Wide Range Of Application Prospects Research Articles

Structural Design on Porous Aromatic Frameworks for Photocatalysis

Photocatalytic technology has shown great potential in various fields such as environmental purification, energy conversion, and chemical transformations due to its green, sustainable, and low‐cost characteristics. Porous aromatic frameworks (PAFs) with high specific surface areas, designable local structures, and abundant active sites could potentially serve as efficient photocatalysts for various catalytic reactions. This makes PAFs have a wide range of application prospects and significant advantages in the field of photocatalysis. This concept discusses the recent progress of photocatalysis over PAFs. Various strategies are used to solve the general problems of photocatalyst, such as poor light absorption, low carrier separation efficiency and poor stability, which further reveal the relationship between their structure and performance.

Edge-dependent photogalvanic effect in 1T′-ReS2-based polarization self-powered photodetectors

Polarization photodetectors with linear/circular photogalvanic effect (L/CPGE) have garnered significant attention due to their wide range of application prospects. However, few kinds of photodetectors are adept at distinguishing between LPGE and CPGE. Here, we investigated a type of polarization-sensitive photodetector based on 1T′-ReS2 nanoribbon (1T′-ReS2 NR) within the framework of density functional theory. It is found that the CPGE photocurrent of 1T′-ReS2 NR along the zigzag direction can be 102 to 103 times larger than that of LPGE. Moreover, the sensitivity to polarized light of 1T′-ReS2 NR can be significantly enhanced. The extinction ratio can be up to 55, which is 4.6 times higher than that the 1T′-ReS2 monolayer. Remarkably, the introduction of magnetism through edge effects enables 1T′-ReS2 NR photodetector to achieve a spin injection efficiency close to 100%. Our results provide an avenue for the design of high-photosensitivity and low-power spintronic devices.

Intelligent Assisted Travel Wheelchair Based on Image Recognition Technology

This paper introduces an intelligent image recognition system integrated into a wheelchair based on deep learning in cold environments, aiming to improve the convenience and safety of disabled individuals. The system adopts advanced image recognition technology to monitor road conditions in real-time through the camera and to detect and measure distance to foreign objects on the road. The system visualizes the detection results on the wheelchair screen to assist the user in avoiding and improving the safety of their daily travel. In addition, the system also includes crawler tracks, seat heating, snow and rain protection, and other functions. The wheelchair has a wide range of application prospects and development potential. It is expected to be widely used in the future, providing a strong guarantee for the safe travel of disabled individuals in China.

Experimental and simulation study on seismic performance of seawater sea-sand PVA cementitious composite columns with GFRP bars

The seismic properties of seven seawater sea-sand (SWSS) PVA cementitious composite columns with Glass Fiber Reinforced Polymer (GFRP) bars were studied. The effects of four parameters, namely polyvinyl alcohol (PVA) fiber content, axial compression ratio, cementitious composite strength and stirrup spacing, on the seismic performance of composite columns were analyzed. The failure of the specimen was observed, and the hysteresis curve, skeleton curve, stiffness degradation, energy dissipation capacity, ductility and strain of the specimen were analyzed. The test results show that the large chip-based spalling will occur when the specimen without fiber incorporation is damaged, and the incorporation of PVA fiber, the reduction of stirrup spacing and the reduction of axial compression ratio will delay the rate of crack formation and development. In addition, through cross-section analysis and considering the reinforcement effect of PVA fibers, a proposed formula for calculating the horizontal bearing capacity of composite columns is proposed. Finally, the finite element model of SWSS PVA cementitious composite columns with GFRP bars is established, and it is found that increasing the strength grade of cementitious materials can greatly improve the seismic performance of composite columns. The conclusions could be references for the engineering application. In the context of the global emphasis on green development and environmental protection, seawater and sea-sand cementitious composites and components with fiber reinforcement will have a wide range of application prospects in the construction of coastal areas.

Quasi-static/dynamic energy absorption characteristics and micromechanical behavior of Al/Ep cast metal braided tubular structures

As a low-density, high-strength material with high energy release potential, Al/Ep cast metal braided tubes have a wide range of application prospects in the combatant shell, which is one of the most important means to realize the integrated destructive effect of kill and blast. In this paper, Al/Ep composites with mass ratios of 3:7, 4:6 and 5:5 were prepared, and the intrinsic model of Al/Ep was established by studying its quasi-static and dynamic mechanical properties. The Al/Ep cast three-dimensional braided metal skeletons were used to obtain the required cast braided tubes with different mass ratios, and the destruction behaviors of the tubes under axial and radial compressive loads were analyzed by a combination of experimental and numerical simulations. The results show that the addition of Al particles can significantly improve the elastic-plastic properties of Al/Ep composites, and the energy storage and absorption capacities are positively correlated with the ratio of the relative contents of Al powder. When the mass ratio of Al powder to epoxy resin is 5:5, the energy absorption of Al/Ep composites is 23.16 MJ/m3, which is optimal among similar specimens and much higher than that of pure epoxy resin materials (the energy absorption of epoxy resin is 9.63 MJ/m3). The strength of binary resin matrix composites is improved, and the intrinsic models of three kinds of different mass ratios of Al/Ep composites are obtained. The intrinsic models of various Al/Ep cast braided tubes with crushing force efficiency CFE, energy absorption capacity, and specific energy absorption SEA decreased with the ratio of mass occupied by the braided filaments.

Study on the suppression of secondary electron emission characteristics based on TiN

Abstract With the continuous development of satellite communications, the problem of high-frequency high-power multipactor caused by the miniaturization of microwave passive components in the aerospace field has become more and more serious. In this paper, for the problem of multipactor suppression of load passive devices, we carried out research on the preparation of TiN thin films based on PEALD and put forward a new method for suppressing SEE with good suppression effect, high consistency, low surface resistance, and other aspects of the unity of the multipactor effect. The use of 20nm TiN coating can make the silver-plated surface secondary electron emission coefficient down to 1.59. The RF surface resistance change rate is less than 3%. In the field of communication, satellite and navigation and other fields have a wide range of application prospects.

Electron spins from a molecular perspective: an interview with Song Gao.

Spin chemistry has emerged as an interdisciplinary field that focuses on electron spins in molecules and related applications in physics, chemistry, biology, materials science and information science. It will play a crucial role in technological innovations. The chemistry of spins is deeply related to the essence of chemical bonds, chemical catalysis, enzyme catalysis, optical and electromagnetic properties, quantum computation and quantum precision measurements. The related research is intersectional, cutting-edge and has a wide range of application prospects. National Science Review (NSR) recently interviewed Prof. Song Gao to discuss spin chemistry. Prof. Gao is a renowned inorganic chemist and an academician of Chinese Academy of Sciences. He is the president of Sun Yat-sen University and the founder of the Spin-X Institute of South China University of Technology. He is recognized as a leader in coordination chemistry and molecular magnetism, and has strong academic influence. Since 2008, he has served on the International Advisory Committee of International Conference on Molecule-Based Magnets, and organized and chaired its 2010 conference. Prof. Gao's primary research topics include molecular nanomagnets; the relationship between geometric structures, electronic structures and magnetism of molecules; and the spin states and reactivity of molecules.

Application of bio-based modified graphene oxide in epoxy composite coatings

This study focuses on the application of bio-based modified graphene oxide epoxy composite coatings and analyzes the coating properties, such as anticorrosive ability, hydrophobicity and self-healing properties, through experimental studies of modified graphene oxide using substances such as cashew nut phenol, lignin and glutamic acid. Summarizing the latest research progress, it is found that the materials such as cardanol, lignin and glutamic acid are from a wide range of sources, are green and have a wide range of application prospects, and it is also shown in the results of EIS analysis that the modified graphene oxide epoxy compliant coatings exhibit higher impedance values at low frequencies, and have good protective properties and barrier properties. The cashew phenol-modified graphene oxide epoxy coating has high densification, high barrier capacity and high hydrophobicity in addition to good coating healing ability using GO modification. The glutamate-modified graphene oxide epoxy coating can be desorbed by using HCL solution to make L-Glu/GO reusable, with good reusability and high application value.

Lonicerae Japonicae Flos with the homology of medicine and food: a review of active ingredients, anticancer mechanisms, pharmacokinetics, quality control, toxicity and applications.

Lonicerae Japonicae Flos (LJF, called Jinyinhua in China), comes from the dried flower buds or flowers to be opened of Lonicera japonica Thunb. in the Lonicera family. It has a long history of medicinal use and has a wide range of application prospects. As modern research advances, an increasing number of scientific experiments have demonstrated the anticancer potential of LJF. However, there is a notable absence of systematic reports detailing the anti-tumor effects of LJF. This review integrates the principles of Traditional Chinese Medicine (TCM) with contemporary pharmacological techniques, drawing upon literature from authoritative databases such as PubMed, CNKI, and WanFang to conduct a comprehensive study of LJF. Notably, a total of 507 compounds have been isolated and characterized from the plant to date, which include volatile oils, organic acids, flavonoids, iridoids, triterpenes and triterpenoid saponins. Pharmacological studies have demonstrated that LJF extract, along with components such as chlorogenic acid, luteolin, rutin, luteoloside, hyperoside and isochlorogenic acid, exhibits potential anticancer activities. Consequently, we have conducted a comprehensive review and summary of the mechanisms of action and clinical applications of these components. Furthermore, we have detailed the pharmacokinetics, quality control, and toxicity of LJF, while also discussing its prospective applications in the fields of biomedicine and preventive healthcare. It is hoped that these studies will provide valuable reference for the clinical research, development, and application of LJF.

A review of advanced helical fibers: formation mechanism, preparation, properties, and applications.

As a unique structural form, helical structures have a wide range of application prospects. In the field of biology, helical structures are essential for the function of biological macromolecules such as proteins, so the study of helical structures can help to deeply understand life phenomena and develop new biotechnology. In materials science, helical structures can give rise to special physical and chemical properties, such as in the case of spiral nanotubes, helical fibers, etc., which are expected to be used in energy, environment, medical and other fields. The helical structure also has unique charm and application value in the fields of aesthetics and architecture. In addition, helical fibers have attracted a lot of attention because of their tendrils' vascular geometry and indispensable structural properties. In this paper, the development of helical fibers is briefly reviewed from the aspects of mechanism, synthesis process and application. Due to their good chemical and physical properties, helical fibers have a good application prospect in many fields. Potential problems and future opportunities for helical fibers are also presented for future studies.

A Review of the Current Research Status of Graphene for the Removal of Microplastics and Antibiotics from Water

As highly representative pollutants among emerging pollutants, antibiotics and microplastics are characterized by strong bioaccumulation, difficult degradation, and high toxicity, and along with the increasing use, the crisis of synergy between the two is increasing. Graphene, a material with high specific surface area and high reactivity, has a wide range of application prospects in the field of water treatment, especially graphene oxide and graphene composites make the application of this material has a certain diversity. The research on graphene and its composites in water membrane treatment and catalytic degradation for the removal of microplastics and antibiotics in recent years is reviewed to explore the research trends and hotspots, and to explore the research prospects.

A Novel Dataset Replenishment Strategy Integrating Time-Series InSAR for Refined Landslide Susceptibility Mapping in Karst Regions

The accuracy of landslide susceptibility mapping is influenced by the quality of sample data, factor systems, and assessment methods. This study aims to enhance the representativeness and overall quality of the sample dataset through an effective sample expansion strategy, achieving greater precision and reliability in the landslide susceptibility model. An integrated interpretative framework for landslide susceptibility assessment is developed using the XGBoost-SHAP-PDP algorithm to deeply investigate the key contributing factors of landslides in karst areas. Firstly, 17 conditioning factors (e.g., surface deformation rate, land surface temperature, slope, lithology, and NDVI) were introduced based on field surveys, satellite imagery, and literature reviews, to construct a landslide susceptibility conditioning factor system in line with karst geomorphology characteristics. Secondly, a sample expansion strategy combining the frequency ratio (FR) with SBAS-InSAR interpretation results was proposed to optimize the landslide susceptibility assessment dataset. The XGBoost algorithm was then utilized to build the assessment model. Finally, the SHAP and PDP algorithms were applied to interpret the model, examining the primary contributing factors and their influence on landslides in karst areas from both global and single-factor perspectives. Results showed a significant improvement in model accuracy after sample expansion, with AUC values of 0.9579 and 0.9790 for the training and testing sets, respectively. The top three important factors were distance from mining sites, lithology, and NDVI, while land surface temperature, soil erosion modulus, and surface deformation rate also significantly contributed to landslide susceptibility. In summary, this paper provides an in-depth discussion of the effectiveness of LSM in predicting landslide occurrence in complex terrain environments. The reliability and accuracy of the landslide susceptibility assessment model were significantly improved by optimizing the sample dataset within the karst landscape region. In addition, the research results not only provide an essential reference for landslide prevention and control in the karst region of Southwest China and regional central engineering construction planning but also provide a scientific basis for the prevention and control of geologic hazards globally, showing a wide range of application prospects and practical significance.

Confinement effect of geocell on the mechanical characteristics of reinforced sand subgrade

Geocell has a confinement effect, limiting the deformation of soil and enhancing the strength of reinforced soil, and has a wide range of application prospects in traffic transportation subgrade engineering. To investigate the confinement effect of geocell on the mechanical characteristics of reinforced sand subgrade, this paper analyzes the macro-mechanical properties of reinforced sand subgrade using triaxial tests, investigates the micro-reinforcement mechanism employing discrete element method (DEM)-based simulations. The potential macro–micro linkages are studied. The experimental results revealed that the volumetric strain of the geocell-reinforced samples increased with the material’s elastic modulus, exhibiting a shear shrinkage phenomenon. The deformation pattern of the reinforced samples presented “segmental deformation,” which differed from that of the unreinforced sand samples. The geocell enhanced the cohesion intercept of the sand samples while having a minimal impact on friction angle. Through the analysis of numerical simulation results, it was found that the geocell constrained the displacement of the soil particles, altering the shear band development trend of the sample and resulting in “segmental deformation”. The geocell facilitated the concentration of force chains, enhancing their stability and resulting in improving the strength in the macro. Additionally, it was observed that the confinement effect of the geocell significantly reduced the fabric and force anisotropy of the granular soil, promoting consistent vertical alignment of force chains. This, in turn, enhanced the vertical force transmission capacity of the sample, explaining the micro-mechanism by which the confinement effect of the geocell increases the peak shear strength of the samples.

Zn-based metal–organic framework for detection and ultra-adsorption of Fe3+ ion and catalytic degradation of methylene blue

Metal-organic frameworks (MOFs) had shown a wide range of application prospects in the removal of pollutants in water because of its designability. In this work, a multifunctional MOF material (S-MOF) had been designed by selecting ligand in advance and introducing specific groups in synthesis process. The S-MOF showed excellent stability. S-MOF could specifically identify Fe3+ ion in water and can selectively remove (442 mg/g) them ultra-efficiently (>99.9 %). Moreover, it can stably identify and remove Fe3+ ion in complex water where many ions exist. It was worth emphasizing that the adsorbed waste (Fe@S-MOF) of S-MOF was also recovered and its properties were studied. Fe@S-MOF exhibited highly efficient catalytic degradation of methylene blue, which could degrade more than 98.7 % of methylene blue, and its pseudo-first-order rate constant was as high as 0.829 min−1. Moreover, the successful preparation of S-MOF and Fe@S-MOF membrane had also simplified the recovery and expanded its application. In general, not only a multi-functional MOF material with application potential had been obtained, but also its recycling promoted the green and sustainable development of MOFs and broadened the road of MOFs materials in development and application.

Research on Automated Modeling Technology of Sluice Gate Project Based on BIM Technology.

In order to improve the efficiency and accuracy of the modeling and design work of the sluice gate project, this paper proposes an automatic generation template of the sluice gate project with customized semantics and project layout scheme, aiming at realizing the rapid assembling of all kinds of components of the sluice gate project. In the construction process, this paper first starts from basic parametric modeling and proposes constraints as the basis of modeling. Subsequently, a template library framework is developed based on the constraints to ensure that the generated templates have a high degree of standardization and consistency. Finally, an efficient and flexible template library is successfully constructed by using the customized classes and functions of Revit API, which provides powerful technical support for the modeling and design work of sluice gate engineering. This achievement helps to promote the informationization and intelligent development of the water conservancy engineering industry, and its versatility and scalability also make it have a wide range of application prospects in other water conservancy engineering fields.

D@MSNs-P/PCL antibacterial nanofibers combined with DBD cold plasma for fresh pork preservation

Fresh pork is easily contaminated by microorganisms, leading to spoilage. Dielectric barrier discharge (DBD) cold plasma technology has shown significant advantages in the preservation of meat. However, severe lipid oxidation of pork resulting from DBD treatment greatly limits its development. Herein, the antibacterial D@MSNs-P/PCL nanofiber membranes were prepared by modification polycaprolactone (PCL) with pre-reported nanomaterials (D@MSNs-P) through electrostatic spinning. Compared with the PCL membranes, the D@MSNs-P/PCL membranes showed better water stability, lower water vapor transmission rate, stronger hydrophobicity, and potent antibacterial activity. The D@MSNs-P/PCL membranes can be used for wrapping fresh pork before treatment with DBD plasma, which can not only improve the antibacterial efficiency but effectively inhibit the lipid oxidation and color change of fresh pork, extending the shelf life for 2 days. The developed D@MSNs-P/PCL membranes can also be used alone to preserve other fresh meat or oily food, with a wide range of application prospects.

Influence of borax on the structure and tribological properties of aluminum alloy plasma electrolytic fluorination film layer

In recent years plasma electrolytic fluorination (PEF), as an emerging surface treatment technology, has been widely used to prepare fluorinated layers on metal surfaces. In this paper, different concentrations of borax are used as additives for plasma electrolytic fluorination of 6061 aluminum alloy. The effect of borax on the discharge characteristics of ion plasma electrolytic fluorination, as well as the coating growth process and the evolution of the tissue structure are systematically investigated. The results show that the surface of the coating prepared by adding a quantitative amount of borax is smoother and flatter, and at the same time has better abrasion and corrosion resistance, so it has a wide range of application prospects in the engineering field.

Mechanically robust superhydrophobic and oleophobic nanofiber membranes with breathability, solvent-resistance, and high-temperature-resistance

Protective materials that can ensure the safety of personnel and equipment in extreme environments have a wide range of application prospects, such as outdoor protective clothing, fire-fighting clothing, etc. However, designing such highly functional materials is still considered a long-standing challenge. Herein, the superhydrophobic and oleophobic fibrous membranes (SOFM) prepared by electrospinning, heat treatment and spraying techniques, endowing the fibrous membranes with good thermal stability, air permeability and outstanding repellence to liquids such as water, oil and low surface energy solvents. The developed SOFM exhibits integrated properties with ethanol intrusion pressure of 0.75 KPa, excellent air permeability of 1.54 mm/s, water vapor transmission rate of 7.99 kg·m−2·d-1, high thermal decomposition temperature of 330 ℃, tensile strength of 9.2 MPa. Therefore, SOFM can effectively protect people and equipment in extreme environments. This work may contribute to the design of fiber materials with higher protection levels in the field of protective clothing.

LSOTB-TIR: A Large-Scale High-Diversity Thermal Infrared Single Object Tracking Benchmark.

Unlike visual object tracking, thermal infrared (TIR) object tracking methods can track the target of interest in poor visibility such as rain, snow, and fog, or even in total darkness. This feature brings a wide range of application prospects for TIR object-tracking methods. However, this field lacks a unified and large-scale training and evaluation benchmark, which has severely hindered its development. To this end, we present a large-scale and high-diversity unified TIR single object tracking benchmark, called LSOTB-TIR, which consists of a tracking evaluation dataset and a general training dataset with a total of 1416 TIR sequences and more than 643 K frames. We annotate the bounding box of objects in every frame of all sequences and generate over 770 K bounding boxes in total. To the best of our knowledge, LSOTB-TIR is the largest and most diverse TIR object tracking benchmark to date. We spilt the evaluation dataset into a short-term tracking subset and a long-term tracking subset to evaluate trackers using different paradigms. What's more, to evaluate a tracker on different attributes, we also define four scenario attributes and 12 challenge attributes in the short-term tracking evaluation subset. By releasing LSOTB-TIR, we encourage the community to develop deep learning-based TIR trackers and evaluate them fairly and comprehensively. We evaluate and analyze 40 trackers on LSOTB-TIR to provide a series of baselines and give some insights and future research directions in TIR object tracking. Furthermore, we retrain several representative deep trackers on LSOTB-TIR, and their results demonstrate that the proposed training dataset significantly improves the performance of deep TIR trackers. Codes and dataset are available at https://github.com/QiaoLiuHit/LSOTB-TIR.

A simple self-supervised learning framework with patch-based data augmentation in diagnosis of Alzheimer’s disease

Alzheimer’s disease (AD) stands as a prominent age-related disorder with significant global impact. Utilizing computer-aided diagnosis aids in the timely identification of mild cognitive impairment, facilitating early intervention and management. Self-supervised learning models have attracted much attention due to their advantages of no manual labeling, so they are very suitable for solving the problems of difficulty in data acquisition and high cost of manual labeling in medical image processing. However, the existing self-supervised algorithms applied to medical images often have poor diagnostic effects and consume large resources, as a consequence, the model’s ability to learn meaningful representations from medical images is hampered, leading to suboptimal performance. Subsequently, diverse patches extracted from the same brain are amalgamated to create contrast views, and attention weights are then employed to enhance the fitting and generalization capacity of the model. Experimental results on the ADNI dataset with 1365 subjects show that PD-SIM has been improved in the diagnosis of different diseases(such as the classification ACC of AD and CN reached 0.797, and the classification ACC of early cognitive impairment reached 0.7036), and also alleviates the problem of large consumption of computer resources, downstream tasks require only 52ms per image. The proposed method performs well in atrophic structure identification and AD diagnosis. Therefore, PD-SIM has a wide range of application prospects and is of great practical significance within the realm of medical image analysis. The data and code can be found at https://github.com/Z1Ting/PD-SIM.