Plasma and space physics
Continuum plasma dynamics, and properties of corona, solar wind, magnetosphere, and transition region
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Continuum plasma dynamics, and properties of corona, solar wind, magnetosphere, and transition region
Empirical estimates of the microphysical response of cloud droplet size distribution to aerosol perturbations are commonly used to constrain aerosol–cloud interactions in climate models. Instead of empirical microphysical estimates, here macroscopic variables are analyzed to address the influence of aerosol particles and meteorological descriptors on instantaneous cloud albedo and the radiative effect of shallow liquid water clouds. Long-term ground-based measurements from the Atmospheric Radiation Measurement (ARM) program over the Southern Great Plains are used. A broad statistical analysis was performed on 14 years of coincident measurements of low clouds, aerosol, and meteorological properties. Here two cases representing conflicting results regarding the relationship between the aerosol and the cloud radiative effect were selected and studied in greater detail. Microphysical estimates are shown to be very uncertain and to depend strongly on the methodology, retrieval technique and averaging scale. For this continental site, the results indicate that the influence of the aerosol on the shallow cloud radiative effect and albedo is weak and that macroscopic cloud properties and dynamics play a much larger role in determining the instantaneous cloud radiative effect compared to microphysical effects. On a daily basis, aerosol shows no correlation with cloud radiative properties (correlation = -0.01 ± 0.03), whereas the liquid water path shows a clear signal (correlation = 0.56 ± 0.02).
The second Hot QCD Matter 2024 conference at IIT Mandi focused on various ongoing topics in high-energy heavy-ion collisions, encompassing theoretical and experimental perspectives. This proceedings volume includes 19 contributions that collectively explore diverse aspects of the bulk properties of hot QCD matter. The topics encompass the dynamics of electromagnetic fields, transport properties, hadronic matter, spin hydrodynamics, and the role of conserved charges in high-energy environments. These studies significantly enhance our understanding of the complex dynamics of hot QCD matter, the quark–gluon plasma (QGP) formed in high-energy nuclear collisions. Advances in theoretical frameworks, including hydrodynamics, spin dynamics and fluctuation studies, aim to improve theoretical calculations and refine our knowledge of the thermodynamic properties of strongly interacting matter. Experimental efforts, such as those conducted by the ALICE and STAR collaborations, play a vital role in validating these theoretical predictions and deepening our insight into the QCD phase diagram, collectivity in small systems, and the early-stage behavior of strongly interacting matter. In conclusion, combining theoretical models with experimental observations offers a comprehensive understanding of the extreme conditions encountered in relativistic heavy-ion and proton-proton collisions.
Young M-type binaries are particularly useful for precise isochronal dating by taking advantage of their extended pre-main sequence evolution. Orbital monitoring of these low-mass objects becomes essential in constraining their fundamental properties, as dynamical masses can be extracted from their Keplerian motion. Here, we present the combined efforts of the AstraLux Large Multiplicity Survey, together with a filler sub-programme from the SpHere INfrared Exoplanet (SHINE) project and previously unpublished data from the FastCam lucky imaging camera at the Nordical Optical Telescope (NOT) and the NaCo instrument at the Very Large Telescope (VLT). Building on previous work, we use archival and new astrometric data to constrain orbital parameters for 20 M-type binaries. We identify that eight of the binaries have strong Bayesian probabilities and belong to known young moving groups (YMGs). We provide a first attempt at constraining orbital parameters for 14 of the binaries in our sample, with the remaining six having previously fitted orbits for which we provide additional astrometric data and updated Gaia parallaxes. The substantial orbital information built up here for four of the binaries allows for direct comparison between individual dynamical masses and theoretical masses from stellar evolutionary model isochrones, with an additional three binary systems with tentative individual dynamical mass estimates likely to be improved in the near future. We attained an overall agreement between the dynamical masses and the theoretical masses from the isochrones based on the assumed YMG age of the respective binary pair. The two systems with the best orbital constrains for which we obtained individual dynamical masses, J0728 and J2317, display higher dynamical masses than predicted by evolutionary models.
An optimal control frequency response problem is defined within the context of the optimal pilot model. The problem is designed to specify pilot model control frequencies reflective of important aircraft system properties, such as control feel system dynamics, airframe dynamics, and gust environment, as well as man machine properties, such as task and attention allocation. This is accomplished by determining a bounded set of control frequencies which minimize the total control cost. The bounds are given by zero and the neuromuscular control frequency response for each control actuator. This approach is fully adaptive, i.e., does not depend upon user entered estimates. An algorithm is developed to solve this optimal control frequency response problem. The algorithm is then applied to an attitude hold task for a bare airframe fighter aircraft case with interesting dynamic properties.
In this study, thermomechanical properties of hardwood and softwood lignin-nitrile butadiene rubber composites were controlled by a thermal annealing process. The presence of thermally unstable linkages within the selected lignins provides free radical sources for crosslinking reactions. The measured dynamic mechanical properties demonstrated substantial improvement in glass transition temperatures (Tg) and storage moduli (E’) of 50 wt. % softwood lignin- and 50 wt. % hardwood lignin-rubber composites after thermal annealing at 180°C. An increase in Tg of approximately 18°C and more than 230% increasing E’ was achieved after annealing the 50 wt. % hardwood lignin-rubber for 5 h. The chemical crosslinking reactions between lignin-nitrile butadiene rubber and lignin-lignin were characterized by in-situ dynamic mechanical analysis and Fourier transform infrared (FTIR) spectroscopy. A mechanism of crosslinking reactions was revealed.
Mechanical properties and natural fracture characteristics are critical to investigate for subsurface engineering applications, including carbon storage, well drilling, and stimulation, as they govern rock stability, fluid flow, and mechanical behavior under stress. This dissertation integrates experimental and machine learning approaches to enhance the prediction and understanding of these properties by analyzing acoustic wave behavior under varied subsurface conditions. First, the influence of temperature, pore pressure, and supercritical CO2 (scCO2) saturation on poroelastic properties is examined using Gray Berea sandstone samples. The results show that temperature and pore pressure significantly affect the bulk modulus and Biot’s coefficient, while scCO2 saturation impacts rock compressibility, informing strategies for effective geological carbon storage. The study extends this understanding by experimentally evaluating the impact of reservoir depletion on the dynamic mechanical properties of the emerging Caney shale in South Oklahoma with the employment of unsupervised machine learning to predict static mechanical properties across the Caney shale. Integrating petrophysical data and chemostratigraphy, the workflow—featuring K-means clustering, principal component analysis (PCA), and inverse distance weighting (IDW)—improves stratigraphic characterization and the estimation of static-to-dynamic modulus ratios, which is vital for optimizing drilling and stimulation strategies. Finally, the work explores how natural fracture characteristics in shale influence acoustic waveforms and shear wave splitting (SWS) analysis. Experimental data on fractured samples under different stress and temperature conditions, combined with machine learning models such as K-nearest neighbors (KNN) and extreme gradient boosting (XGBoost), reveal key fracture properties impacting SWS and wave propagation. Together, these studies provide a comprehensive framework for linking acoustic wave behavior with rock properties, advancing the methods for monitoring and predicting geomechanical changes. The insights offered valuable implications for safer, more efficient CO2 injection, hydrocarbon extraction, and subsurface management.
Despite extensive studies of supercooled water, it remains challenging to understand its peculiar dynamic anomalous properties. In this work, we integrated full atomistic simulations of supercooled water over the temperature range of room temperature to 200 K using a quantum-mechanics-based polarizable force field with the dressed dynamics method that couples fast collision events and slow reorganization dynamics of hydrogen-bond networks. Our analysis unveils the salient multiscale features in the transient relaxation dynamics of supercooled water. A classical Langevin behavior dominates at fast timescales, while long-time relaxations unveil two different activation barriers in two temperature regions: below and above 230 K. The modulation of the entropy spectrum by temperature is elucidated in terms of a three-state model underlined by the complexity of the water dynamics associated with a topological transition of a strong hydrogen-bond network. This state-dependent network topology is quantitatively characterized by power-law exponents of inverse network connectivity from 200 to 298 K. Finally, this work provides valuable guidance for further studies on the transient relaxation dynamics of supercooled water.
Here, we present a comprehensive study of static and dynamic magnetic properties in the Ising-like dipolar antiferromagnet (AFM) DyScO 3 by means of DC and AC magnetization measurements supported by classical Monte Carlo calculations. Our AC-susceptibility data show that the magnetic dynamics exhibit a clear crossover from an Arrhenius-like regime to quantum tunneling of magnetization (QTM) at T*=10K. Below T N =3.2K, DyScO 3 orders in an antiferromagnetic GxAy-type magnetic structure and the magnetization dynamics slow down to the minute timescale. The low-temperature magnetization curves exhibit complex hysteretic behavior, which depends strongly on the magnetic field sweep rate. We demonstrate that the low-field anomalies on the magnetization curve are related to the metamagnetic transition, while the hysteresis at higher fields is induced by a strong magnetocaloric effect. Our theoretical calculations, which take into account dipolar interaction between Dy 3+ moments, reproduce essential features of the magnetic behavior of DyScO 3 . We demonstrate that DyScO 3 represents a rare example of an inorganic compound, which exhibits QTM at a single-ion level and magnetic order due to classical dipolar interaction.
Here, we present simulations using finite-temperature density-functional-theory molecular-dynamics to calculate dynamic dielectric properties in warm dense aluminum. The comparison between exchange-correlation functionals in the Perdew, Burke, Ernzerhof approximation, Strongly Constrained and Appropriately Normed Semilocal Density Functional, and Heyd, Scuseria, Ernzerhof (HSE) approximation indicates evident differences in the electron transition energies, dc conductivity, and Lorenz number. The HSE calculations show excellent agreement with x-ray scattering data as well as dc conductivity and absorption measurements. These findings demonstrate non-Drude behavior of the dynamic conductivity above the Cooper minimum that needs to be taken into account to determine optical properties in the warm dense matter regime.
Multimodal luminescent materials, while promising for anti-counterfeiting, often lack dynamic time-dependent responses and controllable spatial distribution, limiting their encryption capabilities in the spatiotemporal dimension. Here, this work presents a coordinated control strategy based on entropy and defect engineering, and uses a backpropagation (BP) neural network for material screening to successfully prepare spinel Mg 0.8 (Fe 0.04 Co 0.04 Ni 0.04 Cu 0.04 Zn 0.04 )Cr 2 O 4 (MgA 5 CO) phosphors with time-dependent dynamic luminescence behavior. This phosphor simultaneously activated the d-d transition luminescence (∼618 nm) derived from Co 2+ /Cr 3+ and the defect luminescence (∼398 nm) related to zinc vacancies (V Zn ) in a single-phase solid solution. The phosphor exhibits a time-dependent color evolution from pink to purple under fixed-wavelength excitation, due to the different excited-state dynamics and decay lifetimes associated with the d-d transition and defect luminescence. Structural characterization and spectral analysis confirmed the existence of V Zn and its significant role in defect luminescence process. The fluorescent and dynamic luminescent properties of entropy-based spinel oxide enable its use in advanced anti-counterfeiting applications like fingerprint recognition and color-changing dedicated anti-counterfeiting mark, showing promise in high-end and time-dynamic anti-counterfeiting fields. This research not only developed a new type of fluorescent dynamic anti-counterfeiting material, but also provided a new idea for constructing advanced optical functional materials with multiple luminescence mechanisms.
In order to study the interplay between dynamical heterogeneities and structural properties of bulk liquid water in the temperature range 130–350 K, thus including the supercooled regime, we use the explicit trend of the distribution functions of some molecular properties, namely, the rotational relaxation constants, the atomic mean-square displacements, the relaxation of the cross correlation functions between the linear and squared displacements of H and O atoms of each molecule, the tetrahedral order parameter q and, finally, the number of nearest neighbors (NNs) and of hydrogen bonds (HBs) per molecule. Two different potentials are considered: TIP4P-Ew and a model developed in this laboratory for the study of nanoconfined water. The results are similar for the dynamical properties, but are markedly different for the structural characteristics. In particular, for temperatures higher than that of the dynamic crossover between “fragile” (at higher temperatures) and “strong” (at lower temperatures) liquid behaviors detected around 207 K, the rotational relaxation of supercooled water appears to be remarkably homogeneous. However, the structural parameters (number of NNs and of HBs, as well as q) do not show homogeneous distributions, and these distributions are different for the two water models. Another dynamic crossover between “fragile” (at lower temperatures) and “strong” (at higher temperatures) liquid behaviors, corresponding to the one found experimentally at T{sup ∗} ∼ 315 ± 5 K, was spotted at T{sup ∗} ∼ 283 K and T{sup ∗} ∼ 276 K for the TIP4P-Ew and the model developed in this laboratory, respectively. It was detected from the trend of Arrhenius plots of dynamic quantities and from the onset of a further heterogeneity in the rotational relaxation. To our best knowledge, it is the first time that this dynamical crossover is detected in computer simulations of bulk water. On the basis of the simulation results, the possible mechanisms of the two crossovers at molecular level are discussed.
Abstract Subduction of carbonate‐bearing oceanic plates into Earth's interior recycles carbon from the surface to the deep mantle. The subducted carbonates can significantly affect mantle properties and dynamics. Magnesite is recognized as one of the major potential carbon hosts in the deep mantle because of its stability up to deep lower mantle conditions. However, despite many previous studies on the equation of state and elastic properties of magnesite, large discrepancies still exist for its elastic moduli and their pressure and temperature derivatives. Here we report in situ density and elastic wave velocity measurements on a natural magnesite at simultaneous high pressure‐temperature conditions up to ∼8 GPa–1073 K in a multi‐anvil apparatus using ultrasonic and synchrotron X‐ray techniques. Global fitting of the data set to finite strain equations yieldsK S0 = 114.0 ± 1.2 GPa, = 4.9 ± 0.3, = (−0.019 ± 0.002) GPa/K,G 0 = 68.6 ± 0.4 GPa,G′ = 1.6 ± 0.1, and = (−0.018 ± 0.001) GPa/K. Compared to other major upper mantle and transition zone minerals, magnesite has intermediateV P , the lowestV S , and the lowest density. Thus, magnesite possesses higherV P /V S ratio than other mantle minerals in normal mantle regions, whereas this feature is less pronounced in subduction zone environments. Modeling of the velocity profiles of carbonated lithologies along different geotherms suggests that moderately‐enriched magnesite domains are unlikely to be detected seismically in the Earth's mantle.
The dynamic response properties of horizontal vestibulo-ocular reflex (VOR) were characterized in 216 human subjects ranging in age from 7 to 81 years. The object of this cross-sectional study was to determine the effects of aging on VOR dynamics, and to identify the distributions of parameters which describe VOR responses to caloric and to sinusoidal rotational stimuli in a putatively normal population. Caloric test parameters showed no consistent trend with age. Rotation test parameters showed declining response amplitude and slightly less compensatory response phase with increasing age. The magnitudes of these changes were not large relative to the variability within the population. The age-related trends in VOR were not consistent with the anatomic changes in the periphery reported by others which showed an increasing rate of peripheral hair cell and nerve fiber loss in subjects over 55 years. The poor correlation between physiological and anatomical data suggest that adaptive mechanisms in the central nervous system are important in maintaining the VOR.
Differential dynamic programming (DDP) has been demonstrated as a viable approach to low-thrust trajectory optimization, namely with the recent success of NASAs Dawn mission. The Dawn trajectory was designed with the DDP-based Static Dynamic Optimal Control algorithm used in the Mystic software. Another recently developed method, Hybrid Differential Dynamic Programming (HDDP) is a variant of the standard DDP formulation that leverages both first-order and second-order state transition matrices in addition to nonlinear programming (NLP) techniques. Areas of improvement over standard DDP include constraint handling, convergence properties, continuous dynamics, and multi-phase capability. DDP is a gradient based method and will converge to a solution nearby an initial guess. In this study, monotonic basin hopping (MBH) is employed as a stochastic search method to overcome this limitation, by augmenting the HDDP algorithm for a wider search of the solution space.
A computationally inspired Cu(I) metal-to-ligand charge transfer (MLCT) chromophore, [Cu(sbmpep) 2 ] + (sbmpep = 2,9-di( sec -butyl)-3,8-dimethyl-4,7-di(phenylethynyl)-1,10-phenanthroline), was synthesized in seven total steps, prepared from either dichloro- or dibromophenanthroline precursors. Complete synthesis, structural characterization, and electrochemistry, in addition to static and dynamic photophysical properties of [Cu(sbmpep) 2 ] + , are observed on all relevant time scales. UV–Vis absorption spectroscopy revealed significant increases in oscillator strength along with a concomitant bathochromic shift in the MLCT absorption bands with respect to structurally related model complexes (ε = 16 500 M –1 cm –1 at 491 nm). Strong red photoluminescence (Φ = 2.7%, λ max = 687 nm) was determined from [Cu(sbmpep) 2 ] + , which featured an average excited-state lifetime of 1.4 μs in deaerated dichloromethane. Cyclic and differential pulse voltammetry revealed ~300 mV positive shifts in the measured one-electron reversible reduction and oxidation waves in relation to a Cu(I) model complex possessing identical structural elements without the π-conjugated 4,7-substituents. The excited-state redox potential of [Cu(sbmpep) 2 ] + was estimated to be -1.36 V, a notably powerful reductant for driving photoredox chemistry. The combination of conventional and ultrafast transient absorption and luminescence spectroscopy successfully map the excited-state dynamics of [Cu(sbmpep) 2 ] + from initial photoexcitation to the formation of the lowest-energy MLCT excited state and ultimately its relaxation to the ground state. This newly conceived molecule appears poised for photosensitization reactions involving energy and electron-transfer processes relevant to photochemical upconversion, photoredox catalysis, and solar fuels photochemistry.
The underlying microscopic response of filler networks in reinforced rubber to dynamic strain is not well understood due to the experimental difficulty of directly measuring filler network behavior in samples undergoing dynamic strain. This difficulty can be overcome with in situ X-ray photon correlation spectroscopy (XPCS) measurements. The contrast between the silica filler and the rubber matrix for X-ray scattering allows us to isolate the filler network behavior from the overall response of the rubber. This in situ XPCS technique probes the microscopic breakdown and reforming of the filler network structure, which are responsible for the nonlinear dependence of modulus on strain, known in the rubber science community as the Payne effect. These microscopic changes in the filler network structure have consequences for the macroscopic material performance, especially for the fuel efficiency of tire tread compounds. In this work, we elucidate the behavior with in situ dynamic strain XPCS experiments on industrially relevant, vulcanized rubbers filled (13 vol %) with novel air-milled silica of ultrahigh-surface area (UHSA) (250 m 2 /g). The addition of a silane coupling agent to rubber containing this silica causes an unexpected and counterintuitive increase in the Payne effect and decrease in energy dissipation. For this rubber, we observe a nearly two-fold enhancement of the storage modulus and virtually equivalent loss tangent compared to a rubber containing a coupling agent and conventional silica. Interpretation of our in situ XPCS results simultaneously with interpretation of traditional dynamic mechanical analysis (DMA) strain sweep experiments reveals that the debonding or yielding of bridged bound rubber layers is key to understanding the behavior of rubber formulations containing the silane coupling agent and high-surface area silica. These results demonstrate that the combination of XPCS and DMA is a powerful method for unraveling the microscale filler response to strain which dictates the dynamic mechanical properties of reinforced soft matter composites. With this combination of techniques, we have elucidated the great promise of UHSA silica when used in concert with a silane coupling agent in filled rubber. Such composites simultaneously exhibit large moduli and low hysteresis under dynamic strain.
Differential dynamic programming (DDP) has been demonstrated as a viable approach to low-thrust trajectory optimization, namely with the recent success of NASA's Dawn mission. The Dawn trajectory was designed with the DDP-based Static/Dynamic Optimal Control algorithm used in the Mystic software.1 Another recently developed method, Hybrid Differential Dynamic Programming (HDDP),2, 3 is a variant of the standard DDP formulation that leverages both first-order and second-order state transition matrices in addition to nonlinear programming (NLP) techniques. Areas of improvement over standard DDP include constraint handling, convergence properties, continuous dynamics, and multi-phase capability. DDP is a gradient based method and will converge to a solution nearby an initial guess. In this study, monotonic basin hopping (MBH) is employed as a stochastic search method to overcome this limitation, by augmenting the HDDP algorithm for a wider search of the solution space.