Search Results (70)

Inverted (p-i-n) CsPbI_xBr_3−x (x = 0~3) perovskite solar cells (PSCs) are of growing interest due to their excellent thermal stability and optoelectronic performance. However, they suffer from severe energy level mismatch and significant interfacial energy losses at the bottom hole transport layers (HTLs). Herein, we propose a strategy to simultaneously enhance the crystallinity of CsPbI_2.85Br_0.15 and facilitate hole extraction at the HTL/CsPbI_2.85Br_0.15 interface by incorporating semiconducting single-walled carbon nanotubes (SWCNTs) onto [2-(3,6-dimethoxy-9H-carbazol-9-yl)ethyl] phosphonic acid (MeO-2PACz) HTL. The unique electrical properties of SWCNTs enable the MeO-2PACz/SWCNT HTL to achieve high conductivity, optimal energy level alignment, and an adaptable surface. Consequently, the defect density is reduced, hole extraction is accelerated, and interfacial charge recombination is effectively suppressed. As a result, these synergistic benefits boost the power conversion efficiency (PCE) from 15.74% to 18.78%. Moreover, unencapsulated devices retained 92.35% of their initial PCE after 150 h of storage in ambient air and 89.03% after accelerated aging at 85 °C for 10 h. These findings highlight the strong potential of SWCNTs as an effective interlayer for inverted CsPbI_2.85Br_0.15 PSCs and provide a promising strategy for designing high-performance HTLs by integrating SWCNTs with self-assembled monolayers (SAMs). Full article

With the rapid progression of global industrialization and urbanization, emerging contaminants (ECs) have become pervasive in environmental media, posing considerable risks to ecosystems and human health. While multidisciplinary evidence continues to accumulate regarding their environmental persistence and bioaccumulative hazards, critical knowledge gaps persist in understanding their spatiotemporal distribution, cross-media migration mechanisms, and cascading ecotoxicological consequences. This review systematically investigates the global distribution patterns of ECs in aquatic environments over the past five years and evaluates their potential ecological risks. Furthermore, it examines the performance of various treatment technologies, focusing on economic cost, efficiency, and environmental sustainability. Methodologically aligned with PRISMA 2020 guidelines, this study implements dual independent screening protocols, stringent inclusion–exclusion criteria (n = 327 studies). Key findings reveal the following: (1) Occurrences of ECs show geographical clustering in highly industrialized river basins, particularly in Asia (37.05%), Europe (24.31%), and North America (14.01%), where agricultural pharmaceuticals and fluorinated compounds contribute disproportionately to environmental loading. (2) Complex transboundary pollutant transport through atmospheric deposition and oceanic currents, coupled with compound-specific partitioning behaviors across water–sediment–air interfaces. (3) Emerging hybrid treatment systems (e.g., catalytic membrane bioreactors, plasma-assisted advanced oxidation) achieve > 90% removal for recalcitrant ECs, though requiring 15–40% cost reductions for scalable implementation. This work provides actionable insights for developing adaptive regulatory frameworks and advancing green chemistry principles in environmental engineering practice. Full article

This research presents the development of a type-2 fuzzy-controlled autonomous mobile robot specifically designed for monitoring and actively maintaining indoor air quality. The core of this system is the proposed type-2 fuzzy PID dual-mode controller used for stably patrolling rooms along the walls of the environment. The design method ingeniously merges the fast error correction capability of PID control with the robust adaptability of type-2 fuzzy logic control, which utilizes interval type-2 fuzzy sets. Furthermore, the type-2 fuzzy rule table of the right wall-following controller can be extended from the first designed fuzzy left wall-following controller in a symmetrical design manner. As a result, this study eliminates the drawbacks of excessive oscillations arising from PID control and sluggish response to large initial errors in typical traditional fuzzy control. The following of the stable wall and obstacle is facilitated with ensured accuracy and easy implementation so that effective air quality monitoring and active PM2.5 filtering are achieved in a movable manner. Furthermore, the augmented reality (AR) interface overlays real-time PM2.5 data directly onto a user’s visual field, enhancing situational awareness and enabling an immediate and intuitive assessment of air quality. As this type of control is different from that used in traditional fixed sensor networks, both broader area coverage and efficient air filtering are achieved. Finally, the experimental results demonstrate the controller’s superior performance and its potential to significantly improve indoor air quality. Full article

Debonding, especially in plastic materials, refers to the separation occurring at the interface within a bonded structure composed of two or more polymeric layers. Due to the great heterogeneity of materials and layering configurations, highly specialized expertise is often required to detect the presence and extent of such defects. This study presents a novel approach that leverages transfer learning techniques to improve the detection of debonding defects across different surface types using PICUS, an acoustic diagnostic device developed at Roma Tre University for the assessment of defects in heritage wall paintings. Our method leverages a pre-trained deep learning model, adapting it to new material conditions. We designed a planar test object embedded with controlled subsurface cavities to simulate the presence of defects of adhesion and air among the layers. This was rigorously evaluated using non-destructive testing using PICUS, augmented by artificial intelligence (AI). A convolutional neural network (CNN), initially trained on this mock-up, was then fine-tuned via transfer learning on a second test object with distinct geometry and material characteristics. This strategic adaptation to varying physical and acoustic properties led to a significant improvement in classification precision of defect class, from 88% to 95%, demonstrating the effectiveness of transfer learning for robust cross-domain defect detection in challenging diagnostic applications. Full article

University libraries are essential academic spaces, yet existing smart systems often overlook user perception in environmental optimization. A key challenge is the lack of adaptive frameworks balancing objective sensor data with subjective user experience. This study introduces an Internet of Things (IoT)-powered framework integrating real-time sensor data, image-based occupancy tracking, and user feedback to enhance study conditions via machine learning (ML). Unlike prior works, our system fuses objective measurements and subjective input for personalized assessment. Environmental factors—including air quality, sound, temperature, humidity, and lighting—were monitored using microcontrollers and image processing. User feedback was collected via surveys and incorporated into models trained using Logistic Regression, Decision Trees, Random Forest, Support Vector Machine (SVM), K-Nearest Neighbors (KNNs), Extreme Gradient Boosting (XGBoost), and Naive Bayes. KNNs achieved the highest F1 score (99.04%), validating the hybrid approach. A user interface analyzes environmental factors, identifying primary contributors to suboptimal conditions. A scalable fog–cloud architecture distributes computation between edge devices (fog) and cloud servers, optimizing resource management. Beyond libraries, the framework extends to other smart workspaces. By integrating the IoT, ML, and user-driven optimization, this study presents an adaptive decision support system, transforming libraries into intelligent, user-responsive environments. Full article

In future sixth-generation (6G) communication systems, it is foreseen that complex communication scenarios and critical performance requirements will necessitate more flexible air interface configurations. Traditional air interface adaptation will no longer be applicable to 6G due to issues such as high computational complexity, sub-optimal trade-offs among multi-objective performance metrics, outdated configurations due to fast-varying channels, etc. In this paper, the relevant user behaviors, communication environment, and system are virtualized via the digital twinning technique. Then, a knowledge graph-based multi-objective recommendation framework is proposed to configure the digital twinning air interface to adapt to channel conditions, while balancing various service requirements. First, the knowledge graph is applied to reveal complex dependencies between the air interface and the service requirements, and more importantly, to reconcile possibly contradictory performance targets. Furthermore, the air interface configuration, empowered by the digital twin technique, is able to exploit predicted prior knowledge about user behavior and the channel characteristics, thus improving the utilization efficiency of wireless resources promptly. Moreover, the digital twin technique allows the candidate air interfaces to be virtually verified and compared with little effort. Finally, two case studies are presented to demonstrate the potential of the knowledge graph-based recommendation method for the digital twinning air interface. Full article

WS₂ films exhibit excellent tribological properties in a vacuum, but they are prone to failure due to oxidation in air, which severely limits their application. Cu has great potential to improve the tribological properties of WS₂, similar to that of Au and Ag. Thus, to clarify the contribution of Cu to the tribological properties of WS₂ films and provide new insight for the development of new multi-environmentally adaptable films, this study deposited WS₂-Cu composite films under different sputtering powers of the Cu target by magnetron sputtering systems, and the Cu target was supplied by DC power. Then, the structure of films was analyzed by FESEM, EDS and XPS. The results show that Cu is difficult to uniformly dope on the WS₂ film at a high sputtering power of Cu target, showing possibly low solubility of Cu in WS₂ film. However, a uniform and dense WS₂-Cu composite film was deposited under the lower sputtering power of Cu target. Furthermore, the results of the nanoindentation test demonstrated that the WS₂-Cu composite films exhibited high hardness (6.6 GPa). Finally, the tribological properties of the WS₂-Cu films were examined, and their friction interface was characterized by SEM, EDS and TEM. The WS₂-Cu film demonstrated superior tribological behavior in air (the average friction coefficient is 0.09), based on a special sliding interface, low oxidation levels of WS₂ and Cu-rich transfer film. This study provides a new insight and a new method for improving the environmental adaptation ability of WS₂ film. Full article

Selection is a fundamental interaction element in virtual reality (VR) and 3D user interfaces (UIs). Raycasting, one of the most common object selection techniques, is known to have difficulties in selecting small or distant objects. Meanwhile, recent advancements in computer vision technology have enabled seamless vision-based hand tracking in consumer VR headsets, enhancing accessibility to freehand mid-air interaction and highlighting the need for further research in this area. This study proposes a new technique called TouchView, which utilizes a virtual panel with a modern adaptation of the Through-the-Lens metaphor to improve freehand selection for VR UIs. TouchView enables faster and less demanding target selection by allowing direct touch interaction with the magnified object proxies reflected on the panel view. A repeated-measures ANOVA on the results of a follow-up experiment on multitarget selection with 23 participants showed that TouchView outperformed the current market-dominating freehand raycasting technique, Hybrid Ray, in terms of task performance, perceived workload, and preference. User behavior was also analyzed to understand the underlying reasons for these improvements. The proposed technique can be used in VR UI applications to enhance the selection of distant objects, especially for cases with frequent view shifts. Full article

The current study is focused on devising treated diatomite interfaces with the robustness and boiling water resistance necessary for high-temperature purposes. This work describes the synthesis methodology of the diatomite-based coatings, which followed the production of a composite formulation composed by treated diatomite powder dispersed in an epoxy resin matrix. After its preparation, the suspension was applied via the dip-coating technique over AISI-304 stainless-steel foils, which, after being air dried, underwent a post-curing treatment. Also, the interfaces were characterized by diverse techniques such as scanning electron microscopy and optical tensiometry. Apart from this, their thermophysical properties like thermal conductivity were also determined. Further, the physical and chemical durability of the interfaces was also evaluated via the elaboration of robustness tests including abrasion resistance, adhesion strength, solid impact resistance, and solvent resistance. The results showed satisfactory resistant interfaces, and with a wettability characterized by contact angles superior to 150°. Also, the interfaces confirmed improved durability when immersed in boiling water at 1 atm, since their wetting characteristics and durability remained nearly unaltered after 762 h of testing. Additionally, the synthesized interfaces possessed self-cleaning ability and chemical and thermal shock aging resistance. Generally, the fundamental outcomes of this work point out the suitability of the produced diatomite-based interfaces to be explored in high-temperature applications like flow boiling, pool boiling, and condensation. In terms of practicality, the method of preparation of the interfaces was a relatively easy and rapid approach to obtaining enhanced wettability and resilient interfaces, and with the required adaptations like the ratios between the raw materials, its suitability for large-scale applications makes this an appealing option. Full article

Information and decision support systems are essential to conducting scientific field campaigns in the atmospheric sciences. However, their development is costly and time-consuming since each field campaign has its own research goals, which result in using a unique set of sensors and various analysis procedures. To reduce development costs, we present a software framework that is based on the Industrial Internet of Things (IIoT) and an implementation using well-established and newly developed open-source components. This framework architecture and these components allow developers to customize the software to a campaign’s specific needs while keeping the coding to a minimum. The framework’s applicability was tested in two scientific field campaigns that dealt with questions regarding air quality by developing specialized IIoT applications for each one. Each application provided the online monitoring of the acquired data and an intuitive interface for the scientific team to perform the analysis. The framework presented in this study is sufficiently robust and adaptable to meet the diverse requirements of field campaigns. Full article

Conifer forests in Michoacán are facing climate change. Pinus devoniana Lindley, with natural distribution in the state, has shown certain adaptability, and knowing the influence of anatomy in the flow system is essential to delimit how it contributes to safety margins and water efficiency. For this, the pressure gradients in the cell lumens and their ramifications were analyzed by numerical simulations of flow throughout the real microstructure. Xylem were evaluated in radial, tangential and longitudinal directions. With the skeletonization of lumens and their constrictions, a branching system of interconnection between tracheids, ray cells, intercellular chambers, extensions, and blind pits were identified. In the simulation, the branched system bypasses the longitudinal fluid passage through the pores in membranes of pairs of pits to redirect it through the direct path branching, contributing to safety margins and water efficiency. Thus, resilience at low pressures because of the lower pressure drop in the extensions. The interface between the branching system and the cell lumens are sites of higher pressure gradient, more conducive to water-vapor formation or air leakage in the face of the lowest pressure system. The flow lines move along easy paths, regardless of the simulated flow direction. Deposits in the cell extensions were shown to be attached to the S3 layer of the cell wall, leaving the center of the duct free to flow. It is concluded that the spatial architecture of the xylem anatomy of Pinus dvoniana is a factor in the resilience at low pressures due to high water stress of the species. Full article

A trans-media vehicle is a new type of equipment that can adapt to two environments, water and air, to maintain optimal hydrodynamic and aerodynamic performance. However, no matter what kind of trans-media vehicle, its dynamics are much more complicated when traversing the interface of the medium, as the parameters are time-varying due to the change in ambient medium and vehicle attitudes. In order to improve the stability and performance of the trans-media vehicle in complex environments, an accurate mathematical model is established to characterize the dynamics of the trans-media vehicle in this process in this study. The time-varying hydrodynamic coefficients with different attitudes or depths are obtained using computational fluid dynamics software. The mathematical model is solved iteratively using a Runge–Kutta solver to calculate the dynamic response. A prototype of trans-media vehicle is fabricated, and motion experiments are performed in the pool. The experimental results confirm the effectiveness of the established model and lay the foundation for further controller design, providing a reference for the dynamic modeling of other similar equipment operating in complex environments. The primary novelty of this study lies in the fact that the established dynamic model considers the complex interaction between the attitude of the trans-media vehicle and the inherent different properties of water and air and utilizes computational fluid dynamics software to accurately obtain time-varying coefficients under different attitudes and depths. This approach not only recognizes the criticality of orientation-dependent hydrodynamic coefficients but also incorporates their temporal variations, which were often overlooked in previous studies. Full article

To accurately assess the dynamic stability of the damaged ship, this paper performs an experimental campaign and presents a feasible numerical method to analyze the effects of microscopic air–fluid interactions on the motion responses of the damaged ship. The numerical approach can be applied to solve the coupled hydrodynamic behavior between the flooding process and the motion responses of the damaged ship. The volume of fluid (VOF) method was applied to capture the interface of the free surface, while the dynamic fluid–body Interaction (DFBI) morphing technique was applied to deal with mesh adaption. In particular, the UDF (user-defined field) function was activated to realize the initial distribution of the free surface. Firstly, by comparing the experimental and numerical results, the reliability of visualizing the flooding process and dealing with the motion responses of the damaged ship was efficiently verified. The numerical flooding process was able to reproduce the hydrodynamic phenomenon well, including the flooding jet, interaction, and flow between adjacent compartments. The numerical roll motion curve of the damaged ship was consistent with that predicted in the model test, with an error in roll amplitude of no more than 4%. Secondly, based on the verified numerical method, it was seen from the results with different ventilation positions that not only the air compressibility due to varying levels of ventilation cannot be neglected in damage assessment, but also the position of the ventilation hole was crucial. This was because different positions will create different paths for the compressed air to overflow and affect air–fluid interactions. Thus, the flooding force and air-impacting force acting on the internal hull will be different. In conclusion, this paper introduces a new consideration in the damage assessment of ships. Full article

Traditional cold alleys have the ability to adapt to hot climates with cooling and insulation, which is a traditional design method that conforms to sustainable development. Due to the limited depth of space and the adoption of mechanical ventilation in most contemporary architectural design, this passive energy-saving method is gradually being ignored. In this study, we use ventilation measurement and simulation to explore the characteristics of ventilation performance in the cold alleys of the renovation and expansion project of Shixiangyuan Garden. The research, using anemometers and thermometers for measurement, aims to explore how Shixiangyuan Garden can utilize its existing environment and improve it to adapt to local conditions, and also discusses the methods of increasing the number of air vents to improve the overall ventilation performance of the alleys, as well as the effects of form changes caused by utilizing water and plants to supplement the soft interface. Although many studies have explored the mechanisms of cold alleys in traditional architecture, few have discussed the variance of cold alley forms that could adapt to the limited depths of newly constructed buildings. This study attempts to explore the potential for this through simulation. The purpose is to find new ways to inherit the sustainable advantages of cold alleys in new projects. Full article

The precise estimation of fluid motion is critical across various fields, including aerodynamics, hydrodynamics, and industrial fluid mechanics. However, refraction at complex interfaces in the light path can cause image deterioration and lead to severe measurement errors if the aberration changes with time, e.g., at fluctuating air–water interfaces. This challenge is particularly pronounced in technical energy conversion processes such as bubble formation in electrolysis, droplet formation in fuel cells, or film flows. In this paper, a flow field estimation algorithm that can perform the aberration correction function is proposed, which integrates the flow field distribution estimation algorithm based on the Particle Image Velocimetry (PIV) technique and the novel actuator-free adaptive optics technique. Two different multi-input convolutional neural network (CNN) structures are established, with two frames of distorted PIV images and measured wavefront distortion information as inputs. The corrected flow field results are directly output, which are divided into two types based on different network structures: dense estimation and sparse estimation. Based on a series of models, a corresponding dataset synthesis model is established to generate training datasets. Finally, the algorithm performance is evaluated from different perspectives. Compared with traditional algorithms, the two proposed algorithms achieves reductions in the root mean square value of velocity residual error by 84% and 89%, respectively. By integrating both flow field measurement and novel adaptive optics technique into deep CNNs, this method lays a foundation for future research aimed at exploring more intricate distortion phenomena in flow field measurement. Full article