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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 235 records · Page 13

Defect-engineered monolayer MoS 2 with enhanced memristive and synaptic functionality for neuromorphic computing

Two-dimensional transition metal dichalcogenides (TMDs)-based memristors are promising candidates for realizing artificial synapses in next-generation computing. However, practical implementation faces several challenges, such as high non-linearity and asymmetry in synaptic weight updates, limited dynamic range, and cycle-to-cycle variability. Here, utilizing optimal-power argon plasma treatment, we significantly enhance the performance matrix of memristors fabricated from monolayer MoS 2 . Our approach not only improves linearity and symmetry in synaptic weight updates but also increases the number of available synaptic weight updates and enhances Spike-Time Dependent Plasticity. Notably, it broadens the switching ratio by two orders, minimizes cycle-to-cycle variability, reduces non-linear factors, and achieves an energy consumption of ~30 fJ per synaptic event. Implementation of these enhancements is demonstrated through Artificial Neural Network simulations, yielding a learning accuracy of ~97% on the MNIST hand-written digits dataset. Our findings underscore the significance of defect engineering as a powerful tool in advancing the synaptic functionality of memristors.

97 MATHEMATICS AND COMPUTING↗

Spitzer mid-infrared detections of neutron star merger GW170817 suggests synthesis of the heaviest elements

Abstract We report our Spitzer Space Telescope observations and detections of the binary neutron star merger GW170817. At 4.5 μm, GW170817 is detected at 21.9 mag AB at +43 days and 23.9 mag AB at +74 days after merger. At 3.6 μm, GW170817 is not detected to a limit of 23.2 mag AB at +43 days and 23.1 mag AB at +74 days. Our detections constitute the latest and reddest constraints on the kilonova/macronova emission and composition of heavy elements. The 4.5 μm luminosity at this late phase cannot be explained by elements exclusively from the first abundance peak of the r-process. Moreover, the steep decline in the Spitzer band, with a power-law index of 3.4 ± 0.2, can be explained by a few of the heaviest isotopes with half-life around 14 d dominating the luminosity (e.g. 140Ba, 143Pr, 147Nd, 156Eu, 191Os, 223Ra, 225Ra, 233Pa, 234Th) or a model with lower deposition efficiency. This data offers evidence that the heaviest elements in the second and third r-process abundance peak were indeed synthesized. Our conclusion is verified by both analytics and network simulations and robust despite intricacies and uncertainties in the nuclear physics. Future observations with Spitzer and James Webb Space Telescope will further illuminate the relative abundance of the synthesized heavy elements.

Kasliwal, Mansi M. (ORCID:0000000256194938)↗

Constraining the Synthesis of the Lightest 𝑝 Nucleus 74 Se

We provide the first experimental cross section of the 73 As(p, γ) 74 Se reaction to constrain one of the main destruction mechanisms of the p nucleus 74 Se in explosive stellar environments. The measurement was done using a radioactive 73 As beam at incident energies of 3.1 and 3.7 MeV/nucleon. Along with the total cross section measurement, statistical properties of the 74 Se compound nucleus were extracted, constraining the reaction cross section across the entire Gamow window of the γ process. The impact of the experimentally constrained reaction rate on 74 Se production in Type II supernovae is investigated through Monte Carlo one-zone network simulations. The results indicate that the overproduction of 74 Se by Type II supernova models cannot be resolved by nuclear physics and point towards the description of the astrophysical conditions of the γ process.

59 ≤ A ≤ 89↗

Scaling laws for two-dimensional dendritic crystal growth in a narrow channel

Here, we investigate analytically and computationally the dynamics of two-dimensional needle crystal growth from the melt in a narrow channel. Our analytical theory predicts that, in the low supersaturation limit, the growth velocity $\textit{V}$ decreases in time $\textit{t}$ as a power law $V ~t^{–2/3}$, which we validate by phase-field and dendritic-needle-network simulations. Simulations further reveal that, above a critical channel width $Λ ≈ 5l_D$, where $l_D$ is the diffusion length, needle crystals grow with a constant $V < V_s$, where $V_s$ is the free-growth needle crystal velocity, and approaches $V_s$ in the limit $Λ \gg l_D$.

36 MATERIALS SCIENCE↗

Low-energy measurement of the 25 Mg ⁢(𝛼,𝑛)⁢ 28 Si reaction via neutron spectroscopy

During core helium and carbon burning in massive stars, neutrons are produced mainly by the 22 Ne⁢ (𝛼,𝑛) ⁢25 Mg reaction. Some of these released neutrons are captured by heavy seed nuclei from previous nucleosynthesis events, resulting in the slow production of many of the elements between masses 60 ≤ 𝐴 ≤ 90 via the weak 𝑠 process. Determining the overall neutron flux available in this environment is one of the main challenges in modeling its contributions to heavy element production. Not only must the reaction rate be well defined for the primary neutron source, but the rates of neutron poison and recycling reactions must also be well determined. One critical reaction in the simulation network is 25 Mg ⁢(𝛼,𝑛) ⁢ 28 Si. This reaction, together with 25 Mg ⁢(𝑛,𝛾)⁢ 26 Mg and 25 Mg⁢ (𝛼,𝛾) ⁢ 29 Si, determine how 25 Mg nuclei affect the available neutron flux. Past attempts to measure the 25 Mg ⁢(𝛼,𝑛)⁢ 28 Si cross section using neutron moderator counters have been greatly hindered by lower-𝑍 background reactions. Here, in the present work, neutron spectroscopy with deuterated liquid scintillator detectors has been used. The experimental spectra have been analyzed by applying spectrum unfolding techniques to achieve improved background discrimination for the 25 Mg⁢ (𝛼,𝑛)⁢ 28 Si reaction at low energies, down to 𝐸 𝛼 = 1.75 MeV. The separation of the different background contributions gives further insight into the results of previous moderator counter measurements and the measurements lead to a revised and more reliable determination of the reaction rate.

hydrostatic stellar nucleosynthesis↗

Using Distributed Dynamic Voltage Restorers to Improve the Frequency Stability of Low-Inertia Networked Microgrids

This paper elucidates the novel concept of using distributed dynamic voltage restorers (DVRs), which are traditionally used to compensate for voltage sags, to improve the frequency stability of low-inertia networked microgrids. During frequency transients, the distributed DVRs rapidly regulate load voltages within an acceptable range, resulting in a fast change of load power consumption and helping improve frequency stability. To enable large-scale network simulation, a phasor-based model of DVRs is developed and validated against real data from a commercially available device. Finally, simulation results of a modified IEEE 123-node test feeder that comprises three microgrids and six DVRs verify the effectiveness of the proposed method.

Du, Wei↗

Double-Line-Frequency Ripple Model, Analysis & Impedance Design for Energy Stored Single-Phase Quasi-Z Source Photovoltaic System

The battery energy stored quasi-Z-source (BESqZS) based photovoltaic (PV) power generation system combines advantages of the qZS inverter and the battery energy storage system. But, the second harmonic (2ω) power ripple degrades the system’s performance and affects the system’s design. An accurate model to analyze the 2ω ripple is very important. The existing models did not consider the battery, or assumed a symmetric qZS network with L 1 =L 2 and C 1 =C 2 , which limits the design freedom and causes oversized impedance parameters. Our paper proposes a comprehensive model for the single-phase BES-qZS-PV inverter system, where the battery is considered and there is no restriction of L 1 =L 2 and C 1 =C 2 . Based on the built model, a BES-qZS impedance design method is proposed to mitigate the 2ω ripple with asymmetric qZS network. Simulation and experimental results verify the proposed 2ω ripple model and impedance design method.

25 ENERGY STORAGE↗

Islanding Detection of Distributed Generation Using Electrical Variables in Space Vector Domain

This paper presents a new approach for islanding detection in distribution systems incorporating synchronous generator-based distributed generations. The proposed method first utilizes the dynamic equations of three electrical variables under islanding situations. The variables are: change of frequency; rate of change of frequency; and rotor angle deviation. Second, transformation of these variables is conducted in the space vector domain, which gives rise to three parameters, namely, semi-major axis, semi-minor axis, and inclination angle. Finally, exploiting these parameters, a decision boundary is established to classify grid events resulting in the formation of an island or not. The proposed method is comprehensively investigated under different operating conditions, which include excess/deficit of reactive/active power imbalance scenarios in the formed island containing different load-types (constant impedance, constant power, and constant current) with varying quality factor. A large variety of islanding and non-islanding events are generated using a practical distribution network simulated in real time on OPAL-RT digital simulation platform under the aforementioned operating conditions. A detailed evaluation of the proposed approach is conducted and it demonstrates the effectiveness of the method.

F-measure↗

pnnl/socialsim_package

Collection of measurements and metrics to be used on social network data. The task was to develop a set of measurements and metrics that can be used to measure the effectiveness of various social network simulations. Provides a collection of measurements and metrics. This takes a variety of metrics and measurements and packages them into a consistent framework.

New, Zachary↗

Performance trade-offs in reconfigurable networks for HPC

Designing efficient interconnects to support high-bandwidth and low-latency communication is critical toward realizing high performance computing (HPC) and data center (DC) systems in the exascale era. At extreme computing scales, providing the requisite bandwidth through overprovisioning becomes impractical. These challenges have motivated studies exploring reconfigurable network architectures that can adapt to traffic patterns at runtime using optical circuit switching. Despite the plethora of proposed architectures, surprisingly little is known about the relative performances and trade-offs among different reconfigurable network designs. We aim to bridge this gap by tackling two key issues in reconfigurable network design. First, we study how cost, power consumption, network performance, and scalability vary based on optical circuit switch (OCS) placement in the physical topology. Specifically, we consider two classes of reconfigurable architectures: one that places OCSs between top-of-rack (ToR) switches—ToR-reconfigurable networks (TRNs)—and one that places OCSs between pods of racks—pod-reconfigurable networks (PRNs). Second, we tackle the effects of reconfiguration frequency on network performance. Our results, based on network simulations driven by real HPC and DC workloads, show that while TRNs are optimized for low fan-out communication patterns, they are less suited for carrying high fan-out workloads. PRNs exhibit better overall trade-off, capable of performing comparably to a fully non-blocking fat tree for low fan-out workloads, and significantly outperform TRNs for high fan-out communication patterns.

Teh, Min Yee↗

Ground state energy and magnetization curve of a frustrated magnetic system from real-time evolution on a digital quantum processor

Models of interacting many-body quantum systems that may realize new exotic phases of matter, notably quantum spin liquids, are challenging to study using even state-of-the-art classical methods such as tensor network simulations. Quantum computing provides a promising route for overcoming these difficulties to find ground states, dynamics, and more. In this paper, we argue that recently developed hybrid quantum-classical algorithms based on real-time evolution are promising methods for solving a particularly important model in the search for spin liquids, the antiferromagnetic Heisenberg model on the two-dimensional kagome lattice. We show how to construct efficient quantum circuits to implement time evolution for the model and to evaluate key observables on the quantum computer, and we argue that the method has favorable scaling with increasing system size. We then restrict to a 12-spin star plaquette from the kagome lattice and a related 8-spin system, and we give an empirical demonstration on these small systems that the hybrid algorithms can efficiently find the ground state energy and the magnetization curve. For these demonstrations, we use four levels of approximation: exact state vectors, exact state vectors with statistical noise from sampling, noisy classical emulators, and (for the 8-spin system only) real quantum hardware, specifically the Quantinuum H1-1 processor; for the noisy simulations and hardware demonstration, we also employ error mitigation strategies based on the symmetries of the Hamiltonian. Our results strongly suggest that these hybrid algorithms present a promising direction for studying quantum spin liquids and more generally for resolving important unsolved problems in condensed matter theory and beyond.

97 MATHEMATICS AND COMPUTING↗

Multimessengers from the Radioactive Decay of r -process Nuclei

The radioactive β-decay of nuclei synthesized in the rapid neutron capture process (r-process) releases a variety of particles, including electrons, γ-rays, neutrinos, and neutrons. These particles provide a rich set of multimessenger signals that carry information about the astrophysical environments where neutron-rich nucleosynthesis occurs. In this work, we calculate from first principles the emission spectra resulting from the β-decay of r-process nuclei. Our approach incorporates detailed nuclear structure and decay data to model the energy distributions of each particle species. We couple the spectra with a nuclear reaction network simulation to obtain the temporal evolution of these distributions. We find that the emission distributions vary significantly in time and are nonthermal, with substantial average energies. We investigate these nuclear signals as a direct probe of heavy element formation and show that they are complementary observables to kilonova.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Ginsparg-Wilson Hamiltonians with Improved Chiral Symmetry

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

Singh, Hersh [Fermilab]↗

Operations analysis of gravity assisted rapid transit

Gravity assisted rapid transit (GART) with 6 percent grades before and after each station are compared with conventional systems in terms of energy consumption, run time, line capacity and schedule stability under abnormal circumstances. Parametric analyses of run times and energy consumption include the impact of alternate accelerating and braking levels. The capcity analysis uses a network simulation program to determine the location and severity of all signal delays. Based on results of initial simulations, the block design was revised to eliminate bottlenecks in normal operations. The systems are then compared at headways of 80 to 180 seconds. One month of incidence reports of a modern operating transit system are reviewed to determine the failures to be simulated. The impact of failures resulting in station delays (30 to 360 seconds), speed limit reduction (20 mph and 30 mph to one or more trains), vehicle performance (75 percent acceleration) are compared at scheduled headway of 90 to 180 seconds.

Source record↗

Summary of photovoltaic system performance models

A detailed overview of photovoltaics (PV) performance modeling capabilities developed for analyzing PV system and component design and policy issues is provided. A set of 10 performance models are selected which span a representative range of capabilities from generalized first order calculations to highly specialized electrical network simulations. A set of performance modeling topics and characteristics is defined and used to examine some of the major issues associated with photovoltaic performance modeling. Each of the models is described in the context of these topics and characteristics to assess its purpose, approach, and level of detail. The issues are discussed in terms of the range of model capabilities available and summarized in tabular form for quick reference. The models are grouped into categories to illustrate their purposes and perspectives.

Smith, J. H.↗

A neurocomputer based on an analog-digital hybrid architecture

A novel analog-digital hybrid architecture based on the utilization of high density digital random access memories for the storage of the synaptic weights of a neural network, and high speed analog hardware to perform neural computation is described. An electronic neurocomputer based on such an architecture is ideally suited for investigating the dynamics, associative recall properties, and computational capabilities of neural networks and provides significant speed improvement in comparison to conventional software based neural network simulations. As a demonstration of the feasibility of the hybrid architectural concept, a prototype breadboard hybrid neurocomputer system with 32 neurons has been designed and fabricated with off-the-shelf hardware components. The performance of the breadboard system has been tested for variety of applications including associative memory and combinatorial problem solving such as Graph Coloring, and is discussed in this paper.

Moopenn, A.↗