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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

NeuroCoreX: An Open-Source FPGA-Based Spiking Neural Network Emulator with On-Chip Learning

Spiking Neural Networks (SNNs) are computational models inspired by the event-driven communication and connectivity patterns of biological neural circuits. They enable high energy efficiency and natural support for diverse architectures ranging from layered networks to small-world and graphstructured topologies. In this work, we introduce NeuroCoreX, an open-source, FPGA-based spiking neural network emulator that provides real-time, on-chip learning and flexible network organization. NeuroCoreX supports both feedforward sensory inputs streamed directly from sensors or PCs via UART and recurrent on-chip connectivity, enabling simultaneous processing and learning from external stimuli and internal network dynamics-capabilities rarely available in existing FPGA SNN platforms. The system implements a Leaky Integrate-and-Fire (LIF) neuron model with current-based synapses and supports pair-based STDP learning on both feedforward and recurrent synapses. A lightweight Python interface enables interactive configuration, live monitoring, weight read-back, and experiment control. Importantly, NeuroCoreX is tightly integrated with the SuperNeuroMAT simulator, allowing SNN models to be transferred seamlessly from software to hardware for hardware-in-the-loop development. By combining real-time plasticity, flexible connectivity, and an open-source VHDL implementation, NeuroCoreX provides an extensible and accessible platform for neuromorphic research, algorithm-hardware co-design, and energy-efficient edge intelligence.

Gautam, Ashish [ORNL]↗
DOE OSTI2020

Training Spiking Neural Networks Using Combined Learning Approaches

Spiking neural networks (SNNs), the class of neural networks used in neuromorphic computing, are difficult to train using traditional back-propagation techniques. Spike timingdependent plasticity (STDP) is a biologically inspired learning mechanism that can be used to train SNNs. Evolutionary algorithms have also been demonstrated as a method for training SNNs. In this work, we explore the relationship between these two training methodologies. We evaluate STDP and evolutionary optimization as standalone methods for training networks, and also evaluate a combined approach where STDP weight updates are applied within an evolutionary algorithm. We also apply Bayesian hyperparameter optimization as a meta learner for each of the algorithms. We find that STDP by itself is not an ideal learning rule for randomly connected networks, while the inclusion of STDP within an evolutionary algorithm leads to similar performance, with a few interesting differences. This study suggests future work in understanding the relationship between network topology and learning rules.

Elbrecht, Daniel↗
DOE OSTI2019

Multi-Objective Optimization for Size and Resilience of Spiking Neural Networks

Inspired by the connectivity mechanisms in the brain, neuromorphic computing architectures model Spiking Neural Networks (SNNs) in silicon. As such, neuromorphic architectures are designed and developed with the goal of having small, low power chips that can perform control and machine learning tasks. However, the power consumption of the developed hardware can greatly depend on the size of the network that is being evaluated on the chip. Furthermore, the accuracy of a trained SNN that is evaluated on chip can change due to voltage and current variations in the hardware that perturb the learned weights of the network. While efforts are made on the hardware side to minimize those perturbations, a software based strategy to make the deployed networks more resilient can help further alleviate that issue. In this work, we study Spiking Neural Networks in two neuromorphic architecture implementations with the goal of decreasing their size, while at the same time increasing their resiliency to hardware faults. We leverage an evolutionary algorithm to train the SNNs and propose a multiobjective fitness function to optimize the size and resiliency of the SNN. We demonstrate that this strategy leads to well-performing, small-sized networks that are more resilient to hardware faults.

Dimovska, Mihaela↗
DOE OSTI2022

A human antibody reveals a conserved site on beta-coronavirus spike proteins and confers protection against SARS-CoV-2 infection

Broadly neutralizing antibodies (bnAbs) to coronaviruses (CoVs) are valuable in their own right as prophylactic and therapeutic reagents to treat diverse CoVs and as templates for rational pan-CoV vaccine design. We recently described a bnAb, CC40.8, from a CoV disease 2019 (COVID-19) convalescent donor that exhibits broad reactivity with human β-CoVs. Here, we showed that CC40.8 targets the conserved S2 stem helix region of the CoV spike fusion machinery. We determined a crystal structure of CC40.8 Fab with a SARS-CoV-2 S2 stem peptide at 1.6-Å resolution and found that the peptide adopted a mainly helical structure. Conserved residues in β-CoVs interacted with CC40.8 antibody, thereby providing a molecular basis for its broad reactivity. CC40.8 exhibited in vivo protective efficacy against SARS-CoV-2 challenge in two animal models. In both models, CC40.8-treated animals exhibited less weight loss and reduced lung viral titers compared to controls. Furthermore, we noted that CC40.8-like bnAbs are relatively rare in human COVID-19 infection, and therefore, their elicitation may require rational structure-based vaccine design strategies. Overall, our study describes a target on β-CoV spike proteins for protective antibodies that may facilitate the development of pan–β-CoV vaccines.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Structure of a Vaccine-Induced, Germline-Encoded Human Antibody Defines a Neutralizing Epitope on the SARS-CoV-2 Spike N-Terminal Domain

Structural characterization of infection- and vaccination-elicited antibodies in complex with antigen provides insight into the evolutionary arms race between the host and the pathogen and informs rational vaccine immunogen design. We isolated a germ line-encoded monoclonal antibody (mAb) from plasmablasts activated upon mRNA vaccination against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and determined its structure in complex with the spike glycoprotein by electron cryomicroscopy (cryo-EM). We show that the mAb engages a previously uncharacterized neutralizing epitope on the spike N-terminal domain (NTD). The high-resolution structure reveals details of the intermolecular interactions and shows that the mAb inserts its heavy complementarity-determining region 3 (HCDR3) loop into a hydrophobic NTD cavity previously shown to bind a heme metabolite, biliverdin. We demonstrate direct competition with biliverdin and that, because of the conserved nature of the epitope, the mAb maintains binding to viral variants B.1.1.7 (alpha), B.1.351 (beta), B.1.617.2 (delta), and B.1.1.529 (omicron). Our study describes a novel conserved epitope on the NTD that is readily targeted by vaccine-induced antibody responses.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Analysis of the ARTIC Version 3 and Version 4 SARS-CoV-2 Primers and Their Impact on the Detection of the G142D Amino Acid Substitution in the Spike Protein

The ARTIC Network provides a common resource of PCR primer sequences and recommendations for amplifying SARS-CoV-2 genomes. The initial tiling strategy was developed with the reference genome Wuhan-01, and subsequent iterations have addressed areas of low amplification and sequence drop out. Recently, a new version (V4) was released, based on new variant genome sequences, in response to the realization that some V3 primers were located in regions with key mutations. Herein, we compare the performance of the ARTIC V3 and V4 primer sets with a matched set of 663 SARS-CoV-2 clinical samples sequenced with an Illumina NovaSeq 6000 instrument. We observe general improvements in sequencing depth and quality, and improved resolution of the SNP causing the D950N variation in the spike protein. Importantly, we also find nearly universal presence of spike protein substitution G142D in Delta-lineage samples. Due to the prior release and widespread use of the ARTIC V3 primers during the initial surge of the Delta variant, it is likely that the G142D amino acid substitution is substantially underrepresented among early Delta variant genomes deposited in public repositories. In addition to the improved performance of the ARTIC V4 primer set, this study also illustrates the importance of the primer scheme in downstream analyses.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Training Spiking Neural Networks with Synaptic Plasticity under Integer Representation

Neuromorphic computing is emerging as a promising Beyond Moore computing paradigm that employs event-triggered computation and non-von Neumann hardware. Spike Timing Dependent Plasticity (STDP) is a well-known bio-inspired learning rule that relies on activities of locally connected neurons to adjust the weights of their respective synapses. In this work, we analyze a basic STDP rule and its sensitivity on the different hyperparameters for training spiking neural networks (SNNs) with supervision, customized for a neuromorphic hardware implementation with integer weights. We compare the classification performance on four UCI datasets (iris, wine, breast cancer and digits) that depict varying levels of complexity. We perform a search for optimal set of hyperparameters using both grid search and Bayesian optimization. Through the use of Bayesian optimization, we show the general trends in hyperparameter sensitivity in SNN classification problem. With the best sets of hyperparameters, we achieve accuracies comparable to some of the best performing SNNs on these four datasets. With a highly optimized supervised STDP rule we show that these accuracies can be achieved with just 20 epochs of training.

Kulkarni, Shruti↗
DOE OSTI2024

Spiking Markov Reward Process v.0.1

SAND2024-11150O The Spiking Markov Reward Process software is a spiking neural network that streams binary arithmetic and computes the state value function of a Markov reward process. The software will be released to the SpiNNcloud group for development of neuromorphic acceleration. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Wang, Felix↗
DOE OSTI2021

The SARS-CoV-2 Spike Variant D614G Favors an Open Conformational State

The COVID-19 pandemic underwent a rapid transition with the emergence of a dominant viral variant (from the “D-form” to the “G-form”) that carried an amino acid substitution D614G in its “Spike” protein. The G-form is more infectious in vitro and associated with increased viral loads. To gain insight into the molecular-level underpinnings of these characteristics, we employed microsecond all-atom simulations. Here we show that changes in the protein energetics favor a higher population of infection-capable (open) states through release of hydrogen bonds of an asymmetry present in the D-form but not the G-form. Thus, the increased infectivity of the G-form is likely due to a higher rate of profitable binding encounters with the host receptor. It is also predicted to be more neutralization sensitive due to enhanced exposure of the receptor binding domain, a key target region for neutralizing antibodies. These results are significant for vaccine design. The Molecular Dynamics Simulations datasets generated in this study, namely that of the soluble form SARS-CoV-2 Spike protein are made available here. Details of the trajectory and supporting files are given in the README.txt file.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1966

Surface spikes - A perturbation of growth steps.

During the growth of NiBr 2 crystals by sublimation, it has been observed that in addition to the mechanism of growth spirals a secondary mode of nucleation can occur. This is an accelerated growth which appears in the form of surface spikes on growth steps. The surface spikes may move as much as 50 times faster than the unperturbed growth steps. The mechanism of formation is believed to begin with the nucleation of a liquid droplet which wets the growth step and produces the accelerated growth from the liquid phase. The growth occurs at 500°C below the melting point of NiBr 2 . It is believed that the nucleation of the liquid phase at these temperatures is impurity controlled.

Nickel compound↗
NASA NTRS1971

Saturation current spikes eliminated in saturable core transformers

Unsaturating composite magnetic core transformer, consisting of two separate parallel cores designed so impending core saturation causes signal generation, terminates high current spike in converter primary circuit. Simplified waveform, demonstrates transformer effectiveness in eliminating current spikes.

Schwarz, F. C.↗
NASA NTRS1966

Aerodynamic spike nozzle Patent

Constructing fluid spike nozzle to eliminate heat transfer and high temperature problems inherent in physical spikes

Cowell, T. E.↗
NASA NTRS1972

High energy electron spikes at high latitudes

Over 750 spikes of precipitating electrons with E or = 425 KeV were observed aboard the low altitude polar orbiter OGO-D between 30 July 1967 and 31 December 1967. The spikes may be divided into three distinct populations, depending on whether they occur at latitudes below, at, or above the local limit of trapping.

Brown, J. W.↗
NASA NTRS1980

Flow oscillations of spike-tipped bodies

The oscillating flow field around a spike-tipped body has been simulated by the numerical solution of the 3-D compressible Navier-Stokes equations at a Mach number of 3.0 and a nominal Reynolds number of 7.87 x 10 to the 6th/m. Computations were performed using a vectorized 3-D Navier-Stokes program on the STAR 100 computer. Numerical solutions confirmed the experimental result that the self-sustained oscillation occurs within a limited range of the protruded spike length to shoulder height ratio. The numerical result predicted correctly the discrete frequency range as well as the rms pressure intensity. The detailed flow structure is also presented and discussed.

Shang, J. S.↗
NASA NTRS1982

Spike-Free Automatic Level Control

New automatic-level-control circuit protects against signal "overshoot." Zener diodes and series capacitors prevent voltage spikes (caused by sudden increase in input level) from appearing at output. When spike voltage drops below breakdown voltage of Zener diodes, they turn off. Initial output level is determined by Zener breakdown voltage and capacitance of series capacitor.

Toole, P. C.↗
NASA NTRS1981

Elimination of current spikes in buck power converters

Current spikes in a buck power converter due to commutating diode turn-off time are eliminated by using a tapped inductor in the converter with the tap connected to the switching transistor. The commutating diode is not in the usual place, but is instead connected to conduct current from one end of the tapped inductor remote from the load during the interval in which the transistor is not conducting. In the case of a converter having a center-tapped (primary and secondary) transformer between two switching power transistors operated in a push-pull mode and two rectifying diodes in the secondary circuit, current spikes due to transformer saturation are also eliminated by using a tapped inductor in the converter with the tap connected to the rectifying diodes and a diode connected to conduct current from one end of the tapped inductor remote from the load during the interval in which the transistors are not conducting.

Mclyman, W. T.↗
NASA NTRS1981

VLA observations of positions 42 6 centimeter burst peaks associated with hard X-ray burst spikes

Using the Very Large Array with a spatial resolution of 3 arcsec, two-dimensional, 10-second synthesis maps are produced of four 6-cm lambda bursts associated with multiply spiked hard X-ray bursts (20-300 keV). The positional, structural, and polarization characteristics are investigated. It is noted that three of the four burst sources are rather compact (less than approximately 10 arcsec). It is found that the positions of the individual peaks or spikes within a single burst are the same within plus or minus 2 arcsec. Interpreting these different peaks as separate electron acceleration events, the results suggest repeated acceleration of electrons within the same magnetic trap. The trap situation is found to be consistent with the bipolar nature of the burst sources except in one case.

Kundu, M. R.↗