Results for “peak finding” — Page 47

DOE OSTI2023

Reaching percolation and conformal limits in neutron stars

Generating an ensemble of equations of state that fulfill multimessenger constraints, we statistically determine the properties of dense matter found inside neutron stars (NSs). We calculate the speed of sound and trace anomaly and demonstrate that they are driven towards their conformal values at the center of maximally massive NSs. The local peak of the speed of sound is shown to be located at values of the energy and particle densities, which are consistent with deconfinement and percolation conditions in QCD matter. Here, we also analyze fluctuations of the net-baryon number density in the context of possible remnants of critical behavior. We find that the global maxima of the variance of these fluctuations emerge at densities beyond those found in the interiors of NSs.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Search for the e + e − → η b ( 1 S ) ω and e + e − → χ b 0 ( 1 P ) ω processes at s = 10.745 GeV

We search for the e + e − → η b ( 1 S ) ω and e + e − → χ b 0 ( 1 P ) ω processes at a center-of-mass energy of 10.745 GeV, which is close to the peak of the ϒ ( 10753 ) state. We use data collected by the Belle II experiment during a special run, corresponding to an integrated luminosity of 9.8 fb − 1 . We reconstruct ω → π + π − π 0 decays and use the ω meson’s recoil mass to search for the signals. We do not find evidence for either process, and set upper limits on the corresponding Born-level cross sections of 2.5 pb and 7.8 pb, respectively, at the 90% confidence level. The χ b 0 ( 1 P ) ω limit is the result of a combination of this analysis and a previous search using full reconstruction. Published by the American Physical Society 2024

Astronomy & Astrophysics↗

DOE OSTI2020

Seismology in the Cloud: A New Streaming Workflow

Data-intensive research in seismology is experiencing a recent boom, driven in part by large volumes of available data and advances in the growing field of data science. However, there are significant barriers to processing large data volumes, such as long retrieval times from data repositories, complex data management, and limited computational resources. New tools and platforms have reduced the barriers to entry for scientific cluster computing, including the maturation of the commercial cloud as an accessible instrument for research. Here, we build a customized research cluster in the cloud to test a new workflow for large-scale seismic analysis, in which data are processed as a stream (retrieved on-the-fly and acted upon without storing), with data from the Incorporated Research Institutions for Seismology Data Management Center. We use this workflow to deploy a spectral peak detection algorithm over 5.6 TB of compressed continuous seismic data from 2074 stations of the USArray Transportable Array EarthScope network. Using a 50-node cluster in the cloud, we completed the noise survey in 80 hr, with an average data throughput of 1.7 GB per minute. By varying cluster sizes, we find the scaling of our analysis to be sublinear, due to a combination of algorithmic limitations and data center response times. The cloud-based streaming workflow represents an order-of-magnitude increase in acquisition and processing speed compared to a traditional download-store-process workflow, and offers the additional benefits of employing a flexible, accessible, and widely used computing architecture. It is limited, however, due to its reliance on Internet transfer speeds and data center service capacity, and may not work well for repeated analyses or those for which even higher data throughputs are needed. These research applications will require a new class of cloud-native approaches in which both data and analysis are in the cloud.

58 GEOSCIENCES↗

DOE OSTI2020

Kilonova Luminosity Function Constraints Based on Zwicky Transient Facility Searches for 13 Neutron Star Merger Triggers during O3

We present a systematic search for optical counterparts to 13 gravitational wave (GW) triggers involving at least one neutron star during LIGO/Virgo's third observing run (O3). We searched binary neutron star (BNS) and neutron star black hole (NSBH) merger localizations with the Zwicky Transient Facility (ZTF) and undertook follow-up with the Global Relay of Observatories Watching Transients Happen (GROWTH) collaboration. The GW triggers had a median localization area of 4480 deg 2 , a median distance of 267 Mpc, and false-alarm rates ranging from 1.5 to 10 -25 yr -1 . The ZTF coverage in the g and r bands had a median enclosed probability of 39%, median depth of 20.8 mag, and median time lag between merger and the start of observations of 1.5 hr. The O3 follow-up by the GROWTH team comprised 340 UltraViolet/Optical/InfraRed (UVOIR) photometric points, 64 OIR spectra, and three radio images using 17 different telescopes. We find no promising kilonovae (radioactivity-powered counterparts), and we show how to convert the upper limits to constrain the underlying kilonova luminosity function. Initially, we assume that all GW triggers are bona fide astrophysical events regardless of false-alarm rate and that kilonovae accompanying BNS and NSBH mergers are drawn from a common population; later, we relax these assumptions. Assuming that all kilonovae are at least as luminous as the discovery magnitude of GW170817 (-16.1 mag), we calculate that our joint probability of detecting zero kilonovae is only 4.2%. If we assume that all kilonovae are brighter than-16.6 mag (the extrapolated peak magnitude of GW170817) and fade at a rate of 1 mag day -1 (similar to GW170817), the joint probability of zero detections is 7%. If we separate the NSBH and BNS populations based on the online classifications, the joint probability of zero detections, assuming all kilonovae are brighter than -16.6 mag, is 9.7% for NSBH and 7.9% for BNS mergers. Moreover, no more than <57% (<89%) of putative kilonovae could be brighter than -16.6 mag assuming flat evolution (fading by 1 mag day -1 ) at the 90% confidence level. If we further take into account the online terrestrial probability for each GW trigger, we find that no more than <68% of putative kilonovae could be brighter than -16.6 mag. Comparing to model grids, we find that some kilonovae must have M ej < 0.03 M ⊙ , X lan > 10 -4 , or φ > 30° to be consistent with our limits. We look forward to searches in the fourth GW observing run; even 17 neutron star mergers with only 50% coverage to a depth of-16 mag would constrain the maximum fraction of bright kilonovae to <25%.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Can Wholesale Electricity Markets Achieve Resource Adequacy and High Clean Energy Generation Targets in the Presence of Self-Interested Actors?

Wholesale electricity markets are intended to incentivize system generation investments and operations outcomes that meet evolving system needs. In this work, we evaluate the effectiveness of wholesale market structures, rules and policies in achieving system resource adequacy (RA) and clean energy targets in the presence of self-interested generation investors using the Electricity Markets and Investment Suite Agent-based Simulation (EMIS-AS) model. Results highlight that both capacity markets and operating reserve demand curves (ORDCs) can help achieve a reliable system but with different RA compliance timelines and distribution of generation technologies. Structures with capacity markets tend to favor more capital-intensive peaking technologies while reducing wind and solar build-outs due to suppressed energy and clean energy market prices, particularly in the absence of strong clean energy targets. Conversely, ORDCs improve the commitment of available generation units, but this comes at the expense of higher system costs and renewable generation curtailment. We also find that well-calibrated static capacity demand curves can yield similar reliability and total cost compared to capacity market demand curves informed dynamically by resource adequacy while also yielding stable annual capacity prices. Different approaches to formulating ORDC curves can also yield key trade-offs, namely that a more efficient treatment of storage chronology results in lower ORDC curves and prices, yielding less investment and cost but at the expense of reliability. Finally, the effectiveness of wholesale electricity markets in practically achieving very high clean energy generation targets highly depends on the cost-competitiveness of clean energy technologies that can support critical balancing needs across multiple timescales.

capacity expansion↗

DOE OSTI2020

Engineering Edge States of Graphene Nanoribbons for Narrow-Band Photoluminescence

Solid-state narrow-band light emitters are on-demand for quantum optoelectronics. Current approaches based on defect engineering in low-dimensional materials usually introduce a broad range of emission centers. Here, we report narrow-band light emission from covalent heterostructures fused to the edges of graphene nanoribbons (GNRs) by controllable on-surface reactions from molecular precursors. Two types of heterojunction (HJ) states are realized by sequentially synthesizing GNRs and graphene nanodots (GNDs) and then coupling them together. HJs between armchair GNDs and armchair edges of the GNR are coherent and give rise to narrow-band photoluminescence. In contrast, HJs between the armchair GNDs and the zigzag ends of GNRs are defective and give rise to nonradiative states near the Fermi level. At low temperatures, sharp photoluminescence emissions with peak energy range from 2.03 to 2.08 eV and line widths of 2–5 meV are observed. Furthermore, the radiative HJ states are uniform, and the optical transition energy is controlled by the band gaps of GNRs and GNDs. As these HJs can be synthesized in a large quantity with atomic precision, this finding highlights a route to programmable and deterministic creation of quantum light emitters.

36 MATERIALS SCIENCE↗

DOE OSTI2020

The role of geography in the complex diffusion of innovations

The urban–rural divide is increasing in modern societies calling for geographical extensions of social influence modelling. Improved understanding of innovation diffusion across locations and through social connections can provide us with new insights into the spread of information, technological progress and economic development. In this work, we analyze the spatial adoption dynamics of iWiW, an Online Social Network (OSN) in Hungary and uncover empirical features about the spatial adoption in social networks. During its entire life cycle from 2002 to 2012, iWiW reached up to 300 million friendship ties of 3 million users. We find that the number of adopters as a function of town population follows a scaling law that reveals a strongly concentrated early adoption in large towns and a less concentrated late adoption. We also discover a strengthening distance decay of spread over the life-cycle indicating high fraction of distant diffusion in early stages but the dominance of local diffusion in late stages. The spreading process is modelled within the Bass diffusion framework that enables us to compare the differential equation version with an agent-based version of the model run on the empirical network. Although both model versions can capture the macro trend of adoption, they have limited capacity to describe the observed trends of urban scaling and distance decay. We find, however that incorporating adoption thresholds, defined by the fraction of social connections that adopt a technology before the individual adopts, improves the network model fit to the urban scaling of early adopters. Controlling for the threshold distribution enables us to eliminate the bias induced by local network structure on predicting local adoption peaks. Finally, we show that geographical features such as distance from the innovation origin and town size influence prediction of adoption peak at local scales in all model specifications.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Topological and nematic superconductivity mediated by ferro-SU(4) fluctuations in twisted bilayer graphene

We propose an SU(4) spin-valley-fermion model to investigate the superconducting instabilities of twisted bilayer graphene (TBG). In this approach, bosonic fluctuations associated with an emergent SU(4) symmetry, corresponding to combined rotations in valley and spin spaces, couple to the low-energy fermions that comprise the flat bands. These fluctuations are peaked at zero wave vector, reflecting the “ferromagnetic-like” SU(4) ground state recently found in strong-coupling solutions of microscopic models for TBG. Focusing on electronic states related to symmetry-imposed points of the Fermi surface, dubbed here “valley hot-spots” and “van Hove hot-spots,” we find that the coupling to the itinerant electrons partially lifts the huge degeneracy of the ferro-SU(4) ground state manifold, favoring intervalley order, spin-valley coupled order, ferromagnetic order, spin-current order, and valley-polarized order, depending on details of the band structure. Here, these fluctuations, in turn, promote attractive pairing interactions in a variety of closely competing channels, including a nodeless f-wave state, a nodal i-wave state, and topological d+id and p+ip states with unusual Chern numbers 2 and 4, respectively. Nematic superconductivity, although not realized as a primary instability of the system, appears as a consequence of the near-degeneracy of superconducting order parameters that transform as one-dimensional and two-dimensional irreducible representations of the point group D 6 .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

Wholesale Electricity Markets and Resource Adequacy with High Clean Energy Generation Targets

Wholesale electricity markets are intended to incentivize system generation investments and operations outcomes that meet evolving system needs. In this work, we evaluate the effectiveness of wholesale market structures, rules and policies in achieving system resource adequacy (RA) and clean energy targets in the presence of self-interested generation investors using the Electricity Markets and Investment Suite Agent-based Simulation (EMIS-AS) model. Results highlight that both capacity markets and operating reserve demand curves (ORDCs) can help achieve a reliable system but with different RA compliance timelines and distribution of generation technologies. Structures with capacity markets tend to favor more capital-intensive peaking technologies while reducing wind and solar build-outs due to suppressed energy and clean energy market prices, particularly in the absence of strong clean energy targets. Conversely, ORDCs improve the commitment of available generation units, but this comes at the expense of higher system costs and renewable generation curtailment. We also find that well-calibrated static capacity demand curves can yield similar reliability and total cost compared to capacity market demand curves informed dynamically by resource adequacy while also yielding stable annual capacity prices. Different approaches to formulating ORDC curves can also yield key trade-offs, namely that a more efficient treatment of storage chronology results in lower ORDC curves and prices, yielding less investment and cost but at the expense of reliability. Finally, the effectiveness of wholesale electricity markets in practically achieving very high clean energy generation targets highly depends on the cost-competitiveness of clean energy technologies that can support critical balancing needs across multiple timescales.

capacity expansion↗

DOE OSTI2024

Wholesale Electricity Market Design to Support Resource Adequacy

Wholesale electricity markets are intended to incentivize system generation investments and operations outcomes that meet evolving system needs. In this work, we evaluate the effectiveness of wholesale market structures, rules and policies in achieving system resource adequacy (RA) and clean energy targets in the presence of self-interested generation investors using the Electricity Markets and Investment Suite Agent-based Simulation (EMIS-AS) model. Results highlight that both capacity markets and operating reserve demand curves (ORDCs) can help achieve a reliable system but with different RA compliance timelines and distribution of generation technologies. Structures with capacity markets tend to favor more capital-intensive peaking technologies while reducing wind and solar build-outs due to suppressed energy and clean energy market prices, particularly in the absence of strong clean energy targets. Conversely, ORDCs improve the commitment of available generation units, but this comes at the expense of higher system costs and renewable generation curtailment. We also find that well-calibrated static capacity demand curves can yield similar reliability and total cost compared to capacity market demand curves informed dynamically by resource adequacy while also yielding stable annual capacity prices. Different approaches to formulating ORDC curves can also yield key trade-offs, namely that a more efficient treatment of storage chronology results in lower ORDC curves and prices, yielding less investment and cost but at the expense of reliability. Finally, the effectiveness of wholesale electricity markets in practically achieving very high clean energy generation targets highly depends on the cost-competitiveness of clean energy technologies that can support critical balancing needs across multiple timescales.

agent based modeling↗

DOE OSTI2025

Breaking the Linear Scaling Relations for the Oxygen Reduction Reaction with a Dual‐Atom Catalyst Composed of a MnFe‐Porphyrrole Aerogel

Bimetallic catalysts offer enhanced catalytic performance through synergistic interactions between the two metals, allowing them to break the linear scaling relations and reach high electrocatalytic activity. This study presents bimetallic aerogel-based catalyst synthesized as a covalent, three-dimensional framework containing neighboring iron and manganese sites. The aerogel structure provides a high surface area and porosity, facilitating an ultra-high active site density and efficient mass transport. The MnFe porphyrrole's unique structure is obtained by alternately linking Mn-porphyrin and Fe-corrole complexes. It exhibited outstanding performance with an onset potential of 0.99 V RHE . Comparative studies with a free-base Fe porphyrrole catalyst (E onset 0.97 V RHE ) revealed that while Mn incorporation led to only a slight improvement in half-cell performance, it resulted in significantly enhanced performance in anion exchange membrane fuel cell. The MnFe catalyst achieved an OCV of 0.97 V and a peak power density of 0.27 W cm −2 , outperforming the free-base Fe counterpart. Using density functional theory calculations, we show that the higher ORR activity of MnFe-porphyrrole is due to charge transfer between Mn and Fe atoms, which is absent in the reference free-base Fe-porphyrrole. These findings underscore the advantages of bimetallic catalysts in improving ORR activity and fuel cell efficiency by leveraging synergistic effects.

Aerogel↗

DOE OSTI2020

Simulated production of OH, HO 2 , CH 2 O, and CO 2 during dilute fuel oxidation can predict 1st-stage ignition delays

Chemical kinetics simulations are used to explore whether detailed measurements of relevant chemical species during the oxidation of very dilute fuels (less than 1 Torr partial pressure) in a high-pressure plug flow reactor (PFR) can predict autoignition propensity. We find that for many fuels the timescale for the onset of spontaneous oxidation in dilute fuel/air mixtures in a simple PFR is similar to the 1st-stage ignition delay time (IDT) at stoichiometric engine-relevant conditions. For those fuels that deviate from this simple trend, the deviation is closely related to the peak rate of production of OH, HO 2 , CH 2 O, and CO 2 formed during oxidation. We use these insights to show that an accurate correlation between simulated profiles of these species in a PFR and 1st-stage IDT can be developed using convolutional neural networks. Our simulations suggest that the accuracy of such a correlation is 10–50%, which is appropriate for rapid fuel screening and may be sufficient for predictive fuel performance modeling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Antiferromagnetic Order and Linear Magnetoresistance in Fe-Substituted Shandite Co 3 In 2 S 2

Co 3 In 2 S 2 is a shandite phase closely related to the ferromagnetic Weyl semimetal Co 3 Sn 2 S 2 and contains Co atoms on an ideal kagome net. Elemental substitutions in Co 3 Sn 2 S 2 have been shown to invariably suppress its magnetism, and it remains a rare example of a shandite phase with magnetic order. Here, we report a new magnetic shandite compound discovered by substituting Fe into Co 3 In 2 S 2 . Single crystals of (Co 1–x Fe x ) 3 In 2 S 2 were grown, and neutron diffraction, ac and dc magnetization, and heat capacity measurements reveal long-range antiferromagnetic order with an interesting noncollinear structure and transition temperatures from 11 to 17 K. Partially substituting Fe for Co was inspired by calculated electronic structures, which suggest that Co 3 In 2 S 2 is near a magnetic instability and shows a peak in the density of states that can be approached by hole doping. While the focus of the present work is primarily on magnetism, there is a nodal ring below the Fermi energy in Co 3 In 2 S 2 that may also provide interest from a topological perspective. Potentially related to this, we find large, linear, nonsaturating magnetoresistance in this compound. Furthermore, this work expands the scope of magnetic topological materials among shandites and motivates similar chemical manipulation studies to reveal hidden magnetic instabilities in this important family and other topological systems.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Periodicity Analysis of Earthquake Occurrence and Hypocenter Depth Near Parkfield, California, 1994–2002 Versus 2006–2014

In central California, periodic earthquake occurrence suggests a relationship with annual hydrological, atmospheric, thermal, and tidal loadings. Here, in catalogs of declustered earthquakes within 100 km from Parkfield, CA, we study a semiannual periodicity for the monthly number of ≤7.2-km-deep earthquakes and the monthly median hypocenter depth over 1994–2002 and 2006–2014. Peak-trough months in fitted periodic components differ between time spans and event populations. Deeper earthquakes present no semiannual and a weak annual periodicity. Although modeled pore pressure shows a Spring peak, when added to the elastic Coulomb stress from surface hydrospheric loads, it fails to predict a 6-month periodicity for 2006–2014. In 1994–2002, the pore-pressure amplitude appears to be of same order as the elastic stress and may have had a stronger effect. In 2006–2014, we did not find load model parameters explaining the observed pattern or apparent changes following the 2003 San Simeon and 2004 Parkfield earthquakes.

58 GEOSCIENCES↗

DOE OSTI2021

Performance of microchannel plate based detectors for <25 keV x rays: Monte Carlo simulations and comparisons with experimental results

We present the results of Monte Carlo simulations of the microchannel plate (MCP) response to x rays in the 250 eV to 25 keV energy range as a function of both x-ray energy and impact angle and their comparisons with the experimental results from the X8A beamline at the National Synchrotron Light Source at Brookhaven National Laboratory. Incoming x rays interact with the lead glass of the microchannel plate, producing photoelectrons. Transport of the photoelectrons is neglected in this model, and it is assumed that photoelectrons deposit all their energy at the point they are created. This deposition leads to the generation of many secondary electrons, some fraction of which diffuse to the MCP pore surface where they can initiate secondary electron cascades in the pore under an external voltage bias. X-ray penetration through multiple MCP pore walls is increasingly important above 5 keV, and the effect of this penetration on MCP performance is studied. In agreement with past measurements, we find that the dependence of MCP sensitivity with angle relative to the pore bias changes from a cotangent dependence to angular independence and then proceeds to a secant dependence as the x-ray energy increases. We also find that with the increasing x-ray energy, the MCP gain sensitivity as a function of bias voltage decreases. The simulations also demonstrate that for x rays incident normal to the MCP surface, spatial resolution shows little dependence on the x-ray energy but degrades with the increasing x-ray energy as the angle of incidence relative to the surface normal increases. This agrees with experimental measurements. Simulation studies have also been completed for MCPs gated with a subnanosecond voltage pulse. In this work, we find that the optical gate profile width increases as the x-ray energy is increased above 5 keV, a consequence of increased x-ray penetration at energies >5 keV. Simulations of the pulsed dynamic range show that the dynamic range varies between ~100 and 1000 depending on x-ray energy and peak voltage.

47 OTHER INSTRUMENTATION↗

DOE OSTI2021

Formation of edge pressure pedestal and reversed magnetic shear due to toroidal rotation in a tokamak equilibrium

Toroidal rotation is well known to play significant roles in the edge transport and L-H transition dynamics of tokamaks. Our recent calculation finds that a sufficiently strong localized toroidal rotation can directly bring out the formation of edge pressure pedestal with reversed magnetic shear that is reminiscent of an H-mode plasma, purely through the effects of toroidal rotation on the tokamak MHD equilibrium itself. In particular, the enhanced edge toroidal rotation enables a substantial peaking of the parallel current profile near edge in higher β regimes, which leads to the flattening or reversal of the local q (safety factor) profile. Here the formation of pressure pedestal along with the reversed magnetic shear region is shown to be the natural outcome of the MHD tokamak equilibrium in a self-consistent response to the presence of a localized toroidal rotation typically observed in H-mode or QH-mode.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2026

Advancing extreme pulsed lasers through measurements: summary of the pulsed laser metrology workshop

In this report we present consensus findings produced during the pulsed laser metrology (PLM) workshop (Boulder, CO, USA, August 2025). The workshop was a meeting of 35 scientists from private industry, academia, and U.S. government to compile a list of the metrology needs to support extreme pulsed laser development and implementation. We define ‘extreme pulsed lasers’ loosely as those with peak powers above 1 TW or multi-Joule pulse energies. Such lasers are being increasingly used and investigated for use in high energy particle acceleration, short wavelength radiation generation, laser-based fusion, etc. The rapid growth of these fields and the proliferation of extreme lasers for these applications, coupled with the extreme electric fields they generate and relative scarcity of such lasers, presents unique challenges to accuracy in their measurement. The PLM workshop was a two-day event designed to hear from users, developers, and researchers on the current state of optical metrology associated with these extreme pulsed lasers. The goal was to identify the most important measurement challenges limiting development and implementation of these lasers in practical applications. We report here the conclusions and recommendations of this workshop. The hope is that this document will become the first of many iterations which track the status of measurement needs supporting extreme pulsed lasers.

Lasers↗

DOE OSTI2020

Ba ( Ti 1 - x , Zr x ) O 3 relaxors: Dynamic ferroelectrics in the gigahertz frequency range

Relaxor ferroelectrics are of great scientific and technological significance as they exhibit large and unusual responses to external stimuli. Their hallmark features are broadness and frequency dispersion of the peak in the temperature dependence of the dielectric constant. Both are believed to originate from the dynamics of polar nanoregions. Here, we apply first-principles-based molecular dynamics to resolve the gigahertz electric response of dynamically poled Ba (Ti 1 - x , Zr x ) O 3 ferroelectric relaxors that remained overlooked so far. We find that (i) the hallmark relaxor features continue to persist even in the dynamically poled structures, but do not necessarily originate from the polar nanoregions dynamics; (ii) dynamically poled samples exhibit polarization aging which leads to the frequency dependence of both remnant polarization and the Curie temperature; (iii) “dynamical” nature of the latter naturally explains the frequency dependence of the dielectric susceptibility maximum in dynamically poled Ba (Ti 1 - x , Zr x) O 3 ; and (iv) incorporation of the polarization aging into dielectric susceptibility expression explains its enhancing contribution in an intuitive way.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗