Collection Efficiency Research Articles

Experimental investigation and thermodynamic analysis of application of hybrid nanofluid in a parabolic solar trough collector.

In this research, thermal modeling has been done to investigate the effect of nanofluid on the performance of the linear parabolic collector. Therminol vapor/liquid phase fluid (VP-1) has been used as a base fluid; iron oxide nanoparticles have been used to produce mono-nanofluid; and iron oxide multi-walled carbon nanotubes nanocomposite has been used as nanoparticles to produce hybrid nanofluid. The fluid flow inside the absorber tube of the collector is assumed to be turbulent. The results show that when hybrid nanofluid and mono-nanofluid are used, the energy and exergy efficiencies of the collector are higher than those for the conditions of using the base fluid, but their amount is slightly lower with the use of hybrid nanofluid than when the working fluid is mono-nanofluid. According to the obtained results, the highest energy efficiency of the linear parabolic collector using nanofluid and mono-nanofluid is 70.2% and 70.4%, respectively, and the highest exergy efficiency is 35.7% and 35.9%, respectively. Despite this, the friction coefficient of mono-nanofluid compared to hybrid nanofluid was obtained on average about 9% higher. The results showed that the criterion for evaluating the performance of the collector (hydrodynamic thermal efficiency) when hybrid nanofluid is used is more than when mono-nanofluid is used.

Controlling the Magnetic Responsiveness of Cellulose Nanofiber Particles Embedded with Iron Oxide Nanoparticles.

2,2,6,6-tetramethylpiperidine-1-oxyl (TEMPO)-oxidized cellulose nanofiber (TOCN) particles, an innovative biobased material derived from wood biomass, have garnered significant interest, particularly in the biomedical field, for their distinctive properties as biocompatible particle adsorbents. However, their microscopic size complicates their separation in liquid media, thereby impeding their application in various domains. In this study, superparamagnetic magnetite nanoparticles (NPs), specifically iron oxide Fe3O4 NPs with an average size of 15 nm, were used to enhance the collection efficiency of TOCN-Fe3O4 composite particles synthesized through spray drying. These composite particles exhibited a remarkable ζ-potential (approximately -50 mV), indicating their high stability in water, as well as impressive magnetization properties (up to 47 emu/g), and rapid magnetic responsiveness within 60 s in water (3 wt % Fe3O4 to TOCN, 1 T magnet). Furthermore, the influence of Fe3O4 NP concentrations on the measurement of the speed of magnetic separation was quantitatively discussed. Additionally, the binding affinity of the synthesized particles for proteins was assessed on a streptavidin-biotin binding system, offering crucial insights into their binding capabilities with specific proteins and underscoring their significant potential as functionalized biomedical materials.

Improved Fog Collection on a Hybrid Surface with Acylated Cellulose Coating.

Fog collection serves as an efficient method to alleviate water scarcity in foggy, water-stressed regions. Recent research has focused on constructing a hybrid surface to enhance fog collection efficiency, with one approach being the prevention of liquid film formation at hydrophilic sites. Inspired by the desert beetle, a coating (10-MCC) made by partially acylating microcrystalline cellulose (MCC) exhibits hydrophilic sites alongside a hydrophobic skeleton enabling rapid droplet capture despite its overall hydrophobicity. The captured droplets quickly coalesce into a large droplet driven by the wetting gradient created by the hydrophobic backbone and hydrophilic sites. To achieve greater fog collection efficiency, a hydrophobic-superhydrophobic hybrid surface is formed by combining a coating of 10-MCC with a superhydrophobic surface. The construction of superhydrophobic surfaces typically involves creating a rough surface with a distinctive structure produced by the anodization technique and modifying it with stearic acid. The superhydrophobic surface exhibits excellent corrosion resistance and mechanical stability. Moreover, the hybrid surface shows high efficiency in fog collection, with a tested maximum efficiency of approximately 1.5092 g/cm2/h, 1.77 times that of the original Al sheets. The results demonstrate a remarkable enhancement in fog collection capacity. Furthermore, this work serves as an inspiration for the low-cost and innovative design of engineered surfaces for efficient fog collection.

Chiral Covalent Organic Framework Films with Enhanced Photoelectrical Performances.

The desirable superimposed stacking of two-dimensional covalent organic frameworks (2D COFs) benefits out-of-plane charge transfer, whereas the actual stacking deviation cannot leverage the potential of 2D COFs for optoelectrical applications. Herein, we report a chirality-induced strategy to control the parallel AA-stacking sequence for the β-ketoenamine-linked COF film supported on a FTO substrate. The resulting chiral modules are periodically distributed at the framework node, ensuring identical mirrored configurations of layers for parallel stacking. Such unique architectonics exhibit the prolonged charge carrier lifetime, fast charge-transfer dynamics, and ultrahigh electron collection efficiency, thereby allowing for the excellent photocurrent response of 38 μA/cm2 at 0.25 V (vs RHE). The origin of superior performances lies in the intensified exciton gradient distribution and electron density for photoinduced electron-hole dissociation and charge transfer, in stark contrast to achiral analogues. This study highlights the stacking sequence regulated by chiral nanoarchitectonics and promises great potential of chiral COFs in photoelectrical catalysis.

Deterministic Areal Enhancement of Interlayer Exciton Emission by a Plasmonic Lattice on Mirror.

The emergence of interlayer excitons (IX) in atomically thin heterostructures of transition metal dichalcogenides (TMDCs) has drawn great attention due to their unique and exotic optical and optoelectronic properties. Because of the spatially indirect nature of IX, its oscillator strength is 2 orders of magnitude smaller than that of the intralayer excitons, resulting in a relatively low photoluminescence (PL) efficiency. Here, we achieve the PL enhancement of IX by more than 2 orders of magnitude across the entire heterostructure area with a plasmonic lattice on mirror (PLoM) structure. The significant PL enhancement mainly arises from resonant coupling between the amplified electric field strength within the PLoM gap and the out-of-plane dipole moment of IX excitons, increasing the emission efficiency by a factor of around 47.5 through the Purcell effect. This mechanism is further verified by detuning the PLoM resonance frequency with respect to the IX emission energy, which is consistent with our theoretical model. Moreover, our simulation results reveal that the PLoM structure greatly alters the far-field radiation of the IX excitons preferentially to the surface normal direction, which increases the collection efficiency by a factor of around 10. Our work provides a reliable and universal method to enhance and manipulate the emission properties of the out-of-plane excitons in a deterministic way and holds great promise for boosting the development of photoelectronic devices based on the IX excitons.

Assessment of a hybrid solar water heating system: environmental impact and economic viability

ABSTRACT Conventional methods of space heating are not only expensive but also environmentally harmful, as they emit greenhouse gases that contribute to global warming. To tackle this issue, a hybrid solar water heating system assisted by a solar evacuated tube collector has been developed at the Madhav Institute of Technology and Science in Gwalior, India. Experiments conducted from November to February 2022–23 (winter season) revealed promising results. Throughout the winter season, the system achieved a daily average effective solar heat collection of 2.85 kWh, with a daily average collector efficiency of 45.5%. The average coefficient of performance (COP) of the solar water heat exchanger was 3.5. Additionally, the system demonstrated an energy payback time of 1.2 years, shorter than that of conventional systems. Over its lifetime, the developed winter heating system is estimated to mitigate 127.9 tonnes of CO2 emissions, earning a carbon credit of $1408. Economic analysis further revealed a favorable benefit-to-cost ratio for the hybrid system, ranging from 3.13 to 3.36, with a payback period varying from 5.03 to 4.47 years for an inflation rate of 6–13%. These findings affirm the feasibility and efficacy of a solar-powered hybrid active winter heating system.

An intelligent BIM-enabled digital twin framework for real-time structural health monitoring using wireless IoT sensing, digital signal processing, and structural analysis

Structural health monitoring (SHM) of civil infrastructure is critically important due to its direct influence on public safety and economic activities. Exiting Building Information Modeling (BIM)-based SHM systems often use offline data processing techniques to analyze and visualize structural health data. Despite some of them adopting Internet of Things (IoT) to enable real-time sensor data collection, sensor data quality still remains uncertain due to a lack of sensor signal preprocessing in those existing systems. Additionally, the IoT-based SHM systems often disregard structural analysis domain knowledge, which is important for accurate and precise SHM. Therefore, there is still a need to improve existing systems and practices by enabling more efficient and reliable data collection and processing as well as providing more representative SHM data visualization in BIM. As such, this paper proposes an intelligent BIM-enabled digital twin (DT) framework that integrates wireless IoT sensing and communication, digital signal processing (DSP), and structural analysis domain knowledge. The proposed system (1) leverages IoT sensing and wireless communication to enable autonomous and real-time SHM sensor data collection and transmission, (2) applies and compares multiple DSP techniques to preprocess the sensor data/signals, and (3) innovatively embraces structural analysis expertise into structural behavior visualization in BIM by performing sensor data interpolation for enabling the visualization of structural behaviors at different locations of a structural element/component. The proposed BIM-enabled DT framework was demonstrated and tested for monitoring and visualizing the structural deformations of critical structural components using a prototyped structural frame subject to bending forces. The developed framework could be used and extended for any structural elements (such as beams, columns, trusses, slabs, arches, bracings, walls, footings, foundations, and girders, among others) and could be applied to any kind of structure. Experimental results showed that the proposed framework could effectively monitor and intuitively visualize the structural deformations under different load configurations with a high DT updating frequency of 5 Hz. The innovation of this study is reflected by integrating structural analysis expertise with IoT-enabling sensing data analytics in order to improve the representativeness of real-time structural behavior visualization in BIM and to advance the DT-based SHM systems in a faster and more adaptive direction. Ultimately, this paper contributes to the body of knowledge by developing a generic and easily extendable BIM-enabled DT framework for SHM with high sensor data quality and improved visualization to advance the existing practices of BIM-based SHM for civil infrastructure asset management.

Development of a method to measure trace level of uranium and thorium in scintillation films

Abstract We have established a method to measure picograms-per-gram (pg g−1) levels of 238U and 232Th in scintillation films by combining the dry ashing method and inductively coupled plasma mass spectrometry. Trace amounts of 238U and 232Th were measured in up to 2 g of the scintillation film with almost 100% collection efficiency. This paper details the experimental procedure, including the pretreatment of the samples and labware, detection limit of the method, collection efficiencies of 238U and 232Th, and measurement of 238U and 232Th in a polyethylene naphthalate film. This method is also applicable to 238U and 232Th measurements in other low-background organic materials for rare event search experiments.

Deep Reinforcement Learning-Driven UAV Data Collection Path Planning: A Study on Minimizing AoI

As a highly efficient and flexible data collection device, Unmanned Aerial Vehicles (UAVs) have gained widespread application because of the continuous proliferation of Internet of Things (IoT). Addressing the high demands for timeliness in practical communication scenarios, this paper investigates multi-UAV collaborative path planning, focusing on the minimization of weighted average Age of Information (AoI) for IoT devices. To address this challenge, the multi-agent twin delayed deep deterministic policy gradient with dual experience pools and particle swarm optimization (DP-MATD3) algorithm is presented. The objective is to train multiple UAVs to autonomously search for optimal paths, minimizing the AoI. Firstly, considering the relatively slow learning speed and susceptibility to local minima of neural network algorithms, an improved particle swarm optimization (PSO) algorithm is utilized for parameter optimization of the multi-agent twin delayed deep deterministic policy gradient (MATD3) neural network. Secondly, with the introduction of the dual experience pools mechanism, the efficiency of network training is significantly improved. Experimental results show DP-MATD3 outperforms MATD3 in average weighted AoI. The weighted average AoI is reduced by 33.3% and 27.5% for UAV flight speeds of v = 5 m/s and v = 10 m/s, respectively.

Micropatterned Polymer Nanoarrays with Distinct Superwettability for a Highly Efficient Sweat Collection and Sensing Patch.

Wearable sweat sensor offers a promising means for noninvasive real-time health monitoring, but the efficient collection and accurate analysis of sweat remains challenging. One of the obstacles is to precisely modulate the surface wettability of the microfluidics to achieve efficient sweat collection. Here a facile initiated chemical vapor deposition (iCVD) method is presented to grow and pattern polymer nanocone arrays with distinct superwettability on polydimethylsiloxane microfluidics, which facilitate highly efficient sweat transportation and collection. The nanoarray is synthesized by manipulating monomer supersaturation during iCVD to induce controlled nucleation and preferential vertical growth of fluorinated polymer. Subsequent selective vapor deposition of a conformal hydrogel nanolayer results in superhydrophilic nanoarray floor and walls within the microchannel that provide a large capillary force and a superhydrophobic ceiling that drastically reduces flow friction, enabling rapid sweat transport along varied flow directions. A carbon/hydrogel/enzyme nanocomposite electrode is then fabricated by sequential deposition of highly porous carbon nanoparticles and hydrogel nanocoating to achieve sensitive and stable sweat detection. Further encapsulation of the assembled sweatsensing patch with superhydrophobic nanoarray imparts self-cleaning and water-proof capability. Finally, the sweat sensing patch demonstrates selective and sensitive glucose and lactate detection during the on-body test.

Drivers of success in global health outcomes: A content analysis of Exemplar studies.

Applying a positive outlier lens is one effective approach for generating evidence to inform global health policy, program, and funding decisions. Exemplars in Global Health (EGH) is a program that studies positive outlier countries that have made extraordinary progress in health outcomes (despite limited resources) and disseminates their successes through multiple types of outputs. To date, EGH has studied, or is studying, 14 global health topics in 28 countries. This paper aims to identify findings, summarized as themes and sub-themes, that appear among all completed EGH studies. We developed a conceptual framework and used a content analysis approach to identify the top thematic areas that appear as drivers for programmatic success across EGH studies that were completed between June 2020-May 2023. The EGH studies (N = 31) spanned six topics including under-five child mortality (n = 6), childhood stunting (n = 5), community health workers (CHW) (n = 4), vaccine delivery (n = 3), COVID-19 response (n = 6), and newborn and maternal mortality reduction (n = 7) across 19 countries in sub-Saharan Africa, Latin America, South and Central Asia, and the Caribbean regions. Top drivers of success were defined as those critical or catalytic in achieving the intended outcome. Eight key drivers were identified: (1) efficient data collection and use for decision-making, (2) strong political commitment and health leadership, (3) effective stakeholder coordination, (4) a local, connected, and capacitated workforce, (5) intentional women's empowerment and engagement, (6) effective adoption and implementation of national policies, (7) effective and sustainable financing, and (8) equitable, efficient outreach and targeting. These cross-cutting drivers span a broad range of development outcomes, sectors, and populations, and indicate a need to effectively integrate people, systems, and sectors to improve global health outcomes. Findings from this study aim to support peer learning among countries and support evidence-based decision-making for funders, policymakers, and other key stakeholders.

Effect of Community Building on Church Spiritual Growth

Purpose: This study investigates the relationship between community building and spiritual growth within Pentecostal Churches in the Nairobi metropolitan counties of Kenya, focusing on the Pentecostal Evangelical Fellowship of Africa (PEFA), Kenya Assemblies of God (KAG), and Full Gospel Churches of Kenya (FGCK) under the National Council of Churches of Kenya (NCCK). Grounded in servant leadership, empowerment, and spiritual leadership theories, the research combines quantitative and qualitative methods to explore how servant leaders facilitate community building and its impact on church growth. Methodology: The study was guided by servant leadership, empowerment and spiritual leadership theories. The study was conducted across multiple Pentecostal denominations within the Nairobi Metropolitan counties, including Nairobi, Kajiado, Muranga, Kiambu, and Machakos in Kenya. Data collection involved 333 church leaders and members, with 173 from PEFA, 80 from KAG, and 80 from FGCK, resulting in a response rate of 91%. Additionally, two discussion groups comprising pastors and elders from PEFA and KAG churches in Kajiado County were interviewed using an interview guide, totaling 17 members. The total response rate of church leaders and members was 304 (91%). The descriptive cross-sectional survey research design and exploratory designs were adopted for data collection and analysis where respondents provided relevant data. The research was anchored on the pragmatism philosophy. Quantitative data was analyzed using descriptive statistics, correlation and regression analysis, where Statistical Package for Social Sciences (SPSS) version 29 was used. Thematic analysis was employed in analyzing qualitative type of data. Purposive and stratified random sampling techniques were employed to select the sample, ensuring representation of subgroups within the population. This approach facilitated efficient and cost-effective data collection while maintaining the integrity of the study's findings Findings: Data collected from 304 respondents, including pastors, elders, and members, reveals a significant positive association between community building and spiritual growth, with volunteer services rating relatively low. The results showed a positive significance of community building in affecting church spiritual growth. The study findings in all the three models: Model summary, ANOVA and Coefficient confirm the significance of community building in church spiritual growth. The correlation coefficient results yielded a positive relationship of 0.580. However, descriptive statistics on mean scores of how respondents views the practice of community building in their churches, the sub variable of voluntary community services was ranked the lowest (3.7) amongst the other constructs. Nevertheless, there is a need for enhancement of voluntary services by the Pentecostal churches in areas such as health, free cleaning and training services to give back to the community. When church leadership participate in welfare activities such as helping the vulnerable in society, this positively affects church growth both spiritually and numerically. The findings emphasize the importance of enhancing volunteer engagement to foster both spiritual and numerical church growth. This study contributes to theoretical understanding and practical implications for Pentecostal church settings, addressing research gaps and advocating for servant leadership practices that empower church members and promote community building for holistic church growth.Contribution to Theory, Policy and Practice: The study supported servant leadership, empowerment and spiritual leadership theories. Servant leaders play a crucial role in empowering of church members through community building causing effect on church growth. The study revealed and filled a number of conceptual, theoretical, contextual and empirical glaring research gaps in area of servant leadership attribute of community building and church spiritual growth. The most noticeable gap is the contextual gap where many studies on church growth only delved on numerical growth and leaving out spiritual growth of which this study addressed. The study also revealed a gap in volunteer services with a mean of 4.1. Pentecostal churches therefore need to put more efforts to improve volunteer services as well as promotion of spiritual formation so as to enhance church spiritual growth.

Photoelectrochemical Communication Between Cyanobacteria and Electrospun Cellulose‐Acetate–Graphene‐Based Electrodes for Photosynthetic and Respiratorial Photocurrent and Hydrogen Generations via Sustainable Solar Energy

In this article, the potential of biophotovoltaic devices (BPVs) as a sustainable solution for addressing the global energy crisis and combating climate change is explored. BPVs harness renewable electricity from sunlight and water through the photosynthetic activity of microorganisms, such as cyanobacteria and algae, serving as living photocatalysts. The focus is primarily on enhancing photocurrent outputs by developing efficient anode materials. Carbon‐based electrodes, particularly graphene (Gr), emerge as promising candidates due to their cost‐effectiveness, electrical conductivity, and mechanical strength. Despite reduced graphene oxide being commonly used, unoxidized Gr has not been extensively explored until recent research demonstrating its excellent current harvesting capacities. Additionally, 1D‐structured nanomaterials, such as electrospun nanofibers, show potential in promoting electron transport and enhancing charge collection efficiency. An innovative photoanode design is introduced, utilizing cyanobacteria immobilized on a cellulose acetate/Gr electrospun mat, offering a porous structure conducive to cyanobacterial attachment and efficient electron transfer. A complementary cathode structure, employing aniline‐modified Pt nanoparticles, facilitates the reduction of protons to yield hydrogen gas. Overall, in this study, BPVs’ potential is highlighted as a viable clean energy technology and novel approaches to enhance their efficiency and sustainability are presented.

A straightforward technique to obtain genomic DNA from nasal swabs suitable for sheep SNP genotyping analysis

Isolation of high quality and quantity genomic DNA is essential for molecular studies. It is crucial to select a non-invasive and straightforward technique to ensure the efficient collection of DNA, particularly at the farm level. The aim of this study was to determine if nasal swabs are an appropriate biological matrix to obtain good quality genomic DNA suitable for SNP genotyping. In this study, two biological matrices (blood and nasal swabs) were evaluated and compared for the isolation of genomic DNA obtained from 15 female Texel sheep. DNA quality and quantity were assessed using spectrophotometry and gel electrophoreses. Genotype concordance rates were used for comparison. Results showed that the highest concentration mean was obtained from blood samples (159.14 ng/µl), while from nasal swab samples the concentration mean was lower (130.12 ng/µl), but the difference was non-significant. Regarding purity, DNA obtained from nasal swabs presented a higher A260/A280 ratio (1.96), while the one obtained from blood samples was 1.90. Total DNA yield obtained from blood samples (15.91 µg) was significantly higher than the one obtained from nasal swabs (6.51). Blood and nasal swab genotyping concordance rates were high (mean = 0.984). In conclusion, our results indicate that nasal swabs can yield good quality DNA; however, the DNA extraction protocol should be optimized.

The Role of AI in Management

This study investigates "The Role of AI in Management" and aims to understand the impact of AI technologies on various management practices within organizations. The problem of the study arises from the increasing adoption of AI in the business world and the need to comprehend its implications for managerial decision-making, organizational efficiency, and employee experiences. The study focuses on both theoretical and practical aspects, providing insights that can inform academic research and guide organizations in leveraging AI effectively. To address the research problem, a cross-sectional study design using a questionnaire as the primary data collection tool has been selected. This design allows for the collection of quantitative data at a specific point in time, providing a snapshot of the relationship between AI and management practices. The questionnaire will be administered to professionals and managers across diverse industries, representing organizations that have implemented AI technologies in their management processes. The importance of this study lies in its theoretical and practical contributions. Theoretically, it expands the understanding of the role of AI in management by examining its impact on decision-making processes, organizational structures, and employee roles. It contributes to the existing body of knowledge by exploring the nuances and complexities of AI implementation in managerial contexts. Practically, the findings will provide insights and recommendations for organizations seeking to adopt or optimize AI technologies in their management practices. It will guide decision-makers in understanding the potential benefits, challenges, and best practices associated with AI integration. The scope of this study encompasses professionals and managers across various industries, ensuring a diverse representation of AI adoption in management practices. The focus is on organizations that have implemented AI technologies and are actively utilizing them in their decision-making processes, resource allocation, and performance evaluation. The study aims to capture the perceptions, experiences, and attitudes of participants related to the role of AI in management. Data will be collected through a structured questionnaire distributed electronically to the selected participants. The questionnaire will capture quantitative data on participants’ perceptions, experiences, and attitudes towards AI in management. It will include closed-ended and Likert-scale questions, enabling efficient data collection and analysis. The collected data will be analyzed using appropriate statistical techniques, including descriptive statistics, correlation analysis, and regression analysis. By employing this methodology and research tools, this study seeks to provide a comprehensive understanding of the impact of AI on management practices. The findings will contribute to both theoretical knowledge and practical insights, guiding organizations in leveraging AI effectively to enhance decision-making, improve operational efficiency, and foster innovation in management processes.

A Real-to-Sim-to-Real Approach for Vision-Based Autonomous MAV-Catching-MAV

This paper studies the task of vision-based MAV-catching-MAV, where a catcher MAV (micro aerial vehicle) can detect, localize, and pursue a target MAV autonomously. Since it is challenging to develop detectors that can effectively detect unseen MAVs in complex environments, the main novelty of this paper is to propose a real-to-sim-to-real approach to address this challenge. In this method, images of real-world environments are first collected. Then, these images are used to construct a high-fidelity simulation environment, based on which a deep-learning detector is trained. The merit of this approach is that it allows efficient automatic collection of large-scale and high-quality labeled datasets. More importantly, since the simulation environment is constructed from real-world images, this approach can effectively bridge the sim-to-real gap, enabling efficient deployment in real environments. Another contribution of this paper lies in the successful implementation of a fully autonomous vision-based MAV-catching-MAV system including proposed estimation and pursuit control algorithms. While the previous works mainly focused on certain aspects of this system, we developed a completely autonomous system that integrates detection, estimation, and control algorithms on real-world robotic platforms.

The Impact of Geographic Factors on Credit Risk: A Study of Chinese Commercial Banks

Abstract Controlling credit risk is crucial for maintaining financial stability, and the role of geographic factors in this regard is a significant concern for scholars and policymakers. Drawing on the concept of information asymmetry, we developed a theoretical model to analyze how geographic factors influence credit risk. Our theoretical proposition suggests that the spatial organization of banks affects the efficiency of collecting and processing soft information, ultimately impacting the credit risk. To test this proposition, we collected microdata from Chinese commercial banks spanning the period from 2011 to 2022. Employing a mediating effect model, we empirically examined the relationship between spatial organizational structure and credit risk. Our results indicate that the distance between bank operations and functional distance impedes the collection and processing of soft information, thereby exacerbating credit risk in banks. The study focuses on examining how the spatial organizational structure of Chinese commercial banks affects credit risk. By analyzing geographic factors and information asymmetry, the study aims to understand how the organization of banks influences the collection and processing of soft information, which in turn impacts the credit risk. Furthermore, our analysis of the sample reveals that the mediating role of soft information varies between state-owned banks and joint-stock banks due to their distinct customer profiles. On the basis of these findings, we propose several policy recommendations, including a focus on enhancing the collection and processing of soft information, promoting the growth of locally based small and medium-sized banks, and reducing information barriers within bank hierarchies.

Formation of a potential barrier by a ZnSXSe1−X electron-blocking layer to improve the efficiency of CdSe0.3S0.7/CdSe quantum dot sensitized solar cells

We designed and fabricated multilayer quantum dots sensitized solar cells (QDSCs) with TiO2 NPs/CdSe0.3S0.7/CdSe/ZnSXSe1−X, X = S/S + Se = 0, 0.7, 0.8, 0.9, and 1 photoelectrodes to achieve optimum power conversion efficiency (PCE). In the corresponding structure, incoming light is absorbed by the CdSe0.3S0.7 and CdSe quantum dots (QDs), while the ZnSXSe1−X QDs act as an electron blocking layer or passivation layer, forming an energy barrier that restricts electron mobility from the light absorbers to the polysulfide electrolyte. The beneficial effect of the alloyed ZnSXSe1−X layer is the adjustability of its nanoparticle size/bandgap energy proportional to variations in the concentration of anionic precursors X, according to optical results. The PCE value of the reference cell with the TiO2 NPs/CdSe0.3S0.7/CdSe photoanode is 4.15 %. Following the coating of ZnSe, ZnS0.7Se0.3, ZnS0.8Se0.2, ZnS0.9Se0.1, and ZnS QDs via two successive ionic layer adsorption and reaction (SILAR) cycles (2Sc) on the CdSe0.3S0.7/CdSe co-sensitized photoelectrode increasing stability and improving the PCE value to 4.9 %, 5.40 %, 5.70, 5.25 %, and 5.05 %, respectively. Next, by modifying the thickness of the champion cell's passivation layer, the QDSCs with TiO2 NPs/CdSe0.3S0.7/CdSe/ZnS0.8Se0.2 (3Sc) photoelectrode exhibit maximum photovoltaic performance parameters of short circuit current density (JSC) = 26.25 mA/cm2, open circuit voltage (VOC) = 560 mV, fill factor (FF) = 0.42 % and PCE = 6.15 %. This improvement in performance is the result of decreased internal energy loss and recombination of charge carriers at the interface between the electrolyte and photoelectrode, which increases electron collection efficiency and electron injection efficiency in the visible region according to the external and internal quantum efficiency curves.

A Review on Underwater Collection and Transportation Equipment of Polymetallic Nodules in Deep-Sea Mining

In response to the anticipated scarcity of terrestrial land resources in the coming years, the acquisition of marine mineral resources is imperative. This paper mainly summarizes the development of underwater collection and transportation equipment of polymetallic nodules in deep-sea mining. Firstly, the collection equipment is reviewed. The deep-sea mining vehicle (DSMV), as the key equipment of the collection equipment, mainly includes the collecting device and the walking device. The micro and macro properties of sediments have a great influence on the collection efficiency of mining vehicles. For the collecting device, the optimization of the jet head structure and the solid–liquid two-phase flow transport of the hose are discussed. The structure of the walking device restricts mining efficiency. The optimization of the geometric structure is studied, and the geometric passability and lightweight design of the walking device are discussed. Secondly, the core of transportation equipment is the lifting device composed of a riser and lifting pump. In order to explore the key factors affecting mineral transport, the lifting device is summarized, and the design optimization of the lifting pump and the factors affecting the stability of the riser are discussed. Then, the relationship between each device is discussed, and the overall coupling of the device is summarized. Finally, the existing problems and future research focus are summarized.

Simultaneous Mapping of Electrocatalytic Activity and Selectivity via Hybrid Scanning Electrochemical Probe Microscopy.

Nanoscale scanning electrochemical probe microscopy started to elucidate the heterogeneity of electrocatalytic activity at electrode surfaces. However, understanding the heterogeneity in product selectivity, another crucial aspect of interfacial reactivity, remains challenging. Herein, we introduce a method combining scanning electrochemical microscopy (SECM) and scanning electrochemical cell microscopy (SECCM) to enable the spatially resolved mapping of both activity and selectivity in electrocatalysis. A dual-channel nanopipette probe was developed: one channel for activity mapping and the other for product detection with a high collection efficiency (>95%) and sensitivity. Simultaneous mapping of activity and selectivity in the oxygen reduction reaction (ORR) is demonstrated. Combined with colocalized crystal orientation mapping, we uncover the local electrocatalytic performance of ORR at different facets on polycrystalline Pt and Au. The high-resolution selectivity mapping enabled by our method with colocalized structural characterization can provide structure-activity-selectivity relationships that are often unavailable in ensemble measurement, holding promise for understanding key structural motifs controlling interfacial reactivity.