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DOE OSTI2026

String-Breaking Dynamics in Quantum Adiabatic and Diabatic Processes

Confinement prohibits isolation of color charges, e.g., quarks, in nature via a process called string breaking : the separation of two charges results in an increase in the energy of a color flux, visualized as a string, connecting those charges. Eventually, creating additional charges is energetically favored, hence breaking the string. Such a phenomenon can be probed in simpler models, including quantum spin chains, enabling enhanced understanding of string-breaking dynamics. A challenging task is to understand how string breaking occurs as time elapses, in an out-of-equilibrium setting. This work establishes the phenomenology of dynamical string breaking induced by a gradual increase of string tension over time. It, thus, goes beyond instantaneous quench processes and enables tracking the real-time evolution of strings in a more controlled setting. We focus on domain-wall confinement in a family of quantum Ising chains. Our results indicate that, for sufficiently short strings and slow evolution, string breaking can be described by the transition dynamics of a two-state quantum system akin to a Landau-Zener process. For longer strings, a more intricate spatiotemporal pattern emerges: the string breaks by forming a superposition of bubbles (domains of flipped spins of varying sizes), which involve highly excited states. We finally demonstrate that string breaking driven only by quantum fluctuations can be realized in the presence of sufficiently long-ranged interactions. This work holds immediate relevance for studying string breaking in quantum-simulation experiments.

Ising model↗

DOE OSTI2020

Cooperative response of magnetism and superconductivity in the magnetic superconductor RbEuFe 4 As 4

Herein, we present a study of the magnetic-flux evolution in the magnetic superconductor RbEuFe 4 As 4 performed using magneto-optical imaging and magnetization measurements during field cooling and warming and magnetic field cycling at temperatures above and below the magnetic transition point, T$_m$. The vortex patterns emerging at T ≲ T$_m$ reveal that the Eu-spin subsystem serves as an internal pump of the magnetic flux while the superconducting critical current controls the delivery of magnetic-flux quanta into the bulk. The interplay of magnetic susceptibility amplifying the magnetic induction and vortex pinning attenuating the magnetic-flux entry results in a field- and temperature-dependent critical state that emulates a paramagnetic Meissner effect. The observed vortex dynamics corresponds to a nontrivial spatial current distribution and yields a self-consistent inhomogeneous enhancement of the sample magnetization.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Single-nucleon energies changing with nucleon number

The broad range of accumulated experimental data on the binding energies for single-particle states in nuclei is examined as a function of the constituent number of neutrons and protons and an unexpectedly simple pattern emerges. The dependence of the energies of neutron states on the number of constituent protons, or of proton states on the number of neutrons, are very similar to each other and the sign reflects the well-known strong attraction. For the same kind of nucleons changing as in the state – energies for neutron states with neutron number changing or proton states with protons – the dependence is at least a factor of four weaker in magnitude and slightly repulsive, except when the changing nucleons are only within the same orbit as the state. The systematics of the accumulated data are presented with a minimum of use made of model assumptions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2016

Spatial scale drives patterns in soil bacterial diversity: Spatial scale drives soil diversity

Soil microbial communities are essential for ecosystem function, but linking community composition to biogeochemical processes is challenging because of high microbial diversity and large spatial variability of most soil characteristics. We investigated soil bacterial community structure in a switchgrass stand planted on soil with a history of grassland vegetation at high spatial resolution to determine whether biogeographic trends occurred at the centimeter scale. Moreover, we tested whether such heterogeneity, if present, influenced community structure within or among ecosystems. Pronounced heterogeneity was observed at centimeter scales, with abrupt changes in relative abundance of phyla from sample to sample. At the ecosystem scale (> 10 m), however, bacterial community composition and structure were subtly, but significantly, altered by fertilization, with higher alpha diversity in fertilized plots. Moreover, by comparing these data with data from 1772 soils from the Earth Microbiome Project, it was found that 20% diverse globally sourced soil samples, while grassland soils shared approximately 40% of their operational taxonomic units with the current study. By spanning several orders of magnitude, the analysis suggested that extreme patchiness characterized community structure at smaller scales but that coherent patterns emerged at larger length scales.

16S rRNA↗

DOE OSTI2020

ANDES (ARGONNE NUCLEAR DATA EXPLORATION SOFTWARE) - ndviz

The Argonne Nuclear Data Exploration Software (ANDES) is a collection of open-source C++ codes and ROOT scripts that enable the visualization of patterns emerging from nuclear data. From this global view, well-known phenomena such as major nuclear shell closures and pairing effects near N=Z nuclei, as well as more subtle features, such as quantum phase transition around the Zr isotopes or the charge radius staggering in the Hg isotopes, can be observed. This visualization tool apart from having pedagogic application can serve as a tool for discovering previously unknown phenomena in the nuclear chart.

Santiago-Gonzalez, Daniel↗

DOE OSTI2020

ANDES (ARGONNE NUCLEAR DATA EXPLORATION SOFTWARE) - Physics Tools

A collection of physics tools used by the ANDES. The Argonne Nuclear Data Exploration Software (ANDES) is a collection of open-source C++ codes and ROOT scripts that enable the visualization of patterns emerging from nuclear data. From this global view, well-known phenomena such as major nuclear shell closures and pairing effects near N=Z nuclei, as well as more subtle features, such as quantum phase transition around the Zr isotopes or the charge radius staggering in the Hg isotopes, can be observed. This visualization tool apart from having pedagogic application can serve as a tool for discovering previously unknown phenomena in the nuclear chart.

Santiago-Gonzalez, Daniel↗

DOE OSTI2024

Assessment of U.S. Urban Surface Temperature Using GOES-16 and GOES-17 Data: Urban Heat Island and Temperature Inequality

Abstract This study utilizes hourly land surface temperature (LST) data from the Geostationary Operational Environmental Satellite (GOES) to analyze the seasonal and diurnal characteristics of surface urban heat island intensity (SUHII) across 120 largest U.S. cities and their surroundings. Distinct patterns emerge in the classification of seasonal daytime SUHII and nighttime SUHII. Specifically, the enhanced vegetation index (EVI) and albedo (ALB) play pivotal roles in influencing these temperature variations. The diurnal cycle of SUHII further reveals different trends, suggesting that climate conditions, urban and nonurban land covers, and anthropogenic activities during nighttime hours affect SUHII peaks. Exploring intracity LST dynamics, the study reveals a significant correlation between urban intensity (UI) and LST, with LST rising as UI increases. Notably, populations identified as more vulnerable by the social vulnerability index (SVI) are found in high UI regions. This results in discernible LST inequality, where the more vulnerable communities are under higher LST conditions, possibly leading to higher heat exposure. This comprehensive study accentuates the significance of tailoring city-specific climate change mitigation strategies, illuminating LST variations and their intertwined societal implications.

Environmental Sciences & Ecology↗

DOE OSTI2013

Feedback-Based, System-Level Properties of Vertebrate-Microbial Interactions

Improved characterization of infectious disease dynamics is required. To that end, three-dimensional (3D) data analysis of feedback-like processes may be considered. To detect infectious disease data patterns, a systems biology (SB) and evolutionary biology (EB) approach was evaluated, which utilizes leukocyte data structures designed to diminish data variability and enhance discrimination. Using data collected from one avian and two mammalian (human and bovine) species infected with viral, parasite, or bacterial agents (both sensitive and resistant to antimicrobials), four data structures were explored: (i) counts or percentages of a single leukocyte type, such as lymphocytes, neutrophils, or macrophages (the classic approach), and three levels of the SB/ EB approach, which assessed (ii) 2D, (iii) 3D, and (iv) multi-dimensional (rotating 3D) host-microbial interactions. In all studies, no classic data structure discriminated disease-positive (D+, or observations in which a microbe was isolated) from disease-negative (D–, or microbial-negative) groups: D+ and D– data distributions overlapped. In contrast, multi-dimensional analysis of indicators designed to possess desirable features, such as a single line of observations, displayed a continuous, circular data structure, whose abrupt inflections facilitated partitioning into subsets statistically significantly different from one another. In all studies, the 3D, SB/EB approach distinguished three (steady, positive, and negative) feedback phases, in which D– data characterized the steady state phase, and D+ data were found in the positive and negative phases. In humans, spatial patterns revealed false-negative observations and three malaria-positive data classes. In both humans and bovines, methicillin-resistant Staphylococcus aureus (MRSA) infections were discriminated from non-MRSA infections. More information can be extracted, from the same data, provided that data are structured, their 3D relationships are considered, and well-conserved (feedback-like) functions are estimated. Patterns emerging from such structures may distinguish well-conserved from recently developed host-microbial interactions. Applications include diagnosis, error detection, and modeling.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2014

Phosphorylation Site Dynamics of Early T-cell Receptor Signaling

In adaptive immune responses, T-cell receptor (TCR) signaling impacts multiple cellular processes and results in T-cell differentiation, proliferation, and cytokine production. Although individual protein–protein interactions and phosphorylation events have been studied extensively, we lack a systems-level understanding of how these components cooperate to control signaling dynamics, especially during the crucial first seconds of stimulation. Here, we used quantitative proteomics to characterize reshaping of the T-cell phosphoproteome in response to TCR/CD28 co-stimulation, and found that diverse dynamic patterns emerge within seconds. We detected phosphorylation dynamics as early as 5 s and observed widespread regulation of key TCR signaling proteins by 30 s. Development of a computational model pointed to the presence of novel regulatory mechanisms controlling phosphorylation of sites with central roles in TCR signaling. The model was used to generate predictions suggesting unexpected roles for the phosphatase PTPN6 (SHP-1) and shortcut recruitment of the actin regulator WAS. Predictions were validated experimentally. This integration of proteomics and modeling illustrates a novel, generalizable framework for solidifying quantitative understanding of a signaling network and for elucidating missing links.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

Standardized beamline particulate characterization analysis: Initial application to CEBAF and LCLS-II cryomodule components

Despite continuously evolving efforts to minimize and manage the occurrence of particulates in operational SRF accelerator systems, the presence of electron field emission from contaminating particulates on SRF surfaces with high surface electric fields remains a consistent challenge. Jefferson Lab has recently initiated a standardized particulate sampling and characterization practice in order to gain more specific and systematic knowledge of the particulates actually present. It is expected that patterns emerging from such sampling will strengthen source attribution and guide improvement efforts. Initial samples were gathered from a cryomodule and adjoining warm girders that were removed from the CEBAF tunnel for reprocessing. The collection and analysis techniques were also used to characterize particulates on the inside of LCLS-II string components. Samples are transferred to clean industry-standard forensic GSR carbon tape spindles and examined via automated cleanroom SEM scanning for particle localization trends and sizing. The particulates are subsequently analyzed with EDS for elemental composition. A catalogue of found particle types is being accumulated. The methods used and results obtained from these initial applications will be presented.

Reece, Charles↗

DOE OSTI2016

Decreasing Aerosol Loading in the North American Monsoon Region

Here, we examine the spatio-temporal variability of aerosol loading in the recent decade (2005-2014) over the North American Monsoon (NAM) region. Emerging patterns are characterized using aerosol optical depth (AOD) retrievals from the NASA Terra/Moderate Resolution Imaging Spectroradiometer (MODIS) instrument along with a suite of satellite retrievals of atmospheric and land-surface properties. We selected 20 aerosol hotspots and classified them into fire, anthropogenic, dust, and NAM alley clusters based on the dominant driver influencing aerosol variability. We then analyzed multivariate statistics of associated anomalies during pre-, monsoon, and post-monsoon periods. Our results show a decrease in aerosol loading for the entire NAM region, confirming previous reports of a declining AOD trend over the continental United States. This is evident during pre-monsoon and monsoon for fire and anthropogenic clusters, which are associated with a decrease in the lower and upper quartile of fire counts and carbon monoxide, respectively. The overall pattern is obfuscated in the NAM alley, especially during monsoon and post-monsoon seasons. While the NAM alley is mostly affected by monsoon precipitation, the frequent occurrence of dust storms in the area modulates this trend. We find that aerosol loading in the dust cluster is associated with observed vegetation index and has only slightly decreased in the recent decade.

58 GEOSCIENCES↗

DOE OSTI2017

Investigating the Magnetic Imprints of Major Solar Eruptions with SDO /HMI High-cadence Vector Magnetograms

The solar active region photospheric magnetic field evolves rapidly during major eruptive events, suggesting appreciable feedback from the corona. Previous studies of these “magnetic imprints” are mostly based on line of sight only or lower-cadence vector observations; a temporally resolved depiction of the vector field evolution is hitherto lacking. Here, we introduce the high-cadence (90 s or 135 s) vector magnetogram data set from the Helioseismic and Magnetic Imager, which is well suited for investigating the phenomenon. These observations allow quantitative characterization of the permanent, step-like changes that are most pronounced in the horizontal field component (B {sub h}). A highly structured pattern emerges from analysis of an archetypical event, SOL2011-02-15T01:56, where B {sub h} near the main polarity inversion line increases significantly during the earlier phase of the associated flare with a timescale of several minutes, while B {sub h} in the periphery decreases at later times with smaller magnitudes and a slightly longer timescale. The data set also allows effective identification of the “magnetic transient” artifact, where enhanced flare emission alters the Stokes profiles and the inferred magnetic field becomes unreliable. Our results provide insights on the momentum processes in solar eruptions. The data set may also be useful to the study of sunquakes and data-driven modeling of the corona.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Dilute Combustion Control Using Spiking Neural Networks

Dilute combustion with exhaust gas recirculation (EGR) in spark-ignition engines presents a cost-effective method for achieving higher levels of engine efficiency. At high levels of EGR, however, cycle-to-cycle variability (CCV) of the combustion process is exacerbated by sporadic occurrences of misfires and partial burns. Previous studies have shown that temporal deterministic patterns emerge at such conditions and certain combustion cycles have a significant influence over future events. Due to the complexity of the combustion process and the nature of CCV, harnessing all the deterministic information for control purposes has remained challenging even with physics based 0-D, 1-D, and high-fidelity computational fluid dynamics (CFD) models. In this study, we present a data-driven approach to optimize the combustion process by controlling CCV adjusting the cycle-to-cycle fuel injection quantity. Readily available data from in-cylinder pressure was used to train a spiking neural network (SNN) which learns the optimal way to manage fuel injection in order to reduce CCV while maintaining acceptable levels of fuel consumption. SNNs are particularly well suited for powertrain control applications due to their ability to be deployed on FPGA-based neuromorphic hardware which are small, inexpensive, and have a low power demand. The high-performance computing (HPC) resources of Oak Ridge National Laboratory were used to run an evolutionary-based training approach for choosing the best SNN configuration that minimizes the size of the network while achieving the desired goal. The neuromorphic hardware with the optimized SNN deployed was connected to the rapid prototyping engine control system for real-time control implementation and tested on a single cylinder version of a GM LNF 4-cylinder engine. The results show a significant reduction of CCV with a small percentage of additional fuel used to stabilize the charge.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2020

Modeling the smoky troposphere of the southeast Atlantic: a comparison to ORACLES airborne observations from September of 2016

The southeast Atlantic is home to well-defined smoke outflow from Africa coinciding vertically with extensive marine boundary-layer cloud decks, both reaching their climatological maxima in spatial extent around September. A framework is put forth for evaluating the performance of a range of global and regional aerosol models against observations made during the NASA ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) airborne mission in September 2016. The sparse airborne observations are first aggregated into 2o grid boxes and into three vertical layers: the cloud-topped marine boundary layer (MBL), the layer from cloud top to 3 km, and the 3-6 km layer. Aerosol extensive properties simulated for the entire study region for all September suggest that the 2016 ORACLES observations are reasonably representative of the regional monthly average, with systematic deviations of 30% or less. All six models typically place the bottom of the smoke layer at lower altitudes than do the airborne lidar observations by 300-1400 m, whereas model aerosol top heights are within 0-500 m of the observations. All but one of the models that report carbonaceous aerosol masses underestimate the ratio of particulate extinction to the masses, a proxy for mass extinction efficiency, in 3-6 km. Notable findings on individual models include that WRF-CAM5 predicts the mass of black carbon and organic aerosols with minor (~10% or less) biases. GEOS-5 overestimates the carbonaceous particle masses in the MBL by a factor of 3-6. Extinction coefficients in the free troposphere (FT) and above-cloud aerosol optical depth (ACAOD) are 10-30% lower in WRF-CAM5, 30-50% lower in GEOS-5, 10-40% higher in GEOS-Chem, 10-20% higher in EAM-E3SM except for the practically unbiased 3-6 km extinction, and 20-70% lower in the Unified Model, than the airborne in situ, lidar and sunphotometer measurements. ALADIN-Climate also underestimates the ACAOD, by 30%. GEOS-5 and GEOS-Chem predict carbon monoxide in the MBL with small (10% or less) negative biases, despite their overestimates of carbonaceous aerosol masses. Overall, this study highlights a new approach to utilizing airborne aerosol measurements for model diagnosis.

Shinozuka, Yohei↗

DOE OSTI2024

Biosphere Futures: a database of social-ecological scenarios

T. Biosphere Futures (https://biospherefutures.net/) is a new online database to collect and discover scenario studies from across the world, with a specific focus on scenarios that explicitly incorporate interdependencies between humans and their supporting ecosystems. It provides access to a globally diverse collection of case studies that includes most ecosystems and regions, enabling exploration of the multifaceted ways in which the future might unfold. Together, the case studies illuminate the diversity and plurality of people’s expectations and aspirations for the future. The objective of Biosphere Futures is to promote the use of scenarios for sustainable development of the biosphere and to foster a community of practice around social-ecological scenarios. We do so by facilitating the assessment, synthesis, and comparative analysis of scenario case studies, pointing to relevant resources, and by helping practitioners and researchers to disseminate and showcase their own work. This article begins by outlining the rationale behind the creation of the database, followed by an introduction to its functionality and the criteria employed for selecting case studies. Subsequently, we present a synthesis of the first 100 case studies included in the scenarios database, highlighting emerging patterns and identifying potential avenues for further research. Finally, given that broader utilization and contributions to the database will enhance the achievement of Biosphere Futures’ objectives, we invite the creators of social-ecological scenarios to contribute additional case studies. By expanding the database’s breadth and depth, we can collectively foster a more nuanced understanding of the possible trajectories of our biosphere and enable better decision making for sustainable development.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1977

The technical challenge of air transportation - A Government view

This paper reviews the research and technology that must be conducted, and the facility investments that must be made, in order to assure that the United States is adequately prepared to meet the challenges that air transportation will provide in the future. The technical focal points for the next decade are reviewed in the context of the emerging pattern of air transportation needs for the remainder of the Century and the prospects for satisfying these needs are discussed. Particular attention is given to the responsibility that the Government must assume in aviation R&T and to the relationship that must be encouraged between the Government, the Industry and the University Community.

Roberts, L.↗

NASA NTRS1983

Aubrites and diogenites - Trace element clues to their origin

A typically igneous siderophile element pattern emerges from an RNAA analysis of 25 aubrite and nine diogenite samples for 13-29 siderophile, volatile, and lithophile trace elements, although it is noted that abundances are about 10 times higher in the case of aubrites. Se is also surprisingly abundant in aubrites. Factor analysis shows several parallel groupings for aubrites and diogenites. Several element pairs that differ greatly in volatility correlate closely in aubrites, in approximately C1-chondrite proportions, suggesting that aubrites originated by igneous processes in their parent body.

Wolf, R.↗

NASA NTRS1985

Volcanism of the Colorado Plateau - Basin and Range Transition: Implications for Crustal Processes

On the Colorado Plateau-Basin and Range transition in Arizona and New Mexico, basaltic volcanism takes two physiographic forms: (1) Major central composite volcanoes (e.g., San Francisco Peaks) in which basaltic magma differentiates at shallow crustal levels to siliceous and members and (2) large numbers of small cinder cones and a few domes that result from numerous discrete magma batches which apparently had little opportunity for differentiation. This study represents the first look at the petrogenesis of Plateau-bounding volcanic fields, based on rigorous stratigraphic controls, in combination with major and trace-element constraints. The emerging pattern of large volcanic constructs associated with shallow fractional crystallization, and numerous cinder cones associated with limited or no shallow differentiation may provide an analogue for interpreting petrogenetic patterns and/or tectonic settings on Mars.

Condit, C. D.↗