Local Hot Spots Research Articles

Symmetry Breaking in Inorganic Nanostructures: Chirality vs. Optical Activity or Structural vs. Electronic Effects

AbstractThis essay presents the viewpoint of the author on the topic of chirality and optical activity in nanostructures. It particularly focuses on the interaction of chiral molecules with plasmonic and excitonic nanocrystals and on induction of circular dichroism in such achiral nanocrystals. It discusses recent developments in the shape symmetry breaking of achiral metal nanostructures using photochemical processes induced by asymmetric localized plasmonic hot spots excited through circularly polarized light illumination. Finally, it addresses symmetry breaking in intrinsically chiral inorganic nanocrystals using chiral ligands during their formation, leading to 100 % enantiomeric excess in the nanocrystals of TbPO4⋅H2O. These nanocrystals exhibit an interesting nucleation mechanism, which leads to very high chiral amplification (secondary nucleation).

Surging compound drought–heatwaves underrated in global soils

Compound drought-heatwaves (CDHWs) accelerate the warming and drying of soils, triggering soil compound drought-heatwaves (SCDHWs) that jeopardize the health of soil ecosystems. Nevertheless, the behavior of these events worldwide and their responses to climatic warming are underexplored. Here, we show a global escalation in the frequency, duration, peak intensity, and severity of SCDHWs, as well as an increase in affected land area, from 1980 to 2023. The increasing trends, which are particularly prominent since the early 2000 s, and projected to persist throughout this century, are dominated by summertime SCDHWs and enhanced by El Niño. Intensive soil warming as well as climatologically lower soil temperatures compared to air temperatures lead to localized hotspots of escalating SCDHW severity in northern high latitudes, while prolonged duration causes such hotspots in northern South America. Transformation of natural ecosystems, particularly forests and wetlands, to cropland as well as forest degradation substantially enhance the strength of SCDHWs. Global SCDHWs consistently exhibit higher frequencies, longer durations, greater severities, and faster growth rates than CDHWs in all aspects from 1980 to 2023. They are undergoing a critical transition, with droughts replacing heatwaves as the primary constraint. We emphasize the significant intensification of SCDHWs in northern high latitudes as well as the prolonged duration of SCDHWs in the Southern Hemisphere, posing an underrated threat to achieving carbon neutrality and food security goals.

Spatial Analysis of Chronic Kidney Disease of Unknown Aetiology (CKDu) Prevalence in Badulupura Village, Sri Lanka

This study investigated spatial patterns of chronic kidney disease of unknown aetiology (CKDu) patients in Badulupura village. The analysis utilized published locational data for all households, including households affected by CKDu, and all wells used by CKDu-affected patients (CPA wells). The study employed Average Nearest Neighbour (ANN) and Hot Spot Analysis (Getis-Ord Gi*) tools to assess the spatial clustering of CKDu households and CPA wells. The study also explored the impact of topographical factors such as elevation, slope, and distance to watershed boundaries on the spatial distribution of CKDu patients. The ANN analysis revealed a dispersed pattern for all wells, and a random distribution for all households. However, both CKDu households and CPI wells exhibited a clustered pattern, suggesting a location-specific cause for the spatial distribution of the disease. Additionally, overlaying CKDu-affected households on the digital elevation model revealed a concentration of CKDu hot spots in high-elevation areas, while cold spots were observed in low-elevation regions. Furthermore, the t-test was employed to investigate the significance of elevation, slope, and distance to the watershed boundaries in relation to CKDu distribution. The results indicated a significant (p<0.05) prevalence of CKDu in high-elevation areas, while no significant association was found with slope or distance to watershed boundaries. The study revealed the presence of localized CKDu hot spots and cold spots within a small geographical area, highlighting the importance of considering topographical factors and conducting comprehensive hydrogeological and geological studies to gain valuable insights into the spatial distribution of CKDu.

Environmental impact of an anthropogenic groundwater temperature hotspot

Heat emitted by buildings and other infrastructure accumulates in the subsurface. This additional heat can cause a pronounced shift in thermal boundary conditions of the important groundwater ecosystem. Shallow groundwater systems in Central Europe are often inhabited by communities of fauna adapted to cold and stable conditions as well as microorganisms, whose activity is dependent on ambient temperatures. At a local groundwater temperature hotspot of up to 23 °C, caused by a water park, we assessed the environmental impact of this thermal alteration on the shallow groundwater system. The results show that the overall groundwater quality at the site is influenced by anthropogenic land use, compared to wells in a nearby water protection zone. However, neither hydrochemical nor ecological characteristics of groundwater from wells in the vicinity of the water park indicate any significant dependence on temperature. Hence, we conclude that in this eutrophic and anoxic aquifer moderate heat stress does not lead to significant alterations in terms of hydrochemistry as well as microbiological properties. Due to the overall low oxygen concentrations (<1 mg/l), stygofauna is present only occasionally and cannot be used as bioindicators. These results have to be verified for other aquifer types and would benefit from a more in-depth analysis of microbial community composition.

Methane dynamics in the Baltic Sea: investigating concentration, flux, and isotopic composition patterns using the coupled physical–biogeochemical model BALTSEM-CH4 v1.0

Abstract. Methane (CH4) cycling in the Baltic Sea is studied through model simulations that incorporate the stable isotopes of CH4 (12C–CH4 and 13C–CH4) in a physical–biogeochemical model. A major uncertainty is that spatial and temporal variations in the sediment source are not well known. Furthermore, the coarse spatial resolution prevents the model from resolving shallow-water near-shore areas for which measurements indicate occurrences of considerably higher CH4 concentrations and emissions compared with the open Baltic Sea. A preliminary CH4 budget for the central Baltic Sea (the Baltic Proper) identifies benthic release as the dominant CH4 source, which is largely balanced by oxidation in the water column and to a smaller degree by outgassing. The contributions from river loads and lateral exchange with adjacent areas are of marginal importance. Simulated total CH4 emissions from the Baltic Proper correspond to an average ∼1.5 mmol CH4 m−2 yr−1, which can be compared to a fitted sediment source of ∼18 mmol CH4 m−2 yr−1. A large-scale approach is used in this study, but the parameterizations and parameters presented here could also be implemented in models of near-shore areas where CH4 concentrations and fluxes are typically substantially larger and more variable. Currently, it is not known how important local shallow-water CH4 hotspots are compared with the open water outgassing in the Baltic Sea.

Study on heat and mass transfer behavior of coupled electrochemical reaction in porous structure of proton exchange membrane fuel cell

Proton exchange membrane fuel cell (PEMFC) is widely used in transportation, aviation and energy storage due to its unique advantages. Improving the performance of fuel cells depends largely on effective hydrothermal management. In this work, a multi-physical field coupling model based on the lattice Boltzmann method (LBM) is established to analyze the oxygen transport, liquid water transport, heat transfer and electrochemical reaction, mainly considering the difference between the overpotential of the cell and the surface wettability of the structure. The results show that the overpotential is closely related to the reaction process. The rate of water production is significantly accelerated by increasing the overpotential, and the breakage and merging of water clusters are observed. The increase of overpotential will lead to more energy loss in the form of heat, thus increasing the heat production. Enhancing the hydrophobicity of the structure has a positive effect on the performance of the fuel cell, and the possibility of local hot spots in the low-hydrophobic structure is greater. It is feasible to improve water management and fuel cell performance through wettability design.

Numerical Groundwater Model to Assess the Fate of Nitrates in the Coastal Aquifer of Arborea (Sardinia, Italy)

The Arborea plain in Sardinia (Italy) is classified as a nitrate vulnerable zone (NVZ). In the present study, the individual work steps that are necessary to progress from the existing 3D hydrogeological model to a 3D numerical groundwater model using the interactive finite-element simulation system FEFLOW 7.4 are shown. The results of the transient flow model highlight the influence of the drainage network on the overall groundwater management: the total water volume drained by the ditches accounted for approximately 58% of the annual outflow volume. The numerical transport simulations conducted from 2012 to 2020 using hypothetical field-based nitrate input scenarios globally underestimated the high concentrations that were observed in the NVZ. However, as observed in the field, the computed nitrate concentrations in December 2020 still varied strongly in space, from several mg L−1 to several hundreds of mg L−1. The origin of these remaining local hotspots is not yet known. The modeling of rainfall fluctuations under the influence of climate change revealed a general long-term decline in the groundwater level of several tens of centimeters in the long term and, in conjunction with a zero-nitrate scenario, led to a significant decrease in nitrate pollution. Although hotspots were attenuated, the concentrations at several monitoring wells still exceeded the limit value of 50 mg L−1.

Flow boiling in a rectangular micro/mini channel with self-rewetting and non-rewetting fluids

In this experimental investigation the influence of self-rewetting during flow boiling was studied in a horizontal microchannel during one-sided uniform heating. The channel had a width and height of 6 mm and 0.3 mm respectively. Local wall temperature and direct in-time flow visualisation was performed. The working fluids under consideration included water as base reference, pure 1-butanol, pure ethanol, dilute butanol-water self-rewetting mixtures, and a dilute ethanol-water binary mixture. Tests were conducted at mass fluxes of 10, 15 and 25 kg/m2s, over a range of heat fluxes to produce both single phase and two-phase quasi steady state flow data. Within the wall temperature ranges of interest, the butanol-water mixtures (5 % and 7 % by volume butanol) had surface tension characteristics that would draw liquid toward local wall hotspots. Local and average wall temperatures and heat transfer coefficients were obtained and considered against the governing flow pattern visualisations. In contrast to the other fluids, the self-rewetting butanol-water mixtures exhibited significantly more stable flow and more predictable saturation flow boiling heat transfer coefficient trends across all heat fluxes under consideration. At the lowest mass flux, it was found that an increase in the heat flux resulted in an improvement in the self-rewetting fluids heat transfer performance, while at higher mass fluxes this dependence was diminished. Across all mass fluxes and heat fluxes the 5 % butanol-water outperformed its 7 % butanol-water counterpart. The tendency of self-rewetting to reduce local dry-out, even at low mass fluxes are demonstrated.

Multi‐Scale Simulation of Reverse‐Bias Breakdown in All‐Perovskite Tandem Photovoltaic Modules under Partial Shading Conditions

Herein, a multi‐scale simulation approach to quantify the impact of nonuniformities in cell‐level performance on the photovoltaic characteristics of monolithically interconnected large‐area all‐perovskite tandem modules under partial shading conditions is presented, addressing a crucial aspect of the up‐scaling challenge for this promising photovoltaic technology. To this end, current–voltage characteristics of small‐area all‐perovskite tandem solar cells are obtained for dark and illuminated cases from a calibrated optoelectronic device model using drift–diffusion simulation coupled to a quantum transport formalism for the band‐to‐band tunneling underlying the Zener breakdown. These current–voltage curves are computed for varying density of mobile ions and subsequently used as local 1D coupling laws connecting the 2D electrodes in a quasi‐3D large‐area finite‐element simulation approach that then provides the module characteristics under consideration of spatial variation in active area quality related to mobile ion density. The simulation reveals the appearance of localized current hot spots for the case where the shaded cell is strongly reverse biased.

Thermal deviation mechanisms for coupled heat transfer between the combustion side and the furnace tube side in the tubular heating furnace

Temperature deviation significantly affects the safe operation of tubular heating furnaces. This is attributed to the inevitable temperature difference between the flue gas and the working medium on the tube side. To date, little research has considered the dynamic heat transfer between the furnace body and the tubes in tube furnaces, and even less attention has been paid to the thermal deviation within tube furnaces. To optimize the operational parameters of the heating furnace, a comprehensive heat transfer model is established in this paper to numerically couple the heat transfer between the combustion side and the working medium on the tube side in tube furnaces. A hydrogenation feed heating furnace with a processing capacity of 600,000 tons per year in a chemical enterprise is selected as the subject of study. Using Fluent software, on the basis of coupled simulation, a non-uniformity coefficient of temperature distribution is introduced to characterize the thermal deviation within the furnace. The impact of the thermal load and hydrogen doping in the fuel gas on the thermal deviation within the furnace is analyzed. The numerical results demonstrate that with an increase in thermal load, the flame structure in the furnace gradually becomes concentrated, the average temperature of the flue gas increases, and the outlet temperature of the furnace chamber increases by 19%, with the thermal efficiency decreasing by 5.11%; at the same time, the overall non-uniformity coefficient of the temperature distribution in the furnace fluctuates irregularly, indicating a nonlinear relationship between the thermal load and the thermal deviation within the furnace. With an increase in the hydrogen content in the fuel gas, the flame structure in the furnace becomes more dispersed, the average temperature of the flue gas increases, but the combustion efficiency of the heating furnace exhibits irregular fluctuations; the thermal deviation within the furnace initially increases and then decreases, with a lower non-uniformity coefficient of temperature at 50% hydrogen content, which is 2.48% lower than at 40% hydrogen content. Under both conditions, the thermal deviation primarily leads to localized hot spots in the radiant furnace tubes and uneven temperature distribution in the convection section, with a minimal impact on the thermal efficiency of the heating furnace.

Investigation of heat and mass transfer properties of the wave staggered round table cooling flow field with a three-stage forked distribution zone

Research on proton exchange membrane fuel cells (PEMFC) has mainly focused on the design of gas channels, often neglecting the effects of distribution zones and cooling flow fields (CFF) on the cell. Therefore, a novel bipolar plate (BP) structure of metallic material is proposed in this paper, which adopts a three-stage forked distribution zone and a wave staggered round table cooling flow field (WSRTCFF). This study systematically investigates the effects of WSRTCFF presence or absence, flow direction, velocity, and inlet temperature on heat and mass transfer as well as PEMFC performance. The results show that introducing WSRTCFF significantly improves temperature distribution in the flow field. Compared to hydrogen flow direction, oxygen flow direction not only effectively mitigates local hot spot effects but enhances current density by 12.55 % compared to no cooling. When coolant flow velocity is below 0.1 m/s, increasing velocity promotes system heat dissipation, enhancing working efficiency and cell stability. However, when velocity exceeds 0.1 m/s, the change in the flow velocity has minimal effect on PEMFC performance. Furthermore, comparative analysis of different coolant temperatures indicates that at 333.15 K, maximum temperature remains below 348.2 K, maintaining membrane hydration and achieving a good balance of substances, temperatures, and performance.

Relative abundance of a mesocarnivore in a human-dominated, semi-arid rangeland in Namibia

Mesocarnivores fill important roles in ecological communities globally, but their distribution and abundance are often understudied. Many species have historically been regarded as vermin and subject to lethal control due to their role in livestock predation. Identifying the factors influencing mesocarnivore populations can help disentangle their relationship within ecological communities and inform conflict mitigation and conservation priorities. To help identify these factors, we used camera traps to study the community of medium and large mammals in four communal conservancies of northeastern Namibia covering the wet and dry seasons using 99 and 97 camera trap stations, respectively. We modelled black-backed jackal (Lupulella mesomelas) abundance using the robust Royle-Nichols model. Black-backed jackal were widespread, with a mean per site abundance of 2.01 (SD=0.66) in the wet season and 2.41 (SD=0.49) in the dry season. Black-backed jackal showed seasonally contrasting covariate associations, with lower abundance in areas with medium and large-sized wild prey during the wet season, and higher abundance in areas with more villages and close to African wild dog (Lycaon pictus) dens in the dry season. We identified localized hotspots of black-backed jackal abundance during the dry season, which may indicate that when resources are scarce, black-backed jackals rely on anthropogenic food sources despite an elevated risk for conflict, and on carcass remains from African wild dog kills. These findings highlight potential drivers of mesocarnivore abundance that would be obscured in a conventional occurrence modelling framework, and illustrate how local abundance may be influenced by seasonal variability, wild and anthropogenic food sources, and a likely facilitative relationship with a large carnivore. Further investigations in areas with more complex carnivore guilds and higher density of dominant predators are needed to understand black-backed jackal-African wild dog interactions and impacts on population dynamics.

Transient hypoxia drives soil microbial community dynamics and biogeochemistry during human decomposition.

Human decomposition in terrestrial ecosystems is a dynamic process creating localized hot spots of soil microbial activity. Longer-term (beyond a few months) impacts on decomposer microbial communities are poorly characterized and do not typically connect microbial communities to biogeochemistry, limiting our understanding of decomposer communities and their functions. We performed separate year-long human decomposition trials, one starting in spring, another in winter, integrating bacterial and fungal community structure and abundances with soil physicochemistry and biogeochemistry to identify key drivers of microbial community change. In both trials, soil acidification, elevated microbial respiration, and reduced soil oxygen concentrations occurred. Changes in soil oxygen concentrations were the primary driver of microbial succession and nitrogen transformation patterns, while fungal community diversity and abundance was related to soil pH. Relative abundance of facultative anaerobic taxa (Firmicutes and Saccharomycetes) increased during the period of reduced soil oxygen. The magnitude and timing of the decomposition responses were amplified during the spring trial relative to the winter, even when corrected for thermal inputs (accumulated degree days). Further, soil chemical parameters, microbial community structure, and fungal gene abundances remained altered at the end of 1 year, suggesting longer-term impacts on soil ecosystems beyond the initial pulse of decomposition products.

XCT images-based modeling for elucidating electrochemical inert phase-dependent multiscale electrode kinetic behaviors

The electrochemically inert phase (EIP) within the electrode is formed by the combination of carbon black and binder, characterized by a highly heterogeneous spatial distribution and structural morphology. This heterogeneity impairs electrode performance under varying discharge rates and temperatures. In this study, X-ray computed tomography is employed to image the original electrode. The resulting grayscale images are digitally processed to reveal the two-dimensional (2D) and three-dimensional (3D) features of the EIP morphology, thereby providing a design window to understand the influence of EIP morphology. The physical structure characterization indicates that, compared to bulk-like EIP (B-EIP), film-like EIP (F-EIP) tends to cover the active surface of the active material (AM), exacerbating the heterogeneity of the lithiation reactions within the electrode. The reduction in the AM active surface area correlates the state of lithiation (SOL) of particles with their active specific surface area (αa). At low temperatures, the temperature sensitivity of electrodes intensifies the risk of αa loss, promoting heterogeneous reaction transfer between particles. The Biot number (Bi) is used to evaluate the competing mechanisms between interfacial reactions and bulk diffusion within particles. In electrodes with a high EIP content, the reaction rate at the particle/electrolyte interface is accelerated, causing particle performance to be dominated by interfacial reactions. Finally, the electrochemistry and heat generation from the particle-level to the electrode-level in thicker electrodes are examined. It demonstrates that ion diffusion in the pore controls interfacial reactions and heat transport behavior. Aggregated high-flux reactions and localized hot spots exacerbate the heterogeneous degradation and side reactions within the electrode.

Inherent water in green pine needles and cypress leaves induces self-activation in microwave pyrolysis

The response of water to microwaves creates the possibility of activating green waste for the generation of porous biochar with inherent water. This hypothesis is verified herein through the microwave pyrolysis of green and dried pine needles and cypress leaves at 500 to 800 °C. The results indicate that the inherent water in the green samples induce steam reforming or gasification, thereby forming more gases at the expense of biochar and organics, such as light and heavy phenolics in bio-oil. The intensive gasification induced by the inherent water of green pine needles effectively promotes the pore development of biochar at 800 °C (805.9 versus 360.4 m2/g from the dried sample) and the adsorption of phenol (50.3 versus 34.8 mg/g from the dried sample). A similar result is observed for the pyrolysis of cypress leaves at 800 °C (452.1 m2/g from the green samples versus 110.8 m2/g from the dried samples). A lower temperature (i.e., 500 °C) with insufficient gasification results in no marked difference in pore development. Accelerated gasification with steam leads to the excessive removal of aliphatic organics but also introduces more oxygen in the biochar, making it more hydrophilic with a more fragmented surface. Nevertheless, potential local hot spots, if any, do not lead to the decomposition of inorganics, such as CaCO3, in the pyrolysis of green samples, while the pyrolysis of dried cypress does. The pyrolysis in in-situ infrared shows that 500 °C is required to effectively destruct hydrogen bonds in the green samples and the inherent water promotes the formation of more oxygen-containing functionalities but not aromatization.

Integrated Geospatial and Geostatistical Multi-Criteria Evaluation of Urban Groundwater Quality Using Water Quality Indices

Groundwater contamination poses a severe public health risk in Lahore, Pakistan’s second-largest city, where over-exploited aquifers are the primary municipal and domestic water supply source. This study presents the first comprehensive district-wide assessment of groundwater quality across Lahore using an innovative integrated approach combining geographic information systems (GIS), multi-criteria decision analysis (MCDA), and water quality indexing techniques. The core objectives were to map the spatial distributions of critical pollutants like arsenic, model their impacts on overall potability, and evaluate targeted remediation scenarios. The analytic hierarchy process (AHP) methodology was applied to derive weights for the relative importance of diverse water quality parameters based on expert judgments. Arsenic received the highest priority weight (0.28), followed by total dissolved solids (0.22) and hardness (0.15), reflecting their significance as health hazards. Weighted overlay analysis in GIS delineated localized quality hotspots, unveiling severely degraded areas with very poor index values (&gt;150) in urban industrial zones like Lahore Cantt, Model Town, and parts of Lahore City. This corroborates reports of unregulated industrial effluent discharges contributing to aquifer pollution. Prospective improvement scenarios projected that reducing heavy metals like arsenic by 30% could enhance quality indices by up to 20.71% in critically degraded localities like Shalimar. Simulating advanced multi-barrier water treatment processes showcased an over 95% potential reduction in arsenic levels, indicating the requirement for deploying advanced oxidation and filtration infrastructure aligned with local contaminant profiles. The integrated decision support tool enables the visualization of complex contamination patterns, evaluation of remediation options, and prioritizing risk-mitigation investments based on the spatial distribution of hazard exposures. This framework equips urban planners and utilities with critical insights for developing targeted groundwater quality restoration policies through strategic interventions encompassing treatment facilities, drainage infrastructure improvements, and pollutant discharge regulations. Its replicability across other regions allows for tackling widespread groundwater contamination challenges through robust data synthesis and quantitative scenario modeling capabilities.

A hybrid approach for integrating micro-satellite images and sensors network-based ground measurements using deep learning for high-resolution prediction of fine particulate matter (PM2.5) over an indian city, lucknow

The detrimental impacts of fine particulate matter (PM2.5) on human health, climate, ecosystems, crops, and building materials are well-established. However, there remain unresolved inquiries regarding the precise location of the sources of PM2.5. This study is the first attempt to use a calibrated sensors-based ambient air quality monitoring network (SAAQM network) and regulatory government monitors to train micro-satellite images for high spatial-resolution air pollution field determination of PM2.5 in Lucknow, Uttar Pradesh, India. A hybrid approach is developed to integrate three different datasets that include microsatellite images, PM2.5 ground measurements, and supporting information (meteorological parameters and geographical coordinates), to be fed into a Random Trees-Random Forest- Convolutional Neural Network (RT-RF-CNN) joint model to estimate PM2.5 concentrations at a sub-km level. The RT-RF-CNN joint model can derive PM2.5 concentrations at a spatial resolution of 500 m with statistically significant indicators such as spatial r of 0.9, a low root-mean-square error of 26.9 μg/m3 and a mean absolute error of 17.2 μg/m3. Based on our approach, the PM2.5 prediction maps using micro-satellite images (spatial resolution of 3m/pixel) and RT-RF-CNN joint model were generated for each day throughout the study period (December 2021–December 2022). The inter-grid comparison of these maps revealed the intra-urban local hotspots and coolspots at a fine-granular level seasonally, monthly, and daily. It is observed that the monsoon season has the highest number of coolspots (67%), while winter (0.1%), post-monsoon (0.5%) and summer (11%) have fewer. It is noted that the high temporal-spatial information of PM2.5 estimates from our integrated approach is not achievable by ground-based measurements and other existing satellite-based estimates alone. The findings of this study have potential applications on a diverse array, encompassing near real-time daily PM2.5 predicted maps, specific air pollution hotspot identification, PM2.5 exposure assessment at the neighbourhood level, and integration of remote sensing-based micro-satellite images and ground-based measurements.

Marine plankton community and net primary production responding to island-trapped waves in a stratified oligotrophic ecosystem

The oligotrophic Adriatic Sea is characterized during a typical summer by low productivity caused by strong water column stratification, which inhibits vertical mixing and nutrient supply to the euphotic zone. These conditions can be disrupted by transient physical forcing, which enhances nutrient fluxes and creates localized hotspots of relatively high net primary production. In this study, plankton abundance and diversity were investigated in relation to the physical forcing and nutrient concentrations in an area affected by island-trapped waves (ITWs) near Lastovo Island (Adriatic Sea). The episodic ITW events resulted in enhanced uplift and vertical excursion of the thermocline, marked by anomalously higher nutrient concentrations and a corresponding increase in net primary production in the thermocline layer. Physicochemical properties explained 11.7 % (p = 0.002) of the variability in micro- and nanophytoplankton and 88.9 % (p = 0.001) in the picoplankton community. A significant response to the ITW phenomenon in the plankton community composition (p = 0.001) was observed for bacterioplankton. Among the identified amplicon sequence variances, primary producers were scarce and mainly represented cyanobacteria (Synechococcus strain CC9902), stramenopiles (Pelagomonas), and chlorophytes (Ostreococcus). The remaining amplicon sequence variances were assigned to the classes Copepoda, parasitic fungi (Meyerozyma spp.), mixotrophic dinoflagellates (family Peridiniales, mostly the genus Blastodinium), and parasitic Ciliophora (Scuticociliata). Bacterial ecological functions corresponded to chemoheterotrophic, degradation, and fermentation processes, whereas samples collected after the most intense ITW episode also showed abundant bacteria linked to microplastic degradation and parasitosis. These results highlight the ecological role of localized physical phenomena in enhancing nearshore primary productivity and fine shifts in plankton taxa in oligotrophic systems.

Effect of Fe-Co catalysis on the temperature field distribution during the growth of 3C-SiC fibers synthesised by microwave heating

Microwave heating produce local hot spots on materials, which result in uneven heating and other issues. Regulate the microwave temperature field using different catalyst combinations such as Fe (NO3)3·9H2O and Co (NO3)2·6H2O. The electromagnetic and temperature field distributions of 3C–SiC fibers and the molecular dynamics of the SiC interfacial growth process and interfacial oxidation reaction during microwave heating in the presence of a catalyst were simulated and calculated respectively. The results show that the combination of Fe and Co at 9 wt% catalyst concentration can effectively improve the electromagnetic loss capability of SiC fibers. The Fe and Co bimetallic catalysed synthesis of 3C–SiC fibers follows a vapor–liquid–solid growth mechanism. The Fe–Si and Fe–Co–Si alloy phases can induce 3C–SiC growth along (111) crystal faces. The simultaneous exothermic reactions provide a highly catalytically active growth environment that facilitates the enhancement of microwave temperature field uniformity. This phenomenon facilitated the synthesis of 3C–SiC fibers.

Recent evolutionary origin and localized diversity hotspots of mammalian coronaviruses

Several coronaviruses infect humans, with three, including the SARS-CoV2, causing diseases. While coronaviruses are especially prone to induce pandemics, we know little about their evolutionary history, host-to-host transmissions, and biogeography. One of the difficulties lies in dating the origination of the family, a particularly challenging task for RNA viruses in general. Previous cophylogenetic tests of virus-host associations, including in the Coronaviridae family, have suggested a virus-host codiversification history stretching many millions of years. Here, we establish a framework for robustly testing scenarios of ancient origination and codiversification versus recent origination and diversification by host switches. Applied to coronaviruses and their mammalian hosts, our results support a scenario of recent origination of coronaviruses in bats and diversification by host switches, with preferential host switches within mammalian orders. Hotspots of coronavirus diversity, concentrated in East Asia and Europe, are consistent with this scenario of relatively recent origination and localized host switches. Spillovers from bats to other species are rare, but have the highest probability to be towards humans than to any other mammal species, implicating humans as the evolutionary intermediate host. The high host-switching rates within orders, as well as between humans, domesticated mammals, and non-flying wild mammals, indicates the potential for rapid additional spreading of coronaviruses across the world. Our results suggest that the evolutionary history of extant mammalian coronaviruses is recent, and that cases of long-term virus–host codiversification have been largely over-estimated.