Science and Technology of Engineering, Chemistry and Environmental Protection
ISSN 2959-6157(Print) ISSN 2960-1339(Online) Editor: Cosimo Arnesano (University of Southern California) Science and Technology of Engineering, Chemistry and Environmental Protection which provides a platform for researchers, scholars, and professionals to share their latest findings and insights in the fields of engineering, chemistry, and environmental protection. One of the key reasons why people should choose Science and Technology of Engineering, Chemistry and Environmental Protection as their preferred journal is its multidisciplinary focus. The journal covers a wide range of topics in the fields of engineering, chemistry, and environmental protection, including but not limited to materials science, environmental engineering, chemical synthesis, renewable energy, and pollution control. This breadth of coverage ensures that readers are exposed to the latest and most relevant research in various interdisciplinary areas. The journal is committed to promoting research that has real-world applications and can inform industry and policy-making. As such, readers can expect to find articles that not only contribute to theoretical knowledge but also have practical implications for professionals in these fields. Introducing the chief editor of IEEE will help journals enhance their influence and introduce the most authoritative audit requirements.
The Advancements and Applications of Machine Learning in Predicting Football Scores
Football stands as one of the world's most popular sports, where match prediction significantly contributes to its development and enhances its economic and cultural value. This calls for a comprehensive review of the technology used to predict football scores. The study first examines three traditional machine learning methods with simple single-layer architectures. While these methods are straightforward to understand, they suffer from limitations such as low accuracy and slow computational speed, rendering them less advantageous for practical applications. Subsequently, this paper explores four deep learning approaches, whose multi-layered structures outperform traditional methods in model capacity, learning efficiency, and computational power. Consequently, deep learning has become a primary direction for both current and future research in football scoring prediction. However, these approaches face challenges including generalization, accuracy, and explainability. To address these challenges, this paper proposes adversarial domain adaptation techniques to tackle generalization challenges. The introduction of high-dimensional dynamic feature data enhances accuracy. By integrating models, their respective strengths are leveraged to resolve interpretability challenges, while presenting optimistic prospects for deep learning applications in football scoring prediction. This article provides a comprehensive review of machine learning in football score prediction, which is conducive to readers' in-depth and comprehensive understanding of this field, and provides readers with reference for subsequent independent exploration and innovation.
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Effects of Nanomaterials on Drug Co-encapsulation and Targeted Drug Delivery
Porous nanocarriers have emerged as versatile platforms for overcoming key limitations of traditional drug delivery systems by enabling precise co-encapsulation of multiple therapeutics and highly selective tumor targeting. This review surveys three major categories of nanocarriers, such as lipid-based, polymeric, and inorganic architectures, and highlights representative strategies such as liposome-in-liposome concentrisomes, mesoporous lipid nanoparticles (MLNPs), polymer-gatekeeper hollow silica nanoparticles (PHMSNs), and pH-sensitive gold nanoclusters. The article discuss how co-loading hydrophilic and hydrophobic agents at fixed ratios enhances therapeutic synergy and bypasses multidrug resistance and how surface functionalization or environmental triggers drive tumor-specific accumulation. Key challenges including complex syntheses, high manufacturing costs, immune clearance, premature payload leakage, and regulatory hurdles are examined. Finally, the article outlines current limitations of multi-stage delivery architectures, insufficient deeper tumor penetration, and the absence of robust and scalable production frameworks. By integrating these advances, nanocarriers hold promise for more effective, patient-friendly therapies across oncology and beyond.
Beta-Ga2O3 power semiconductor: material properties, doping and devices
Doping and heterojunction engineering are essential to modern semiconductor technologies, enabling them to have impressive performances. N-type and P-type doping introduce electrons and holes into semiconductor crystals, which are the basis for many electronic devices. Over the years,researchers have achieved precise control of doping in common materials like silicon, but new challenges have emerged with novel materials and nanoscale devices. For instance, some wide-bandgap materials show intrinsic resistance to being doped. At the same time heterojunctions, interfaces between different semiconductor materials, have revolutionized efficiently. The purpose of this paper is to synthesize recent advances and persisting challenges in n-type doping, p-type doping, and semiconductor heterojunctions. Highlighting how improved doping techniques and clever material combinations are addressing these challenges, and providing suggestions for further research. The main conclusion is that while enormous progress has been made -from stabilizing n-type doping in organic films to designing lattice-matched heterostructures for minimal defectsfurther innovation in doping methods remains crucial.
Survey of Communication Modification on Federated Learning
The widespread adoption of artificial intelligence technologies, particularly deep learning, has exposed significant security vulnerabilities that pose substantial challenges to cyberspace safety. Traditional cloud-centric distributed machine learning relies on centralized data collection from participants, making the system vulnerable to security breaches and privacy violations during data exchange and model updates. These risks often result in system performance degradation or sensitive data exposure. Federated Learning emerges as a privacy-preserving distributed machine learning paradigm that mitigates these issues. By facilitating encrypted model parameter exchanges between clients and a central parameter server, while retaining raw data locally, Federated Learning, unlike other training model, enables collaborative model training with significantly reduced privacy leakage risks, at the same time it maintains the performance of the whole training process. However, as deep learning models scale and Federated Learning tasks grow more complex, communication overhead becomes a major barrier to deployment. Consequently, optimizing FL communication efficiency has become a critical research focus.
Highway Traffic Flow Prediction: Methods, Challenges, and Trends
Traffic flow prediction is a core function of intelligent transportation systems. Accurate short‑term forecasts help reduce congestion, support signal control, and improve travel reliability. This paper reviews major methods for highway traffic flow prediction in clear, simple English. We organize the literature into four families: traditional statistical models, classic machine learning (ML), modern deep learning (DL), and hybrid approaches that combine multiple ideas. Statistical models (e.g., ARIMA) are simple and fast but struggle with nonlinear and spatial effects. ML methods (e.g., SVM, random forests, shallow neural networks) capture nonlinear patterns better but often require manual feature design. DL methods (e.g., LSTM/RNN, CNN, and graph neural networks) learn complex spatiotemporal patterns directly from data and now achieve state‑of‑the‑art accuracy on common benchmarks. Hybrids (e.g., ConvLSTM, graph‑attention networks, decomposition+DL) further improve robustness and accuracy. We also summarize widely used datasets and metrics, discuss open challenges (generalization, long‑horizon prediction, real‑time deployment, interpretability), and outline future directions (transfer learning, adaptive graphs and attention, uncertainty estimation, and cloud–edge deployment). The discussion is supported by real, citable studies and public datasets.
Progress in Cathode Materials for Sodium-Ion Batteries and Industrialization Research
With the development of society, humans have begun to pursue and explore more environmentally friendly and cost-effective lifestyles. And sodium-ion batteries, as an emerging industry, are constantly disrupting the traditional battery sector. Since sodium is more abundant than lithium and its cost is also much lower, and it has a high safety factor; it is also an indispensable development direction in the future. This article summarizes the advantages and disadvantages of the anion compounds, Prussian blue-like substances, and layered oxides of the current mainstream sodium-ion battery positive electrode materials, and finds that the cyanide wastewater in the synthesis of Prussian blue needs to be strictly treated, while vanadium-based materials face the problem of mining pollution. In contrast, sodium iron phosphate (NaFePO₄) has the advantages of low cost and low toxicity, and may become the mainstream choice for energy storage stations in the future. This article can promote the development of the research on sodium-ion battery positive electrodes and provides a research basis and direction for the design and improvement of subsequent sodium-ion battery positive electrode materials and manufacturing processes.
Research Progress in CO2 Capture and Storage Technology
With the intensification of global climate change, carbon dioxide (CO₂), as a major greenhouse gas, has become a key focus in achieving sustainable development and carbon neutrality. Carbon Capture and Storage (CCS) technology, an essential method for controlling emissions in industrial and energy sectors, has attracted wide attention. This paper first outlines the primary sources of CO₂ emissions from both daily life and industrial production, highlighting key sectors such as power generation, steel, and cement as major targets for emission control. It then introduces two typical CO₂ capture methods—adsorption and cryogenic separation—explaining their technical principles, advantages, limitations, and applicable scenarios. On the storage side, geological storage technology has matured and has been commercialized in regions such as Northern Europe. Based on this, the paper further explores the future prospects of CCS, emphasizing the need for progress in four areas: technology integration, cost optimization, policy incentives, and market mechanisms. By systematically reviewing current research and practical applications, this paper aims to provide theoretical support and strategic references for CCS development both in China and globally.
Waste Rubber Recycling Technologies and Reclaimed Rubber Applications
Waste rubber has emerged as a critical global concern, with its annual production skyrocketing. These discarded rubber products, resistant to decomposition, not only consume vast land resources but also release harmful substances, polluting soil and groundwater. Moreover, they pose a high - risk fire hazard and emit foul odors, severely degrading the surrounding environment. Simultaneously, as rubber resources are scarce, over 70% of natural rubber in China relies on imports. This review delves into the evolution of reclaimed rubber production technologies, from the 1846 lime chloride boiling method—plagued by pollution and low yields—to contemporary physical (microwave, ultrasound, twin - screw extrusion), chemical, biological, and thermochemical methods. New - age green technologies like supercritical devulcanization are enhancing eco - friendliness and production efficiency. Applications in building materials (such as asphalt modification and rubber concrete) and as fillers in rubber products are also explored. These technologies not only enhance resource utilization by converting waste into value - added materials but also adhere to circular economy principles, supporting environmental protection and contributing to carbon neutrality and the UN Sustainable Development Goals.
Applications of Calculus in Economics: Marginal Function as an Example
Mathematics is the cornerstone of life. It helps people to calculate, plan, predict and solve problems, enhances people’s logical thinking and decision-making abilities, and is widely applied in finance, engineering, technology and other fields, providing strong support for daily life and career development. In addition, calculus is a core tool in modern science and engineering, used to study rates of change (derivatives) and accumulated quantities (integrals). It is indispensable in fields such as physics, economics, and engineering, providing a powerful framework for understanding and solving dynamic problems. This essay will examine the original and applications of calculus. To this end, in this paper the author will focus on how to use calculus to solve some problems in economics field. Besides, the author will also present examples to illustrate the application of calculus in economics, such as marginal function, price elasticity of demand, and so forth. This work highlights the importance of calculus in solving problems of economics.
Influencing Factors of Mental Health Issues among Adolescents
This paper focuses on exploring the influencing factors of mental health issues. Utilizing a binary Logit regression model and a dataset comprising 1,000 samples, it examines the impact of four key variables-stress level, sleep duration, working hours, and physical activity duration-on mental health status. The analytical results reveal that the p-values of all four variables exceed 0.05, indicating that none of them exert a statistically significant effect on mental health. Additionally, the overall prediction accuracy of the model stands at 54.30%, reflecting poor predictive performance. The study suggests that the underperformance of the model may be attributed to weak correlations between the selected variables, the omission of complex factors such as family environment, and limitations in measurement methods. To enhance the explanatory power and prediction accuracy for population mental health issues and provide a solid foundation for formulating intervention strategies, future research should expand the range of variables, optimize measurement methods, and experiment with alternative models.
Radioisotope Thermoelectric Generators in Space Exploration
This research essay will explore the mechanism and performance of radioisotope thermoelectric generators used in spacecrafts, aiming to manifest its validity in the space exploration industry. Data gathered by experts will be utilized to examine its performance, and further compare it with other space power systems. The results indicates that the technology is suitable for powering long-range space missions, and even surpasses new technologies such as advanced Stirling radioisotope generators. Instead of relying on the environment like solar panels, it generates thermal energy using radioactive decay and converts it directly into electricity. Although using thermoelectric effect could lower efficiency, it simplifies the manufacturing process, reducing the cost of its production. This highlights the utility of the technology, and its potential in powering countless more space missions in the future. In the end, the essay will conclude with a summary of main points and the key challenges that lies ahead for radioisotope thermoelectric generators in space exploration.
Radioisotope Thermoelectric Generators (RTG)
Advanced Stirling Radioisotope Generators (ASRG)
Optimization of Geothermal ORC Power Generation Technologies
Grounding the analysis in thermodynamic principles, this comprehensive review systematically deciphers the efficiency constraints inherent in geothermal Organic Rankine Cycle (ORC) power generation technology. Progressing to a coupled examination of working fluid thermophysical properties and system architectural configurations, it reveals the divergent impact of environmental regulations and resource endowment on technological pathway selection. Through comparative assessment of globally representative cases (including Iceland's high-enthalpy fields, Hubei's policy-driven zones, and North China's hybrid models), the study turns out to elucidate how regional development disparities precipitate technical standard fragmentation. Conclusively, a synergistic technology-policy framework is proposed, demonstrating the integrated value of supercritical CO₂ working fluids, artificial intelligence optimization, and carbon pricing mechanisms (e.g. CBAM) in overcoming efficiency barriers. The perspective extends to ORC's evolving role within smart energy networks, projecting its transition toward baseload integration in future energy internet ecosystems. Last but not the least, this review does not involve complex theoretical analysis, system integration, or component analysis. Its purpose is to help beginners understand the underlying logic.
Jet Engine: Evolution, 3D Printing Applications, and Future with Clean Energy
The development of jet engines is the key to driving the development of the aviation industry and changing the military, economic, and social landscape. This article reviews the evolution of jet engine technology, from early piston engines to modern turbofan engine systems, emphasizing their role in achieving higher speeds, altitudes, and fuel efficiency. It explored key innovations such as 3D printing, with practical applications including GE Aviation, Rolls Royce and Pratt & Whitney’s 3D printing components, demonstrating potential to reduce weight, material waste, and production time. However, challenges such as component consistency and scalability still exist. In addition, this article also investigates clean energy alternatives, particularly hydrogen. It can eliminate carbon emissions, but its application still faces challenges such as high combustion rates, high-temperature nitrogen oxide emissions, and high resource and economic costs. Through a review of existing research, this article emphasizes the transformative impact of jet engines and identifies future development directions, including advanced manufacturing and sustainable energy solutions, to provide guidance for the sustainable development of the aviation industry.
Research on The Advantages, Practical Applications and Optimization of Stirling Cryocoolers
The Stirling cryocooler machine is a refrigeration device that uses the Stirling cycle. It can quickly reduce the temperature to a very low level. Compare with other refrigeration machines, it is environmentally friendly and high efficency. That is the reason why it is widely used in various fields, such as aerospace technology research (James Webb Space Telescope), low-temperature physics experiments (Achieves millikelvin-level cooling), medical devices (MRI systems), and equipment used in Antarctic scientific research. Stirling cryocoolers also have the advantage of vibration-free operation, so it is widely used in precision processing. Its operation process consists of four steps Isothermal Compression, Isochoric Regeneration, Isothermal Expansion, Isochoric Heat Storage. It works based on thermodynamic principles. Stirling cryocoolers contain five core components: the compressor, the cooler, the regenerator, the expander and the working fluid. Each of them plays the important role in machine. However, Stirling cryocoolers still face risks and challenges. So there are many ways to optimize them such as improve structures, use better materials and so on.
Research on the Design of Advanced Combined Cycle Power Plants
Combined cycle power plants are an important bridge technology between today's fossil fuel power plants and tomorrow's clean power plant facilities. The paper analyze from the perspective of thermodynamics, technology and engineering practice introduces the main structure, design points, fundamentals of advanced combined cycle power plants (CCPPs), key technology innovations, and application cases through the analysis of how the two cycles, namely, Brayton cycle and Rankine cycle, work together and how advancements have brought better CCPPs, which include Brayton cycle optimization, multi-pressure steam system, and regenerative heat exchange techniques. The description is based on the case study of Hassyan hybrid power plant, Huaneng Shantou 700°C A-USC Project and NET Power zero-carbon demonstration project，Compared with traditional power plants, the differences in fuel types, cycle methods, and fuel utilization are summarized. The working principles and special cycle methods of these typical cases are explained respectively, and the future trend of combined cycle power plants is further summarized. It is demonstrated that current modern CCPPs' operational efficiencies might surpass 60%, indicating potential and adaptability for the change in low carbon emission.
Real-Time Neural Style Transfer in Game Engines: A Comprehensive Review
Neural Style Transfer (NST) has evolved into a transformative technique in computer vision and computer graphics, enabling the integration of artistic styles into digital media. In recent years, the application of NST in real-time scenarios—especially within game engines—has attracted significant academic and industrial interest. This paper provides a comprehensive review of the development of NST from its origins in 2D image transformation to its extension in video, 3D meshes, and real-time rendering. We further examine the role of modern game engines in supporting NST pipelines, summarize key advances in integrating stylization within interactive environments, and analyze both the benefits and limitations of such approaches. In addition, the paper highlights the existing research gaps, challenges, and possible future directions for advancing real-time NST in games.
EHR Forecasting via Implicit Neural ODEs
The widespread adoption of Electronic Health Record (EHR) systems has generated vast repositories of valuable clinical data. Utilizing this information enables the development of predictive methods for proactive healthcare, enhanced medical services, and optimized resource allocation.This study employs the MIMIC-IV dataset to address challenges in generating actionable insights from longitudinal EHR data. We introduce a novel model based on Implicit Neural Ordinary Differential Equations (Neural ODEs), focusing on predicting Length of Stay (LoS) and In-Hospital Mortality (IHM). The model first encodes multimodal clinical codes into a low-dimensional space via a clinical embedding module, mitigating noise from heterogeneous data. An implicit Neural ODE network then captures the temporal dynamics of vital signs and lab results for efficient continuous-time modeling，The key experimental results show that the AUC of the proposed model in the prediction of hospital stay reaches 0.81, and the accuracy reaches 97%, which is 12% and 9% higher than that of the baseline model, respectively. In terms of mortality prediction, it also showed advantages, with AUC reaching 0.785 and mean square error decreasing from 0.0084 to 0.0036, a decrease of about 39.5%, which was significantly better than the prediction effect of the baseline model.
Research on Optimal Scheduling Strategies of Energy Storage Systems for Peak Shaving in Power Systems with High Renewable Energy Penetration
With the rapid growth of wind and solar, modern power systems face widening peak–valley gaps and variability that traditional dispatch cannot absorb. This paper presents a comprehensive review of energy storage for peak shaving under high renewable penetration. We synthesize modeling paradigms, including deterministic, stochastic, robust, and model predictive control, combined with degradation-aware, network-constrained, and carbon-cost formulations. This paper examines scheduling across multiple horizons: real time, intraday, day ahead, and seasonal; and across architectures such as utility-scale batteries, behind-the-meter fleets, and hybrid storage. The review catalogs evaluation metrics such as peak reduction, curtailment, reliability, cost, and emissions, and compares representative case studies. We assess implementation challenges, including forecast uncertainty, battery aging, coordination of heterogeneous assets, market rules, and cyber-physical limits at the distribution level. We identify research gaps in uncertainty-aware data-driven dispatch, valuation of stacked services, and scalable coordination of distributed storage. The contribution is a structured synthesis and a research agenda to guide more flexible, economical, and low-carbon grid operation, informing planners and regulators where storage delivers the highest marginal system value.
Cost-benefit Analysis of Ecological Protection in China's Coastal Zone: A Case Study of the Beibu Gulf Coastal Zone
The coastal zone, a crucial area for human resources and ecological services, is facing significant ecological damage due to human overexploitation. As economic development shifts towards the ocean, the contradiction between coastal ecosystem protection and economic development intensifies. This paper presents an opportunity cost assessment system for coastal ecological environment protection, focusing on the Beibu Gulf coastal zone. The study reveals that the average annual opportunity cost of the Beibu Gulf coastal ecosystem is 1.36×109 yuan, with government opportunity costs dominating due to strict environmental protection policies. Residents face 4.5×107 yuan, mainly due to limited aquaculture and planting industries, and enterprises face 3.18×107 yuan, mainly due to suspended production and rectification of small and micro enterprises.
PID Control and Simulation Analysis of DC Motor for UAV Application
In contemporary society, the rapid advancement of technology has facilitated the widespread adoption of proportional-integral-derivative (PID) control systems, which are among the most employed closed-loop systems across various applications. PID control is widely used in the field of automatic control, enabling precise management of dynamic systems. However, within the specific context of unmanned aerial vehicles (UAV), proportional-integral (PI) control currently prevails due to its effectiveness under certain flight conditions. This study aims to design a PID control system specifically tailored for UAV applications. To achieve this objective, the research compares the performance of PID control with that of PI, proportional-derivative (PD) control, and Proportional (P) control. This comparative analysis will facilitate a thorough evaluation of the advantages and efficacy of the PID approach in enhancing UAV performance. After the contrast, the study finds a specific combination of the PID control to make the UAV performance more stable and effective. The study enhances the UAV’s performance in future applications.
Application of Remote Sensing Data-based Detection of Forest Vegetation Water Content in Forest Fire Prevention
Forest fires occurring on Earth cause huge losses every year and their frequency is on the rise. In order to reduce the occurrence of forest fires, there have been a number of new technologies that have emerged to predict and dynamically monitor forest fires based on remote sensing technology. In this paper, the Normalised difference infrared index (NDII) value of the study area is based on remote sensing satellite image data to detect and estimate the water content of the vegetation in the forest area to predict the occurrence of forest fires, so as to strengthen the precautionary measures for forest fires and reduce the probability of forest fires. The results showed that vegetation water content was significantly negatively correlated with the risk of forest fires, and when the vegetation NDII value was lower than -0.8486, it indicated that the water content of the vegetation area had dropped to a very low level, and it would be highly combustible and the probability of fire would be very high. For the study area, the water content of the vegetation tends to be even lower especially during the hot and dry seasons, making the overall increase in the forest fire risk level. This paper further validates that the water content of vegetation is one of the key indicators in forest fire risk assessment. This study provides more prevention indicators for forest fire prevention facilities and improves the prevention system.
Analysis of the Application of Sludge BC in the Removal of Organic Dyes from Wastewater
With industry development, wastewater discharge has triggered serious environmental pollution problems, especially the most prominent in the dye industry. Biochar(BC) adsorption is a cost-effective means of wastewater treatment and can achieve sludge resourcing, which has become a hot research topic. This paper summarizes the adsorption mechanism of BC. It focuses on various factors affecting the adsorption performance of BC, covering the performance characteristics of BC itself, such as pore size and specific surface area, as well as the dosage of adsorbent and adsorption time during the operation process, and also the effects of the initial pollutant concentration and pH value. In addition, the optimal preparation process of sludge BC and its applicable conditions are summarized. The paper also describes the performance deficiencies of sludge BC in practical applications and the pollution problems caused by it and summarizes the current modification methods for sludge BC. This review provides a reference for the application of sludge BC and its improvement for further enhancement in the field of environmental protection.
Study on the Relationship between Vegetation Cover and Land Surface Temperature Based on Remote Sensing - A Case Study of Changzhou, China
With the acceleration of urbanization, the environmental problems caused by the urban heat island effect are becoming increasingly noticeable. Investigating the connection between land surface temperature and vegetation cover is crucial to reducing the urban heat island effect. This paper uses Landsat data from 2021 to 2024 in the main urban region of Changzhou City, Jiangsu Province, China, as the study area to evaluate the geographical and temporal evolution of vegetation cover and land surface temperature and their coupling connection. The results show that the annual average value of vegetation cover in the main urban region of Changzhou City from 2021 to 2024 is 0.6025, with an overall upward trend, and the spatial pattern is characterized by a ‘ring-like’ distribution with a high level in the periphery of the city and a low level in the heart of the city. In addition, the land surface temperature showed a decreasing trend in the same period, and the middle of Wujin District and the outskirts of Xinbei District were the areas with the highest temperatures, while the sub-medium-temperature region appeared in the arable land area with good vegetation cover and around the water body. Lastly, in Changzhou City's central urban region, there is a highly substantial negative correlation between vegetation cover and land surface temperature; for every 10% increase in plant cover, the land surface temperature drops by 0.20 to 0.49℃.
Analysis of the Characteristics and Applications of Wind-Solar-Storage Systems in the Smart Grid
At present, with the rapid development of smart grid, scenery storage system, as the core carrier of multi-energy complementarity, has shown significant advantages in improving the energy absorption capacity of renewable energy, enhancing the flexibility and stability of power grid. However, the intermittent and uncertainty of renewable energy generation poses many challenges to the grid operation. This paper takes wind energy, photovoltaic and energy storage as the basic entry point, combines the actual situation, extends the overall architecture of the landscape storage smart grid and analyzes the architecture. Then, the key technologies of the wind light storage system under the background of the smart grid are systematically analyzed. For example, the characteristics and application progress of technologies such as renewable energy grid, energy storage, demand side response, virtual power plant and other technologies, although these technologies have been successful, some problems remain. At the end of this paper, the research bottlenecks, optimizable items and prospects for the future are also discussed.
Application and research status of semiconductor refrigeration technology
In recent years, global modernization has become an irreversible trend. However, the excessive use of energy has also brought about numerous severe challenges, including global warming, ozone layer depletion, light pollution, and the shortage of non-renewable resources. This article briefly introduces semiconductor cooling technology and provides a detailed explanation of how semiconductor cooling sheets work. By analyzing the current research progress in thermoelectric materials, the article predicts the future development direction of these materials. It then summarizes the optimal operating conditions for semiconductor coolers and discusses their heat dissipation methods, including natural convection, forced convection, water cooling, and heat pipe cooling. The aim is to highlight the importance of efficient energy utilization and enhanced heat transfer in improving cooling efficiency and reducing energy loss. Additionally, the article envisions the structure of semiconductor cooling sheets, optimizing them into pipes. Using SOLIDWORK software for modeling, it applies knowledge of heat transfer to imagine the usage conditions and suitable applications of this new structure. It also looks forward to the application prospects of semiconductor cooling technology in areas such as human protection, solar cooling, and infrared detection.
Comparative Analysis of Wireless Charging Systems
With the accelerated progress of global modernization, electric energy, as one of the most important basic energy sources in human society, has deeply penetrated all areas of production and life. From industrial production to smart homes, from transportation to information communication, the stable supply and efficient transmission of electric energy are always the key elements to support the operation of modern society. In this context, although the traditional wire transmission method is technologically mature, its inherent limitations such as complex wiring, high maintenance costs, safety hazards, and other issues are becoming increasingly prominent, especially in special environments (e.g., the ocean, high altitude, mobile equipment, etc.) in the application of serious constraints. As a breakthrough energy transmission method, wireless energy transmission technology is gradually becoming a research hotspot in the field of energy transmission by virtue of its non-contact, flexible, convenient, safe, and reliable advantages. This paper summarizes the comparative analysis of various wireless transmission methods. Firstly, it introduces the development history and basic principles of different wireless transmission methods. Secondly, it compares the performance of different wireless transmission methods, their construction costs, and transmission efficiency, and finally discusses the application scenarios of different wireless transmission methods, and analyzes the advantages and disadvantages, so that they can be better applied in different fields and reduce the resource application of the mismatch.
Study on the Influence of Different Raw Materials and Pyrolysis Conditions on the Performance of Biochar in Remediating Heavy Metal-Contaminated Soils
The issue of soil heavy metal pollution is becoming increasingly severe, posing a critical environmental challenge that threatens ecological security and human health. Biochar-based soil remediation technology has drawn significant attention due to its potential advantages, and it is of great significance for improving soil environmental quality. This paper focuses on using biochar to remediate heavy metal-contaminated soils and explores the influence mechanisms of different raw materials and pyrolysis conditions on its remediation performance. Through a systematic analysis of three practical cases, the action patterns of key factors such as biochar raw material types, pyrolysis temperatures, and heating rates on the remediation effect of soil heavy metals are deeply understood. The research results provide a practical basis for the engineering application of biochar-based soil remediation technology and reveal the interaction mechanism among biochar, soil, and heavy metals from a theoretical perspective. This is of great significance for promoting the development of more efficient and sustainable strategies in the field of soil pollution remediation.
Rice Straw Preparation of Biochar Process and Its Prospective Data Analysis
With the development of global agriculture, the annual output of rice straw, one of the crop wastes, exceeds 700 million tons. However, traditional treatment methods pollute the environment and waste resources. Therefore, the preparation of biochar from rice straw has become a hot research topic. This study aims to analyze the process of preparing biochar from rice straw, to explore the effects of pyrolysis process parameters on the characteristics of biochar, and to give a prediction of the yield of biochar under ideal conditions. On the basis of available data, this study found that the biochar produced under 200°C and 1 h pyrolysis condition has the highest yield and carbon content, which is an ideal soil conditioner; the biochar produced under 400°C and 1 h condition has high carbon content and good stability, which is more suitable for long-term carbon storage. In addition, biochar is effective in improving soil quality, increasing agricultural production, and reducing greenhouse gas emissions. This study opens up new ideas for the high-value utilization of rice straw, which can help promote the sustainable development of agriculture and realize the synergistic development of efficient resource utilization and environmental protection.
Exploring the Application Status of Iron-Modified Biochar to Remove Heavy Metals from Wastewater
With the rapid development of industrialization, the degree of heavy metal pollution in water bodies has continued to increase, seriously threatening the ecosystem, human health and social development. As an efficient heavy metal adsorption material, iron-modified biochar not only inherits the advantages of the original biochar such as wide sources and developed pore structure, but also enhances the adsorption active sites on the surface of the material through iron modification, effectively overcoming the shortcomings of the original biochar in terms of adsorption capacity and selectivity. Therefore, iron-modified biochar has attracted widespread attention in the field of wastewater treatment in recent years. This paper aims to analyze the preparation method and structural characteristics of iron-modified biochar, and deeply analyze its removal mechanism for heavy metals. At the same time, this paper also discusses the challenges faced by iron-modified biochar in practical applications and looks forward to its application prospects and research directions in heavy metal pollution control. The analysis of this paper can provide an important reference for the application of heavy metal pollution control in water bodies.
Research Progress on the Remediation and Treatment of Heavy Metal Ions in Water by Biochar
With the rapid development of industrialization and urbanization, heavy metal pollution in water bodies poses a major threat to the environment and human health. However, conventional heavy metal pollution control technologies often face problems such as high cost, cumbersome operation and secondary pollution risk. Therefore, the development of new and efficient repair technology is urgent and has environmental significance. This paper aims to explore the preparation method, modification technology and adsorption mechanism of biochar, analyze the regulation mechanism of its physical and chemical properties on adsorption performance, and discuss its remediation effect in complex water environments. This paper concluded that optimizing the preparation and modification conditions of biochar can significantly improve its adsorption efficiency and reduce the repair cost. Biochar shows the characteristics of high efficiency and low cost in the actual water remediation, and has significant environmental and economic benefits. Future research should further explore the combination of biochar and other remediation technologies, develop more efficient preparation methods, and further explore the adsorption mechanism to promote its wide application in the field of water treatment.