Peak Density Research Articles

A Numerical Study on the Impact of E × B Drift on the Vertical Distribution of the Plasma Density Over the Geomagnetic Equatorial Ionospheric Region

AbstractUsing an in–house developed Quasi Two–Dimensional (QTD) physics–based ionospheric model, the impact of E × B drift velocity on the vertical distribution of the electron density over the equatorial latitude has been investigated. The vertical drift measurements from (a) drift analysis software of Digisonde (b) derived from Digisonde ionograms (c) calculated from the Scherliess–Fejer (SF) model, and (d) obtained from the magnetometer ΔH measurements have been used in this study. Four quiet days in a low solar activity year, representing four seasons of the year 2010, have been chosen for the study. The model–derived electron density profiles using the vertical drifts from all four methods matched well with the Digisonde observation below ∼150 km at all the Local Times (LTs) for all 4 days. However, since the Digisonde–derived drifts were very low, centered mostly around zero, it led to the overestimation/underestimation of the F–region peak plasma density (nmF2)/height (hmF2). The model simulated electron density profiles using the SF model, and ΔH derived vertical drifts showed good agreement with the observation up to an altitude of ∼350 km. The study showed that vertical drift is a factor that controls the nmF2 trough around noon over the equatorial latitude. It is seen that plasma diffusion occurs only beyond an altitude of 350 km, while the range of altitudes between 320 and 350 km acts as the “diffusion threshold height.” This finding has significant implications for understanding plasma dynamics in the equatorial ionosphere.

Two-dimensional quantum droplets in binary quadrupolar condensates

We study the stability and characteristics of two-dimensional (2D) quasi-isotropic quantum droplets (QDs) of fundamental and vortex types, formed by binary Bose–Einstein condensate with magnetic quadrupole–quadrupole interactions (MQQIs). The magnetic quadrupoles are built as pairs of dipoles and antidipoles polarized along the x-axis. The MQQIs are induced by applying an external magnetic field that varies along the x-axis. The system is modeled by the Gross–Pitaevskii equations including the MQQIs and Lee-Huang-Yang correction to the mean-field approximation. Stable 2D fundamental QDs and quasi-isotropic vortex QDs with topological charges S⩽4 are produced by means of the imaginary-time-integration method for configurations with the quadrupoles polarized parallel to the system’s two-dimensional plane. Effects of the norm and MQQI strength on the QDs are studied in detail. Some results, including an accurate prediction of the effective area, chemical potential, and peak density of QDs, are obtained in an analytical form by means of the Thomas-Fermi approximation. Collisions between moving QDs are studied by means of systematic simulations.

First-principles calculation of P-type Mg3Sb2 thermoelectric performance modification by Ge and Si doping

Mg3Sb2 has been considered a highly promising thermoelectric material for mid-temperature applications. Optimizing the properties of the material is crucial for accelerating its commercial use. In this work, first-principles molecular simulations of P-type Mg3Sb2 doped with the carbon group elements Ge and Si have been carried out. Results indicate that doping with Ge and Si enhances the thermodynamic stability and electrical conductivity of the material. This improvement is achieved by decreasing the bandgap, increasing the local and peak density of states, flattening the band structure, and elevating the relative mass of carriers. Additionally, doping with Ge and Si decreases the phonon velocity and Debye temperature, which weakens the thermal transport properties of the material. These findings suggest that Ge and Si doping is an effective method for improving the thermoelectric properties of the material. At the same doping concentration, the Si single-doped system possesses the smallest bandgap value with the highest peak density of states and forms an indirect bandgap, leading to the best electrical transport properties; the Ge single-doped system has the lowest phonon velocity and Debye temperature, which has the most significant effect in attenuating the thermal transport properties of the material; and the Ge–Si co-doped system has the highest relative mass of carriers, which is conducive to the enhancement of Seebeck coefficient. The results offer theoretical guidance for experimentally analyzing the effects of Ge and Si doping on the thermoelectric properties of Mg3Sb2.

Influence of temperature changes and vertically transported trace species on the structure of MLT region during major SSW events

Sudden stratospheric warming (SSW) events are large-scale dynamic phenomena which can significantly affect the circulation, temperature, and composition of different atmospheric layers. The circulation changes during these events induce variations in the atmospheric neutral and ion densities and cause the vertical transport of various trace species. The severity of effects induced by major SSW events in the mesosphere and lower thermosphere (MLT) region has received less attention than that in the lower atmosphere. The major influence of temperature and vertically transported trace species on the energetics, thermal and compositional structure of the MLT region has been investigated during two major SSW events with elevated stratopause. Variations in the nitric oxide volume emission rates (NO-VER), a measure of infrared radiative cooling by NO, are reported for the first time in the context of the dynamical changes during SSW events. This study investigates the role of temperature and NO variability on the energetics of the MLT region, particularly during the formation of elevated stratopause. The effects of supplemented NO density on the secondary ozone layer has also been investigated during these events, the anti-correlation between secondary ozone and NO does not conclude on the role of NO in the secondary ozone peak density variations. Notwithstanding the similarity in terms of defining characteristics, both SSW events impact the secondary ozone layer differently. In contrast to earlier studies, it is suggested that along with temperature, the availability of atomic oxygen is the major factor for the observed variation in secondary ozone during the SSW events.

An Investigation on the Distribution of Martian Ionospheric Particles, Based on the Mars Atmosphere and Volatile Evolution (MAVEN)

In this paper, we use the key parameters data set of the Neutral Gas and Ion Mass Spectrometer from the Mars Atmosphere and Volatile Evolution (MAVEN) mission. The particle density profiles of electrons, CO2+/N2+, CO+, O2+, O+, NO+, O2 and O from 90 to 500 km have been deduced by adopting the Chapman modeling methodology. The correlation of the peak density/altitude with the solar zenith angle, the changes in the profile of the Martian ionosphere during solar flares, and the effects of Martian dust storms are analyzed. The results exhibit a positive/negative correlation between the peak density/altitude of the M2 layer and the solar zenith angle. Within the MAVEN observational record available, only three C-Class flares occurred on 26 August 2016, 29 November 2020, and 26 August 2021. The analysis reveals during these solar flare events, the electron density of the M2 layer above 200 km increases obviously. The peak density of M1 increases by 33.4%, 13.2% and 7.4%, while the peak height decreases by 0.1%, 10.2% and 4.4%, respectively. The Martian dust storm causes the peak height of the M2 layer to increase by 19.5 km, and the peak density to decrease by 4.2 × 109 m−3. Our study shows that the Martian ionosphere is similar to the Earth’s, which is of great significance for understanding the planetary ionosphere.

A Case Study of Ionospheric Storm‐Time Altitudinal Differences at Low Latitudes During the May 2021 Geomagnetic Storm

AbstractPrevious studies paid little attention to the ionospheric storm‐time altitudinal differences due to insufficiency of ionospheric measurements. In this work, multiple instrumental observations were used to investigate the ionospheric storm‐time response at low latitudes in the American and Asian‐Australian sectors during the May 2021 geomagnetic storm. The ground‐based Global Navigation Satellite Systems (GNSS) total electron content (TEC) and Low Earth Orbit (LEO) satellite topside TEC presented opposite (positive/negative) variations in the low‐latitude and equatorial region of both sectors during this storm. The electron density profiles from the Constellation Observing System for Meteorology, Ionosphere, and Climate‐2 (COSMIC‐2) and the Sanya Incoherent Scatter Radar showed a good agreement and well explained the opposite variations between GNSS TEC and LEO satellite topside TEC. The F2‐layer peak height (hmF2) and peak density (NmF2) displayed inverse variations, and the feature was present mostly in the regions between equatorial ionization anomaly crests. The combined modulation effects of the storm‐time zonal electric fields and the field‐aligned transports possibly resulted in the contrary variations of hmF2 and NmF2 in the low‐latitude and equatorial region, leading to the storm‐time altitudinal differences during this storm. Relatively, the storm‐time thermospheric composition disturbances might be a minor factor responsible for these differences.

Surface topography prediction of slider races using formed grinding wheel shape and material removal mechanism

Compared with the roughness, the three-dimensional (3D) topography parameters, surface microstructure geometric characteristics and other information can more fully evaluate the grinding quality of the slider raceway surface. In this paper, based on the 3D topography model of the abrasive particle distribution on the surface of the formed grinding wheel, the material removal mechanism between the abrasive particle and the raceway surface is analyzed. With the undeformed chip thickness distribution model as the intermediate variable, the 3D topography model of the slider raceway surface is established, and the model verification is carried out from the roughness and the geometric characteristics of the surface microstructure, respectively. At the same time, the surface microstructure is extracted from the topography model, and the effects of different grinding process parameters on the geometric characteristics such as the height to width ratio, depth to width ratio and distribution density of groove, convex peak and peak valley structures are studied. Results are shown that AS,TH increase from [0.05 0.6 μm] to [0.25 0.8 μm] and FGH grows from [0.11 1.05 μm] to [0.5 1.61 μm] when the grinding depth rises from 1 μm to 4 μm. AS, TH are firstly decreased from [0.17 0.61 μm] to [0.08 0.52 μm] and then increased to [0.26 0.78 μm], and the FGH declines from [0.34 1.01 μm] to [0.16 0.86 μm] and then increases to [0.51 1.38 μm] with the feeding speed is in [25, 28 m/min]. In addition, in the range of grinding wheel linear velocity [28, 34 m/s], the AS,TH decreases from [0.19 0.81 μm] to [0.1 0.55 μm] and the FGH decreases from [0.55 1.6 μm] to [0.2 1.1 μm]. This can prepare for the subsequent research on the impact of the topography characteristics on the friction coefficient and wear amount of the slider raceway surface.

Measurement of pressure fluctuation distribution on a flat wall behind supported square cylinder with pressure-sensitive paint

The pressure fluctuation distribution on the floor surface behind a supported square cylinder in a turbulent boundary layer was measured by using pressure-sensitive paint (PSP). Specifically, the accuracy and frequency response of PSP at a Mach number around M = 0.3 were examined. Four square cylinders with different dimensions were investigated in the same turbulent boundary layer, and the detailed relationship between these conditions and Kármán vortex shedding structures was discussed. The values measured with PSP had a similar trend to those measured with a pressure transducer at up to 5 kHz. The peak power spectral density (PSD) of the pressure fluctuations due to Kármán vortex shedding was observed within an error of approximately 30 % at up to frequencies greater than 3 kHz. Moreover, the peak frequency of Kármán vortex shedding was found to decrease with the cylinder height in a manner similar to a previous empirical equation for the Strouhal number. The peak PSD value for the shortest square cylinder (h/w = 3.5, h/δ = 1.1) was twice as high as that for the other cylinders; also, the high-pressure fluctuation area in this case did not spread downstream, which suggests that the flow from the top of the cylinder affected the Kármán vortex shedding generated from the cylinder’s sides. One contour of the two main modes extracted for the highest PSD via the right singular vector vi at the Kármán vortex frequency had an asymmetric distribution behind the supported taller square cylinders (h/w ≥ 7.0, h/δ ≥ 2.3). This result is considered to be derived from the Kármán vortex shedding being mainly generated from the mainstream rather than the boundary-layer flow.

Capillary Condensation of Water in Graphene Nanocapillaries.

Recent experiments have revealed that the macroscopic Kelvin equation remains surprisingly accurate even for nanoscale capillaries. This phenomenon was so far explained by the oscillatory behavior of the solid-liquid interfacial free energy. We here demonstrate thermodynamic and capillarity inconsistencies with this explanation. After revising the Kelvin equation, we ascribe its validity at nanoscale confinement to the effect of disjoining pressure. To substantiate our hypothesis, we employed molecular dynamics simulations to evaluate interfacial heat transfer and wetting properties. Our assessments unveil a breakdown in a previously established proportionality between the work of adhesion and the Kapitza conductance at capillary heights below 1.3 nm, where the dominance of the work of adhesion shifts primarily from energy to entropy. Alternatively, the peak density of the initial water layer can effectively probe the work of adhesion. Unlike under bulk conditions, high confinement renders the work of adhesion entropically unfavorable.

Molecular insight into sequence-defined polyelectrolytes for energy storage devices

Polyelectrolyte (PE) adsorption on charged surfaces is a complex phenomenon that has an array of applications ranging from healthcare to designing energy storage devices. PE adsorption on surfaces involves surface charge polarization effects which arise due to the dielectric dissimilarities between the PE and the charged surface. PEs owing to their high potential window, and leakage-resistant behavior are used as supercapacitor electrolytes. Recent experimental evidence suggests co-block polymers as potential design materials for energy storage devices (ESDs). It is imperative to mention that the structural variation of the co-block polymers under spatial confinements will have a key role in designing electrodes and electrolytes for ESDs which demands a detailed investigation. This study reveals that the spatial orientations of the charged groups have an impressive impact on the changes in PE charge density peaks, charge amplification peaks, PE adsorption, counter-ion adsorption, and differential and integral capacitance while confined by graphene electrodes. It is startling to observe that the counter-ion distribution within the electrical double layer of the positively charged surface significantly depends on the orientation of the PEs. However, with increasing solvent dielectric constant the variations in the above-mentioned properties subside due to reduced electrostatic interactions. The differential capacitance and the integral capacitance are also found to be dependent on the dielectric constants of the solvent. These findings will be immensely useful in determining the key factors needed to describe the preferred spatial configuration of a PE suitable for various ESDs and applications involving PEs in a confined system.

Elucidating the impact of massive neutrinos on halo assembly bias

ABSTRACT Massive neutrinos have non-negligible impact on the formation of large-scale structures. We investigate the impact of massive neutrinos on the halo assembly bias effect, measured by the relative halo bias $\hat{b}$ as a function of the curvature of the initial density peak $\hat{s}$, neutrino excess ϵν, or halo concentration $\hat{c}$, using a large suite of ΣMν = 0.0 and 0.4 eV simulations with the same initial conditions. By tracing dark matter haloes back to their initial density peaks, we construct a catalogue of halo ‘twins’ that collapsed from the same peaks but evolved separately with and without massive neutrinos, thereby isolating any effect of neutrinos on halo formation. We detect a 2 per cent weakening of the halo assembly bias as measured by $\hat{b}(\epsilon _\nu)$ in the presence of massive neutrinos. As there exists a significant correlation between $\hat{s}$ and ϵν (rcc = 0.319), the impact of neutrinos persists at a reduced level (0.1 per cent) in the halo assembly bias measured by $\hat{b}(\hat{s})$. However, we do not detect any neutrino-induced impact on $\hat{b}(\hat{c})$, consistent with earlier studies and the lack of correlation between $\hat{c}$ and ϵν (rcc = 0.087). We also discover an analogous assembly bias effect for the ‘neutrino haloes’, whose concentrations are anticorrelated with the large-scale clustering of neutrinos.

Wavelet Analysis of Atmospheric Ozone and Ultraviolet Radiation on Solar Cycle-24 over Lumbini, Nepal

This research aims to comprehensively examine the clearness index (KT), total ozone column (TOC), and ultraviolet A (UVA) and ultraviolet B radiation (UVB) over Lumbini, Nepal (27°28’ N, 83°16’ E, and 150 m above sea level) throughout the 11 years of solar cycle 24 (2008 to 2018). The Lumbini, a highly polluted region, is important in advancing the identification and analysis of TOC variations across regions with similar geographical and climatic attributes. Data from the Ozone Monitoring Instrument (OMI) of the EOS-AURA satellite of NASA were used to analyze the daily, monthly, seasonal, and annual trends in the clearness index (KT), ultraviolet A (UVA), ultraviolet B (UVB), and TOC from the Comprehensive Environmental Data Archive (CEDA). The study found that the yearly averages for KT, TOC, UVA, and UVB were 0.55 ± 0.13, 272 ± 14 DU, 12.61 ± 3.50 W/m2, and 0.32 ± 0.11 W/m2, respectively. These values provide insights into the long-term variations in atmospheric parameters at Lumbini. The study also applied the continuous wavelet transform (CWT) to analyze KT, TOC, UVA, and UVB temporal variations. The power density peak of 35,000 DU2 in the TOC was observed from the end of 2010 to the end of 2011, within 8.5 years, underscoring the significance of analyzing TOC dynamics over extended durations to understand atmospheric behavior comprehensively.

Secure deep learning-based energy efficient routing with intrusion detection system for wireless sensor networks

In general, wireless sensor networks are used in various industries, including environmental monitoring, military applications, and queue tracking. To support vital applications, it is crucial to ensure effectiveness and security. To prolong the network lifetime, most current works either introduce energy-preserving and dynamic clustering strategies to maintain the optimal energy level or attempt to address intrusion detection to fix attacks. In addition, some strategies use routing algorithms to secure the network from one or two attacks to meet this requirement, but many fewer solutions can withstand multiple types of attacks. So, this paper proposes a secure deep learning-based energy-efficient routing (SDLEER) mechanism for WSNs that comes with an intrusion detection system for detecting attacks in the network. The proposed system overcomes the existing solutions’ drawbacks by including energy-efficient intrusion detection and prevention mechanisms in a single network. The system transfers the network’s data in an energy-aware manner and detects various kinds of network attacks in WSNs. The proposed system mainly comprises two phases, such as optimal cluster-based energy-aware routing and deep learning-based intrusion detection system. Initially, the cluster of sensor nodes is formed using the density peak k-mean clustering algorithm. After that, the proposed system applies an improved pelican optimization approach to select the cluster heads optimally. The data are transmitted to the base station via the chosen optimal cluster heads. Next, in the attack detection phase, the preprocessing operations, such as missing value imputation and normalization, are done on the gathered dataset. Next, the proposed system applies principal component analysis to reduce the dimensionality of the dataset. Finally, intrusion classification is performed by Smish activation included recurrent neural networks. The proposed system uses the NSL-KDD dataset to train and test it. The proposed one consumes a minimum energy of 49.67 mJ, achieves a better delivery rate of 99.92%, takes less lifetime of 5902 rounds, 0.057 s delay, and achieves a higher throughput of 0.99 Mbps when considering a maximum of 500 nodes in the network. Also, the proposed one achieves 99.76% accuracy for the intrusion detection. Thus, the simulation outcomes prove the superiority of the proposed SDLEER system over the existing schemes for routing and attack detection.

Gravitational waves from nonradial oscillations of stochastically accreting neutron stars

Abstract Oscillating neutron stars are sources of continuous gravitational waves. We study analytically the excitation of stellar oscillations by the mechanical impact on the stellar surface of ‘clumps’ of stochastically accreted matter. We calculate the waveform and spectrum of the gravitational wave signal emitted by the accretion-driven pulsations. Results are generated for an idealised model of a nonrotating, unmagnetised, one-component star with uniform polytropic index npoly assuming Newtonian gravity and the Cowling approximation. We find that the excited mode amplitudes grow with increasing npoly and mode order n. The gravitational wave signal forms a sequence of amplitude-modulated packets for npoly = 1, lasting ∼10−3s after each impact. The gravitational wave strain increases with increasing npoly, but decreases with increasing n and increasing multipole order l for npoly = 1. In the observing band of current long-baseline interferometers, g-modes emit higher, narrower peaks in the amplitude spectral density than f- and p-modes, with the highest peaks reaching ∼10−26Hz−1/2 for modes with damping time τnl ∼ 108yr. The root-mean-square strain hrms, calculated by summing over modes with 2 ≤ l ≤ 4 and τnl ≤ 108yr, spans the range 10−33 ≤ hrms ≤ 10−32 for 1 ≤ npoly ≤ 2.

Fully automated operational modal identification based on scale-space peak picking algorithm and power spectral density estimation

Modal analysis is a fundamental and essential research direction in the field of structural engineering. The ultimate goal is to determine the modal parameters of the structures. However, the existing modal analysis algorithms often require a large number of parameter adjustments and manual intervention during operation, which cannot be fully automated. In order to realize the automatic identification of modal parameters, the automatic operational modal identification method (AOMI) is proposed based on the interpolated power spectral density estimation (IPSE). To achieve more precise spectrum analysis in the low-frequency band, IPSE is employed to perform Fourier transform on the original frequency domain segment with optimized frequency resolution. This enhances the sharpness of the obtained spectrum in the low-frequency range, making peak frequencies more discernible. Subsequently, the scale-space peak picking algorithm is used to automatically obtain the peak of the power spectral density (PSD), thus enabling the automatic identification of the natural frequency. Finally, the frequency domain decomposition method (FDD) is used to identify modal parameters based on the natural frequencies. The effectiveness of AOMI is verified through the modal identification of the old steel truss bridge and the three layer framework. Under the environmental excitation, the frequencies identified by the IPSE method is close to that of FDD, Bayesian fast fourier transform (FFT) and covariance driven stochastic subspace identification (SSI-COV). Furthermore, the PSD obtained through IPSE has sharper peak than that of FDD and the Welch’s method. The damping ratio identification accuracy and modal assurance criterion (MAC) are satisfactory in AOMI, which can improve the automatic performance.

Vibrational properties of disordered stealthy hyperuniform 1D atomic chains

Disorder hyperuniformity is a recently discovered exotic state of many-body systems that possess a hidden order in between that of a perfect crystal and a completely disordered system. Recently, this novel disordered state has been observed in a number of quantum materials including amorphous 2D graphene and silica, which are endowed with unexpected electronic transport properties. Here, we numerically investigate 1D atomic chain models, including perfect crystalline, disordered stealthy hyperuniform (SHU) as well as randomly perturbed atom packing configurations to obtain a quantitative understanding of how the unique SHU disorder affects the vibrational properties of these low-dimensional materials. We find that the disordered SHU chains possess lower cohesive energies compared to the randomly perturbed chains, implying their potential reliability in experiments. Our inverse partition ratio (IPR) calculations indicate that the SHU chains can support fully delocalized states just like perfect crystalline chains over a wide range of frequencies, i.e. ω∈(0,100) cm−1, suggesting superior phonon transport behaviors within these frequencies, which was traditionally considered impossible in disordered systems. Interestingly, we observe the emergence of a group of highly localized states associated with ω∼200 cm−1, which is characterized by a significant peak in the IPR and a peak in phonon density of states at the corresponding frequency, and is potentially useful for decoupling electron and phonon degrees of freedom. These unique properties of disordered SHU chains have implications in the design and engineering of novel quantum materials for thermal and phononic applications.

ВИЗНАЧЕННЯ ТЕХНОЛОГІЧНИХ ПАРАМЕТРІВ ЛАЗЕРНОГО ВИПРОМІНЕННЯ ДЛЯ ОТРИМАННЯ СУБМІКРО- ТА НАНОСТРУКТУР У ЗМІЦНЮВАЛЬНИХ ПОКРИТТЯХ НА СТАЛЯХ

Using the previously developed model of theoretical processes in the zone of laser irradiation, where thermal and thermomechanical processes are described, including the influence of crystallization energy and other internal energies during the formation of nanostructures at various temperature levels, further investigation of the thermal and thermomechanical characteristics of different structural steels during the formation of nanostructures on their surfaces using laser irradiation was conducted. To validate the model, temperature fields were determined in the zone of laser irradiation on steel 20 (Fig. 1a) and steel 50 (Fig. 1b), considering both heating and cooling processes. Calculations were performed for heat flux densities and durations of exposure close to those necessary for obtaining nanostructures (500...2000 K) and with temperature rise rates exceeding 10^7 K/s. As a result of calculations using the refined thermal model, temperature distributions at a depth of 1 μm during laser irradiation on steel with different carbon contents (steel 20, 38Х, 50, and У8) at various peak heat flux densities in the surface layer were obtained. A spatiotemporal distribution of temperatures along the radius of the laser spot and over time during laser irradiation with a heat flux density of q=3∙10^8 W/m^2 at a spot radius of 0.1 mm was constructed. Zones of nanostructure formation were identified depending on the heat flux density over the duration of laser irradiation. Theoretical investigations using the updated thermal model confirmed the need to consider the temperature rise rate, as exceeding it increases the likelihood of thermomechanical failure. At the same time, due to insufficient temperature rise rates during laser nanostructure formation in the surface layers of carbon steels, more micro- and sub microstructures are formed.

Unravelling the collision scenario of the dissociative galaxy cluster Abell 56 through hydrodynamic simulations

ABSTRACT In galaxy cluster collisions, the gas can be separated from dark matter haloes. Abell 56 displays signatures of a dissociative bullet-like merger with a possible high-inclination angle between the plane of orbit and the sky. Our objective is to provide a comprehensive description of the features observed in the collision scenario of Abell 56. Additionally, we aim to apply a potential weak lensing mass bias correction attributed to the merger to evaluate its impact on our findings. To investigate this, we perform tailored hydrodynamical N-body simulations, varying the impact parameter. We initially identified an early scenario at 0.12 Gyr after the central passage that reproduces some observational features. However, the mean temperature of 9.7 keV exceeded the observed value. Our best model corresponds to the late scenario at 0.52 Gyr after the pericentre, reproducing observed features of Abell 56, with an inclination of 58°. These features include the offset of 103 kpc between the main gas density peak and the south dark matter density peak, gas morphology, a line-of-sight relative velocity of 184 km s−1, and a mean temperature of 6.7 keV. This late model provides a plausible scenario to describe the dynamics of Abell 56. The weak lensing mass bias did not significantly impact the overall dynamics of this cluster merger.

Chaotic mixotroph dynamics arise with nutrient loading: Implications for mixotrophy as a harmful bloom forming mechanism

Mixotrophic nutrition, in which organisms combine aspects of heterotrophic and autotrophic nutrition, is a common characteristic amongst the phytoplankton, and especially amongst harmful algae bloom (HAB) species. To explore how the addition of a mixotrophic population influences a theoretical plankton system under different enrichment levels, we employ a previously published numerical plankton model that reproduces seasonal succession dynamics. Through this work we found potential for chaos to occur as the system was enriched. Focusing on occurrence of chaos in the mixotroph population, a novel finding, we conducted a bifurcation analysis which demonstrated a period doubling route to chaos. Further, we demonstrate that the occurrence of chaotic dynamics in the model system is not an artifact of the mixotroph life-history trait values used in our initial simulations, rather chaos was found to occur under a wide range of mixotroph trait value combinations. Through our trait analysis, we also found that regardless of whether or not the system was chaotic for a specific combination of values, variation in the mixotroph population peak population density could be high between consecutive years. These findings have implications that are important for the management of nutrients in aquatic systems and HABs. Results shed light on why it may be difficult to predict the occurrence of mixotrophic HABs based solely on environmental variables, when the year-to-year peak density of the mixotroph is chaotic or highly variable with enrichment. These results also demonstrate how initiation of a mixotrophic HAB might occur with enrichment, due to erratic population spikes, when broadcast allelopathic or toxic chemicals are at low concentrations, a novel bloom initiation mechanism.

Molecular Mechanisms of Sorbed Ion Effects during Boehmite Particle Aggregation.

Classical theories of particle aggregation, such as Derjaguin-Landau-Verwey-Overbeek (DLVO), do not explain recent observations of ion-specific effects or the complex concentration dependence for aggregation. Thus, here, we probe the molecular mechanisms by which selected alkali nitrate ions (Na+, K+, and NO3-) influence aggregation of the mineral boehmite (γ-AlOOH) nanoparticles. Nanoparticle aggregation was analyzed using classical molecular dynamics (CMD) simulations coupled with the metadynamics rare event approach for stoichiometric surface terminations of two boehmite crystal faces. Calculated free energy landscapes reveal how electrolyte ions alter aggregation on different crystal faces relative to pure water. Consistent with experimental observations, we find that adding an electrolyte significantly reduces the energy barrier for particle aggregation (∼3-4×). However, in this work, we show this is due to the ions disrupting interstitial water networks, and that aggregation between stoichiometric (010) basal-basal surfaces is more favorable than between (001) edge-edge surfaces (∼5-6×) due to the higher interfacial water densities on edge surfaces. The interfacial distances in the interlayer between aggregated particles with electrolytes (∼5-10 Å) are larger than those in pure water (a few Ångströms). Together, aggregation/disaggregation in salt solutions is predicted to be more reversible due to these lower energy barriers, but there is uncertainty on the magnitudes of the energies that lead to aggregation at the molecular scale. By analyzing the peak water densities of the first monolayer of interstitial water as a proxy for solvent ordering, we find that the extent of solvent ordering likely determines the structures of aggregated states as well as the energy barriers to move between them. The results suggest a path for developing a molecular-level basis to predict the synergies between ions and crystal faces that facilitate aggregation under given solution conditions. Such fundamental understanding could be applied extensively to the aggregation and precipitation utilization in the biological, pharmaceutical, materials design, environmental remediation, and geological regimes.