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At least 1,603 records · Page 89
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Stochastic lag time in nucleated linear self-assembly

Protein aggregation is of great importance in biology, e.g., in amyloid fibrillation. The aggregation processes that occur at the cellular scale must be highly stochastic in nature because of the statistical number fluctuations that arise on account of the small system size at the cellular scale. We study the nucleated reversible self-assembly of monomeric building blocks into polymer-like aggregates using the method of kinetic Monte Carlo. Kinetic Monte Carlo, being inherently stochastic, allows us to study the impact of fluctuations on the polymerization reactions. One of the most important characteristic features in this kind of problem is the existence of a lag phase before self-assembly takes off, which is what we focus attention on. We study the associated lag time as a function of system size and kinetic pathway. We find that the leading order stochastic contribution to the lag time before polymerization commences is inversely proportional to the system volume for large-enough system size for all nine reaction pathways tested. Finite-size corrections to this do depend on the kinetic pathway.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Fabrication of electrocatalytic Ta nanoparticles by reactive sputtering and ion soft landing

About 40 years ago, it was shown that tungsten carbide exhibits similar catalytic behavior to Pt for certain commercially relevant reactions, thereby suggesting the possibility of cheaper and earth-abundant substitutes for costly and rare precious metal catalysts. In this work, reactive magnetron sputtering of Ta in the presence of three model hydrocarbons (2-butanol, heptane, and m-xylene) combined with gas aggregation and ion soft landing was employed to prepare organic-inorganic hybrid nanoparticles (NPs) on surfaces for evaluation of catalytic activity and durability. The electro-catalytic behavior of the NPs supported on glassy carbon was evaluated in acidic aqueous solution by cyclic voltammetry. The Ta-heptane and Ta-xylene NPs were revealed to be active and robust toward promotion of the oxygen reduction reaction, an important process occurring at the cathode in fuel cells. In comparison, pure Ta and Ta-butanol NPs were essentially unreactive. Characterization techniques including atomic force microscopy (AFM), X-ray photoelectron spectroscopy (XPS), and transmission electron microscopy (TEM) were applied to probe how different sputtering conditions such as the flow rates of gases, sputtering current, and aggregation length affect the properties of the NPs. AFM images reveal the focused size of the NPs as well as their preferential binding along the step edges of graphite surfaces. In comparison, TEM images of the same NPs on carbon grids show that they bind randomly to the surface with some agglomeration but little coalescence. The TEM images also reveal morphologies with crystalline cores surrounded by amorphous regions for NPs formed in the presence of 2-butanol and heptane. In contrast, NPs formed in the presence of m-xylene are amorphous throughout. XPS spectra indicate that while the percentage of Ta, C, and O in the NPs varies depending on the sputtering conditions and hydrocarbon employed, the electron binding energies of the elements are similar for all of the NPs. Here, the difference in reactivity between the NPs is attributed to their Ta/C ratios. Collectively, the findings presented herein indicate that reactive magnetron sputtering and gas aggregation combined with ion soft landing offer a promising physical approach for the synthesis of organic-inorganic hybrid NPs that have potential as low-cost durable substitutes for precious metals in catalysis

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Experimental collaboration for thick concrete structures with alkali-silica reaction

Alkali-Silica Reaction (ASR) is a reaction that occurs over time in concrete between alkaline cement paste and reactive, non-crystalline silica in aggregates. An expansive gel is formed within the aggregates which results in micro-cracks in aggregates and adjacent cement paste. The reaction requires the presence of water and has been predominantly detected in groundwater-impacted portions of below grade structures, with limited impact to exterior surfaces in above grade structures. ASR can potentially affect concrete properties and performance characteristics such as compressive strength, modulus of elasticity, shear strength, and tensile strength. Since ASR degradation often takes significant amounts of time, developing ASR detection techniques is important to the sustainability and extended operation lifetimes of nuclear power plants (NPPs). The University of Tennessee, Knoxville (UTK) in collaboration with Oak Ridge National Laboratory (ORNL) designed and built an experiment representative of typical NPP structures to study ASR in thick concrete structures.

Ezell, N Dianne Bull↗
DOE OSTI2023

High-bandwidth density silicon photonic resonators for energy-efficient optical interconnects

The growth of artificial intelligence applications demands ever larger and more complex deep learning models, dominating today's—and tomorrow's—data center and high-performance computing systems. While traditional electronics are failing to keep pace with application demands, silicon photonic (SiPh) interconnects have emerged as a necessary technology to support these systems. SiPh-driven wavelength-division multiplexing (WDM) offers a particularly promising path toward supporting incredibly high-aggregate link bandwidth in a compact and efficient form factor. One of the basic building blocks of these integrated WDM interconnects is the SiPh resonator. Their inherent wavelength selectivity and compact footprint allow for efficient data transmission multiplexed across dozens of carrier wavelengths. Used as add-drop (AD) filters, SiPh resonators are critical to constructing integrated tunable wavelength-selective optical circuit switches as well as for demultiplexing the different carrier wavelengths toward independent wavelength-insensitive photodiodes in a dense wavelength-division multiplexing receiver. Resonators in the all-pass (AP) configuration are widespread as well, allowing for wavelength-selective modulation to drive aggregate link bandwidths far beyond the individual channel data rate. Unlike SiPh Mach–Zehnder modulators (MZM), resonant modulators can be driven using low, complementary metal-oxide-semiconductor drive voltages, allowing for tight co-integration between photonic integrated circuits, fabricated with larger process node technologies, and electronic integrated circuits, designed to exploit the advantages of the latest node. To push toward practical peta-scale interconnects, a comprehensive review of SiPh resonators is required, addressing bottlenecks and design constraints at both the architecture and device levels. We first describe the predominant integrated link architectures and identify their limits. We then discuss the device-level design considerations that can be made for both AD and AP configuration resonators to overcome the system level limits with novel resonator device designs. Analytical models and numerical simulation of resonators are validated by experimental measurement of devices fabricated in a commercial 300-mm foundry, showing a clear path toward volume manufacturing. The demonstrated resonant modulators and filters support the feasibility of increasing the aggregate bandwidth of resonator-driven SiPh interconnects into the peta-scale regime.

42 ENGINEERING↗
DOE OSTI2017

Atomic structure of a toxic, oligomeric segment of SOD1 linked to amyotrophic lateral sclerosis (ALS)

Fibrils and oligomers are the aggregated protein agents of neuronal dysfunction in ALS diseases. Whereas we now know much about fibril architecture, atomic structures of disease-related oligomers have eluded determination. Here, we determine the corkscrew-like structure of a cytotoxic segment of superoxide dismutase 1 (SOD1) in its oligomeric state. Mutations that prevent formation of this structure eliminate cytotoxicity of the segment in isolation as well as cytotoxicity of the ALS-linked mutants of SOD1 in primary motor neurons and in a Danio rerio (zebrafish) model of ALS. Cytotoxicity assays suggest that toxicity is a property of soluble oligomers, and not large insoluble aggregates. Here, our work adds to evidence that the toxic oligomeric entities in protein aggregation diseases contain antiparallel, out-of-register β-sheet structures and identifies a target for structure-based therapeutics in ALS.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Ring currents modulate optoelectronic properties of aromatic chromophores at 25 T

The properties of organic molecules can be influenced by magnetic fields, and these magnetic field effects are diverse. They range from inducing nuclear Zeeman splitting for structural determination in NMR spectroscopy to polaron Zeeman splitting organic spintronics and organic magnetoresistance. A pervasive magnetic field effect on an aromatic molecule is the aromatic ring current, which can be thought of as an induction of a circular current of π-electrons upon the application of a magnetic field perpendicular to the π-system of the molecule. While in NMR spectroscopy the effects of ring currents on the chemical shifts of nearby protons are relatively well understood, and even predictable, the consequences of these modified electronic states on the spectroscopy of molecules has remained unknown. In this work, we find that photophysical properties of model phthalocyanine compounds and their aggregates display clear magnetic field dependences up to 25 T, with the aggregates showing more drastic magnetic field sensitivities depending on the intermolecular interactions with the amplification of ring currents in stacked aggregates. These observations are consistent with ring currents measured in NMR spectroscopy and simulated in time-dependent density functional theory calculations of magnetic field-dependent phthalocyanine monomer and dimer absorption spectra. Here, we propose that ring currents in organic semiconductors, which commonly comprise aromatic moieties, may present new opportunities for the understanding and exploitation of combined optical, electronic, and magnetic properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Structure-based design of nanobodies that inhibit seeding of Alzheimer’s patient–extracted tau fibrils

Despite much effort, antibody therapies for Alzheimer’s disease (AD) have shown limited efficacy. Challenges to the rational design of effective antibodies include the difficulty of achieving specific affinity to critical targets, poor expression, and antibody aggregation caused by buried charges and unstructured loops. To overcome these challenges, we grafted previously determined sequences of fibril-capping amyloid inhibitors onto a camel heavy chain antibody scaffold. These sequences were designed to cap fibrils of tau, known to form the neurofibrillary tangles of AD, thereby preventing fibril elongation. The nanobodies grafted with capping inhibitors blocked tau aggregation in biosensor cells seeded with postmortem brain extracts from AD and progressive supranuclear palsy (PSP) patients. The tau capping nanobody inhibitors also blocked seeding by recombinant tau oligomers. Another challenge to the design of effective antibodies is their poor blood–brain barrier (BBB) penetration. In this study, we also designed a bispecific nanobody composed of a nanobody that targets a receptor on the BBB and a tau capping nanobody inhibitor, conjoined by a flexible linker. We provide evidence that the bispecific nanobody improved BBB penetration over the tau capping inhibitor alone after intravenous administration in mice. Our results suggest that the design of synthetic antibodies that target sequences that drive protein aggregation may be a promising approach to inhibit the prion-like seeding of tau and other proteins involved in AD and related proteinopathies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Membrane-mediated fibrillation and toxicity of the tau hexapeptide PHF6

The aggregation of the tau protein into neurofibrillary tangles is believed to correlate with cognitive decline in several neurodegenerative disorders, including Alzheimer's disease. Recent studies suggest that tau's interactions with the cell membrane could serve as a toxicity pathway and also enhance fibrillation into paired helical filaments (PHFs). Conformational changes associated with tau-membrane interactions are poorly understood, and their characterization could improve our understanding of tau pathogenicity. In this study, we investigated the molecular level structural changes associated with the interaction of the tau hexapeptide PHF6 with model lipid membranes and characterized the effects of these interactions on membrane stability and peptide fibrillation. We used two PHF6 forms, the aggregation-prone PHF6 with N-terminal acetylation (Ac-PHF6) and the non-aggregation prone PHF6 with a standard N terminus (NH$^+_3$-PHF6). We found that both PHF6 peptides are neurotoxic and exhibit similar membrane-mediated changes, consisting of: 1) favorable interactions with anionic membranes, 2) membrane destabilization through lipid extraction, and 3) membrane-mediated fibrillation. The rate at which these changes occurred was the main difference between the two peptides. NH$^+_3$-PHF6 displayed slow membrane-mediated fibrillation after 6 days of incubation, whereas Ac-PHF6 adopted a β-sheet conformation at the surface of the membrane within hours. Ac-PHF6 interactions with the membrane were also accompanied by membrane invagination and rapid membrane destabilization. Overall, our results reveal that membrane interactions could play a critical role in tau toxicity and fibrillation, and highlight that unraveling these interactions is important for significantly advancing the development of therapeutic strategies to manage tau-associated neurodegenerative diseases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Online Data Handling and Storage at the CMS Experiment

During the LHC Long Shutdown 1, the CMS Data Acquisition (DAQ) system underwent a partial redesign to replace obsolete network equipment, use more homogeneous switching technologies, and support new detector back-end electronics. The software and hardware infrastructure to provide input, execute the High Level Trigger (HLT) algorithms and deal with output data transport and storage has also been redesigned to be completely file- based. All the metadata needed for bookkeeping are stored in files as well, in the form of small documents using the JSON encoding. The Storage and Transfer System (STS) is responsible for aggregating these files produced by the HLT, storing them temporarily and transferring them to the T0 facility at CERN for subsequent offline processing. The STS merger service aggregates the output files from the HLT from ~62 sources produced with an aggregate rate of ~2GB/s. An estimated bandwidth of 7GB/s in concurrent read/write mode is needed. Furthermore, the STS has to be able to store several days of continuous running, so an estimated of 250TB of total usable disk space is required. In this article we present the various technological and implementation choices of the three components of the STS: the distributed file system, the merger service and the transfer system.

Andre, J. M.↗
DOE OSTI2018

PIP4Kγ as a potential target for Huntington's disease

Phosphoinositide lipids provide spatial and temporal regulation of cell signaling and membrane traffic. The PI5P‐4‐kinase family is one of the less studied phosphoinositide lipid kinases. These enzymes catalyze the conversion of phosphatidylinositol 5‐phosphate to phosphatidylinositol 4,5‐bis phosphate. A recent study by Vicinanza et al., a suggested that depletion of the PI5P‐4‐kinase, PIP4Kγ promotes a non‐canonical autophagy pathway. Moreover, this depletion reduced the presence of huntingtin‐exon1‐polyglutamine aggregates. Expression of exon1 of huntingtin with an extended polyglutamine tract is a model for huntingtin protein aggregates. To further test the hypothesis that PIP4Kγ is a potential target to reduce huntingtin aggregates, we tested the depletion of PIP4Kγ in cell culture models that express full length mutant huntingtin (mHtt). We determined that depletion of PIP4Kγ, but not PIP4Kα or PIP4Kβ, lowers the levels of mHtt in patient fibroblasts and in immortalized Hdh Q111 mouse striatal neurons. We show that PIP4Kγ‐dependent depletion of mHtt requires lysosomal function because the depletion is blocked by the lysosomal inhibitor, bafilomycin A1. Moreover, we show that depletion of PIP4Kγ increases autophagic flux, as measured by an increase in LC3‐II levels by western blot analysis and an increase in LC3‐II puncta by microscopy. Our studies suggest that PIP4kγ should be further pursued as a target for Huntington's disease. Support or Funding Information This work was supported by AHA postdoctoral fellowship 14POST20480137 (Sai Srinivas Panapakkam Giridharan), NIH grants R01GM050403 and NS064015 (Lois S Weisman) and by HSS funding 1R03MH084839 (Juan Marugan)

Giridharan, Sai Srinivas Panapakkam↗
DOE OSTI2021

Toward witnessing molecular exciton entanglement from spectroscopy

Entanglement is a defining feature of quantum mechanics that can be a resource in engineered and natural systems, but measuring entanglement in experiment remains elusive especially for large chemical systems. Most practical approaches require determining and measuring a suitable entanglement witness which provides some level of information about the entanglement structure of the probed state. A fundamental quantity of quantum metrology is the quantum Fisher information (QFI), which is a rigorous witness of multipartite entanglement that can be evaluated from linear response functions for certain states. Here, in this paper, we explore measuring the QFI of molecular exciton states of the first-excitation subspace from spectroscopy. In particular, we utilize the fact that the linear response of a pure state subject to a weak electric field over all possible driving frequencies encodes the variance of the collective dipole moment in the probed state, which is a valid measure for QFI. The systems that are investigated include the molecular dimer, N-site linear aggregate with nearest-neighbor coupling, and N-site circular aggregate, all modeled as a collection of interacting qubits. Our theoretical analysis shows that the variance of the collective dipole moment in the brightest dipole-allowed eigenstate is the maximum QFI. The optical response of a thermally equilibrated state in the first-excitation subspace is also a valid QFI. Theoretical predictions of the measured QFI for realistic linear dye aggregates as a function of temperature and energetic disorder due to static variations of the host matrix show that two- to three-partite entanglement is realizable. This paper lays some groundwork and inspires measurement of multipartite entanglement of molecular excitons with ultrafast pump-probe experiments.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Impact of Uncertainty from Load-Based Reserves and Renewables on Dispatch Costs and Emissions

Aggregations of controllable loads are considered to be a fast-responding, cost-efficient, and environmental-friendly candidate for power system ancillary services. Unlike conventional service providers, the potential capacity from the aggregation is highly affected by factors like ambient conditions and load usage patterns. Previous work modeled aggregations of controllable loads (such as air conditioners) as thermal batteries, which are capable of providing reserves but with uncertain capacity. A stochastic optimal power flow problem was formulated to manage this uncertainty, as well as uncertainty in renewable generation. In this paper, we explore how the types and levels of uncertainty, generation reserve costs, and controllable load capacity affect the dispatch solution, operational costs, and CO2 emissions. We also compare the results of two methods for solving the stochastic optimization problem, namely the probabilistically robust method and analytical reformulation assuming Gaussian distributions. Case studies are conducted on a modified IEEE 9-bus system with renewables, controllable loads, and congestion. We find that different types and levels of uncertainty have significant impacts on dispatch and emissions. More controllable loads and less conservative solution methodologies lead to lower costs and emissions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

Evaluating the Value of High Spatial Resolution in National Capacity Expansion Models using ReEDS

Power sector capacity expansion models (CEMs) have a broad range of spatial resolutions. This paper uses the Regional Energy Deployment System (ReEDS) model, a long-term national scale electric sector CEM, to evaluate the value of high spatial resolution for CEMs. ReEDS models the United States with 134 load balancing areas (BAs) and captures the variability in existing generation parameters, future technology costs, performance, and resource availability using very high spatial resolution data, especially for wind and solar modeled at 356 resource regions. In this paper we perform planning studies at three different spatial resolutions--native resolution (134 BAs), state-level, and NERC region level--and evaluate how results change under different levels of spatial aggregation in terms of renewable capacity deployment and location, associated transmission builds, and system costs. The results are used to ascertain the value of high geographically resolved models in terms of their impact on relative competitiveness among renewable energy resources.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Impacts of Lock-off Time on Virtual Battery Model from Thermostatically Controlled Loads

We test through simulation the influence of lock-off time on the aggregated flexibility of thermostatically controllable loads (TCLs), which is modeled by virtual battery (VB) models. The VB model provides a simple but effective way to quantify the aggregated flexibility of TCLs, but its efficacy is not clear when there is lock-off time for TCLs. TCLs cannot be turned on during the lock-off period, and so lock-off time imposes inevitable restrictions on not only the flexibility of individual TCLs but also the aggregated flexibility of a group of TCLs. We first test the influence of lock-off time on the efficacy of VB models with two artificial signals. One of the signal is of low frequency while the other is of high frequency. We then use real-world data to test the influence. One set of data is from a duck curve from CAISO while the other set of data is from AGC signals from PJM. The duck curve changes slowly while the AGC signals change rapidly over time. From both the artificial signals and real-word data, we find that lock-off time has a more significant impact on rapid signals than on slow signals.

Wang, Peng↗
DOE OSTI2022

Consensus-Based Approach for Active Power Control and Reserve Estimation in Distributed PV Systems

With the increased adoption of distributed energy resources (DER), they are expected to contribute to power system reliability services and enhance power system stability. This paper presents a distributed consensus control approach for the real-time active power reserve estimation and power management in distributed PV (photovoltaic) systems. The proposed method estimates the cumulative active power reserve from numerous PV generators using only the sparse communication network for a DER aggregator to provide active power regulation services. The real-time active power reserve estimation using the proposed approach can be used by DER aggregators to manage curtailment in distributed PV systems to maintain stipulated reserves and further to provide power system frequency regulation. Using the proposed approach, the DER aggregator only requires measurements at the feeder substation and it does not require information from individual DER units, thereby improving system resiliency. The proposed distributed consensus control method is validated on IEEE 123 testbed using PSCAD simulations.

active power reserve↗
DOE OSTI2024

Robust VAR Capability Curve of DER with Uncertain Renewable Generation

Active distribution system with high penetration of inverter based distributed energy resources(DER), can be utilized for var-related ancillary services at the transmission side interface. In order to utilize the DER flexibility, transmission system operator must be presented the aggregated DER flexibility of distribution system. However, the uncertainty in renewable generation, questions the credibility of aggregated capability curve in practice. In this paper, we incorporate the uncertainty into aggregation process to develop capability curve while preserving the real physics (unbalance and lossy nature) of distribution system. The Resulting capability curve with the associated probability can be harnessed by the TSO for decision making for both planning and operation.

Kar, Aditya Shankar↗
DOE OSTI2021

Simulation of PV Variability as a Function of PV Generation and Plant Size

The deployment of photovoltaic (PV) systems continues to show significant expansion; however, this growth has brought added attention to issues around the variability of the solar resource. Both spatial and temporal variability exist. Temporal scales can range from the sub-second to multiyear, whereas spatial scales can range from a few meters to tens of kilometers. There are multiple methods described in the literature to quantify PV variability at various spatial and temporal scales. This study focuses on short-term temporal variability and uses similar approaches with the addition of PV plant size a parameter to quantify variability. The method employed here incorporates the normalization of clear-and cloudy-sky conditions and PV plant size to quantify nominal variability metrics. The distribution and fluctuations of these metrics provide relevant information that is useful for system operations. The National Solar Radiation Database (NSRDB) is used to simulate PV variability as a function of PV generation and plant size. Hypothetical but realistic system information at 33 locations is used to model PV generation by feeding NSRDB solar irradiance data to the National Renewable Energy Laboratory’s System Advisor Model (SAM). Over the selected region, it is found that the aggregated ramp rates for the 1-minute data are associated with standard deviations ranging from 0.002–0.055 on a daily basis; however, hourly intervals induce higher aggregated ramp rates than the other timescales. Even though minute-to-minute variations are significant for the 1-minute time-scale, the standard deviation aggregated into a daily metric is smaller because of the cancellation of values.

irradiance↗
DOE OSTI2024

HAPPA: A Modular Platform for HPC Application Resilience Analysis with LLMs Embedded

High-performance computing (HPC) systems are increasingly vulnerable to soft errors, which pose significant challenges in maintaining computational accuracy and reliability. Predicting the resilience of HPC applications to these errors is crucial for robust code protection and detailed resilience analysis. In this study, we present HAppA, a modular platform designed for HPC Application Resilience Analysis. Embedding Large Language Models (LLMs), HAppA addresses understanding the context information of long code sequences typical in HPC applications. HAppA implements a novel code representation module that chunks the code into fixed-size segments and aggregates the embeddings of these segments. Three aggregation methods have been explored: MeanPooling, MaxPooling, and LSTM-based techniques. We built a DAtaset for REsilience analysis using Fault Injection (FI), named DARE. Using our DARE dataset, HAppA is trained for regression prediction tasks. Our evaluation results demonstrate the predictive accuracy of HAppA compared to other models, particularly noting that the LSTM-based aggregation method -- HAppA-LSTM -- achieves a mean squared error (MSE) of 0.078 for SDC prediction, surpassing the existing state-of-the-art PARIS model, which recorded an MSE of 0.1172. Additionally, HAppA with the KeyBERT model extracts a list of keywords representing the source code. A comprehensive importance analysis of these keywords further elucidates the code patterns contributing to the error rate. These findings highlight the effectiveness of HAppA in analyzing the resilience of HPC applications and establish a new benchmark for predictive accuracy in resilience.

Jiang, Hailong [Kent State University]↗