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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Shotgun Immunoproteomic Approach for the Discovery of Linear B-Cell Epitopes in Biothreat Agents Francisella tularensis and Burkholderia pseudomallei

Peptide-based subunit vaccines are coming to the forefront of current vaccine approaches, with safety and cost-effective production among their top advantages. Peptide vaccine formulations consist of multiple synthetic linear epitopes that together trigger desired immune responses that can result in robust immune memory. The advantages of linear compared to conformational epitopes are their simple structure, ease of synthesis, and ability to stimulate immune responses by means that do not require complex 3D conformation. Prediction of linear epitopes through use of computational tools is fast and cost-effective, but typically of low accuracy, necessitating extensive experimentation to verify results. On the other hand, identification of linear epitopes through experimental screening has been an inefficient process that requires thorough characterization of previously identified full-length protein antigens, or laborious techniques involving genetic manipulation of organisms. In this study, we apply a newly developed generalizable screening method that enables efficient identification of B-cell epitopes in the proteomes of pathogenic bacteria. As a test case, we used this method to identify epitopes in the proteome of Francisella tularensis (Ft), a Select Agent with a well-characterized immunoproteome. Our screen identified many peptides that map to known antigens, including verified and predicted outer membrane proteins and extracellular proteins, validating the utility of this approach. We then used the method to identify seroreactive peptides in the less characterized immunoproteome of Select Agent Burkholderia pseudomallei (Bp). This screen revealed known Bp antigens as well as proteins that have not been previously identified as antigens. Although B-cell epitope prediction tools Bepipred 2.0 and iBCE-EL classified many of our seroreactive peptides as epitopes, they did not score them significantly higher than the non-reactive tryptic peptides in our study, nor did they assign higher scores to seroreactive peptides from known Ft or Bp antigens, highlighting the need for experimental data instead of relying on computational epitope predictions alone. The present workflow is easily adaptable to detecting peptide targets relevant to the immune systems of other mammalian species, including humans (depending upon the availability of convalescent sera from patients), and could aid in accelerating the discovery of B-cell epitopes and development of vaccines to counter emerging biological threats.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

ALD-Derived WO 3– x Leads to Nearly Wake-Up-Free Ferroelectric Hf 0.5 Zr 0.5 O 2 at Elevated Temperatures

Breaking the memory wall in advanced computing architectures will require complex 3D integration of emerging memory materials such as ferroelectrics─either within the back-end-of-line (BEOL) of CMOS front-end processes or through advanced 3D packaging technologies. Achieving this integration demands that memory materials exhibit high thermal resilience, with the capability to operate reliably at elevated temperatures, such as 125°C, due to the substantial heat generated by front-end transistors. However, silicon-compatible HfO 2 -based ferroelectrics tend to exhibit antiferroelectric-like behavior in this temperature range, accompanied by a more pronounced wake-up effect, posing significant challenges to their thermal reliability. Here, we report that by introducing a thin tungsten oxide (WO 3–x ) layer─known as an oxygen reservoir─and carefully tuning its oxygen content, ultrathin Hf 0.5 Zr 0.5 O 2 (5 nm) films can be made robust against the ferroelectric-to-antiferroelectric transition at elevated temperatures. This approach not only minimizes polarization loss in the pristine state but also effectively suppresses the wake-up effect, reducing the required wake-up cycles from 10 5 to only 10 at 125°C, a qualifying temperature for back-end memory integrated with front-end logic, as defined by the JEDEC standard. First-principles density functional theory (DFT) calculations reveal that WO 3 enhances the stability of the ferroelectric orthorhombic phase (o-phase) at elevated temperatures by increasing the tetragonal-to-orthorhombic phase energy gap and promoting favorable phonon mode evolution, thereby supporting o-phase formation under both thermodynamic and kinetic constraints.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Ligand Substituent Effects on the Electronic Properties of Lindqvist‐Type Polyoxometalate Multi‐Level‐Switches in the Gas Phase, Solution and on Surfaces

Abstract Although the intrinsic electronic properties of polyoxometalates (POMs) can be greatly influenced by modifying them with organic substituents, their resistive switching behavior on surfaces dependent on the organic substituents remains largely unexplored. In this work, we assessed the importance of electron‐withdrawing and electron‐donating ligand substituents on the material properties of a series of hybrid Lindqvist‐type hexavanadates TBA 2 [V 6 O 13 ((OCH 2 ) 3 CCH 2 OH) 2 ] (TBA 2 V 6 ‐OH), TBA 2 [V 6 O 13 ((OCH 2 ) 3 CMe) 2 ] (TBA 2 V 6 ‐Me), TBA 2 [V 6 O 13 ((OCH 2 ) 3 CNHCOCH 2 Cl) 2 ] (TBA 2 V 6 ‐Cl), and TBA 2 [V 6 O 13 ((OCH 2 ) 3 CNHCOCH 2 ‐OOCC 10 H 15 ) 2 ] (TBA 2 V 6 ‐Ad) as potential resistive random‐access memory (ReRAM) components. Compared to their redox behavior in solution, changing the ligand substituents on surfaces results in no significant effect on the potential and, thus, no effect on the resistance steps in the current‐voltage profiles. However, while the current‐voltage characteristics do not change, the peripheral metal‐free substituents in the trisalkoxide framework of Lindqvist‐type hexavanadate molecules influence the adsorption and switching stability of these POMs on gold. This work highlights the noticeable differences between hexavanadate's redox properties in solution (which follow the trend observed in the gas phase) and hexavanadate's resistive switching properties on conducting surfaces. Importantly, their multi‐state switching behavior is not significantly altered by the different type of substituent at the periphery of the trisalkoxo ligands.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Forecasting Multi-Step-Ahead Street-Scale Nuisance Flooding using a seq2seq LSTM Surrogate Model for Real-Time Application in a Coastal-Urban City

In coastal-urban cities facing an elevated risk of nuisance flooding (by rain and tide) due to increased heavy rainfall, sea level rise, urbanization, and aging drainage systems, real-time flood forecasting at the street-scale can provide useful information to transportation decision-makers. Physics-Based Models (PBMs) that offer high accuracy come with high computational runtimes and costs that limit their application for real-time flood forecasting. To address this challenge, Machine Learning (ML) surrogate models trained from PBMs have been proposed to provide street-scale flood forecasts. Previous related studies have focused on using Long Short-Term Memory (LSTM) architectures to model hourly flood depth on streets. While LSTM models can capture input sequences effectively, they fall short in accurately preserving output sequences, limiting their suitability for multi-step-ahead forecasts. The seq2seq LSTM architecture offers a key advantage here by capturing the full sequence of input–output, making it potentially more suitable for multi-step-ahead flood forecasts compared to traditional LSTM models. However, seq2seq LSTM has not been tested for street-scale flood forecasting, particularly for rapidly fluctuating nuisance flooding events which require special attention to its temporal sequences. Hence, in this study, we applied the seq2seq LSTM model to explore multi-step-ahead street-scale nuisance flooding and compared its results to the traditional LSTM model as a benchmark model. LSTM and seq2seq LSTM surrogate models were applied to 22 flood-prone streets in Norfolk, Virginia, as a case study with a 4-hr (short-term) and 8-hr (long-term) lead time. The models were trained with environmental (rainfall and tide) and topographic (elevation, Topographic Wetness Index, and Depth-To-Water) features along with PBM-derived water depths for different storm events. The results demonstrated satisfactory performance of both LSTM and seq2seq LSTM surrogate models throughout the forecast period compared to the PBM. However, the seq2seq LSTM showed lower Mean Absolute Error (MAE)/ Root Mean Square Error (RMSE) and higher Nash–Sutcliffe Efficiency (NSE)/ correlation than the LSTM across most lead times, particularly for long-term forecasting due to its supremacy in handling both input–output sequences together, which is missing in the traditional LSTM. For example, in the long-term, the average RMSE ranges were 0.0268–0.0373 m for LSTM and 0.0226–0.0319 m for seq2seq LSTM, while in the short-term, they were 0.0263–0.0293 m and 0.0261–0.0283 m, respectively. Additionally, while both models exhibited similar performance in distinguishing flooded and non-flooded streets for flood depth ≥ 0.1 m, the seq2seq LSTM model demonstrated superior performance for higher flood depths (such as ≥ 0.2 m and ≥ 0.3 m). Once trained, inference took only 0.09 to 0.11 s (short-term) and 0.30 to 0.35 s (long-term) per storm event for the 22 streets, making the application highly suitable for real-time decision-making during nuisance flood events.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

How arsenic makes amorphous GeSe a robust chalcogenide glass for advanced memory integration

The 3D integration technology in semiconductor fabrication requires a key component, the ovonic threshold switching (OTS) selector, to suppress the current leakage. The As doped amorphous (a-) GeSe glass is a commercialized OTS material in 3D phase-change memory, but the understanding of such a doping mechanism is still inadequate. Here we systematically explore the effect of As doping on the structural, bonding, and dynamics properties of a-GeAsSe using ab initio molecular dynamics simulations. The results reveal that As atoms form strong bonds with both Ge and Se atoms. The distorted octahedral structures and the 5-fold rings linked by atoms are increased. All of these structural features lead to a more disordered configuration. Moreover, as atoms have notably slowed down the atomic mobility, rendering a-GeAsSe a high stability. Overall, our studies offer insightful understanding of As-doping in OTS materials, paving the way for the design and application of advanced selector devices.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Magnetization dynamics driven by displacement currents across a magnetic tunnel junction

Understanding the high-frequency transport characteristics of magnetic tunnel junctions (MTJs) is crucial for the development of fast-operating spintronics memories and radio frequency devices. Here, we present the study of a frequency-dependent capacitive current effect in Co Fe B / Mg O -based MTJs and its influence on magnetization dynamics using a time-resolved magneto-optical Kerr effect technique. In our device, operating at gigahertz frequencies, we find a large displacement current of the order of mA, which does not break the tunnel barrier of the MTJ. Importantly, this current generates an Oersted field and spin-orbit torque, inducing magnetization dynamics. Our discovery holds promise for building robust MTJ devices operating under high current conditions, also highlighting the significance of capacitive impedance in high-frequency magnetotransport techniques. Published by the American Physical Society 2024

Safeer, C. K. (ORCID:0000000323969730)↗
DOE OSTI2022

Emergent ferroelectricity in subnanometer binary oxide films on silicon

The critical size limit of voltage-switchable electric dipoles has extensive implications for energy-efficient electronics, underlying the importance of ferroelectric order stabilized at reduced dimensionality. Here, we report on the thickness-dependent antiferroelectric-to-ferroelectric phase transition in zirconium dioxide (ZrO 2 ) thin films on silicon. The emergent ferroelectricity and hysteretic polarization switching in ultrathin ZrO 2 , conventionally a paraelectric material, notably persists down to a film thickness of 5 angstroms, the fluorite-structure unit-cell size. This approach to exploit three-dimensional centrosymmetric materials deposited down to the two-dimensional thickness limit, particularly within this model fluorite-structure system that possesses unconventional ferroelectric size effects, offers substantial promise for electronics, demonstrated by proof-of-principle atomic-scale nonvolatile ferroelectric memory on silicon. Additionally, it is also indicative of hidden electronic phenomena that are achievable across a wide class of simple binary materials.

42 ENGINEERING↗
NASA NTRS1983

Potential of minicomputer/array-processor system for nonlinear finite-element analysis

The potential of using a minicomputer/array-processor system for the efficient solution of large-scale, nonlinear, finite-element problems is studied. A Prime 750 is used as the host computer, and a software simulator residing on the Prime is employed to assess the performance of the Floating Point Systems AP-120B array processor. Major hardware characteristics of the system such as virtual memory and parallel and pipeline processing are reviewed, and the interplay between various hardware components is examined. Effective use of the minicomputer/array-processor system for nonlinear analysis requires the following: (1) proper selection of the computational procedure and the capability to vectorize the numerical algorithms; (2) reduction of input-output operations; and (3) overlapping host and array-processor operations. A detailed discussion is given of techniques to accomplish each of these tasks. Two benchmark problems with 1715 and 3230 degrees of freedom, respectively, are selected to measure the anticipated gain in speed obtained by using the proposed algorithms on the array processor.

Strohkorb, G. A.↗
NASA NTRS1987

Implementation of a fast digital optical matrix-vector multiplier using a holographic look-up table and residue arithmetic

The design and implementation of a digital (numerical) optical matrix-vector multiplier are presented. A Hughes liquid crystal light valve, the residue arithmetic representation, and a holographic optical memory are used to construct position coded optical look-up tables. All operations are performed in effectively one light valve response time with a potential for a high information density.

Habiby, Sarry F.↗
NASA NTRS2003

Support of Multidimensional Parallelism in the OpenMP Programming Model

OpenMP is the current standard for shared-memory programming. While providing ease of parallel programming, the OpenMP programming model also has limitations which often effect the scalability of applications. Examples for these limitations are work distribution and point-to-point synchronization among threads. We propose extensions to the OpenMP programming model which allow the user to easily distribute the work in multiple dimensions and synchronize the workflow among the threads. The proposed extensions include four new constructs and the associated runtime library. They do not require changes to the source code and can be implemented based on the existing OpenMP standard. We illustrate the concept in a prototype translator and test with benchmark codes and a cloud modeling code.

Jin, Hao-Qiang↗
NASA NTRS2010

Performance Bounds on Two Concatenated, Interleaved Codes

A method has been developed of computing bounds on the performance of a code comprised of two linear binary codes generated by two encoders serially concatenated through an interleaver. Originally intended for use in evaluating the performances of some codes proposed for deep-space communication links, the method can also be used in evaluating the performances of short-block-length codes in other applications. The method applies, more specifically, to a communication system in which following processes take place: At the transmitter, the original binary information that one seeks to transmit is first processed by an encoder into an outer code (Co) characterized by, among other things, a pair of numbers (n,k), where n (n > k)is the total number of code bits associated with k information bits and n k bits are used for correcting or at least detecting errors. Next, the outer code is processed through either a block or a convolutional interleaver. In the block interleaver, the words of the outer code are processed in blocks of I words. In the convolutional interleaver, the interleaving operation is performed bit-wise in N rows with delays that are multiples of B bits. The output of the interleaver is processed through a second encoder to obtain an inner code (Ci) characterized by (ni,ki). The output of the inner code is transmitted over an additive-white-Gaussian- noise channel characterized by a symbol signal-to-noise ratio (SNR) Es/No and a bit SNR Eb/No. At the receiver, an inner decoder generates estimates of bits. Depending on whether a block or a convolutional interleaver is used at the transmitter, the sequence of estimated bits is processed through a block or a convolutional de-interleaver, respectively, to obtain estimates of code words. Then the estimates of the code words are processed through an outer decoder, which generates estimates of the original information along with flags indicating which estimates are presumed to be correct and which are found to be erroneous. From the perspective of the present method, the topic of major interest is the performance of the communication system as quantified in the word-error rate and the undetected-error rate as functions of the SNRs and the total latency of the interleaver and inner code. The method is embodied in equations that describe bounds on these functions. Throughout the derivation of the equations that embody the method, it is assumed that the decoder for the outer code corrects any error pattern of t or fewer errors, detects any error pattern of s or fewer errors, may detect some error patterns of more than s errors, and does not correct any patterns of more than t errors. Because a mathematically complete description of the equations that embody the method and of the derivation of the equations would greatly exceed the space available for this article, it must suffice to summarize by reporting that the derivation includes consideration of several complex issues, including relationships between latency and memory requirements for block and convolutional codes, burst error statistics, enumeration of error-event intersections, and effects of different interleaving depths. In a demonstration, the method was used to calculate bounds on the performances of several communication systems, each based on serial concatenation of a (63,56) expurgated Hamming code with a convolutional inner code through a convolutional interleaver. The bounds calculated by use of the method were compared with results of numerical simulations of performances of the systems to show the regions where the bounds are tight (see figure).

Moision, Bruce↗
NASA NTRS1986

Progression-regression effects in tracking repeated patterns

Subjects used a position control system to perform compensatory tracking of a repeated input pattern. The input pattern was 20 seconds in duration and was either an arctangent function or the sum of two sine waves. Tracking error decreased with practice and increased with the addition of a concurrent memory task. The shape of the ensemble-average tracking error resembled the shape of the input velocity signal throughout these changes in performance. Regression analyses were used to parameterize these effects and compare these results with the predictions of several conceptualizations of perceptual-motor learning.

Jagacinski, R. J.↗
NASA NTRSDate not supplied

Molecular Dynamics Simulations of Microstructural Effects on Austenite-Martensite Interfaces in NiTi

The formation and migration of austenite-martensite interfaces plays the key role in reversible martensitic transformations of shape memory alloys (SMAs). How these interfaces interact with the SMA microstructure is a primary determining factor in important functional properties such as hysteresis and transformation span. As such, successful microstructural engineering of SMAs requires in-depth knowledge of interface behavior. The rapid nature of martensitic transformations makes experimental observations of moving austenite-martensite interfaces challenging. Molecular dynamics (MD) simulation is a unique tool which can probe the atomic-scale details of austenite-martensite interfaces as they migrate through different microstructures. However, in focusing on the entire transformation process, including the nucleation of new phases, MD studies are usually performed so far from equilibrium that their relevance to experiment is questionable. Here, we demonstrate new MD techniques to generate energetically preferred austenite-martensite interfaces in NiTi under near-equilibrium conditions. The interfaces are semi-coherent, exhibiting a series of structural disconnections, and they can migrate rapidly through single crystals under only small thermodynamic driving forces. In contrast, when interfaces migrate in polycrystals, their motion is impeded by thermoelastic effects as well as changes in orientation relationships at grain boundaries. Microstructures which accumulate large amounts of elastic energy tend to release some fraction through irreversible, hysteresis-inducing mechanisms. We demonstrate that engineering microstructures with less constraints is a viable strategy to produce SMAs with reduced hysteresis and transformation span. Similar thermoelastic and hysteresis-inducing mechanisms also arise when austenite-martensite interfaces encounter precipitates and can be controlled by tuning characteristics of the precipitate distribution.

Gabriel Plummer↗
NASA NTRS1986

Analysis of memory use for improved design and compile-time allocation of local memory

Trace analysis techniques are used to study memory referencing behavior for the purpose of designing local memories and determining how to allocate them for data and instructions. In an attempt to assess the inherent behavior of the source code, the trace analysis system described here reduced the effects of the compiler and host architecture on the trace by using a technical called flattening. The variables in the trace, their associated single-assignment values, and references are histogrammed on the basis of various parameters describing memory referencing behavior. Bounds are developed specifying the amount of memory space required to store all live values in a particular histogram class. The reduction achieved in main memory traffic by allocating local memory is specified for each class.

Mcniven, Geoffrey D.↗
NASA NTRS2011

Dynamical Evolution of Meteoroid Streams, Developments Over the Last 30 Years

As soon as reliable methods for observationally determining the heliocentric orbits of meteoroids and hence the mean orbit of a meteoroid stream in the 1950s and 60s, astronomers strived to investigate the evolution of the orbit under the effects of gravitational perturbations from the planets. At first, the limitations in the capabilities of computers, both in terms of speed and memory, placed severe restrictions on what was possible to do. As a consequence, secular perturbation methods, where the perturbations are averaged over one orbit became the norm. The most popular of these is the Halphen- Goryachev method which was used extensively until the early 1980s. The main disadvantage of these methods lies in the fact that close encounter can be missed, however they remain useful for performing very long-term integrations. Direct integration methods determine the effects of the perturbing forces at many points on an orbit. This give a better picture of the orbital evolution of an individual meteoroid, but many meteoroids have to be integrated in order to obtain a realistic picture of the evolution of a meteoroid stream. The notion of generating a family of hypothetical meteoroids to represent a stream and directly integrate the motion of each was probably first used by Williams Murray & Hughes (1979), to investigate the Quadrantids. Because of computing limitations, only 10 test meteoroids were used. Only two years later, Hughes et. al. (1981) had increased the number of particles 20-fold to 200 while after a further year, Fox Williams and Hughes used 500 000 test meteoroids to model the Geminid stream. With such a number of meteoroids it was possible for the first time to produce a realistic cross-section of the stream on the ecliptic. From that point on there has been a continued increase in the number of meteoroids, the length of time over which integration is carried out and the frequency with which results can be plotted so that it is now possible to produce moving images of the stream. As a consequence, over recent years, emphasis has moved to considering stream formation and the role fragmentation plays in this.

Williams, I. P.↗
DOE OSTI2021

InversionNet3D: Efficient and Scalable Learning for 3-D Full-Waveform Inversion

Seismic full-waveform inversion (FWI) techniques aim to find a high-resolution subsurface geophysical model provided with waveform data. Some recent effort in data-driven FWI has shown some encouraging results in obtaining 2-D velocity maps. However, due to high computational complexity and large memory consumption, the reconstruction of 3-D high-resolution velocity maps via deep networks is still a great challenge. Here, in this article, we present InversionNet3D (InvNet3D), an efficient and scalable encoder–decoder network for 3-D FWI. The proposed method employs group convolution in the encoder to establish an effective hierarchy for learning information from multiple sources while cutting down unnecessary parameters and operations at the same time. The introduction of invertible layers further reduces the memory consumption of intermediate features during training and, thus, enables the development of deeper networks with more layers and higher capacity as required by different application scenarios. Experiments on the 3-D Kimberlina dataset demonstrate that InvNet3D achieves state-of-the-art reconstruction performance with lower computational cost and lower memory footprint compared to the baseline.

58 GEOSCIENCES↗
DOE OSTI2024

Effects of input gradient regularization on neural networks time-series forecasting of thermal power systems

This study proposes using neural networks, specifically gated recurrent unit (GRU), long-short-term memory (LSTM), and transformer networks, to improve control strategies in a 450 MW coal-fired power plant. However, neural networks face issues of becoming overly dependent on just a few variables to make predictions, which negatively impacts control decisions that rely on the model to determine the value of all manipulated variables. The paper introduces regularization techniques, including noise injection and input gradient regularization, during the training phase. Here, the work presents novel contributions in adapting neural networks to control industrial systems and applying regularization techniques from computer vision to industrial process control. Results demonstrate the effectiveness of input gradient regularization in reducing model dependence on subsets of variables, emphasizing the balance between fidelity and controllability. Further exploration is recommended, including the development of recurrent transformers, closed-loop control testing, and a sensitivity analysis on computer models to provide further insight.

20 FOSSIL-FUELED POWER PLANTS↗
NASA NTRS2010

Scaled CMOS Technology Reliability Users Guide

The desire to assess the reliability of emerging scaled microelectronics technologies through faster reliability trials and more accurate acceleration models is the precursor for further research and experimentation in this relevant field. The effect of semiconductor scaling on microelectronics product reliability is an important aspect to the high reliability application user. From the perspective of a customer or user, who in many cases must deal with very limited, if any, manufacturer's reliability data to assess the product for a highly-reliable application, product-level testing is critical in the characterization and reliability assessment of advanced nanometer semiconductor scaling effects on microelectronics reliability. A methodology on how to accomplish this and techniques for deriving the expected product-level reliability on commercial memory products are provided.Competing mechanism theory and the multiple failure mechanism model are applied to the experimental results of scaled SDRAM products. Accelerated stress testing at multiple conditions is applied at the product level of several scaled memory products to assess the performance degradation and product reliability. Acceleration models are derived for each case. For several scaled SDRAM products, retention time degradation is studied and two distinct soft error populations are observed with each technology generation: early breakdown, characterized by randomly distributed weak bits with Weibull slope (beta)=1, and a main population breakdown with an increasing failure rate. Retention time soft error rates are calculated and a multiple failure mechanism acceleration model with parameters is derived for each technology. Defect densities are calculated and reflect a decreasing trend in the percentage of random defective bits for each successive product generation. A normalized soft error failure rate of the memory data retention time in FIT/Gb and FIT/cm2 for several scaled SDRAM generations is presented revealing a power relationship. General models describing the soft error rates across scaled product generations are presented. The analysis methodology may be applied to other scaled microelectronic products and their key parameters.

Microelectronics Reliability↗