Physical Mechanisms Research Articles

Physical mechanisms of femtosecond laser induced refractive index change in direct-written mid-infrared fiber Bragg gratings

Physical mechanisms of femtosecond laser induced refractive index change in direct-written mid-infrared fiber Bragg gratings

Drainage estimation across mountainous regions from large-scale soil moisture observations

Drainage is a crucial soil hydrological process that governs the partitioning of rainfall into runoff, groundwater recharge, soil water storage and evapotranspiration. Despite its significance, the drainage process is poorly understood due to the difficulty in direct measurements and insufficient understanding of its underlying physical mechanisms. To address these challenges, we present an innovative, physically-based, data-driven approach, SM2D (Soil Moisture to Drainage), to estimate drainage. SM2D was applied and examined using soil moisture data from a large-scale observation network over mountainous areas during 2014–2020. The soil moisture threshold governing drainage initiation proves to be significantly lower than the commonly employed field capacity metric in hydrological models. This threshold is influenced by factors such as mean soil moisture, bulk density, residual soil moisture, soil organic carbon, and parameters n and α of soil retention curve. Notably, field capacity has minimal impact on this threshold. Additionally, our analysis reveals that the drainage process is more influenced by the Soil Water Storage Increment (SWSI) than by mean soil moisture (MSM) that has traditionally been recognized as a key factor in drainage control. In comparison to commonly used exponential equations and those in models such as the Soil & Water Assessment Tool (SWAT), SM2D demonstrates superior performance in estimating drainage. The exponential equation derived from the SWSI outperforms those derived from other soil moisture metrics, including the commonly utilized MSM, challenging prevailing norms in drainage equations. SM2D holds the potential to generate extensive drainage datasets from satellite or large-scale soil moisture observations, advancing large-scale hydrological studies.

Influence of magnetic interaction on four-peak GMI profile in FINEMET/Fe35Ni65 composite ribbons

The study of magnetic interactions is crucial in understanding magnetic materials, where both exchange coupling and dipole interactions significantly affect the magnetic properties of composite materials. Separating and utilizing these two types of interactions have consistently been a research focus. In this study, FINEMET/Fe35Ni65 composite ribbons with varying coating thicknesses were fabricated using magnetron sputtering. Notably, obvious four-peak giant magnetoimpedance profiles can be observed as the Fe35Ni65 film thickness varied from 10 to 50 nm. Additionally, the manifestation of the four-peak profile was attributed to the variation in the magnetic properties in the FINEMET ribbon induced by exchange coupling and dipole interaction. This analysis is crucial for advancing our understanding of the underlying physical mechanisms of magnetic interactions in composite ribbons.

Ultralow magnetic susceptibility in pure and Fe(Bi)-doped Au-Pt alloys improved by structural strain regulation

Designing and manufacturing multi-component alloy samples with ultralow magnetic susceptibilityχ(<10-6cm3mol-1) is crucial for producing high-quality test masses to successfully detect gravitational wave in the LISA and TianQin projects. Previous research has idenfified AuPt alloys as a potential candidate for test masses, capable of achieving ultralow magnetic susceptibility that meets the requirements from both theoretical and experimental perspectives. In this study, we discover that the structural strain regulation (i.e. tensile and stress) can effectively optimize and further reduce the ultralow magnetic susceptibility of AuPt allpys, while fully understanding their underlying physical mechanisms. More importantly, even when doped with trace elements such as Fe or Bi impurity, strain regulation can still effectively reduce the magnetic susceptibility of the doped AuPt alloy to the desired range. Our theoretical calculations also reveal that, when the strain ratioηis controlled within in a relatively small range (<2.0%), the regulaton effect on the ultralow magnetic susceptibilities of pure or doped-AuPt alloys remains significant. This property is beneficial for achieving ultralow or even near-zero magnetic susceptibility in real AuPt alloy samples.

Adsorption behavior and quantum chemical analysis of surface functionalized polystyrene nano-plastics on gatifloxacin.

In this paper, the adsorption of gatifloxacin (GAT) by three types of polystyrene nano-plastics (PSNPs), including 400 nm polystyrene (PS), amino-modified PS (PS-NH2), and carboxyl-modified PS (PS-COOH) was studied and the adsorption mechanism were assessed. Experimental findings revealed that the equilibrium adsorption capacity of PSNPs to GAT followed the order PS-NH2 > PS-COOH > PS. The adsorption was regulated by both physical and chemical mechanisms, with intra-particle and external diffusion jointly controlling the adsorption rate. The adsorption process was heterogeneous, spontaneous, and entropy-driven. Sodium chloride (NaCl), alginic acid, copper ions (Cu2+), and zinc ions (Zn2+) inhibited adsorption, with Cu2+ and Zn2+ having the strongest effect on PS-NH2. Theoretical computations indicated that π-π and electrostatic interactions dominated PS adsorption of GAT, while PS-COOH and PS-NH2 adsorbed GAT through electrostatic interactions, hydrogen bonds, and van der Waals (vdW) forces. The surface electrostatic potential of PS-COOH and PS-NH2 was considerably higher than that of PS, with the maximum vdW penetration distance of GAT-PS-NH2 being 1.20 Å. This study's findings provide a theoretical foundation for the migration and synergistic removal of antibiotics, micro-plastics (MPs), and nano-plastics (NPs).

The Feedback of Ocean Cold Wakes on Three Successive Northward-Moving Tropical Cyclones in 2022

Abstract In 2022, three tropical cyclones (TCs) successively moved northward in the Northwest Pacific. Both the preceding and subsequent TCs can cause obvious sea surface temperature cooling (SSTC), which may last from a few days to a month. In this study, an uncoupled atmosphere-only model and a coupled ocean-atmosphere model were employed to investigate the effects of the SSTC caused by the preceding TCs on the track and intensity of the subsequent TCs. The results indicated that in the atmosphere-only simulations, the subsequent TC had a northeast shift in the track and a reduced intensity. The ocean-atmosphere coupled simulations showed similar TC track adjustments, but different TC intensity change results. The analysis suggested that the deviation of the TC track is the combined effect of the changes in the steering flow, beta drift, and diabatic heating. For the change of TC intensity, not only the SSTC but also the thickness of the oceanic mixed layer needs to be considered. The related physical mechanisms are analyzed in this paper.

Linear magnetoresistance from glassy orders

Several strongly correlated metals display B-linear magnetoresistance (LMR) with a universal slope, in sharp contrast to the [Formula: see text] scaling predicted by Fermi liquid theory. We provide a unifying explanation of the origin of LMR by focusing on a common feature in their phase diagrams-proximity to symmetry-breaking orders. Specifically, we demonstrate via two microscopic models that LMR with a universal slope arises ubiquitously near ordered phases, provided the order parameter either i) has a finite wave-vector, or ii) has nodes on the Fermi surface. We elucidate the distinct physical mechanisms at play in these two scenarios and derive upper and lower bounds on the field range for which LMR is observed. Finally, we discuss possible extensions of our picture to strange metal physics at higher temperatures and argue that our theory provides an understanding of recent experimental results on thin film cuprates and moiré materials.

Different Effects of a Super Storm on Atmospheric Electric Fields at Different Latitudes

Geomagnetic storms have a significant impact on Earth’s magnetosphere and ionosphere, as well as on the global atmospheric circuit. This study focuses on investigating the anomalous variations in the vertical atmospheric electric field at eight mid-latitude and low-latitude stations during a mega-geomagnetic storm on 24 April 2023. The majority of stations observed vertical atmospheric electric field increases, while only three nearby stations exhibited vertical atmospheric electric field decreases. The analysis revealed that vertical atmospheric electric field changes ranged from 19 to 370 V/m, and the time differences between extreme vertical atmospheric electric field values and the minimum Dst value ranged from 0 to 5.3 h. Other response patterns to this super magnetic storm at different latitudes are summarized, and the physical mechanisms of different effects of magnetic storms on the electric fields of stations at different latitudes are also discussed.

Third-order nonlinear optical properties of metal oxide nanoparticles and nanocomposites: A review

This paper reviews the vibrant field of nonlinear optical (NLO) properties of metal oxide nanoparticles and nanocomposites. It includes a historic introduction which discusses the birth and successive developments of NLO. An attempt is made to give a summary in a nutshell about the basic concepts of nonlinear optics and different NLO phenomena with special attention to third-order phenomenon and [Formula: see text]-scan technique. The review also touches on the topic of science and technology of metal oxide nanoparticles and nanocomposites, various synthesis processes that include co-precipitation, micro-emulsion, sol–gel route, etc. have been discussed. Metal oxide nanoparticles and nanocomposites are introduced with a deep focus on the origin of various physical mechanisms and optical properties. The origin of NLO properties from these important structures has also been discussed. Some recently studied metal oxide nanocomposites along with their NLO coefficients are also given.

Vertical Carbon Export During a Phytoplankton Bloom in the Chukchi Sea: Physical Setting and Frontal Subduction

AbstractIn order to quantify pelagic‐benthic coupling on high‐latitude shelves, it is imperative to identify the different physical mechanisms by which phytoplankton are exported to the sediments. In June–July 2023, a field program documented the evolution of an under‐ice phytoplankton bloom on the northeast Chukchi shelf. Here, we use in situ data from the cruise, a simple numerical model, historical water column data, and ocean reanalysis fields to characterize the physical setting and describe the dynamically driven vertical export of chlorophyll associated with the bloom. A water mass front separating cold, high‐nutrient winter water in the north and warmer summer waters to the south—roughly coincident with the ice edge—supported a baroclinic jet which is part of the Central Channel flow branch that veers eastward toward Barrow Canyon. A plume of high chlorophyll fluorescence extending from the near‐surface bloom in the winter water downwards along the front was measured throughout the cruise. Using a passive tracer to represent phytoplankton in the model, it was demonstrated that the plume is the result of subduction due to baroclinic instability of the frontal jet. This process, in concert with the gravitational sinking, pumps the chlorophyll downwards an order of magnitude faster than gravitational sinking alone. Particle tracking using the ocean reanalysis fields reveals that a substantial portion of the chlorophyll away from the front is advected off of the northeast Chukchi shelf before reaching the bottom. This highlights the importance of the frontal subduction process for delivering carbon to the sea floor.

Biochemical and cytological studies of Typha domingensis used for bioethanol production

AbstractTypha domingensis (cattails) is an emergent invasive aquatic macrophyte; it belongs to Typhaceae family inhabiting multiple Egyptian water bodies like rivers, lakes, and wetlands. Due to the scarcity of food, the depletion of fossil fuels, population growth, and increased industrial development, sustainable renewable bioenergy production has gained a lot of attention lately. Typha is an excellent lignocellulosic biomass for biofuel production because it does not compete with food but rather endangers aquatic life and prevents water from flowing through drainage channels and canals, which rises evapotranspiration. Although it is beneficial in phytoremediation, its removal is a necessity due to previous reasons. Chemical pretreatment has been widely used to degrade complex chains of lignocellulosic materials. Enzymatic hydrolysis is used to enhance fermentable sugars production from cellulose. Fermentation process has been conducted by yeast for centuries. Saccharomyces cerevisiae tolerance to ethanol can be increased by mutation; it is induced either chemically, physically, or biologically. Geneticists frequently utilize gamma radiation, one of the physical mutagenesis mechanisms, to change the DNA of microorganisms. Scanning electron microscope (SEM) is concerned with examination and analysis of microstructure morphology and chemical composition. Changes in internal organelles of Saccharomyces cerevisiae after mutation has been tracked using transmission electron microscope (TEM) in order to distinguish between native and mutant yeast and to examine their ultrastructural changes.

Key feature identification of internal kink mode using machine learning

The internal kink mode is one of the crucial factors affecting the stability of magnetically confined fusion devices. This paper explores the key features influencing the growth rate of internal kink modes using machine learning techniques such as Random Forest, Extreme Gradient Boosting (XGboost), Permutation, and SHapley Additive exPlanations (SHAP). We conduct an in-depth analysis of the significant physical mechanisms by which these key features impact the growth rate of internal kink modes. Numerical simulation data were used to train high-precision machine learning models, namely Random Forest and XGBoost, which achieved coefficients of determination values of 95.07% and 94.57%, respectively, demonstrating their capability to accurately predict the growth rate of internal kink modes. Based on these models, key feature analysis was systematically performed with Permutation and SHAP methods. The results indicate that resistance, pressure at the magnetic axis, viscosity, and plasma rotation are the primary features influencing the growth rate of internal kink modes. Specifically, resistance affects the evolution of internal kink modes by altering current distribution and magnetic field structure; pressure at the magnetic axis impacts the driving force of internal kink modes through the pressure gradient directly related to plasma stability; viscosity modifies the dynamic behavior of internal kink modes by regulating plasma flow; and plasma rotation introduces additional shear forces, affecting the stability and growth rate of internal kink modes. This paper describes the mechanisms by which these four key features influence the growth rate of internal kink modes, providing essential theoretical insights into the behavior of internal kink modes in magnetically confined fusion devices.

On the Inverse Correlation Between the Thermosphere Winter Helium Bulge and Solar Activity: Impact of Gravity Wave Drag From the Mesosphere

AbstractUnderstanding the temporal and spatial variations in the ideal inert tracer helium can provide insight into the dynamic evolution of the thermosphere. The magnitude of the thermospheric winter helium bulge was inversely correlated with the level of solar activity. However, this feature has been found to be not reproduced by the Thermosphere‐Ionosphere Electrodynamic General Circulation Model (TIEGCM), and the associated physical mechanisms remain unknown. Using the Thermosphere‐Ionosphere‐Mesosphere Electrodynamic General Circulation Model (TIME‐GCM), we found that mesospheric gravity wave drag (GWD) is a factor contributing to this inverse correlation. Specifically, the summer‐to‐winter circulation in thermosphere becomes the main cause of the helium bulge, as mesospheric GWD can play a role in strengthening this circulation. The GWD contributions to temperature change below the lower thermosphere do not depend prominently on solar activity. However, because the temperature impacts on the pressure gradient force are height‐integrated according to the background temperature of the neutral gas, the higher background temperature in the thermosphere at the solar maximum corresponds to a relatively weaker response in pressure gradient force in the thermosphere. Therefore, the response of the thermospheric circulation that might be expected to accompany increasing solar activity is suppressed due to the influence of mesospheric GWD, which results in a decrease in the magnitude of the winter helium bulge with increasing solar activity. Thus, our results demonstrated that lower atmosphere forcing can play a significant role in the response of thermospheric helium to solar activity.

Bacterial community dynamics as a result of growth-yield trade-off and multispecies metabolic interactions toward understanding the gut biofilm niche

Bacterial communities are ubiquitous, found in natural ecosystems, such as soil, and within living organisms, like the human microbiome. The dynamics of these communities in diverse environments depend on factors such as spatial features of the microbial niche, biochemical kinetics, and interactions among bacteria. Moreover, in many systems, bacterial communities are influenced by multiple physical mechanisms, such as mass transport and detachment forces. One example is gut mucosal communities, where dense, closely packed communities develop under the concurrent influence of nutrient transport from the lumen and fluid-mediated detachment of bacteria. In this study, we model a mucosal niche through a coupled agent-based and finite-volume modeling approach. This methodology enables us to model bacterial interactions affected by nutrient release from various sources while adjusting individual bacterial kinetics. We explored how the dispersion and abundance of bacteria are influenced by biochemical kinetics in different types of metabolic interactions, with a particular focus on the trade-off between growth rate and yield. Our findings demonstrate that in competitive scenarios, higher growth rates result in a larger share of the niche space. In contrast, growth yield plays a critical role in neutralism, commensalism, and mutualism interactions. When bacteria are introduced sequentially, they cause distinct spatiotemporal effects, such as deeper niche colonization in commensalism and mutualism scenarios driven by species intermixing effects, which are enhanced by high growth yields. Moreover, sub-ecosystem interactions dictate the dynamics of three-species communities, sometimes yielding unexpected outcomes. Competitive, fast-growing bacteria demonstrate robust colonization abilities, yet they face challenges in displacing established mutualistic systems. Bacteria that develop a cooperative relationship with existing species typically obtain niche residence, regardless of their growth rates, although higher growth yields significantly enhance their abundance. Our results underscore the importance of bacterial niche dynamics in shaping community properties and succession, highlighting a new approach to manipulating microbial systems.

Collective buoyancy-driven dynamics in swarming enzymatic nanomotors

Enzymatic nanomotors harvest kinetic energy through the catalysis of chemical fuels. When a drop containing nanomotors is placed in a fuel-rich environment, they assemble into ordered groups and exhibit intriguing collective behaviour akin to the bioconvection of aerobic microorganismal suspensions. This collective behaviour presents numerous advantages compared to individual nanomotors, including expanded coverage and prolonged propulsion duration. However, the physical mechanisms underlying the collective motion have yet to be fully elucidated. Our study investigates the formation of enzymatic swarms using experimental analysis and computational modelling. We show that the directional movement of enzymatic nanomotor swarms is due to their solutal buoyancy. We investigate various factors that impact the movement of nanomotor swarms, such as particle concentration, fuel concentration, fuel viscosity, and vertical confinement. We examine the effects of these factors on swarm self-organization to gain a deeper understanding. In addition, the urease catalysis reaction produces ammonia and carbon dioxide, accelerating the directional movement of active swarms in urea compared with passive ones in the same conditions. The numerical analysis agrees with the experimental findings. Our findings are crucial for the potential biomedical applications of enzymatic nanomotor swarms, ranging from enhanced diffusion in bio-fluids and targeted delivery to cancer therapy.

Assessment of a Tropical Transition over the Southwestern South Atlantic Ocean: The Case of Cyclone Akará

Tropical cyclones are rare in the South Atlantic Ocean. Hurricane Catarina (2004), developed from a tropical transition, was the first documented case, followed by Iba (2019), which had a purely tropical genesis. In February 2024, the southeastern South Atlantic recorded its third tropical cyclone, Akará, initially a subtropical system. Due to the specific conditions required for tropical cyclones to develop in this ocean basin, the main purpose of this study is to describe the physical mechanisms that triggered the genesis of Akará’s precursor and its tropical transition. Data from various sources and methodologies, including the cyclone phase space diagram, are used in this study. Results show that the passage of a cold front created an environment with horizontal wind shear, contributing to most of the cyclonic relative vorticity in the genesis region. This was the primary driver of cyclogenesis at 1200 UTC on 15 February, along with other secondary processes. The tropical transition occurred as the vertical shear weakened, and turbulent heat fluxes from the ocean to the atmosphere increased, enhancing diabatic processes that warmed the atmosphere. This led to the tropical transition at 0600 UTC on 17 February.

Review of Yu–Shiba–Rusinov bound state in quantum impurity structures: basic principle and current progress

Abstract Magnetic impurities connected to superconductors reservoir result in bound states within the superconducting gap, so called Yu–Shiba–Rusinov (YSR) state. In the past few years, this field has gained much attention since it is crucial for engineering novel superconducting many-body states, with the perspective of manufacturing Majorana Fermions. The underlying physical picture of YSR state depends closely on the form of the impurities connected to the leads, the manner in which the impurities are organized, and also the diverse local interactions, which is always disclosed with the aid of quantum impurity models. This article provides a comprehensive overview of the progress achieved by previous studies, focusing on the issues demonstrated by quantum impurity structures. The physical mechanisms and the related phenomena assisted by different interactions are discussed in detail. Furthermore, a comprehensive overview of recent experimental achievements is presented, using various metal phthalocyanine molecules as illustrative examples, thereby establishing a robust foundation for future inquiries in this domain.

Centennial‐Scale Variability of the Atlantic Meridional Overturning Circulation in CMIP6 Models Shaped by Arctic–North Atlantic Interactions and Sea Ice Biases

AbstractClimate variability on centennial timescales has often been linked to internal variability of the Atlantic Meridional Overturning Circulation (AMOC). However, due to the scarceness of suitable paleoclimate proxies and long climate model simulations, large uncertainties remain on the magnitude and physical mechanisms driving centennial‐scale AMOC variability. For these reasons, we perform a systematic multi‐model comparison of centennial‐scale AMOC variability in pre‐industrial control simulations of state‐of‐the‐art global climate models. Six out of nine models in this study exhibit a statistically significant mode of centennial‐scale AMOC variability. Our results show that freshwater exchanges between the Arctic Ocean and the North Atlantic provide a plausible driving mechanism in a subset of models, and that AMOC variability can be amplified by ocean–sea ice feedbacks in the Labrador Sea. The amplifying mechanism is linked to sea ice cover biases, which could provide an observational constraint for centennial‐scale AMOC variability.

Nonequilibrium steady state full counting statistics in the noncrossing approximation.

Quantum transport is often characterized not just by mean observables like the particle or energy current but by their fluctuations and higher moments, which can act as detailed probes of the physical mechanisms at play. However, relatively few theoretical methods are able to access the full counting statistics (FCS) of transport processes through electronic junctions in strongly correlated regimes. While most experiments are concerned with steady state properties, most accurate theoretical methods rely on computationally expensive propagation from a tractable initial state. Here, we propose a simple approach for computing the FCS through a junction directly at the steady state, utilizing the propagator noncrossing approximation. Compared to time propagation, our method offers reduced computational cost at the same level of approximation, but the idea can also be used within other approximations or as a basis for numerically exact techniques. We demonstrate the method's capabilities by investigating the impact of lead dimensionality on electronic transport in the nonequilibrium Anderson impurity model at the onset of Kondo physics. Our results reveal a distinct signature of one dimensional leads in the noise and Fano factor not present for other dimensionalities, showing the potential of FCS measurements as a probe of the environment surrounding a quantum dot.

Extended Spectrum β-Lactamase: Tackling Antibiotic Resistance and Overcoming Treatment Challenges

Antibiotics, also known as antibacterials, kill or inhibit bacterial growth but are ineffective against viruses, fungi, or parasites, often leading to misuse. They are categorized by molecular structure, mode of action, and spectrum of activity. Antimicrobial Resistance (AMR) occurs when pathogens no longer respond to antimicrobial drugs, arising naturally or through acquisition. Resistance mechanisms include enzymatic (most common), genetic and physical. Bacteria produce various β-lactamases, such as Extended Spectrum β-lactamases (ESBLs), AmpC enzymes, and carbapenemase to exert resistance to Beta-Lactam (βL) class of antibiotics. ESBL families include TEM, SHV, and CTX-M, with E. coli being the most prevalent host. Any Gram-Negative Bacteria (GNB) can be an ESBL producer, but most common ones are the Enterobacteriaceae including Escherichia coli, Klebsiella pneumoniae, Klebsiella oxytoca and Proteus mirabilis. ESBL-producing Enterobacteriaceae (ESBL-E) resist penicillin, aztreonam, and cephalosporins except cephamycins and carbapenems, posing a significant public health risk. Genetic resistance mechanisms involve random mutations and horizontal gene transfer through either of the following processes namely conjugation, transformation, transduction. Physical mechanisms include efflux pump production and decreased porin channels. In some microbiological laboratories, ESBL production are often not determined, rather resistance based on MIC values to third generation Cephalosporins are considered as resistance due to ESBL production. Antibiotic use in agriculture and medicine has increased Multi-drug resistant (MDR) ESBL-producing E. coli and evidenced in retail meat and among meat shop employees. Community-acquired ESBL-E infections are a growing concern, with hospital transmission primarily occurring among patients sharing rooms with ESBL carriers. Empirical and definitive therapies for ESBL-E infections must be adjusted based on Antibiotic Susceptibility Testing (AST). The MERINO trial identified urinary tract infections as the most common source of ESBL-E bacteremia, with E. coli being predominant. For critically ill patients with non-urinary tract infections, Meropenem or Imipenem-cilastatin are recommended. For uncomplicated UTIs, Nitrofurantoin, Cotrimoxazole, and Piperacillin-Tazobactam (Pip-Taz) are effective, while Cotrimoxazole, Fluoroquinolones, and Ceftolozane-tazobactam are suitable for complicated UTIs. New β-lactamase inhibitors like avibactam, vaborbactam, and relebactam are promising for treatment. Misuse of antibiotics, such as inappropriate dosing and duration, contributes to AMR, a growing global challenge. Deaths from AMR, estimated at 1.27 million in 2019, could reach 10 million by 2050. ESBLs drive the use of broad-spectrum antibiotics, accelerating resistance development. Inadequate therapy exacerbates infections, leading to prolonged hospital stays, complications, and increased mortality. Balancing new drug development with resistance emergence is crucial to combat AMR.