Core Dynamics Research Articles

Structure and Non‐Ideal Mixing of Fe‐Ni‐S Liquid at High Temperature and Pressure and Its Implication for the Earth's Outer Core Composition

AbstractThe effect of light elements (LEs) such as sulfur on the physical properties of liquid iron‐nickel alloy under the earth's outer core conditions is critical for understanding the core composition and dynamics. First‐principles molecular dynamics simulations were employed to model Fe‐Ni‐S liquid with S concentrations in the range of (0–25) atomic percent (at%) at 4050 K and (0–33.33) at% at 5530 K and pressures relevant to the core‐mantle boundary (CMB) and inner core boundary (ICB), respectively. The thermodynamic mixing properties of Fe‐Ni‐S liquid were calculated, showing that the excess volume for Fe‐Ni‐S alloys deviates negatively from ideal mixing by −0.33% at 12.5 at% S at the CMB and −0.35% at 17 at% S at the ICB. Similarly, the excess enthalpy negatively deviated from the ideal mixing by −3.4 kJ/mole and −13 kJ/mole at the similar S concentrations at CMB and ICB, respectively, indicating non‐ideal mixing throughout the outer core. Similar behaviors are observed for isothermal bulk modulus (KT) and seismic velocity. The short‐ and intermediate‐range structures were analyzed and used to explain the non‐ideal mixing behaviors. The results suggest that extrapolations using ideal mixing underestimates the sound velocity by ∼0.14 km/s near CMB and ∼0.10 km/s near ICB, which is significant for constraining the core composition. If S is the only LE, the density at 10–12 wt% S matches the preliminary reference earth model (PREM). The seismic velocity at 12–15 wt% S matches PREM. These results suggest the presence of other LEs in the outer core.

Limiting regimes of turbulent horizontal convection. Part 1. Intermediate and low Prandtl numbers

We report the existence of two new limiting turbulent regimes in horizontal convection (HC) using direct numerical simulations at intermediate to low Prandtl numbers. In our simulations, the flow is driven by a step-wise buoyancy profile imposed at the surface, with free-slip, no-flux conditions along all other boundaries, except along the spanwise direction, where periodicity is assumed. The flow is shown to transition to turbulence in the plume and the core, modifying the rate of heat and momentum transport. These transitions set a sequence of scaling laws that combine theoretical arguments from Shishkina, Grossmann and Lohse (SGL) and Hughes, Griffiths, Mullarney and Peterson (HGMP). The parameter range extends through Rayleigh numbers in the range [ $6.4\times 10^5, 1.92\times 10^{15}$ ] and Prandtl numbers in the range [ $2\times 10^{-3},2$ ]. At low Prandtl numbers and intermediate Rayleigh numbers, a core-driven regime is shown to follow a Nusselt-number scaling with $Ra^{1/6}Pr^{7/24}$ . For Rayleigh numbers larger than $10^{14}$ , the Nusselt number scales with $Ra^{0.225}Pr^{0.417}$ . For these particular regimes, the Reynolds number is found to scale as $Ra^{2/5}Pr^{-3/5}$ for the low-Prandtl-number regime and $Ra^{1/3}Pr^{1}$ for Rayleigh numbers larger than $10^{14}$ . These results embed the HGMP model in the SGL theory and extend the known regime diagram of HC at high Rayleigh numbers. In particular, we show that HC and Rayleigh–Bénard share similar turbulent characteristics at low Prandtl numbers, where HC is shown to be ruled by its core dynamics and turbulent boundary layers. This new scenario confirms that fully turbulent HC enhances the transport of heat and momentum with respect to previously reported regimes at high Rayleigh numbers. This work provides new insights into the applicability of HC for geophysical flows such as overturning circulations found in the atmosphere, the oceans, and flows near the Earth's inner core.

Regulating IL-2 immune signaling function via a core allosteric structural network.

NMR and molecular dynamics simulations revealed distinct conformational dynamics and allosteric networks in computationally re-designed IL-2 superkines compared to wild-type IL-2, despite their similar crystal structures.The superkines S1 and S15 exhibit altered sampling of excited state conformations at an intermediate timescale, with slower conformational exchange rates compared to wild-type IL-2.A rationally designed mutation (L56A) in the S1 superkine's core allosteric network partially reverted its dynamics, receptor binding affinity, and T cell signaling behavior towards that of wild-type IL-2.Our study demonstrates that IL-2 core dynamics play a critical role in receptor binding and signaling function, providing a foundation for engineering more selective IL-2-based immunotherapies.

Probing the inner structure and dynamics of pH-sensitive block copolymer nanoparticles with nitroxide radicals using scattering and EPR techniques

This research emphasizes the crucial role of electron paramagnetic resonance (EPR) spectroscopy in nanoparticle analysis, showcasing its distinctive ability to probe molecular-level details. We demonstrate the synthesis and self-assembly of a new class of pH-responsive amphiphilic diblock copolymers, specifically poly[N-(2-hydroxypropyl)-methacrylamide]-block-poly[2-(diisopropylamino)ethyl methacrylate] (PHPMA-b-PDPA), incorporating 2,2,6,6-tetramethylpiperidine-1-oxyl (TEMPO) radicals covalently bound to the hydrophilic PHPMA segment. The copolymer synthesis involved a three-step process, combining reversible addition − fragmentation chain transfer (RAFT) polymerization with carbodiimide (DCC) chemistry. TEMPO radical-containing nanoparticles (RNPs) were created using microfluidic (MF) nanoprecipitation, a technique essential for generating uniform nanoparticles with predictable biodistribution and cellular uptake. Adjusting MF protocol parameters allowed fine-tuning of RNP sizes. EPR spectroscopy confirmed the formation of core–shell RNPs, with features aligning closely with those obtained from scattering techniques like dynamic light scattering (DLS), static light scattering (SLS), small-angle X-ray scattering (SAXS), and cryo-transmission electron microscopy (cryo-TEM). EPR spectroscopy emerges as a potent tool for molecular-level analysis of colloidal polymer systems. This study highlights the EPR-spin label method’s efficacy in probing the internal structural features and dynamics of core–shell nanoparticles, especially their response to pH-triggered disassembly. The findings open new avenues for the use of pH-responsive TEMPO-labeled diblock copolymers in controlled drug delivery applications.

Marginal stability analyses for thermochemical convection and its implications for the dynamics of continental lithosphere and core–mantle boundary regions

SUMMARY Significant compositional differences may exist in the lithospheric mantle and above the core–mantle boundary (CMB) relative to the ambient mantle. The intrinsic density differences may affect the development of thermal boundary layer (TBL) instabilities associated with lithospheric delamination and formation of thermochemical plumes. In this study, we explored the instability of two-layer thermochemical fluid using two different techniques: marginal stability analysis with a propagator-matrix method and finite element modelling. We investigated both the instabilities in lithospheric mantle (i.e. lithospheric instability) and the mantle above the CMB (i.e. plume-forming instability) using a background temperature Tbg(z) with the TBL. For lithospheric instability, we found that two-layer fluid with free-slip boundary conditions mainly undergoes the same three different convective modes (i.e. two oscillatory convection modes and one layered convection regime) as that with no-slip boundary conditions reported in Jaupart et al. However, with free-slip boundary conditions, the transitions between these convection modes occur at larger values of buoyancy number B. Free-slip boundary conditions lead to smaller critical Rayleigh number Rac, but larger convective wavelength and oscillation frequency ωc, compared with those with no-slip boundary conditions. Our numerical modelling results demonstrate that Rac and ωc predicted from the classical marginal stability analyses using Tbg(z) with TBL temperature may have significant errors when the oscillatory period is comparable with or larger than the timescale of lithospheric thermal diffusion that causes Tbg(z) to vary with time significantly. In this case, using a more gently sloped background temperature profile ignoring the TBL temperature, the stability analysis predicts more accurate stability conditions, thus presenting an effective remedy to the stability analysis. For plume-forming instability, because of the reduced viscosity in the hot and compositionally dense bottom layer, the transition to the layered convection occurs at significantly smaller B values, and in the oscillatory convection regime, Rac is larger but ωc is smaller, compared with those for lithospheric instability. Finally, our study provides a successful benchmark of numerical models of thermochemical convection by comparing Rac and ωc from numerical models with those from the marginal stability analysis.

Individual differences in decision-making shape how mesolimbic dopamine regulates choice confidence and change-of-mind.

Nucleus accumbens dopamine signaling is an important neural substrate for decision-making. Dominant theories generally discretize and homogenize decision-making, when it is in fact a continuous process, with evaluation and re-evaluation components that extend beyond simple outcome prediction into consideration of past and future value. Extensive work has examined mesolimbic dopamine in the context of reward prediction error, but major gaps persist in our understanding of how dopamine regulates volitional and self-guided decision-making. Moreover, there is little consideration of individual differences in value processing that may shape how dopamine regulates decision-making. Here, using an economic foraging task in mice, we found that dopamine dynamics in the nucleus accumbens core reflected decision confidence during evaluation of decisions, as well as both past and future value during re-evaluation and change-of-mind. Optogenetic manipulations of mesolimbic dopamine release selectively altered evaluation and re-evaluation of decisions in mice whose dopamine dynamics and behavior reflected future value.

Melting temperature of iron under the Earth’s inner core condition from deep machine learning

Constraining the melting temperature of iron under Earth’s inner core conditions is crucial for understanding core dynamics and planetary evolution. Here, we develop a deep potential (DP) model for iron that explicitly incorporates electronic entropy contributions governing thermodynamics under Earth’s core conditions. Extensive benchmarking demonstrates the DP’s high fidelity across relevant iron phases and extreme pressure and temperature conditions. Through thermodynamic integration and direct solid–liquid coexistence simulations, the DP predicts melting temperatures for iron at the inner core boundary, consistent with previous ab initio results. This resolves the previous discrepancy of iron’s melting temperature at ICB between the DP model and ab initio calculation and suggests the crucial contribution of electronic entropy. Our work provides insights into machine learning melting behavior of iron under core conditions and provides the basis for future development of binary or ternary DP models for iron and other elements in the core.

The application of unsupervised machine learning for the elucidation of the burial effect of lignin in peatland: Case of TMAH thermochemolysis

Lignin is one of the major components of organic macromolecules in peatland. Analysis of lignin in sediments is considered as a valuable tool for understanding peat vegetation as well as carbon cycle. It provides valuable perspectives on different sides such as occurrence of various vegetation types and the extent of decay in terrestrial organic material. Thermochemolysis technique using tetramethyl ammonium hydroxide (TMAH) was used for lignin analysis, in an ombrotrophic peatland. It specifically breaks of O-aryl bonds followed by methylation of the lignin components yielding phenolic subunits. Several discrepancies exist between TMAH thermochemolysis findings and those obtained from previous investigations with CuO oxidation. This could be explained by the specific pool of aryl ether, specifically targeted by the thermochemolysis, with discarding of C-C bonds. Hence, this would show the capacity of TMAH thermochemolysis to cleave oxidised lignin leaving lignin of fresh and preserved organic matter intact. The TMAH thermochemolysis method's efficiency in molecular characterization and lignin degradation was evaluated using principal component analysis (PCA). PCA reduced dimensionality and redundancy of component contributions, with the first two principal components accounting for 70.33 % of the total variance. PCA has reinforced the selectively of the thermochemolytic approach in targeting O-aryl bonds while maintaining C-C bonding of polyphenolic sub-units. Hence, two distinct oxidation phases: recent (acrotelm and mesotelm) and older (catotelm) have been revealed. PCA was applied to diagenetic and source vegetation proxies, revealing strong agreement among variables which is supported by the use of molecular ratios as indicators of organic matter source and dynamics in a peat core.

Micromagnetic analysis of magnetic vortex dynamics for reservoir computing

Reservoir computing (RC) has generated significant interest for its ability to reduce computational costs compared to traditional neural networks. The performance of the RC element is quantified by its memory capacity (MC) and prediction capability. In this study, we utilize micromagnetic simulations to investigate a magnetic vortex based on a permalloy ferromagnetic layer and its dynamics in RC. The nonlinear dynamics of the vortex core (VC), driven by continuous oscillating magnetic fields and binary digit data as spin-polarized current pulses, are analyzed. The highest MC observed is 4.1, corresponding to the nonlinear VC dynamics. Additionally, the prediction capability is evaluated using the Nonlinear Auto-Regressive Moving Average 2 task, demonstrating a normalized mean squared error of 0.0241 highlighting the time-series data prediction performance of the vortex as a reservoir.

Mechanochemical synthesis of nitrogen-modified microscale zero-valent iron for efficient Cr(VI) removal: The role of lattice strain

Lattice engineering of Fe0 based on heteroatom doping holds great promise in water purification owing to their tunable geometric and electronic structure. However, there is limited understanding of how nitrogen atom in Fe0 lattice structure affects its local microenvironment and corresponding reactivity toward target contaminants. Herein, microscale zero-valent iron with interstitial N doping (N-mZVI) was successfully prepared by a facile mechanochemical method for heavy metal pollution control. N-mZVI exhibited excellent reactivity for Cr(VI) elimination, and both removal efficiency and conversion rate could reach 100 %, which was 8.06 and 2.73 times higher than that of pristine ball milled mZVI, respectively. Besides, the rate constant of various heavy metals sequestration (Cr(VI), Ni(II), Pb(II), Cu(II), and Cd(II)) over N-mZVI was 61.3 ∼ 115.6-fold faster than that of pristine ball milled mZVI. N-mZVI was also demonstrated to be pH-universal, long-term stability, and environmental applicability. Experimental results and theoretical calculations indicated that tensile strain induced by interstitial N doping expanded Fe0 lattice and weakened the lattice Fe-Fe interaction, thus significantly accelerating electron transport dynamics in Fe0 core. Meanwhile, iron nitride species on the surface of N-mZVI promoted electron transfer from iron shell layer to heavy metals. This work comprehensively investigates the structure–property relationships of lattice engineering-based N-mZVI, and provides a new insight into rational design of modified mZVI with high reactivity.

Inulin Amphiphilic Copolymer-Based Drug Delivery: Unraveling the Structural Features of Graft Constructs.

In this study, the structural attributes of nanoparticles obtained by a renewable and non-immunogenic "inulinated" analog of the "pegylated" PLA (PEG-PLA) were examined, together with the potential of these novel nanocarriers in delivering poorly water-soluble drugs. Characterization of INU-PLA assemblies, encompassing critical aggregation concentration (CAC), NMR, DLS, LDE, and SEM analyses, was conducted to elucidate the core/shell architecture of the carriers and in vitro cyto- and hemo-compatibility were assayed. The entrapment and in vitro delivery of sorafenib tosylate (ST) were also studied. INU-PLA copolymers exhibit distinctive features: (1) Crew-cut aggregates are formed with coronas of 2-4 nm; (2) a threshold surface density of 1 INU/nm2 triggers a configuration change; (3) INU surface density influences PLA core dynamics, with hydrophilic segment stretching affecting PLA distribution towards the interface. INU-PLA2NPs demonstrated an outstanding loading of ST and excellent biological profile, with effective internalization and ST delivery to HepG2 cells, yielding a comparable IC50.

Contributions of core, mantle and climatological processes to Earth’s polar motion

Earth’s spin axis slowly moves relative to the crust over time. A 120-year-long record of this polar motion from astronomical and more modern geodetic measurements displays interannual and multidecadal fluctuations of 20 to 40 milliarcseconds superimposed on a secular trend of about 3 milliarcseconds per year. Earth’s polar motion is thought to be driven by various surface and interior processes, but how these processes operate and interact to produce the observed signal remains enigmatic. Here we show that predictions made by an ensemble of physics-informed neural networks trained on measurements to capture geophysical processes can explain the main features of the observed polar motion. We find that glacial isostatic adjustment and mantle convection primarily account for the secular trend. Mass redistribution on the Earth’s surface—for example, ice melting and global changes in water storage—yields a relatively weak trend but explains about 90% of the interannual and multidecadal variations. We also find that core processes contribute to both the secular trend and fluctuations in polar motion, either due to variations in torque at the core–mantle boundary or dynamical feedback of the core in response to surface mass changes. Our findings provide constraints on core–mantle interactions for which observations are rare and global ice mass balance over the past century and suggest feedback operating between climate-related surface processes and core dynamics.

Dynamics of Core–Shell-Structured Sorbents for Enhanced Adsorptive Separation of Carbon Dioxide

Dynamics of Core–Shell-Structured Sorbents for Enhanced Adsorptive Separation of Carbon Dioxide

Mode decomposition of core dynamics transients using higher-order DMD method

Accurately predicting three-dimensional power distribution within a reactor core during reactivity transients is crucial for optimizing reactor operational control. This paper proposes a higher-order dynamic mode decomposition (DMD) method for analyzing highly nonlinear dynamic systems in nuclear reactors. Through analysis of the 3-D LWR Core Transient Benchmark (3DLWRCT) with rod ejection accident, traditional DMD reconstruction techniques were found inadequate in accurately capturing the system’s dynamic evolution using the given simulation data, primarily due to the nonlinear features and local high-order characteristics of the reactor system. In contrast, the HODMD approach demonstrated its effectiveness in predicting future variations in the core’s state. These findings establish the feasibility of employing the HODMD method for transient analysis of core dynamics, leading to promising prospects for dynamic analysis in nuclear energy systems. Future research directions for improving the reconstructive accuracy of HODMD include capturing nonlinear characteristics, automating parameter selection, enabling multi-scale analysis, enhancing anomaly detection capabilities, and providing a broader context for analysis.

Tunable temporal dynamics of dipole response in graphene-wrapped core–shell nanoparticles

The investigation on the temporal dynamics of graphene-wrapped core–shell nanoparticles under the illumination of a Gaussian impulse have been carried out. By altering the graphene layers and the aspect ratio of the core–shell structure, we can adjust the resonant modes into typical cases in regime of terahertz. Accordingly, different scenarios for the temporal evolution are detected, which include two kinds of ultrafast oscillation with exponential decay tendency, pure exponential decay, and Gaussian shape, when the pulse duration of the incident pulse is much shorter than, similar to, and much longer than the localized surface plasmon lifetime. To one's interest, when the coupling between two resonant modes exists, one predicts the long-periodic oscillation, whose period is just the difference between the frequencies of the resonant modes. Hence, the intrinsic properties of the ultrafast oscillation can be hardly influenced by the input signals. Further quantitative calculation demonstrate that the periods of the ultrafast oscillations can be tuned by different physical mechanisms, which are, respectively, based on the self-interacting correction of a single resonance and the strong coupling between the resonant modes in frequency domain. Our results may be applicable in the fields of optical sensors, optical information processing, and other nanophotonic devices.

Interface State Assisted Ultrafast Carrier Dynamics in Core–Shell Structure ZIF-8@ZIF-67

Interface State Assisted Ultrafast Carrier Dynamics in Core–Shell Structure ZIF-8@ZIF-67

Analyses of the unavailability dynamics of emergency core cooling system

Abstract The Probabilistic Safety Assessment (PSA) studies can be used to evaluate the time-dependence of the safety systems availability. The purpose of this work is to analyze the unavailability dynamics of the Emergency Core Cooling System (ECCS). Using the PSA methodology, the ECCS was modeled. In order to show how the unavailability of the system varies as function of time (mission time, test interval and component ageing), sensitivity analyses are carried out. Following these analyses, polynomial functions of ECCS unavailability as function of time have been obtained. These functions allow to estimate the unavailability without modelling other ECCS fault trees being a simplified estimation of the system unavailability. In the same time, taking into account that the ECCS unavailability must be less than 10−2, the best time variations can be established to have the unavailability complied with this criterion. Also, the best time variations could be similarly established for any safety systems having the unavailability less than 10−3.

Research on core and mantle dynamics based on the electrical conductivity of materials of the Earth and planetary interior

Research on core and mantle dynamics based on the electrical conductivity of materials of the Earth and planetary interior

Cultural Inheritance and Artistic Construction of Non-heritage Dance in Northern Anhui in the Era of Artificial Intelligence

Abstract This paper explores the integration of image processing, motion capture, and virtual reality technologies to digitize and visualize dance. We capture the core dynamics of dance movements by extracting key frames and movement features from dance videos. Our analysis of motion capture data, exemplified by the “Flower Drum Lantern” dance, reveals a maximum vertical foot displacement of 72 cm and hip displacement of 93 cm. Virtual display technology significantly enhances the visual representation and dissemination of dance performances. This innovative approach to documenting and showcasing dance not only aids in preserving and transmitting intangible cultural heritage but also boosts public awareness and appreciation for such heritage.

Finite-temperature screw dislocation core structures and dynamics in α-titanium

A multiscale approach based on molecular dynamics (MD) and kinetic Monte Carlo (kMC) methods is developed to simulate the dynamics of an 〈a〉 screw dislocation in α-Ti. The free energy barriers for the core dissociation transitions and Peierls barriers for dislocation glide as a function of temperature are extracted from the MD simulations (based on machine learning interatomic potentials and optimization); these form the input to kMC simulations. Dislocation random walk trajectories from kMC agree well with those predicted by MD. On some planes, dislocations move via a locking-unlocking mechanism. Surprisingly, some dislocations glide in directions that are not parallel with the core dissociation direction. The MD/kMC multiscale method proposed is applicable to dislocation motion in simple and complex materials (not only screw dislocations in Ti) as a function of temperature and stress state.