2017

The Effect of Firn-Aquifer Drainage on the Greenland Subglacial System or Subglacial Efficiency and Storage Modified by the Temporal Pattern of High-Elevation Meltwater Input

Ice flow in marginal region of the Greenland Ice Sheet dynamically responds to summer melting as surface meltwater is routed through the supraglacial hydrologic system to the bed of the ice sheet via crevasses and moulins. Given the expected increases in surface melt production and extent, and the potential for high elevation surface-to-bed connections, it is imperative to understand how meltwater delivered to the bed from different high-elevation supraglacial storage features affects the evolution of the subglacial hydrologic system and associated ice dynamics. Here, we use the two-dimensional subglacial hydrologic model, GLaDS, which includes distributed and channelized water flow, to test how the subglacial system of an idealized outlet glacier responds to cases of high-elevation firn-aquifer-type and supraglacial-lake-type englacial drainage over the course of 5 years. Model outputs driven by these high elevation drainage types are compared to steady-state model results, where the subglacial system only receives the 1980- 2016 mean MERRA-2 runoff via low-elevation moulins. Across all experiments, the subglacial hydrologic system displays inter-annual memory, resulting in multiyear declines in subglacial pressure during the onset of seasonal melting and growth of subglacial channels. The gradual addition of water in firn-aquifer-type drainage scenarios resulted in small increases in subglacial water storage but limited changes in subglacial efficiency and channelization. Rapid, supraglacial- lake-type drainage resulted in short-term local increases in subglacial water pressure and storage, which gave way to spatially extensive decreases in subglacial pressure and downstream channelization. These preliminary results suggest that the character of high-elevation englacial drainage can have a strong, and possibly outsized, control on subglacial efficiency throughout the ablation zone. Therefore, understanding both how high elevation meltwater is stored supraglacially and the probability of crevassing at high elevations will play an important role in how the subglacial system, proglacial discharge and ice motion will respond to future increases in surface melt production and runoff.

Andrews, Lauren C.↗
NASA NTRS2018

Two-Dimensional Planetary Surface Landers

We proposed to develop a new landing approach that significantly reduces development time and obviates the most complicated, most expensive, and highest-risk phase of a landing mission. The concept is a blanket- or carpet-like two-dimensional (2D) lander (~1-m × 1-m surface area and <1-cm thick) with a low mass/drag ratio, which allows the lander to efficiently shed its approach velocity and provide a more robust structure for landing integrity. The form factor of these landers allows dozens to be stacked on a single spacecraft for transport and distributed en masse to the surface. Lander surfaces will be populated on both sides by surface-mount, low-profile sensors and instruments, surface-mount telecom, solar cells, batteries, processors, and memory. Landers will also incorporate thin flexible electronics, made possible in part by printable electronics technology. The mass and size of these highly capable technologies further reduces the required stiffness and mass of the lander structures to the point that compliant, lightweight, robust landers capable of passive landings are possible. This capability avoids the costly, complex use of rockets, radar, and associated structure and control systems. This approach is expected to provide an unprecedented science payload mass to spacecraft mass ratio of approximately 80% (estimated based on current knowledge). This compared to ~1% for Pathfinder, ~17% for MER, and 22% for MSL rovers. Clearly, one difference is rovers vs. a lower capability lander. An outcome of the Phase I study is a clear roadmap for near-term demonstration and long-term technology development.

Landers↗