Local Hot Spots Research Articles

Selling out the city? Airbnb’s amateur and professional listings across cities, time, and hotspots

Abstract In the early days of its existence, Airbnb was heralded as a champion of the “sharing economy”, enabling amateur hosts to offer short-term lodging to a global community of guests. Since then, public debates and research have highlighted the rise of professional hosts as an indication for the commercialization of Airbnb. However, it is neither well understood how Airbnb listings developed across cities and time nor how they are distributed across local hotspots. The paper conceptualizes the Airbnb marketplace in its spatial constitution, as a network space brokering accommodation at specific places within designated city territories. It asks who dominates the digital marketplace across cities and time, distinguishing between professional and amateur listings. Based on an extensive dataset of 45 cities all over the world over a period of eight years, the paper investigates the distribution of amateur and professional listings. The article then focuses on the spatial diffusion of Airbnb listings in four selected cities (Amsterdam, Berlin, London, San Francisco) which represent diverse regulatory approaches, to identify local hotspots and establish who dominates these hotspots. The results show a worldwide trend of professional listings rising to dominate Airbnb, alongside few pockets of amateur marketplaces. Within cities, amateurs prevail only in local hotspots in specific cities—which, moreover, tend to be found only in peripheral locations. The results provide rich empirical insights into the commercialization and diversity of Airbnb as a network space around the world.

Ulitníky pseudokrasovej tiesňavy Parkaň v pohorí Bachureň na východnom Slovensku [Gastropods of the Parkaň pseudokarst gorge in the Bachureň Mountains in Eastern Slovakia

A pseudokarst gorge with the local name „Parkaň“ is located near the village of Renčišov in the Bachureň Mountains. This area was surveyed in 2023. In total, we recorded 52 species of terrestrial gastropods. These were predominantly forest species (38; 73%), euryvalent species were less represented (13; 25%), and one open country species was also found (1; 2%). The local microtopographic diversity (moist rubble, rock walls covered with moss, dead wood) with historic habitat continuity support the high species diversity of the gastropod fauna. The results highlight the conservation importance of the area and the presence of sensitive species such as Argna bielzi, Macrogastra tumida, Pseudalinda stabilis and Bulgarica cana, indicating the well-preserved state of the habitat. This area represents a local diversity hotspot surrounded by mostly disturbed production forest monocultures. The discovery of one, slightly damaged shell of the species Helicigona lapicida is interesting. Since we could not find live individuals, we do not consider this finding a reason to include the species in the malacofauna of Slovakia.

EXPERIMENTAL INVESTIGATION OF A CONVERGENT NOZZLE FOR THERMAL HOMOGENIZATION OF AIR

This study employed a 2 kW<sub>th</sub> solar air tower simulator system for experimental validation, explicitly focusing on the effectiveness of a custom-designed mixer assembly under conditions of even and uneven heat flux distribution. Non-uniform heat dispersion within the absorbers can create localized hotspots and temperature disparities, resulting in thermal stress within the pipeline system. To address this challenge, a mixer assembly was devised to equalize the temperature differential in the heated air. The study concentrates on scrutinizing the temperature variance along both the axial and azimuthal axes within the mixer assembly, examining scenarios with aperture power of 1000 W and 1500 W, as well as mass flow rates of 6.37 g/s and 14.87 g/s. Notably, the study identified a maximum temperature differential of 7°C at the mixer's outlet when the initial temperature variance at the inlet stood at 37°C.

Range and accuracy of in-plane anisotropic thermal conductivity measurement using the laser-based Ångstrom method.

High heat fluxes in electronic devices must be effectively dissipated to prevent local hotspots, which are critical for long-term device reliability. In particular, advanced semiconductor packaging trends toward thin form factor products increase the need for understanding and improving in-plane conduction heat spreading in anisotropic materials. The 2D laser-based Ångstrom method, an extension of traditional Ångstrom and lock-in thermography techniques, measures in-plane thermal properties of anisotropic sheet-like materials. This method uses non-contact infrared temperature mapping to measure the thermal response to periodic laser heating at the center of a suspended sample. The spatiotemporal temperature data are analyzed via an inverse fitting algorithm to extract thermal conductivities in the in-plane orthotropic directions that best adhere to the governing heat conduction equation. Using this algorithm, we present an approach to simultaneously fit data across multiple heating frequencies, which improves measurement sensitivity because the thermal penetration depth varies with frequency. The accuracy of this technique is assessed by tuning experimental parameters such as sample dimensions and heating frequency. A standardized workflow is proposed for measuring unknown materials and for processing the data, including filtering out regions influenced by laser absorption and heat sink boundary effects. Numerical simulations validate the method across a wide range of thermal conductivities (0.1-1000W m-1 K-1) and material thicknesses (0.1-10mm), with accuracy demonstrated for anisotropy ratios up to 1000:1. Experimental measurements on isotropic and anisotropic materials agree well with the benchmark values. Ultimately, standardization of this technique supports the development of engineered anisotropic heat-spreading materials for thermal management and packaging applications.

Microwave catalytic treatment using magnetically separable CoFe2O4 spinel catalyst for high-rate degradation of malachite green dye.

The release of toxic chemical dyes from the industrial effluent poses huge challenges for the environmental engineers to treat it. Azo dyes encompass the huge part of textile discharges which are difficult to degrade due to their complex chemical aromatic structures and due to the presence of strong bonds (-N=N-). Thus, the removal of a carcinogenic azo dye (i.e., malachite green (MG)), via microwave (MW) - assisted technology in the presence of spinel cobalt ferrite (CoFe2O4) catalyst was investigated. The synthesized CoFe2O4 nanoparticles were characterized via XRD, FTIR, TGA, VSM, and SEM-EDAX analytical techniques. The nanoparticles were found to be spherical (17.42nm), and crystalline in nature. The impact of MW power (300-700W), MW temperature (60°- 90°C), CoFe2O4 dosage (0-1.2g/L), and initial MG dye concentrations (15-100mg/L) on MG removal were studied. The maximum MG decolorization (>90%) was observed within 2min, and the remaining decolorization was completed within next 3min under the optimized condition. The reaction rates were significantly boosted by MW irradiation, resulting in faster MG degradation with pseudo second-order kinetics rate (R2 ∼ 0.99). The MW irradiation would induce the localised hotspot zones over the catalytic surface, thus promoting the reactive radical species generation, which targeted the organic pollutant achieving the higher degree of mineralization (TOC∼90%). The toxicity reduction after the MW treatment suggests that the bulky toxic aromatic chains of the dye compound might have fragmented into simpler, smaller, and less toxic compounds. The ⦁OH played a major role in the degradation of MG dye through demethylation, elimination of benzene rings, and subsequent mineralization to CO2, and H2O. No detectable leaching of cobalt (Co) metal was observed from the catalyst, which ensured the stability of Co in the catalyst. Moreover, CoFe2O4 was recovered easily after the MW treatment via external magnetic separation, due to its high saturation magnetization value (i.e., 59.5 emu/g). Additionally, cost incurred for dye removal via MW irradiation was compared ($ 308 per kg of the dye pollutant removed) with several other processes, and found on economic side in comparison. According to the findings, the microwave irradiation process assisted by CoFe2O4 treatment offers a practical, and potential approach for treating dye laden wastewater, along with the easier catalyst retrieval mechanism using magnetism.

Hierarchical accompanying and inhibiting patterns on the spatial arrangement of taxi local hotspots

ABSTRACT The spatial arrangement of taxi hotspots indicates their inherent distribution relationships, reflecting their spatial organization structure, and has received attention in urban studies. Previous studies have primarily explored large-scale hotspots through visual analysis or simple indices, which typically spans hundreds or even thousands of meters. However, the spatial arrangement patterns of small-scale hotspots representing specific popular pick-up and drop-off locations have been largely overlooked. In this study, we quantitatively examine the spatial arrangement of local hotspots in Wuhan and Beijing, China, using taxi trajectory data. Local hotspots are small-scale hotspots with the highest density near the center. Their optimal radius is adaptively calculated based on the data, which is 90 m × 90 m and 110 m × 110 m in Wuhan and Beijing, respectively. Popular hotspots are typically surrounded by less popular ones, although regions with many popular hotspots inhibit the presence of less popular ones. These configurations are termed as hierarchical accompanying and inhibiting patterns. Finally, inspired by both patterns, a KNN-based model is developed to describe these relationships and successfully reproduce the spatial distribution of less popular hotspots based on the most popular ones. These insights enhance our understanding of local urban structures and support urban planning.

INFLUENCE OF VENTILATION PLACEMENT ON THE COOLING EFFICIENCY OF LITHIUM-ION BATTERIES UNDER FORCED AIRFLOW CONDITIONS

In line with a rise in demand for lithium-ion batteries (LIBs) around the globe, LIB thermal management optimization is desirable. Moreover, the temperature rise of LIBs while discharging and charging affects their degradation and thermal runaway. The objective of this study is to investigate cooling performance in LIBs due to battery pack ventilation configuration. In this study, twenty 18650 lithium-ion cells (in 10S2P configuration) were simulated in Altair HyperWorks CFD - AcuSolve. The analysis provides a significant finding for the best thermal management approach by Design 2 with the position of an inlet at the top and outlet at the bottom of the battery pack, indirectly promoting uniform temperature distribution across the pack and avoiding local hot spots. These findings contribute significant insights into the effect of battery ventilation configuration for enhancing lithium-ion cooling performance

Biofidelity Assessment of the GHBMC M50-O Seated in a Honda Accord Seat in a Rear-Facing Configuration during a High-Speed Frontal Impact

<div>Vehicles equipped with automated driving systems (ADS) may have non-traditional seating configurations, such as rear-facing for front-row occupants. The objectives of this study are (1) to generate biomechanical corridors from kinematic data obtained from postmortem human subjects (PMHS) sled tests and (2) to assess the biofidelity of the Global Human Body Models Consortium (GHBMC) 50th male (M50-O) v6.0 seated in an upright (25-deg recline) Honda Accord seat with a fixed D-ring (FDR) in a 56 km/h rear-facing frontal impact. A phase optimization technique was applied to mass-normalized PMHS data for generating corridors. After replicating the experimental boundary conditions in the computational finite element (FE) environment, the performance of the rigidized FE seat model obtained was validated using LSTC Hybrid III FE model simulations and comparison with experiments. The most recent National Highway Traffic Safety Administration (NHTSA) Biofidelity Ranking System (BRS) method was used to assess the biofidelity of the GHBMC M50-O. The occupant response score for GHBMC was 2.00. The average normalized root mean squared deviation (NRMSD) for seat reaction loads in the GHBMC simulation was less than 10%. Peak T-spine accelerations (avg. BRS = 2.28) and anterior-to-posterior (AP) chest deflection (BRS = 2.61) were underestimated. No rib fractures were predicted in the GHBMC using the default failure strain criteria of 1.8%; however, fractures were predicted in the 3rd rib (both left and right sides) using an updated failure strain criteria of 0.52%. Ramping up the seat back, as indicated by pelvis Z-displacement, was underestimated using a coefficient of contact friction of 0.2 (BRS = 3.65) but improved using a coefficient of 0.1 (BRS = 1.44). Local strain hotspots were predicted at the pubic rami locations in the GHBMC, corresponding well with fracture sites in the PMHS.</div>

Spatiotemporal Multivariate Weather Prediction Network Based on CNN-Transformer.

Weather prediction is of great significance for human daily production activities, global extreme climate prediction, and environmental protection of the Earth. However, the existing data-based weather prediction methods cannot adequately capture the spatial and temporal evolution characteristics of the target region, which makes it difficult for the existing methods to meet practical application requirements in terms of efficiency and accuracy. Changes in weather involve both strongly correlated spatial and temporal continuation relationships, and at the same time, the variables interact with each other, so capturing the dynamic correlations among space, time, and variables is particularly important for accurate weather prediction. Therefore, we designed a spatiotemporal coupled prediction network based on convolution and Transformer for weather prediction from the perspective of multivariate spatiotemporal fields. First, we designed a spatial attention encoder-decoder to comprehensively explore spatial representations for extracting and reconstructing spatial features. Then, we designed a multi-scale spatiotemporal evolution module to obtain the spatiotemporal evolution patterns of weather using inter- and intra-frame computations. After that, in order to ensure that the model has better prediction ability for global and local hotspot areas, we designed a composite loss function based on MSE and SSIM to focus on the global and structural distribution of weather to achieve more accurate multivariate weather prediction. Finally, we demonstrated the excellent effect of STWPM in multivariate spatiotemporal field weather prediction by comprehensively evaluating the proposed algorithm with classical algorithms on the ERA5 dataset in a global region.

A new modeling approach for denitrification taking internal chemical gradients into account

AbstractIn this paper a new modeling approach for denitrification and similar processes, which depend on the geochemical gradient between the air-filled larger pores in a soil and a water-filled matrix, is presented. The new modeling approach is capable of taking soil structural properties (obtained e.g. from X-ray CT) into account without requiring a high-resolution simulation. The model approach is explained and its application is demonstrated by simulating denitrification experiments conducted with repacked soil samples to assess the challenges and possibilities of the new approach. The main result of the modeling is that the nitrous oxide emission measured in the experiment can not be explained by a limited supply with oxygen alone at a carbon turnover rate derived from carbon dioxide emissions. It is additionally necessary that the microbial activity is concentrated in localized hot spots to create anaerobic conditions. This is confirmed by analytical solutions.

A novel framework for fatigue hotspot localization and damage assessment of multi-defect marine structures under random vibration

In ocean engineering, assessing vibration-induced fatigue under random loads is critical, particularly for ocean structures with multiple defects, as fatigue is highly sensitive to local structural flaws. Recently, incorporating structural dynamic characteristics into vibration fatigue assessments has emerged as a significant trend and formidable challenge, involving three key obstacles: precise localization of fatigue hotspots, extraction of key modes, and determination and integration of modal damage contributions. This paper introduces a novel framework for fatigue hotspot localization and damage assessment in the context of random vibration fatigue in ocean structures. By initially identifying fatigue hotspots and hot regions using stress mode shapes, refining the finite element mesh in hot regions, and conducting reanalysis, the exact locations of fatigue hotspots can be determined, enabling structural dimensionality reduction. The introduction of a modal damage contribution factor allows for the evaluation of each mode's damage contribution and the identification of key modes, further facilitating modal reduction. For the precisely localized fatigue hotspots, the proposed method combines the damage contributions of key modes, enabling rapid and accurate assessment of fatigue damage under random vibration loads. Finite element case studies and vibration fatigue test results demonstrate that the proposed framework effectively addresses the challenges of random vibration fatigue evaluation, achieving structural and modal reduction while significantly enhancing the efficiency of damage assessment without compromising accuracy.

Mapping a Novel Metric for Flash Flood Recovery Using Interpretable Machine Learning

Abstract Flash floods are one of the most devastating natural disasters, yet many aspects of their severity and impact are poorly understood. The recession limb is related to postflood recovery and its impact on communities, yet it remains less documented than the rising limb of the hydrograph to predict the peak discharge and timing of floods. This work introduces a new metric called flash flood recovery or recoveriness, which is the potential for recovery of a watershed to preflood conditions. Using a comprehensive database of 78 years and supervised machine learning algorithms, flash flood recovery is mapped in the conterminous United States. A suite of geomorphological and climatological variables is used as predictors to provide probabilistic estimates of recoveriness. Slope index, river basin area, and river length are found to be the most significant predictors to predict recoveriness. Several new localized hotspots were identified, such as the western slopes of the Appalachians consisting of Kentucky, Tennessee, and West Virginia and the interlinked areas of western Montana and northern Idaho. This new metric can be useful for prioritizing relief and rehabilitation efforts as well as precautionary measures for disaster risk reduction.

The spatiotemporal distribution patterns and impact factors of bird species richness: A case study of urban built-up areas in Beijing, China

This study aims to investigate the distribution patterns of bird species in urban built-up areas and their impact factors from multiple dimensions, including spatiotemporal distribution, environmental changes, and anthropogenic disturbances, as well as overall distribution and local hotspots. Leveraging geographic distribution data of 383 bird species from 70 families and 21 orders, the study recorded dynamic changes in bird distribution within urban built-up areas characterized by highly heterogeneous core areas and suburban areas. It examined species distribution across different seasons and land cover types, evaluated population fluctuations based on migratory behaviors, and assessed the relative abundance of bird families and species in hotspot areas. Additionally, this study employed three tree-based machine learning algorithms—Decision Tree (DT), Random Forest (RF), and Extreme Gradient Boosting (XGBoost)—to investigate the influence of environmental factors on bird species distribution within urban built-up areas. The findings showed that, temporally, the number of observed bird species in the study area peaked in May and September, while the lowest numbers of species (54.83 %) and individuals (5.45 %) were recorded during the high-temperature period from June to August. Spatially, (1) woodlands, including stable mature forests, unstable juvenile forests, and sparse vegetation, recorded the highest frequencies of bird observations (2,053 times), bird species (369 species), and bird individuals (38,623 individuals); (2) comprehensive parks, where bird species demonstrated higher adaptability to anthropogenic disturbances, experienced a more significant decline in species richness compared to country parks; and (3) the number of bird species in hotspot areas located in the core areas, which developed earlier, has decreased annually, while the number of species in suburban areas, which developed later, has increased annually. In terms of impact factors, water area (WA), point of interest kernel density (DPOI), relative humidity (RH), green space area (GSA), and nighttime light pollution (NL) were identified as the five most important environmental factors affecting bird species richness. These results suggest that although birds exhibit some adaptability to environmental changes and anthropogenic disturbances, species distribution remains significantly impacted. This research aims to provide a planning framework for future urban development that promotes biodiversity and adaptability, thereby bolstering the resilience of urban ecosystems.

The role of thermal properties in the wear mechanisms of an AlSi-polyester abradable

During run-in and operation, the blades of a gas turbine engine may rub against the engine casing. To allow for these blade rubs an abradable coating is applied to the casing. However, the coating does not always cut smoothly, potentially wearing the blade. This paper focuses on the wear mechanics which occur with Metco 601, an AlSi-Polyester abradable which has been shown to produce a combination of blade wear and adhesion.In this study, by testing AlSi-Polyester of different hardnesses at various incursion rates and blade speeds, it has been shown that there is a statistically significant difference in the wear behaviour observed at 0.02μm/pass compared with those observed between 0.2 and 2 μm/pass. Simultaneous recording of the blade front, thermal hotspots on the blade and abradable, and force measurements have been used to relate observed wear mechanics to the thermal behaviour of the abradable. Results showed that at incursion rates above 0.2μm/pass high force application rates lead to localised hotspots on the abradable and sporadic adhesion events. At 0.02μm/pass the force application rate, and hence thermal energy flux into the abradable, is more gradual, allowing heat to spread across the abradable surface. The more uniform abradable temperature leads to large areas of simultaneous wear, demonstrating how the abradables ability to manage the thermal energy can have a significant impact on its wear performance. This has been further verified through the observation of a reduction in abradable temperature as the test progresses which aligns with a reduction in the thermal resistance through the abradable and also an observed transition from adhesion to blade wear.This work has shown that the management of thermal energy within AlSi-Polyester has a significant impact on the observed wear mechanisms, improving the understanding of why the wear mechanics vary with incursion rate.

Numerical simulation and experimental investigation on the thermal-fluid-solid multi-physical field coupling characteristics of wet friction pairs considering cavitation effect

The coupling characteristics of thermal-fluid-solid multi-physical fields are crucial in determining the operational performance and service life of wet clutches. However, the underlying mechanism behind the influence of cavitation effect on these coupling characteristics remains unclear. Therefore, we propose a numerical solution method for considering cavitation effect in the coupling characteristics based on the multi-physical field coupling platform MPCCI combined with ABAQUS and FLUENT. The distribution patterns and intercoupling relationships among temperature field, flow field, and stress-strain field are comprehensively analyze. The influence of relative speed, cross-sectional shape of oil grooves, and oil flow on the coupling characteristics is investigated. Experimental validation confirms that the proposed model accurately predicts temperature variation by accounting for cavitation effect. The temperature distribution of steel discs is notably affected by the cavitation effect, leading to an elevation in the maximum temperature and uneven distribution characterized by localized hot spots along the circumferential direction. Accounting for the cavitation effect reduces errors between calculated and experimental values of temperature rise. The convective heat transfer coefficient gradually decreases radially, with a more pronounced decrease in the cavitation region. An increase in relative speed and a decrease in oil flow both lead to greater cavitation volume, resulting in higher temperature of steel discs. Among three different cross-sectional shapes of oil grooves investigated, rectangular grooves exhibit larger areas affected by cavitation compared to triangular grooves. These research findings provide a theoretical basis and technical support for accurate prediction of thermal characteristics within high-power wet clutches.

Effect of Multisized Packing on the Heat Transfer Characteristics of a Face-Centered-Cubic-Structured Pebble Bed

Inserting small spheres of a fixed size into a pebble bed can enhance heat transfer, lower the surface temperature of fuel elements, and reduce the risk of local hot spots. However, does a multisized pebble bed outperform a double-sized pebble bed in terms of heat transfer? To address this question, numerical simulations were conducted to evaluate the heat transfer characteristics of face-centered-cubic-structured pebble beds with two and three types of small spheres, maintaining a constant solid volume. The results showed that the average heat transfer coefficients of the multisized pebble bed were nearly identical to those of the double-sized bed. This suggests that using two types of small spheres does not necessarily provide better heat transfer performance than using a double-sized bed. Additionally, the number, size, and placement of the spheres influenced the pressure drop. These findings offer insights into the heat transfer behavior of high-temperature reactor cores and provide a useful reference for the design of future pebble bed reactor cores.

Design and performance evaluation of the snowflake slope composite flow field based on a biomimetic principle

To address the problems of uneven mass distribution and hydrothermal management imbalance in flow fields, this study proposes a snowflake slope composite flow field (SSCFF). A three-dimensional multiphase computational fluid dynamics (CFD) model was developed to analyze the differences between the SSCFF and traditional flow fields, and to investigate the effects of gas inlet and outlet configurations, height ratios (Ld/D), and the number of main channels (N) on the performance. The study shows that the SSCFF excels in gas distribution and temperature control, with a maximum power density 35.5% higher than the honeycomb structure. The diagonal inlet and outlet configuration effectively reduces the risk of local hotspots and flooding. With Ld/D of 0.9, the uniformity of oxygen distribution improves significantly and the current density reaches 1.168 A cm−2. Additionally, with 6 main channels, the proton exchange membrane (PEM) achieves a higher hydration level, which boosts catalytic activity and working efficiency.

Groundwater flow and salinity dynamics in swash Zones: Combined effects of Evaporation, Waves, and geologic heterogeneity

This study employs groundwater simulations to examine the combined effects of waves, evaporation, and geologic heterogeneity on the flow and salinity dynamics in a shallow beach environment. The modeling results reveal that wave motion generates a saline plume beneath the swash zone, with hypersalinity near the surface triggered by evaporation. Geologic heterogeneity critically controls the temporal and spatial patterns of evaporation, moisture content, and salinity in the swash zone. Heterogeneous capillarity creates localized moisture hotspots within the unsaturated zone, which support enhanced evaporation and therefore facilitate salt accumulation at the surface, even when the overall moisture conditions along the swash zone are not conducive to high rates of evaporation. The formation of capillary barriers allows these moisture hotspots to persist over tidal cycles, leading to the retention of saltwater pockets within heterogeneous unsaturated finer sediments. As the swash zone recedes and evaporation intensifies, salt begins to accumulate near the beach surface. The moisture hotspots create preferential pathways that facilitate the penetration of hypersaline water into deeper, saturated sediments. In contrast, within the saturated zone, groundwater flow and salt transport are predominantly driven by preferential flow within high-permeability coarse sediments where capillarity is relatively low. Such transport and capillary mechanisms are crucial for a better understanding of coastal groundwater flow, interstitial habitats, biogeochemical conditions, and consequent nutrient cycling and contaminant transport in coastal zones. This highlights the necessity of considering integrated coastal physical drivers when investigating flow and transport processes in coastal swash zones.

Vortex-enhanced jet impingement and the role of impulse generation rate in heat removal using additively manufactured synthetic jet devices

This article presents an approach to the design and fabrication of synthetic jet devices (SJDs) using rapid prototyping via additive manufacturing, marking the first study to employ this method for such devices. This manufacturing technique empowers researchers with complete design freedom, enabling the production of ultra-thin SJDs—as thin as 4 mm—without mechanical fasteners and facilitating the rapid fabrication of multiple devices with varying geometries. To showcase the potential of this method, SJDs with conical and cylindrical cavities and orifices ranging from 1.6 mm to 7 mm were designed, fabricated, and tested.These devices achieved air jet exit velocities exceeding 106 m/s using a single piezoelectric diaphragm—among the highest reported in the literature—validating the effectiveness of this manufacturing approach. This high jet velocity is significant for practical applications requiring efficient thermal management, such as cooling high-power-density electronics, where compact and energy-efficient solutions are essential. Beyond achieving high velocities, it was revealed that maximizing jet velocity alone is not always optimal for heat removal. The hydrodynamic impulse generation rate was introduced as a more significant factor influencing heat transfer performance. By fabricating and testing multiple SJDs with different geometries, it was demonstrated that the impulse generation rate, which accounts for both jet velocity and flow rate, better correlates with enhanced heat transfer capabilities than jet velocity alone. This insight addresses an often-overlooked parameter in SJD design and has substantial implications for optimizing heat removal performance. Moreover, lumped element modeling, tuned solely on diaphragm deflection behavior, accurately predicted device performance and was validated using a hotwire anemometer. This model effectively characterizes center-axis orifice devices and confirms its applicability to thin-cavity designs, providing a valuable tool for future SJD development. Despite moderate volume flow rates (0.2 to 0.8 m3/h), the fabricated SJDs delivered significant improvements in heat transfer. Compared to natural convection, these devices achieved over 13 times greater heat removal rates, with an average heat transfer coefficient exceeding 120 W/m2·K over a 30 mm × 30 mm heated surface. These findings demonstrate the practicality and effectiveness of vortex-enhanced synthetic jet impingement for targeted and efficient cooling of localized hot spots. This approach offers multiple advantages over traditional rotary cooling systems like fans, including increased reliability, lower profile, while consuming less than 100 mW. The ability to rapidly prototype and optimize SJDs using additive manufacturing accelerates research and development in this field, paving the way for advanced thermal management solutions in real-world applications.

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).