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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Overcoming persistent challenges in putting environmental flow policy into practice: a systematic review and bibliometric analysis

The implementation of environmental flows (e-flows) aims to reduce the negative impacts of hydrological alteration on freshwater ecosystems. Despite the growing attention to the importance of e-flows since the 1970s, actual implementation has lagged. Therefore, we explore the limitations in e-flows implementation, their systemic reasons, and solutions. We conducted a systematic review and a bibliometric analysis to identify peer-reviewed articles published on the topic of e-flows implementation research in the last two decades, resulting in 68 research and review papers. Co-occurrence of terms, and geographic and temporal trends were analyzed to identify the gaps in environmental water management and propose recommendations to address limitations on e-flows implementation. We identify the underlying causes and potential solutions to such challenges in environmental water management. The limitations to e-flow implementation identified were categorized into 21 classes. The most recognized limitation was the competing priorities of human uses of water (n = 29). Many secondary limitations, generally co-occurring in co-causation, were identified as limiting factors, especially for implementing more nuanced and sophisticated e-flows. The lack of adequate hydrological data (n = 24) and ecological data (n = 28) were among the most mentioned, and ultimately lead to difficulties in starting or continuing monitoring/adaptive management (n = 28) efforts. The lack of resource/capacity (n = 21), experimentation (n = 19), regulatory enforcement (n = 17), and differing authorities involved (n = 18) were also recurrent problems, driven by the deficiencies in the relative importance given to e-flows when facing other human priorities. In order to provide a clearer path for successful e-flow implementation, system mapping can be used as a starting point and general-purpose resource for understanding the sociohydrological problems, interactions, and inherited complexity of river systems. Secondly, we recommend a system analysis approach to address competing demands, especially with the use of coupled water-energy modeling tools to support decision-making when hydropower generation is involved. Such approaches can better assess the complex interactions among the hydrologic, ecological, socioeconomic, and engineering dimensions of water resource systems and their effective management. Lastly, given the complexities in environmental water allocation, implementation requires both scientific rigor and proven utility. Consequently, and where possible, we recommend a move from simplistic flow allocations to a more holistic approach informed by hydroecological principles. To ease conflicts between competing water demands, water managers can realize more 'pop per drop' by supporting key components of a flow regime that include functional attributes and processes that enhance biogeochemical cycling, structural habitat formation, and ecosystem maintenance.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Characterizing manufacturing sector disruptions with targeted mitigation strategies

It has become clear in recent decades that manufacturing supply chains are increasingly vulnerable to disruptions of varying geographical scales and intensities. These disruptions—whether intentional, accidental, or resulting from natural disasters—cause failures and capacity reductions to manufacturing infrastructure, with lasting effects that can cascade throughout the manufacturing network. An overall lack of understanding of solutions to mitigate disturbances has rendered the challenge of reducing manufacturing supply chain vulnerability even more difficult. Additionally, the variability of disruptions and their impacts complicates policy maker and stakeholder efforts to plan for specific disruptive scenarios. It is necessary to comprehend different kinds of disturbances and group them based on stakeholder-provided metrics to support planning processes and modeling efforts that promote adaptable, resilient manufacturing supply chains. This paper reviews existing methods for risk management in manufacturing supply chains and the economic and environmental impacts of disruptions. In addition, we develop a framework using agglomerative hierarchical clustering to classify disruptions using U.S. manufacturing network data between 2000 and 2021 and characteristic metrics defined in the literature. Our review identifies five groups of disruptions and discusses both general mitigation methods and strategies targeting each identified group. Further, we highlight gaps in the literature related to estimating and including environmental costs in disaster preparedness and mitigation planning. We also discuss the lack of easily available metrics to quantify environmental impacts of disruptions and how such metrics could be included into our methodology.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Additive manufacturing of multiscale NiFeMn multi-principal element alloys with tailored composition

Nanostructured multi-principal element alloys (MPEAs) have been explored as next-generation engineering materials due to unique mechanical and functional properties which have significant advantages over traditional dilute alloys. However, the practical applications of nanostructured MPEAs are still limited due to the lack of scalable processing approaches to prepare a large quantity of nanostructured MPEAs, as well as lack of an efficient pathway for high-throughput discovery of better functional nanostructured MPEAs within their vast compositional space. Here we tackle these challenges by presenting an integrated approach by combining direct-ink-writing-based additive manufacturing, solid-state sintering, and chemical dealloying to manufacture hierarchically porous MPEAs. The hierarchical structure is comprised of macro- and micro-scale pores introduced via extrusion printing and polymer decomposition during sintering, as well as nanoscale pores formed via chemical dealloying. The macro- and micro-scale pores allow efficient dealloying of a large mass of material as the diffusion length that the corroding medium must penetrate remains at the scale of the ligaments formed after sintering (∼10 μm), despite the large volume of the 3D-printed samples. In addition, this integrated approach enables versatile control of the alloy composition via precisely tuning the ratio of elemental powders in the starting ink, thus offering a pathway for high-throughput discovery of novel functional MPEAs. As a case study, multiscale macro/micro/nanoporous NiFeMn MPEAs with three different compositions were investigated as catalysts to reduce the overpotential of oxygen evolution reaction (OER), where NiFeMn-based electrocatalysts display composition-dependent performance such that the overpotential measured at a current of 0.5 A g −1 for OER increases in the order of Ni 58 Fe 29 Mn 13 ⩽ Ni 64 Fe 26 Mn 10 < Ni 76 Fe 18 Mn 6 . This introduced manufacturing process offers new opportunities for scalable fabrication and rapid screening of nanostructured multi-component complex alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Automated annotation of scientific texts for ML-based keyphrase extraction and validation

Advanced omics technologies and facilities generate a wealth of valuable data daily; however, the data often lack the essential metadata required for researchers to find, curate, and search them effectively. The lack of metadata poses a significant challenge in the utilization of these data sets. Machine learning (ML)–based metadata extraction techniques have emerged as a potentially viable approach to automatically annotating scientific data sets with the metadata necessary for enabling effective search. Text labeling, usually performed manually, plays a crucial role in validating machine-extracted metadata. However, manual labeling is time-consuming and not always feasible; thus, there is a need to develop automated text labeling techniques in order to accelerate the process of scientific innovation. This need is particularly urgent in fields such as environmental genomics and microbiome science, which have historically received less attention in terms of metadata curation and creation of gold-standard text mining data sets. In this paper, we present two novel automated text labeling approaches for the validation of ML-generated metadata for unlabeled texts, with specific applications in environmental genomics. Our techniques show the potential of two new ways to leverage existing information that is only available for select documents within a corpus to validate ML models, which can then be used to describe the remaining documents in the corpus. The first technique exploits relationships between different types of data sources related to the same research study, such as publications and proposals. The second technique takes advantage of domain-specific controlled vocabularies or ontologies. In this paper, we detail applying these approaches in the context of environmental genomics research for ML-generated metadata validation. Our results show that the proposed label assignment approaches can generate both generic and highly specific text labels for the unlabeled texts, with up to 44% of the labels matching with those suggested by a ML keyword extraction algorithm.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2021

The first sequenced Sphaerotilus natans bacteriophage– characterization and potential to control its filamentous bacterium host

ABSTRACT Bacteriophages (phages) are ubiquitous entities present in every conceivable habitat as a result of their bacterial parasitism. Their prevalence and impact in the ecology of bacterial communities and their ability to control pathogens make their characterization essential, particularly of new phages, improving knowledge and potential application. The isolation and characterization of a new lytic phage against Sphaerotilus natans strain DSM 6575, named vB_SnaP-R1 (SnaR1), is here described. Besides being the first sequenced genome of a Sphaerotilus natans infecting phage, 99% of its 41507 bp genome lacks homology with any other sequenced phage, revealing its uniqueness and previous lack of knowledge. Moreover, SnaR1 is the first Podoviridae phage described infecting this bacterium. Sphaerotilus natans is an important filamentous bacterium due to its deleterious effect on wastewater treatment plants (WWTP) and thus, phages may play a role as novel biotechnological tools against filamentous overgrowth in WWTP. The lytic spectrum of SnaR1 was restricted to its host strain, infecting only one out of three S. natans strains and infection assays revealed its ability to reduce bacterial loads. Results suggest SnaR1 as the prototype of a new phage genus and demonstrates its potential as a non-chemical alternative to reduce S. natans DSM 6575 cells.

Ferreira, Rute↗
DOE OSTI2020

Towards real-time monitoring: data assimilated time-lapse full waveform inversion for seismic velocity and uncertainty estimation

SUMMARY Rapid development of time-lapse seismic monitoring instrumentations has made it possible to collect dense time-lapse data for tomographically retrieving time-lapse (even continuous) images of subsurface changes. While traditional time-lapse full waveform inversion (TLFWI) algorithms are designed for sparse time-lapse surveys, they lack of effective temporal constraint on time-lapse data, and, more importantly, lack of the uncertainty estimation of the TLFWI results that is critical for further interpretation. Here, we propose a new data assimilation TLFWI method, using hierarchical matrix powered extended Kalman filter (HiEKF) to quantify the image uncertainty. Compared to existing Kalman filter algorithms, HiEKF allows to store and update a data-sparse representation of the cross-covariance matrices and propagate model errors without expensive operations involving covariance matrices. Hence, HiEKF is computationally efficient and applicable to 3-D TLFWI problems. Then, we reformulate TLFWI in the framework of HiEKF (termed hereafter as TLFWI-HiEKF) to predict time-lapse images of subsurface spatiotemporal velocity changes and simultaneously quantify the uncertainty of the inverted velocity changes over time. We demonstrate the validity and applicability of TLFWI–HiEKF with two realistic CO2 monitoring models derived from Frio-II and Cranfield CO2 injection sites, respectively. In both 2-D and 3-D examples, the inverted high-resolution time-lapse velocity results clearly reveal a continuous velocity reduction due to the injection of CO2. Moreover, the accuracy of the model is increasing over time by assimilating more time-lapse data while the standard deviation is decreasing over lapsed time. We expect TLFWI-HiEKF to be equipped with real-time seismic monitoring systems for continuously imaging the distribution of subsurface gas and fluids in the future large-scale CO2 sequestration experiments and reservoir management.

58 GEOSCIENCES↗
DOE OSTI2020

Seismoacoustic analysis of underground explosions using the Rayleigh integral

SUMMARY A coupled seismoacoustic model is developed for the analysis of acoustic signals produced by underground explosive events with an aim to develop a means of improving estimated depth and yield for explosion monitoring. A ground spall model is used to predict surface motion characteristics produced by an underground explosion and the Rayleigh integral is applied to relate the surface motion to the acoustic signal some distance from surface ground zero. The low-frequency component of the ground motion associated with the prolonged free fall of lofted material during spall is found to dominate the acoustic signal propagating away from surface ground zero at shallow angles. The model is applied to observed ground motion and acoustic signals recorded during the Source Physics Experiment (SPE) with promising results. In addition to accurately predicting characteristics of the observed acoustic signals from several of the SPE events, the model provides a means of explaining the lack of signals observed during several events in the SPE due to the directionality of the higher frequency acoustic signals associated with the uplift and closure components as well as the lack of a spatially localized, longer duration dwell.

58 GEOSCIENCES↗
DOE OSTI2020

A new pinnotherid crab of the genus Pinnixulala Palacios Theil, Cuesta & Felder, 2016 from uncertain infaunal hosts in the northern Gulf of Mexico, with a rediagnosis and updated synonymy for the polychaete symbiont Pinnixulala retinens (Rathbun, 1918) (Decapoda: Brachyura: Pinnotheridae)

Abstract A new infaunal pinnotherid crab, Pinnixulala heardin. sp., is described from muddy substrates of the middle to inner continental shelf of the northern Gulf of Mexico. Molecular genetic analysis supports its separation from P. retinens (Rathbun, 1918), the only other western Atlantic member of the genus and a species most commonly found living as a symbiont of large polychaete worms. Both western Atlantic species are clearly separated from several described and undescribed populations of congeners occurring along shorelines of the eastern Pacific. We herein include a rediagnosis of P. retinens to facilitate morphological comparisons with P. heardin. sp. Unlike P. retinens, which is more common in shallow inshore waters and reaches larger sizes, the new species lacks development of a strong distally directed spine on the fourth pereopod ischium and has chelae that are at least as heavily developed as the second and third pereopods. In addition, the mature male first gonopods in P. heardin. sp. are tapered over their terminal one-third and directed distally, rather than being curved in their terminal one-third with the tips directed mesially, as they are in P. retinens. The new species is invariably collected from samples including infaunal worms and other invertebrates, but the specific hosts remain to be determined

Marine & Freshwater Biology↗
DOE OSTI2021

Patient-Reported Outcomes in Pediatric Cancer Registration Trials: A US Food and Drug Administration Perspective

Pediatric patient-reported outcome (PRO) data can help inform the US Food and Drug Administration’s (FDA’s) benefit-risk assessment of cancer therapeutics by quantifying symptom and functional outcomes from the patient’s perspective. This study assessed use of PROs in commercial pediatric oncology trials submitted to the FDA for regulatory review. FDA databases were searched to identify pediatric oncology product applications approved between 1997 and 2020. Sponsor-submitted documents were reviewed to determine whether PRO data were collected, which instruments were used, and the quality of collected data (ie, sample size, completion rates, and use of fit-for-purpose instruments). The role of PROs in each trial (endpoint hierarchy) was also recorded in addition to whether any PRO endpoints were included in product labeling. We reviewed 17 pediatric oncology applications, 4 of which included PRO data: denosumab, tisagenlecleucel, larotrectinib, and selumetinib. In these 4 instances, PROs served as exploratory endpoints and were not incorporated in product labeling. Trials that collected PRO data were phase II or phase I/II single-arm studies with sample sizes of 28 to 88 patients. Symptomatic adverse events (AEs) were characterized using clinician-reported Common Terminology Criteria for Adverse Events (CTCAE) without additional patient self-report. PROs were infrequently used in pediatric cancer registration trials. When PROs were used, PRO data were limited by lack of a clear research objective and corresponding prospective statistical analysis plan. Contemporary PRO symptom libraries, such as the National Cancer Institute’s Pediatric PRO-CTCAE, may provide an opportunity to better evaluate the occurrence and impact of symptomatic AEs, from the patient’s perspective, in pediatric oncology trials.

Oncology↗
DOE OSTI2021

A best-practice guide to predicting plant traits from leaf-level hyperspectral data using partial least squares regression

Partial least squares regression (PLSR) modelling is a statistical technique for correlating datasets, and involves the fitting of a linear regression between two matrices. One application of PLSR enables leaf traits to be estimated from hyperspectral optical reflectance data, facilitating rapid, high-throughput, non-destructive plant phenotyping. This technique is of interest and importance in a wide range of contexts including crop breeding and ecosystem monitoring. The lack of a consensus in the literature on how to perform PLSR means that interpreting model results can be challenging, applying existing models to novel datasets can be impossible, and unknown or undisclosed assumptions can lead to incorrect or spurious predictions. We address this lack of consensus by proposing best practices for using PLSR to predict plant traits from leaf-level hyperspectral data, including a discussion of when PLSR is applicable, and recommendations for data collection. Further, we provide a tutorial to demonstrate how to develop a PLSR model, in the form of an R script accompanying this manuscript. This practical guide will assist all those interpreting and using PLSR models to predict leaf traits from spectral data, and advocates for a unified approach to using PLSR for predicting traits from spectra in the plant sciences.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

The chemical properties of the Milky Way’s on-bar and off-bar regions: evidence for inhomogeneous star formation history in the bulge

ABSTRACT Numerous studies of integrated starlight, stellar counts, and kinematics have confirmed that the Milky Way is a barred galaxy. However, far fewer studies have investigated the bar’s stellar population properties, which carry valuable independent information regarding the bar’s formation history. Here, we conduct a detailed analysis of chemical abundance distributions ([Fe/H] and [Mg/Fe]) in the on-bar and off-bar regions to study the azimuthal variation of star formation history (SFH) in the inner Galaxy. We find that the on-bar and off-bar stars at Galactocentric radii 3 kpc < rGC < 5 kpc have remarkably consistent [Fe/H] and [Mg/Fe] distribution functions and [Mg/Fe]–[Fe/H] relation, suggesting a common SFH shared by the long bar and the disc. In contrast, the bar and disc at smaller radii (2 kpc < rGC < 3 kpc) show noticeable differences, with relatively more very metal-rich ($\rm [Fe/H] \sim 0.4$) stars but fewer solar abundance stars in the bar. Given the three-phase star formation history proposed for the inner Galaxy in Lian et al., these differences could be explained by the off-bar disc having experienced either a faster early quenching process or recent metal-poor gas accretion. Vertical variations of the abundance distributions at small rGC suggest a wider vertical distribution of low-α stars in the bar, which may serve as chemical evidence for vertical heating through the bar buckling process. The lack of such vertical variations outside the bulge may then suggest a lack of vertical heating in the long bar.

Lian, Jianhui↗
DOE OSTI2022

Deprojection of X-ray data in galaxy clusters: confronting simulations with observations

ABSTRACT Numerical simulations with varying realism indicate an emergent principle−multiphase condensation and large cavity power occur when the ratio of the cooling time to the free-fall time (tcool/tff) falls below a threshold value close to 10. Observations indeed show cool-core signatures when this ratio falls below 20–30, but the prevalence of cores with tcool/tff ratio below 10 is rare as compared to simulations. In X-ray observations, we obtain projected spectra from which we have to infer radial gas density and temperature profiles. Using idealized models of X-ray cavities and multiphase gas in the core and 3D hydro jet-ICM simulations, we quantify the biases introduced by deprojection based on the assumption of spherical symmetry in determining tcool/tff. We show that while the used methods are able to recover the tcool/tff ratio for relaxed clusters, they have an uncertainty of a factor of 2−3 in systems containing large cavities (≳ 20 kpc). We also show that the mass estimates from these methods, in the absence of X-ray spectra close to the virial radius, suffer from a degeneracy between the virial mass (M200) and the concentration parameter (c) in the form of M200c2 ≈ constant. Additionally, the lack of soft-X-ray (≲ 0.5 keV) coverage and poor spatial resolution makes us overestimate min(tcool/tff) by a factor of few in clusters with min(tcool/tff) ≲ 5. This bias can largely explain the lack of cool-core clusters with min(tcool/tff) ≲ 5.

Sarkar, Kartick C. (ORCID:0000000277678472)↗
DOE OSTI2021

RNase R is associated in a functional complex with the RhpA DEAD-box RNA helicase in Helicobacter pylori

Abstract Ribonucleases are central players in post-transcriptional regulation, a major level of gene expression regulation in all cells. Here, we characterized the 3′-5′ exoribonuclease RNase R from the bacterial pathogen Helicobacter pylori. The ‘prototypical’ Escherichia coli RNase R displays both exoribonuclease and helicase activities, but whether this latter RNA unwinding function is a general feature of bacterial RNase R had not been addressed. We observed that H. pylori HpRNase R protein does not carry the domains responsible for helicase activity and accordingly the purified protein is unable to degrade in vitro RNA molecules with secondary structures. The lack of RNase R helicase domains is widespread among the Campylobacterota, which include Helicobacter and Campylobacter genera, and this loss occurred gradually during their evolution. An in vivo interaction between HpRNase R and RhpA, the sole DEAD-box RNA helicase of H. pylori was discovered. Purified RhpA facilitates the degradation of double stranded RNA by HpRNase R, showing that this complex is functional. HpRNase R has a minor role in 5S rRNA maturation and few targets in H. pylori, all included in the RhpA regulon. We concluded that during evolution, HpRNase R has co-opted the RhpA helicase to compensate for its lack of helicase activity.

Tejada-Arranz, Alejandro↗
DOE OSTI2024

Stereoselective recognition of morphine enantiomers by μ -opioid receptor

Stereospecific recognition of chiral molecules plays a crucial role in biological systems. The μ-opioid receptor (MOR) exhibits binding affinity towards (-)-morphine, a well-established gold standard in pain management, while it shows minimal binding affinity for the (+)-morphine enantiomer, resulting in a lack of analgesic activity. Understanding how MOR stereoselectively recognizes morphine enantiomers has remained a puzzle in neuroscience and pharmacology for over half-a-century due to the lack of direct observation techniques. To unravel this mystery, we constructed the binding and unbinding processes of morphine enantiomers with MOR via molecular dynamics simulations to investigate the thermodynamics and kinetics governing MOR's stereoselective recognition of morphine enantiomers. Our findings reveal that the binding of (-)-morphine stabilizes MOR in its activated state, exhibiting a deep energy well and a prolonged residence time. In contrast, (+)-morphine fails to sustain the activation state of MOR. Furthermore, the results suggest that specific residues, namely D114 2.50 and D147 3.32 , are deprotonated in the active state of MOR bound to (-)-morphine. This work highlights that the selectivity in molecular recognition goes beyond binding affinities, extending into the realm of residence time.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Aspartate Residues in a Forisome-Forming SEO Protein Are Critical for Protein Body Assembly and Ca 2+ Responsiveness

Forisomes are protein bodies known exclusively from sieve elements of legumes. Forisomes contribute to the regulation of phloem transport due to their unique Ca 2+ -controlled, reversible swelling. The assembly of forisomes from sieve element occlusion (SEO) protein monomers in developing sieve elements and the mechanism(s) of Ca 2+ -dependent forisome contractility are poorly understood because the amino acid sequences of SEO proteins lack conventional protein–protein interaction and Ca 2+ -binding motifs. Here we selected amino acids potentially responsible for forisome-specific functions by analyzing SEO protein sequences in comparison to those of the widely distributed SEO-related (SEOR), or SEOR proteins. SEOR proteins resemble SEO proteins closely but lack any Ca 2+ responsiveness. We exchanged identified candidate residues by directed mutagenesis of the Medicago truncatula SEO1 gene, expressed the mutated genes in yeast ( Saccharomyces cerevisiae ) and studied the structural and functional phenotypes of the forisome-like bodies that formed in the transgenic cells. We identified three aspartate residues critical for Ca 2+ responsiveness and two more that were required for forisome-like bodies to assemble. The phenotypes observed further suggested that Ca 2+ -controlled and pH-inducible swelling effects in forisome-like bodies proceeded by different yet interacting mechanisms. Finally, we observed a previously unknown surface striation in native forisomes and in recombinant forisome-like bodies that could serve as an indicator of successful forisome assembly. To conclude, this study defines a promising path to the elucidation of the so-far elusive molecular mechanisms of forisome assembly and Ca 2+ -dependent contractility.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Four Families of Folate-independent Methionine Synthases

Abstract Although most organisms synthesize methionine from homocysteine and methyl folates, some have “core” methionine synthases that lack folate-binding domains and use other methyl donors. In vitro , the characterized core synthases use methylcobalamin as a methyl donor, but in vivo , they probably rely on corrinoid (vitamin B12-binding) proteins. We identified four families of core methionine synthases that are distantly related to each other (under 30% pairwise amino acid identity). From the characterized enzymes, we identified the families MesA, which is found in methanogens, and MesB, which is found in anaerobic bacteria and archaea with the Wood-Ljungdahl pathway. A third uncharacterized family, MesC, is found in anaerobic archaea that have the Wood-Ljungdahl pathway and lack known forms of methionine synthase. We predict that most members of the MesB and MesC families accept methyl groups from the iron-sulfur corrinoid protein of that pathway. The fourth family, MesD, is found only in aerobic bacteria. Using transposon mutants and complementation, we show that MesD does not require 5-methyltetrahydrofolate or cobalamin. Instead, MesD requires an uncharacterized protein family (DUF1852) and oxygen for activity.

Price, Morgan↗
DOE OSTI2025

Competing Electronic Ground States in the Heavy-Fermion Superconductor CeRh 2 As 2

CeRh 2 ⁢As 2 is rare among superconductors, in that the magnetic field tunes it between two distinct superconducting phases. Combined with a lack of local inversion symmetry and an upper critical field exceeding the Pauli paramagnetic limit, this excitingly suggests triplet multicomponent superconductivity. Preceding the superconducting onset, 𝑓-electron correlations cause long-range order, attributed both to local antiferromagnetism and itinerant (quadrupole) density waves. A magnetic field provides a significant perturbation of the 𝑓 electrons and may reveal the nature of the many-body correlations. Therefore, we report comprehensive magnetization and magnetotransport studies on microstructured devices in fields of up to 73 T. Applied along the 𝑐 axis, the field causes a low-temperature change of majority (hole) carrier density at 𝜇 0⁢ 𝐻 ≈ 2⁢4 T. By contrast, in-plane fields produce a cascade of phase transitions; the field-induced in-plane conductivity anisotropy and lack of accompanying magnetic features, plus the closed-dome nature of the overall phase boundary is consistent with a hierarchy of field-induced density-wave states.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Operator dynamics in Floquet many-body systems

We study operator dynamics in many-body quantum systems, focusing on generic features of systems that are ergodic, spatially extended, and lack conserved densities. Quantum circuits of various types provide simple models for such systems. We focus on Floquet quantum circuits, comparing their behavior with what has been found previously for circuits that are random in time. Floquet circuits, which have discrete time-translation symmetry, represent an intermediate case between circuits that are random in time and lack any symmetry, and systems with a time-independent Hamiltonian and continuous time-translation invariance. By making this comparison, one of our aims is to identify signatures of time-translation symmetry in Floquet operator dynamics. To characterize behavior we examine a variety of quantities in solvable models and numerically: operator autocorrelation functions; the partial spectral form factor; the out-of-time-order correlator (OTOC); and the paths in operator space that make the dominant contributions to the ensemble-averaged autocorrelation functions. Our most striking result is that ensemble-averaged autocorrelation functions show behavior that is distinctively different in Floquet systems compared to systems in which successive time-steps are independent. Specifically, while average autocorrelation functions decay on a microscopic timescale for circuits that are random in time, in Floquet systems they have a late-time tail with a duration that grows parametrically with the size of the operator support. In the simplest models this tail is separated from the initial decay by a minimum, so that the average autocorrelation function has an intermediate-time peak. The existence of these tails provides a way to understand deviations of the spectral form factor from random matrix behavior at times shorter than the Thouless time. In contrast to this feature in autocorrelation functions, we find no new aspects to the behavior of OTOCs for Floquet models compared to random-in-time circuits. We show that this difference between averaged autocorrelation functions and OTOCs can be understood in terms of the paths in operator space that contribute to the two quantities: paths for the former retain a limited support at late times, while paths for the latter are dominated by operator spreading. Published by the American Physical Society 2025

Yoshimura, Takato (ORCID:0000000309159846)↗