Extreme Properties Research Articles

Synergistic ecological remediation of tailings in high altitude ecologically fragile areas by ryegrass (Lolium perenne L.) and activated carbon

The ecological vulnerability and extreme physicochemical properties of tailings in high-altitude mining areas pose challenges to the ecological restoration of tailings. Therefore, the aims of the current study were to remediate tailings in high-altitude mining areas by combining ryegrass (Lolium perenne L.) and activated carbon. Ryegrass potting experiments with Cu and Pb–Zn tailings and the two tailings amended with activated carbon. The effects of synergistic treatment of ryegrass and activated carbon on the physicochemical properties, heavy metal content, and enzyme activity of Cu tailings and Pb–Zn tailings were studied. Compared with planting ryegrass group, activated carbon significantly improved the water holding capacity of the two tailings. After restoration, the water holding capacity of Cu tailings and Pb–Zn tailings were 47.33% and 47.67%, respectively. In addition, the combination of ryegrass and activated carbon improved the quality of tailings, effectively increasing the organic carbon and available phosphorus content of tailings. Ryegrass and activated carbon synergistically activate tailings enzyme activity. The decrease in heavy metals in the tailings was mainly attributed to uptake by ryegrass rather than immobilization by activated carbon. The synergistic remediation of ryegrass and activated carbon is a potential ecological restoration treatment for tailings in high-altitude ecologically fragile areas.

Characterization of a Peculiar Einstein Probe Transient EP240408a: An Exotic Gamma-Ray Burst or an Abnormal Jetted Tidal Disruption Event?

Abstract We present the results of our multiwavelength (X-ray to radio) follow-up campaign of the Einstein Probe transient EP240408a. The initial 10 s trigger displayed bright soft X-ray (0.5–4 keV) radiation with peak luminosity L X ≳ 1049 (1050) erg s−1 for an assumed redshift z ≳ 0.5 (2.0). The Neil Gehrels Swift Observatory and Neutron star Interior Composition ExploreR discovered a fading X-ray counterpart lasting for ∼5 days (observer frame), which showed a long-lived (∼4 days) plateau-like emission (t −0.5) before a sharp power-law decline (t −7). The plateau emission was in excess of L X ≳ 1046 (1047) erg s−1 at z ≳ 0.5 (2.0). Deep optical and radio observations resulted in nondetections of the transient. Our observations with Gemini South revealed a faint potential host galaxy (r ≈ 24 AB mag) near the edge of the X-ray localization. The faint candidate host, and lack of other potential hosts (r ≳ 26 AB mag; J ≳ 23 AB mag), imply a higher redshift origin (z ≳ 0.5), which produces extreme X-ray properties that are inconsistent with many known extragalactic transient classes. In particular, the lack of a bright gamma-ray counterpart, with the isotropic-equivalent energy (10–10,000 keV) constrained by GECam and Konus-Wind to E γ,iso ≲ 4 × 1050 (6 × 1051) erg at z ≈ 0.5 (2.0), conflicts with known gamma-ray bursts of similar X-ray luminosities. We therefore favor a jetted tidal disruption event as the progenitor of EP240408a at z ≳ 1.0, possibly caused by the disruption of a white dwarf by an intermediate-mass black hole. The alternative is that EP240408a may represent a new, previously unknown class of transient.

Enhanced understanding on spatial and dependence properties of rainfall extremes and storm tides in coastal cities

Enhanced understanding on spatial and dependence properties of rainfall extremes and storm tides in coastal cities

Mechanical causes and implications of repetitive DNA motifs

Experimental research suggests that local patterns in DNA sequences can result in stiffer or more curved structures, potentially impacting chromatin formation, transcription regulation, and other processes. However, the effect of sequence variation on DNA geometry and mechanics remains relatively underexplored. Using rigid base pair models to aid rapid computation, we investigated the sample space of 100 bp DNA sequences to identify mechanical extrema based on metrics such as static persistence length, global bend, or angular deviation. Our results show that repetitive DNA motifs are overrepresented in these extrema. We identified specific extremal motifs and demonstrated that their geometric and mechanical properties significantly differ from standard DNA through hierarchical clustering. We provide a mathematical argument supporting the presence of DNA repeats in extremizing sequences. Finally, we find that repetitive DNA motifs with extreme mechanical properties are prevalent in genetic databases and hypothesize that their unique mechanical properties could contribute to this abundance.

Ionic liquid functionalized binary montmorillonite nanomaterials as water-based lubricant additives for steel/steel contact.

Two-dimensional (2D) nanomaterials have attracted much attention for the lubrication enhancement of water. Stably dispersing nanosheets in water for an extended period is a challenging task. 2D montmorillonite (MMT) nanosheets are modified with protonic ionic liquids (PILs) with the assistance of simple and efficient mechanochemical synthesis, which can stably disperse in water. With the help of TEM, FTIR, and XPS characterization, it is further demonstrated that the one-step mechanochemical stirring synthesis method can introduce the anions and cations of PILs into the MMT interlayer simultaneously, which gives the binary-modified MMT nanosheets some of the advantages of PILs, such as designability and functionalization. The successful intercalation and grafting of ionic liquids between the MMT nanosheets made it possible to obtain ultra-thin thickness and micro-nano size of the binary MMT nanosheets, and the synergistic effect of the 2D MMT nanosheets and the PIL laid a good foundation for the realization of the excellent lubricity, the easy-sliding interlayer structure, and the adsorption of the film more easily. Using the modified MMT nanosheets, the coefficient of friction and wear volume can be reduced by 76% and 94% at a high frequency and high load, respectively. The successful intercalation of PILs endows the MMT nanomaterial with better thermal stability and extreme pressure properties, with the maximum bite-free load (PB) being nearly 17 times higher than water. The friction mechanism shows that the enhancement of the lubrication and anti-wear performance is attributed to the boundary adsorbed tribofilm of MMT nanosheets achieving a repairing effect of the friction interfaces, which provides effective lubrication for steel/steel contact, thus preventing further wear of the friction pair surface. This work provides green, economical guidance for developing natural water-based lubricant additives and has great potential in sustainable lubrication.

Machine Learning for Explanation of Subgrid Convective Precipitation: A Case Study over CONUS Using a Convection-Allowing Model and SHAP Analysis

Abstract Understanding the role of dynamic, thermodynamic, and cloud microphysical parameters governing the occurrence and magnitude of convective precipitation at subgrid scales is crucial for reducing uncertainties in extreme precipitation properties projected by global climate models. This study evaluates the efficacy of extreme gradient boosting decision trees in detecting subgrid convective precipitation features (CPFs) and estimating their extent using convection-allowing simulations based on observations across the contiguous United States (CONUS). Our annual analysis reveals that despite the imbalanced nature of detecting subgrid CPFs, the model achieves an 85% F1 score using key CPF predictors at 100-km grids. Performance metrics for CPF detection and extent estimation show significant seasonal variations corresponding to mesoscale environmental conditions influencing their space–time dynamics. Shapley values from the model indicate that cloud liquid and ice water content are primary predictors in CPF detection, while midlevel vorticity induced by convective heating profiles predominantly influences CPF extent estimation. Significance Statement Understanding future changes in precipitation extremes requires a grasp of small-scale convective processes, which global circulation models currently cannot explain. This study aims to enhance our understanding of where, when, and to what extent machine learning can characterize the occurrence and extent of convective precipitation features. Learning from convective-enabled simulations and ground-based radar data over the contiguous United States, the findings demonstrate that extreme gradient-boosted decision trees can effectively capture these features and explain the relative importance of cloud microphysics, thermodynamics, and dynamic environmental forces that drive the space–time variability of convective precipitation.

Relationship of Locally Inhomogeneous, Elastic and Magnetic Fields in Mn–Zn Ferrites

Using the methods of X-ray diffraction analysis, X-ray spectroscopy and theoretical physics, we studied the patterns of changes in the atomic, electronic and magnetic subsystems in ferrites of variable composition MnxZnyFezO4 associated with the formation of clusters differing in the composition of cations. Experimentally detected clusters, which appear in X-ray diffraction patterns as a halo, are characterized by a certain superposition of ion states, the magnetic moment of which depends not only on the spin of the electron, but also on its orbital moment and the spin of the nucleus. A phase transition was discovered in the mesoscopic cluster structure from manganese-containing clusters, caused by the interaction of trivalent manganese ions with oxygen ions, to clusters with a predominance of di- and trivalent manganese ions with oxygen ions. It is found that the clustered structure of manganese-zinc ferrites is responsible for the appearance of extreme magnetic properties; the maximum corresponds to a change in the dominant type of clusters. It is found that with an increase in mass density, a repopulation of energy states occurs as a decrease in the states of the low-energy electron group and an increase in the high-energy Fermi surface in the form of a saddle. It has been established that the peculiarities of condensation of the fundamental and soft modes of complexes (clusters) containing manganese and oxygen ions lead to changes in the physical parameters of the samples.

STUDY OF TRIBOLOGICAL PROPERTIES OF ORGANIC COM-POUNDS OF VARIOUS LUBRICANTS IN CASTROL ALPHA SP 680 OIL

Castrol ALPHA Sp 680 transmission grease, based on highly refined mineral oil, is used to lubri-cate gears in mechanisms. The presence in its composition of various functional groups and ele-ments provides the required performance properties of this oil. Castrol Alpha SP 680 gear oil, along with lubricating properties, has high antioxidant and anti-foam properties. The disadvantage of the oil is that it has low corrosion and extreme pressure properties. Therefore, the goal of our research was to develop a universal high-quality gear oil based on multifunctional and high-quality additives that meets modern requirements. The article presents an analysis of the IHP-14M addi-tive in Castrol Alpha SP 680 gear oil and the results of comparative tribological tests with foreign additives with the same functional properties. Keywords: transmission oils, tribological properties, additives, corrosion, lubricating effect.

Hidden tail chains and recurrence equations for dependence parameters associated with extremes of stationary higher-order Markov chains

Abstract We derive some key extremal features for stationary kth-order Markov chains that can be used to understand how the process moves between an extreme state and the body of the process. The chains are studied given that there is an exceedance of a threshold, as the threshold tends to the upper endpoint of the distribution. Unlike previous studies with $k>1$ , we consider processes where standard limit theory describes each extreme event as a single observation without any information about the transition to and from the body of the distribution. Our work uses different asymptotic theory which results in non-degenerate limit laws for such processes. We study the extremal properties of the initial distribution and the transition probability kernel of the Markov chain under weak assumptions for broad classes of extremal dependence structures that cover both asymptotically dependent and asymptotically independent Markov chains. For chains with $k>1$ , the transition of the chain away from the exceedance involves novel functions of the k previous states, in comparison to just the single value, when $k=1$ . This leads to an increase in the complexity of determining the form of this class of functions, their properties, and the method of their derivation in applications. We find that it is possible to derive an affine normalization, dependent on the threshold excess, such that non-degenerate limiting behaviour of the process, in the neighbourhood of the threshold excess, is assured for all lags. We find that these normalization functions have an attractive structure that has parallels to the Yule–Walker equations. Furthermore, the limiting process is always linear in the innovations. We illustrate the results with the study of kth-order stationary Markov chains with exponential margins based on widely studied families of copula dependence structures.

Extreme Cold Mechanical Properties of Concrete with Additive-Based Freeze Protection System

Extreme Cold Mechanical Properties of Concrete with Additive-Based Freeze Protection System

Multi-material topology optimization design of microstructures with extreme mechanical properties

Multi-material topology optimization design of microstructures with extreme mechanical properties

An Extremal Property of Self-Normalized Sums for SymmetricSummands

Sharp moment inequalities are obtained for a class of analytic functions of self-normalizedsums of independent symmetrically distributed random variables.

(Invited) Investigating New Avenues for the Bulk Single Crystal Growth of BN

Boron nitride (BN) is a fascinating ultra-wide bandgap semiconductor offering extreme material properties that can be leveraged in a range of potential applications including (opto-)electronic and quantum devices. Availability of high-quality, large-area and volume, single-crystal material would provide a significant boon to the community facilitating or enabling development of devices. BN has been successfully grown using high pressure, high temperature presses and precipitation from a solvent on the order of a few millimeters. While these methods have yielded high-quality material, scaling of these approaches is challenging motivating the search for additional bulk synthesis methods. This talk will present foundational work being performed in the pursuit of bulk BN growth using two industrial scalable methods: the ammonothermal method and a flux-based approach.The ammonothermal method utilizes supercritical ammonia at temperatures and pressures around 400—600 °C and 100—250 MPa, respectively. One or more mineralizers are added to the solution to enhance the solubility of BN. This talk will demonstrate temperature-dependent solubility of BN in basic ammonothermal solutions containing alkali [1] and/or alkaline earth metals. Initial crystal growth experiments were performed using sodium as the mineralizer yielding the spontaneous nucleation and growth of sub-mm sized hexagonal and rhombohedral BN.The flux-based method uses a solvent exhibiting exceptionally high solubility of nitrogen and boron. A dedicated growth system has been developed and initial growth runs have demonstrated the solubility and growth of BN from solution. Preliminary growth campaigns have successfully demonstrated the growth of ~ >0.1 mm sized BN crystals after 1-2 days.This work has been supported by NSF DMR 1832824, NSF CAREER 2046468, ARL DEVCOM UWBG RF Electronics Center, and Lehigh Startup Funds.[1] Dooley, J., Stoddard, N., Landskron, K. & Pimputkar, S. On the solubility of boron nitride in supercritical ammonia-sodium solutions. J. Cryst. Growth 621, 127381 (2023). doi: 10.1016/j.jcrysgro.2023.127381

Swift Observations of Mrk 421 in Selected Epochs. IV. Physical Implications of X-Ray Flaring Activity and Features of Relativistic Magnetic Reconnection in 2018 April–2023 December

We present the spectral and timing results obtained during the intense observations of Mrk 421 by the Swift-based ultraviolet to X-ray instruments during 2018 April–2023 December. The source showed various strengths of X-ray flaring activity, exceeding a level of 3.5 × 10−9 erg cm−2 s−1 during the strongest 0.3–10 keV flares. Our study identifies a number of intraday brightness variability, including 61 instances that occurred within 1 ks exposures that are consistent with the shock-in-jet scenario and accompanied by significant, fast spectral changes. The source exhibited extreme spectral properties with dominance of the log-parabolic distributions of photons with energy and the frequent occurrence of hard photon indices in the 0.3–10 keV and 0.3–300 GeV bands, with the peak of synchrotron spectral energy distribution E p detected at the energies beyond 29 keV for the first time. The source showed very fast transitions of log-parabolic-to-power-law spectra, most plausibly caused by turbulence-driven relativistic magnetic reconnection. Our spectral results also demonstrate the importance of the first-order Fermi mechanism within the magnetic field of different confinement efficiencies, stochastic acceleration, transitions in the turbulence spectrum, and hadronic cascades. The X-ray, UV, and γ-ray fluxes showed a lognormal variability, which hints at the imprint of accretion disk instabilities on the blazar jet, as well as the possible presence of hadronic cascades. The UV and γ-ray variabilities demonstrated weak correlations with the X-ray flaring activity, which is not consistent with simple synchrotron self-Compton models and requires more complex particle acceleration and emission scenarios.

Three-state p-SOS models on binary Cayley trees

Abstract We consider a version of the solid-on-solid model on the Cayley tree of order two in which vertices carry spins of value 0 , 1 or 2 and the pairwise interaction of neighboring vertices is given by their spin difference to the power p > 0. We exhibit all translation-invariant splitting Gibbs measures (TISGMs) of the model and demonstrate the existence of up to seven such measures, depending on the parameters. We further establish general conditions for extremality and non-extremality of TISGMs in the set of all Gibbs measures and use them to examine selected TISGMs for a small and a large p. Notably, our analysis reveals that extremality properties are similar for large p compared to the case p = 1, a case that has been explored already in previous work. However, for the small p, certain measures that were consistently non-extremal for p = 1 do exhibit transitions between extremality and non-extremality.

On the role of embeddability in conformal pseudo-hermitian geometry

Abstract In this article, we review some recent results about the role of embeddability in conformal CR (Cauchy-Riemann) geometry. We will show how this condition enters in the second variation of the pseudo-hermitian counterpart of the Einstein-Hilbert action, in the positivity of the pseudohermitian mass and in the extremality properties of the CR (Cauchy-Riemann) Yamabe quotient. Given also some explicit examples at hand, this aspect shows sharp differences compared to the Riemannian case.

Reconstruction of a granite structure composed of multiple irregular minerals

Accurately reconstructing rock structures using numerical methods is vital in rock mechanics research community, especially when obtaining rock samples is difficult and expensive. The reconstructed models must reflect the comprehensive characteristics of natural rock, including mineral content and spatial distributions. This study employs the bubbling method to reconstruct granite containing multiple minerals in both two- (2D) and three-dimensions (3D), proposing a general procedure for granite structure reconstruction. The bubbling method utilizes numerous bubbles (hemispheres or spheres) of varying sizes and gradually changing properties, which are randomly overlapped to create a heterogeneous plane (2D) or space (3D). The properties of these overlapped areas are adjusted based on the sum of neighboring bubbles' properties, allowing specific regions with extreme properties to be selected and intercepted to form the desired mineral shapes. The results demonstrate that the reproduced granite samples can accurately exhibit the mineral distributions and sizes of real granite, quantified by fractal dimension (D) and the hourglass parameter (). The proposed method is also suitable for reconstructing anisotropic granite models, with anisotropy described by a fitted elliptic curve derived from ratios between directional mineral sizes and cross-sectional dimensions. Based on these findings, a series of numerical granite models with similar structures were reconstructed and tested. Results indicate that different mineral distributions significantly impact the macroscopic mechanical behaviors, but variability in numerical simulation results decreases with increasing specimen size. The compressive and tensile strength values of the reconstructed numerical models show less variation than those of natural granite specimens. This suggests that, beyond mineral distribution, other factors such as internal defects within natural granite contribute to the observed discrepancies. Additionally, the bubbling method shows great potential for modeling porous structures and offers high computational efficiency.

Information–Theoretic Analysis of Visibility Graph Properties of Extremes in Time Series Generated by a Nonlinear Langevin Equation

In this study, we examined how the nonlinearity α of the Langevin equation influences the behavior of extremes in a generated time series. The extremes, defined according to run theory, result in two types of series, run lengths and surplus magnitudes, whose complex structure was investigated using the visibility graph (VG) method. For both types of series, the information measures of the Shannon entropy measure and Fisher Information Measure were utilized for illustrating the influence of the nonlinearity α on the distribution of the degree, which is the main topological parameter describing the graph constructed by the VG method. The main finding of our study was that the Shannon entropy of the degree of the run lengths and the surplus magnitudes of the extremes is mostly influenced by the nonlinearity, which decreases with with an increase in α. This result suggests that the run lengths and surplus magnitudes of extremes are characterized by a sort of order that increases with increases in nonlinearity.

Lubrication and antibacterial performance and mechanism of functionalized ionic liquids in glycerol media with different water contents

Glycerol lubricants face limitations in industrial applications due to their inadequate antimicrobial properties. In this study, a functionalized long-chain quaternary ammonium salt ionic liquid, BTA-16-BTA, was synthesized. The antimicrobial and tribological properties of BTA-16-BTA as a lubricant additive in glycerol media with different water contents were investigated. The results show that the antimicrobial performance of the glycerol medium is positively correlated with the amount of BTA-16-BTA added. At the optimal concentration of 1.5 % BTA-16-BTA dispersion, excellent friction-reducing, anti-wear, and extreme pressure properties were observed. The friction-reducing and anti-wear effects were further enhanced when 1 % water was added to the system. The liquid medium containing BTA-16-BTA can inhibit the growth of Escherichia coli, indicating that BTA-16-BTA possesses antimicrobial properties.

Introducing a new model for solid-state batteries: Parameter estimation and sensitivity analysis on diffusion, concentration, and electrochemical kinetics

Despite their potential, solid-state batteries (SSBs) are challenging to optimize due to the complexity of their materials and the early stage of their modeling, especially compared to liquid-electrolyte technologies. Many existing models rely on empirical equations that cannot represent internal mass-transport and kinetic phenomena. Even studies based on mechanistic models often focus on theoretical explanations of experimental phenomena or generating hard-to-obtain experimental data. In this work, a simple yet versatile mechanistic model – able to simulate any battery composed of a metallic anode, solid electrolyte and intercalation cathode – is proposed and used in a parameter estimation routine to identify the material properties of a Li/LiPON/LiCoO2 battery. After validation, a parametric study is made to address how each material property impacts concentration profiles, discharge curves, overpotentials, and core key-performance indexes (KPIs) related to energy efficiency and battery capacity. Findings reveal that cathode diffusion is critical to enhancing Extraction Efficiency, in some cases reaching 98.9% of the theoretical capacity without enhancing any other parameter. In the case of Energy Efficiency being a priority over capacity, electrolyte diffusion and concentration showed a pivotal role, in the range of parameters studied, to increase Voltaic Efficiency up to 97.8%. Despite not directly affecting the Extraction Efficiency, it is discussed how high overpotentials caused by Electrolyte Concentration and Kinetic Constants still can harm battery capacity, for charge–discharge cycles limited by boundaries in electrical potential. Finally, studies simultaneously varying two or more parameters show that, despite extreme property enhancements (up to ca 500x higher than the standard case) indeed lead to exceptional results (up to 96.4% for Voltaic Efficiency and 98.9% for Extraction Efficiency), to use such materials at its full potential will result in other zones of the device usually neglected – such as the overpotentials from the metal anode or even the current collector – may become the new stumbling block, underscoring the significance of considering the battery as a holistic system that will inherently exhibit bottlenecks. This also implies, however, in the perpetual potential for enhancement across its components.