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At least 973 records · Page 54

Host population dynamics influence Leptospira spp. transmission patterns among Rattus norvegicus in Boston, Massachusetts, US

Leptospirosis (caused by pathogenic bacteria in the genus Leptospira ) is prevalent worldwide but more common in tropical and subtropical regions. Transmission can occur following direct exposure to infected urine from reservoir hosts, or a urine-contaminated environment, which then can serve as an infection source for additional rats and other mammals, including humans. The brown rat, Rattus norvegicus , is an important reservoir of Leptospira spp. in urban settings. We investigated the presence of Leptospira spp. among brown rats in Boston, Massachusetts and hypothesized that rat population dynamics in this urban setting influence the transportation, persistence, and diversity of Leptospira spp. We analyzed DNA from 328 rat kidney samples collected from 17 sites in Boston over a seven-year period (2016–2022); 59 rats representing 12 of 17 sites were positive for Leptospira spp. We used 21 neutral microsatellite loci to genotype 311 rats and utilized the resulting data to investigate genetic connectivity among sampling sites. We generated whole genome sequences for 28 Leptospira spp. isolates obtained from frozen and fresh tissue from some of the 59 positive rat kidneys. When isolates were not obtained, we attempted genomic DNA capture and enrichment, which yielded 14 additional Leptospira spp. genomes from rats. We also generated an enriched Leptospira spp. genome from a 2018 human case in Boston. We found evidence of high genetic structure among rat populations that is likely influenced by major roads and/or other dispersal barriers, resulting in distinct rat population groups within the city; at certain sites these groups persisted for multiple years. We identified multiple distinct phylogenetic clades of L. interrogans among rats that were tightly linked to distinct rat populations. This pattern suggests L. interrogans persists in local rat populations and its transportation is influenced by rat population dynamics. Finally, our genomic analyses of the Leptospira spp. detected in the 2018 human leptospirosis case in Boston suggests a link to rats as the source. These findings will be useful for guiding rat control and human leptospirosis mitigation efforts in this and other similar urban settings.

Stone, Nathan E.↗

Dataset for: Price Controls for Scarcity Events in Real-Time and Transactive Energy Systems

Real time pricing (RTP) is often promoted as a mechanism to improve the economic efficiency of the electricity system. However, many regulators have been hesitant to adopt RTP due to concerns about exposing customers to extreme price swings. To balance these concerns, this paper proposes a methodology for establishing price controls, based on the supply of demand-side flexibility in the system. As an illustrative example, we measure price responsiveness using an agent-based simulation model that is representative of the ERCOT market. The model is composed of a distribution feeder that has 250 customers with active agents controlling their HVAC systems in response to the historical ERCOT RTP with an artificially added high-price event. These agents are subjected to increasing electricity prices during the event, which we then use to create a supply curve for demand-side resources in our modeled scarcity event. We set potential price caps at points on the supply curve where customers’ have exhausted their flexible capacity. Using historical prices, we examine the systemic costs of these price caps, and present regulatory options for recouping them. Utilities and regulators interested in limiting consumer risk from dynamic pricing can utilize these methods to develop rate structures and encourage conservation. The attached data upload allows for the duplication or modification of the analysis performed in this study.

Kerby, Jessica R↗

Ultrafast Terahertz Field Control of the Emergent Magnetic and Electronic Interactions at Oxide Interfaces

Ultrafast electric-field control of emergent electronic and magnetic states at oxide interfaces offers exciting prospects for the development of the next generation of energy-efficient devices. Here, it is demonstrated that the electronic structure and emergent ferromagnetic interfacial state in epitaxial LaNiO3/CaMnO3 superlattices can be effectively controlled using intense, single-cycle THz electric-field pulses. A suite of advanced X-ray spectroscopic techniques is employed to measure a detailed magneto-optical profile and the thickness of the ferromagnetic interfacial layer. Then, a combination of time-resolved and temperature-dependent optical measurements is used to disentangle several correlated electronic and magnetic processes driven by ultrafast, high-field THz pulses. Sub-picosecond non-equilibrium Joule heating of the electronic system is observed, ultrafast demagnetization of the ferromagnetic interfacial layer, and slower dynamics indicative of a change in the magnetic state of the superlattice due to the transfer of spin-angular momentum to the lattice. These findings suggest a promising avenue for the efficient control of 2D ferromagnetic states at oxide interfaces using ultrafast electric-field pulses.

X-ray spectroscopy and scattering↗

Factors Influencing Preferential Anion Interactions during Solvation of Multivalent Cations in Ethereal Solvents

Most multivalent secondary batteries have employed electrolytes composed of cyclic ether solvents such as tetrahydrofuran or linear glycol ether solvents (glymes) such as 1,2-dimethoxyethane (G1). A robust understanding of multivalent cation solvation tendencies in these classes of solvents provides insight into corresponding structure–property relationships which, in turn, promotes the design and discovery of improved electrolytes. In this work, our goal is to systematically address how electrolyte constituent properties, namely, ether solvent structure and dication size, direct the solvation interactions of divalent electrolytes and their resultant properties. This study utilizes pulsed-field gradient (PFG) nuclear magnetic resonance (NMR) spectroscopy in conjunction with Raman spectroscopy and ionic conductivity measurements to elucidate the preferential interactions between multivalent cations, anions, and solvent molecules along with their correlated ion dynamics. These investigations incorporate two representative divalent cations (Ca 2+ and Zn 2+ ) as well as two ethereal solvent representatives from both the cyclic ether and glyme structural classes. The results reveal that anions coordinate more readily with divalent cations in cyclic ethers than in glymes. Furthermore, the coordination of the anions with Ca 2+ , i.e., contact-ion pair (CIP) formation is more pronounced than with Zn 2+ in a glyme solvent of limited chain length (G1), providing insight into cation size effects that are important for translating solvation behavior across various multivalent electrolytes. Importantly, we find that specific anion coordination is more strongly controlled by solvent structure than by salt concentration in the practical range of 0.1–0.5 M. However, simply reducing these inner-sphere inter-ionic interactions by changing solvent structure does not necessarily de-correlate ionic motion. Instead, concentration-dependent changes in molar ionic conductivity suggest that second-shell interactions, i.e., solvent separated ion pairs (SSIPs), are prevalent in these electrolytes and that the solution dielectric constant, which is increased by the presence of dipolar ion pairs, is critical for controlling these interactions. These findings thus provide a basis for understanding the physical chemistry of multivalent battery electrolytes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Machine Intelligence-Centered System for Automated Characterization of Functional Materials and Interfaces

Classic design of experiment relies on a time-intensive workflow that requires planning, data interpretation, and hypothesis building by experienced researchers. Here, in this paper, we describe an integrated, machine-intelligent experimental system which enables simultaneous dynamic tests of electrical, optical, gravimetric, and viscoelastic properties of materials under a programmable dynamic environment. Specially designed software controls the experiment and performs on-the-fly extensive data analysis and dynamic modeling, real-time iterative feedback for dynamic control of experimental conditions, and rapid visualization of experimental results. The system operates with minimal human intervention and enables time-efficient characterization of complex dynamic multifunctional environmental responses of materials with simultaneous data processing and analytics. The system provides a viable platform for artificial intelligence (AI)-centered material characterization, which, when coupled with an AI-controlled synthesis system, could lead to accelerated discovery of multifunctional materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Alkali cation-induced cathodic corrosion in Cu electrocatalysts

The reconstruction of Cu catalysts during electrochemical reduction of CO 2 is a widely known but poorly understood phenomenon. Herein, we examine the structural evolution of Cu nanocubes under CO 2 reduction reaction and its relevant reaction conditions using identical location transmission electron microscopy, cyclic voltammetry, in situ X-ray absorption fine structure spectroscopy and ab initio molecular dynamics simulation. Our results suggest that Cu catalysts reconstruct via a hitherto unexplored yet critical pathway - alkali cation-induced cathodic corrosion, when the electrode potential is more negative than an onset value (e.g., –0.4 V RHE when using 0.1 M KHCO 3 ). Having alkali cations in the electrolyte is critical for such a process. Consequently, Cu catalysts will inevitably undergo surface reconstructions during a typical process of CO 2 reduction reaction, resulting in dynamic catalyst morphologies. While having these reconstructions does not necessarily preclude stable electrocatalytic reactions, they will indeed prohibit long-term selectivity and activity enhancement by controlling the morphology of Cu pre-catalysts. Alternatively, by operating Cu catalysts at less negative potentials in the CO electrochemical reduction, we show that Cu nanocubes can provide a much more stable selectivity advantage over spherical Cu nanoparticles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Lattice thermal transport in two-dimensional alloys and fractal heterostructures

Abstract Engineering thermal transport in two dimensional materials, alloys and heterostructures is critical for the design of next-generation flexible optoelectronic and energy harvesting devices. Direct experimental characterization of lattice thermal conductivity in these ultra-thin systems is challenging and the impact of dopant atoms and hetero-phase interfaces, introduced unintentionally during synthesis or as part of deliberate material design, on thermal transport properties is not understood. Here, we use non-equilibrium molecular dynamics simulations to calculate lattice thermal conductivity of $${\mathrm {(Mo|W)Se_2}}$$ ( Mo | W ) Se 2 monolayer crystals including $${\mathrm {Mo}}_{1-x}{\mathrm {W}}_x{\mathrm {Se_2}}$$ Mo 1 - x W x Se 2 alloys with substitutional point defects, periodic $${\mathrm {MoSe_2}|\mathrm {WSe_2}}$$ MoSe 2 | WSe 2 heterostructures with characteristic length scales and scale-free fractal $${\mathrm {MoSe_2}}|{\mathrm {WSe_2}}$$ MoSe 2 | WSe 2 heterostructures. Each of these features has a distinct effect on phonon propagation in the crystal, which can be used to design fractal and periodic alloy structures with highly tunable thermal conductivities. This control over lattice thermal conductivity will enable applications ranging from thermal barriers to thermoelectrics.

42 ENGINEERING↗

Photosynthesis Protein Collective Vibrations Role in Energy Transfer and Dissipation (Final Technical Report)

This project investigates how low‑frequency collective vibrations of photosynthetic proteins control energy transfer and dissipation, using terahertz (THz) spectroscopy and advanced theoretical analysis. The central hypothesis is that specific long‑range protein scaffold motions, rather than just local chromophore dynamics, steer exciton transport and photoprotection by modulating energy gaps and coupling between pigments.

14 SOLAR ENERGY↗

Time scales for nonlinear processes in preheating after multifield inflation with nonminimal couplings

We have conducted extensive lattice simulations to study the postinflation dynamics of multifield models involving nonminimal couplings. In this work, we explore the parameter dependence of preheating in these models and describe the various time scales that control such nonlinear processes as energy transfer, rescattering, and the approach to radiation domination and thermalization. In the limit of large nonminimal couplings ($ξ_I$ ~ 100), we find that efficient transfer of energy from the inflaton condensate to radiative degrees of freedom, emergence of a radiation-dominated equation of state, and the onset of thermalization each consistently occur within $N_{\text{reh}} ≲ 3 e$-folds after the end of inflation, largely independent of the values of the other couplings in the models. The exception is the case of negative ellipticity, in which there is a misalignment between the dominant direction in field space along which the system evolves and the larger of the nonminimal couplings $ξ_I$. In those cases, the field-space-driven parametric resonance is effectively shut off. More generally, the competition between the scalar fields’ potential and the field-space manifold structure can yield interesting phenomena such as two-stage resonances. Across many regions of parameter space, we find efficient re-scattering between the distinct fields, leading to a partial memory loss of the shape of the initial fluctuation spectrum. Despite the explosive particle production, which can lead to a quick depletion of the background energy density, the nonlinear processes do not induce any superhorizon correlations after the end of inflation in these models, which keeps predictions for cosmic microwave background observables unaffected by the late-time amplification of isocurvature fluctuations. Hence the excellent agreement between primordial observables and recent observations is preserved for this class of models, even when we consider postinflation dynamics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Integrated hydrogeophysical modelling and data assimilation for geoelectrical leak detection

Time-lapse electrical resistivity tomography (ERT) measurements provide indirect observations of hydrological processes in the Earth's shallow subsurface at high spatial and temporal resolution. ERT has been used in the past decades to detect leaks and monitor the evolution of associated contaminant plumes. Specifically, inverted resistivity images allow visualization of the dynamic changes in the structure of the plume. However, existing methods do not allow the direct estimation of leak parameters (e.g. leak rate, location, etc.) and their uncertainties. We propose an ensemble-based data assimilation framework that evaluates proposed hydrological models against observed time-lapse ERT measurements without directly inverting for the resistivities. Each proposed hydrological model is run through the parallel coupled hydro-geophysical simulation code PFLOTRAN-E4D to obtain simulated ERT measurements. The ensemble of model proposals is then updated using an iterative ensemble smoother. In this paper, we demonstrate the proposed framework on synthetic and field ERT data from controlled tracer injection experiments. Our results show that the approach allows joint identification of contaminant source location, initial release time, and solute loading from the cross-borehole time-lapse ERT data, alongside with an assessment of uncertainties in these estimates. We demonstrate a reduction in site-wide uncertainty by comparing the prior and posterior plume mass discharges at a selected image plane. This framework is particularly attractive to sites that have previously undergone extensive geological investigation (e.g., nuclear sites). It is well suited to complement ERT imaging and we discuss practical issues in its application to field problems.

58 GEOSCIENCES↗

A comprehensive review of nonlinear oscillators in hydrokinetic energy harnessing using flow-induced vibrations

A comprehensive review of hydrokinetic energy converters based on alternating lift technology (ALT) is provided. Emphasis is on nonlinear oscillators based on Flow Induced Vibration (FIV) or Oscillation (FIO). Due to strong coupling in Fluid-Structure Interaction (FSI), and in order to maximize the hydrokinetic harnessed energy, design of nonlinear oscillators and analysis by model tests or computational fluid dynamics dominates this area. Research confirmed that the nonlinear oscillator can harvest energy from a stochastic excitation modeled by a generic wide spectrum, and overcome the most severe oscillator limitations: specifically, the need for continuous frequency tuning due to the narrow bandwidth response, and low efficiency outside the narrow bandwidth oscillator response. This review covers the following aspects of nonlinear oscillators in ALT converters: (1) Geometric changes in oscillator cross-section; e.g., circular, square, rectangular, or trilateral shapes. (2) Passive turbulence control of FIV/FIO. (3) Position based nonlinear stiffness. (4) Multi-cylinder synergistic FIV/FIO. (5) Mechanically linked oscillators. (6) Velocity-based, nonlinear, adaptive harnessing damping.

42 ENGINEERING↗

Scaling relationships for the elastic moduli and viscosity of mixed lipid membranes

The elastic and viscous properties of biological membranes play a vital role in controlling cell functions that require local reorganization of the membrane components as well as dramatic shape changes such as endocytosis, vesicular trafficking, and cell division. These properties are widely acknowledged to depend on the unique composition of lipids within the membrane, yet the effects of lipid mixing on the membrane biophysical properties remain poorly understood. Here, we present a comprehensive characterization of the structural, elastic, and viscous properties of fluid membranes composed of binary mixtures of lipids with different tail lengths. We show that the mixed lipid membrane properties are not simply additive quantities of the single-component analogs. Instead, the mixed membranes are more dynamic than either of their constituents, quantified as a decrease in their bending modulus, area compressibility modulus, and viscosity. While the enhanced dynamics are seemingly unexpected, we show that the measured moduli and viscosity for both the mixed and single-component bilayers all scale with the area per lipid and collapse onto respective master curves. This scaling links the increase in dynamics to mixing-induced changes in the lipid packing and membrane structure. More importantly, the results show that the membrane properties can be manipulated through lipid composition the same way bimodal blends of surfactants, liquid crystals, and polymers are used to engineer the mechanical properties of soft materials, with broad implications for understanding how lipid diversity relates to biomembrane function.

59 BASIC BIOLOGICAL SCIENCES↗

Speciation and Reactivity Control of Cu-Oxo Clusters via Extraframework Al in Mordenite for Methane Oxidation

The stoichiometric conversion of methane to methanol by Cu-exchanged zeolites can be brought to highest yields by the presence of extraframework Al and high CH 4 chemical potentials. Here, combining theory and experiments, the differences in chemical reactivity of monometallic Cu-oxo and bimetallic Cu-Al-oxo nanoclusters stabilized in zeolite mordenite (MOR) are investigated. Cu-L 3 edge X-ray absorption near-edge structure (XANES), infrared (IR), and ultraviolet–visible (UV–vis) spectroscopies, in combination with CH 4 oxidation activity tests, support the presence of two types of active clusters in MOR and allow quantification of the relative proportions of each type in dependence of the Cu concentration. Ab initio molecular dynamics (MD) calculations and thermodynamic analyses indicate that the superior performance of materials enriched in Cu-Al-oxo clusters is related to the activity of two μ-oxo bridges in the cluster. Replacing H 2 O with ethanol in the product extraction step led to the formation of ethyl methyl ether, expanding this way the applicability of these materials for the activation and functionalization of CH 4 . We show that competition between different ion-exchanged metal-oxo structures during the synthesis of Cu-exchanged zeolites determines the formation of active species, and this provides guidelines for the synthesis of highly active materials for CH 4 activation and functionalization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Kinetic Monte Carlo Framework for Coupled Degradation and Dehydration of Anion Exchange Membranes

Kinetic Monte Carlo (kMC) simulations, augmented with temporal-acceleration schemes, can efficiently handle stiff reaction-transport networks when fast processes rapidly relax to quasi-equilibrium on a fixed lattice. However, in glassy anion-exchange membranes (AEM), rare and irreversible chemical degradation events continuously reshape the nanoscale morphology, and the associated hydration and transport degrees of freedom remain far from a well-defined local equilibrium. This combination of evolving state space and nonequilibrated fast dynamics lies outside the scope of existing kMC acceleration frameworks. Here, to address this challenge, we introduce an auxiliary-particle kinetic Monte Carlo (AP-kMC) scheme. In AP-kMC, short-lived mobile particles spawned at degradation sites execute hop, water-elimination, and decay moves, enforcing rapid local relaxation of the hydration structure while preserving the stochastic rules of kMC. Parameterized with molecular-dynamics morphologies and experimental solution degradation kinetics, AP-kMC reproduces the evolution of ion-exchange capacity, water uptake, and conductivity, and reveals a feedback loop in which poorly hydrated sites degrade first and each degradation event induces further local dehydration. The resulting thinning and fragmentation of water channels cause loss of hydrophilic percolation and abrupt conductivity collapse well before complete charge loss. AP-kMC thus reframes AEM durability as a coupled degradation–drying–percolation problem and provides a transferable strategy to simulate reactive, out-of-equilibrium polymer electrolytes where local solvation controls reactivity.

organic↗

Metal Site Substitution and Role of the Dimer on Symmetry Breaking in FePS 3 and CrPS 4 under Pressure

We combine infrared absorption, Raman scattering, and diamond anvil cell techniques to explore the properties of FePS 3 and CrPS 4 under pressure, comparing our findings with a symmetry analysis, lattice dynamics calculations, and an examination of the energy landscape. Although these complex chalcogenides are considered to be members of the same family of materials, they display remarkably different phase progressions on account of the metal center orbital filling, character of the P–P linkage, layer corrugation, and differing size of the van der Waals gap. Here, we discuss the space group progressions, structure–property relations, and development of pressure-induced metallicity in terms of the competition between local and long-range symmetry transformations and structural distortion pathways. These findings place the properties of FePS 3 and CrPS 4 on a firm foundation for work under strain control and in the single layer limit.

36 MATERIALS SCIENCE↗

Validation of FAST.Farm Against Full-Scale Turbine SCADA Data for a Small Wind Farm

FAST.Farm is a new midfidelity engineering tool developed by the National Renewable Energy Laboratory targeted at accurately and efficiently predicting wind turbine power production and structural loading in wind farm settings, including wake interactions between turbines. FAST.Farm is based on some of the principles of the Dynamic Wake Meandering model—including passive tracer modeling of wake meandering—but addresses many of the limitations of previous Dynamic Wake Meandering (DWM) implementations. Previous FAST.Farm verification studies show the similarities and differences between FAST.Farm and large-eddy simulations for rigid and flexible turbines. In this validation study, FAST.Farm turbine responses are compared to multiturbine measurements from a subset of a full-scale wind farm. FAST.Farm predictions of turbine generator power, rotor speed, and blade pitch for five-turbine simulations are compared to supervisory control and data acquisition results. Results reveal that FAST.Farm generator power mean and standard deviation results reasonably match measured data for upstream and downstream turbines, as well as the mean rotor speed and blade pitch above rated wind speeds. However, FAST.Farm generally underpredicts the mean rotor speed and overpredicts the mean blade pitch below rated operation. These errors are likely related to inaccuracies in the generic controller simulated. Despite controller differences, FAST.Farm predicts the same overall relative rotor power trends for all waked turbines at all wind speeds.

17 WIND ENERGY↗

Science Validation for Dark Energy Research with Optical Imaging Surveys

The Universe has been expanding at an accelerating rate over the past several billion years, as though an unknown form of dark energy permeates all of space. The ultimate scientific goal of the proposed research is to distinguish between different physical mechanisms that could account for this observed accelerated expansion, for example, the zero-point energy of the vacuum, a dynamical form of energy that varies in time and/or space, or a modification to our theory of gravity. Wide- field optical imaging surveys of the night sky can test these competing models by measuring both the cosmic expansion history and the growth of large-scale structure. To this end, the Dark Energy Survey (DES) has cataloged several hundred million galaxies and thousands of supernovae. The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST), will enlarge the census to billions of galaxies and hundreds of thousands of supernovae. A critical question for these dark energy experiments is whether systematic uncertainties can continue to be controlled at a level to keep pace with the statistical precision offered by such enormous datasets. The immediate research objectives of this project were (1) to prepare and validate input datasets that are the foundation of cosmological analyses with DES, and (2) to prepare for value-added characterization of Rubin Observatory commissioning data to inform early operations and accelerate the realization of dark energy science from LSST data products. For DES, we assembled and curated cosmology-ready data releases that include value-added components such as enhanced photometric and astrometric calibrations, alternative source extraction algorithms, maps of the survey coverage and survey conditions, object classifications, object quality selections, galaxy shapes, and photometric redshifts. We used the galaxy clustering technique to validate the photometric redshift distributions of various galaxy samples to be used as lenses in combined studies of galaxy clustering and weak gravitational lensing. The galaxy clustering redshift analysis was enhanced by use of a larger sample of reference galaxies from the eBOSS spectroscopic survey that extends to higher redshifts. For LSST, we prepared for science validation studies of commissioning data aimed at dark energy science capability that extend beyond the normative system-level tests to be done by the Rubin Observatory Construction Project. We identified a set of proposed survey strategies and candidate target fields that could be observed during the commissioning period to enhance science validation activities related to studies of dark energy.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗