Production Efficiency Research Articles

Development of Software for Hydrometallurgical Calculation of Metal Extraction

Hydrometallurgy plays a critical role in the metallurgical industry by providing an efficient method for extracting metals from ores and secondary materials using aqueous solutions. This approach is particularly advantageous for processing low-grade and complex ores, as well as secondary resources that cannot be effectively processed by traditional pyrometallurgical methods. The objective of this study is to develop specialized software to automate and optimize the calculations necessary for metal extraction in hydrometallurgical processes. The software integrates a complete computational framework for automating the various stages of the hydrometallurgical process, including ore composition initialization, total element mass calculations, and the determination of metal concentrations in both metal products (matte) and by-products (slag). The methodology involves the design and implementation of a web-based application using Django for the user interface and MySQL for robust data storage. The computational module, written in Python, automates the mathematical operations required to simulate complex chemical reactions and metal extraction processes. This module supports real-time processing and ensures accurate calculations for each stage of metal extraction, including leaching, extraction, re-extraction, sorption, and electrolysis. The software also features detailed tables and dynamic graphs that allow users to analyze the distribution of valuable metals and assess the influence of key operational parameters on extraction efficiency. The results show that the developed software successfully manages large datasets, enhances the precision of hydrometallurgical calculations, and minimizes the risk of human error. The implementation of the software leads to significant improvements in the economic efficiency of production by optimizing metal recovery rates and reducing operational costs. Additionally, it supports comprehensive process control by providing actionable insights into each stage of extraction, thus improving the quality of the final metal product. Overall, the software represents a significant technological advancement in the field, offering a scalable solution for industries aiming to streamline hydrometallurgical processes.

LEM-Detector: An Efficient Detector for Photovoltaic Panel Defect Detection

Photovoltaic panel defect detection presents significant challenges due to the wide range of defect scales, diverse defect types, and severe background interference, often leading to a high rate of false positives and missed detections. To address these challenges, this paper proposes the LEM-Detector, an efficient end-to-end photovoltaic panel defect detector based on the transformer architecture. To address the low detection accuracy for Crack and Star crack defects and the imbalanced dataset, a novel data augmentation method, the Linear Feature Augmentation (LFA) module, specifically designed for linear features, is introduced. LFA effectively improves model training performance and robustness. Furthermore, the Efficient Feature Enhancement Module (EFEM) is presented to enhance the receptive field, suppress redundant information, and emphasize meaningful features. To handle defects of varying scales, complementary semantic information from different feature layers is leveraged for enhanced feature fusion. A Multi-Scale Multi-Feature Pyramid Network (MMFPN) is employed to selectively aggregate boundary and category information, thereby improving the accuracy of multi-scale target recognition. Experimental results on a large-scale photovoltaic panel dataset demonstrate that the LEM-Detector achieves a detection accuracy of 94.7% for multi-scale defects, outperforming several state-of-the-art methods. This approach effectively addresses the challenges of photovoltaic panel defect detection, paving the way for more reliable and accurate defect identification systems. This research will contribute to the automatic detection of surface defects in industrial production, ultimately enhancing production efficiency.

Emergy-based evaluation of production efficiency and sustainability of diversified multi-cropping systems in the Yangtze River Basin

Excessive agricultural investment brought about by increased multiple-cropping index may compromise environmental sustainability. There are few studies on the sustainability of diversified multi-cropping systems in the Yangtze River Basin (YRB). Therefore, this study selected five representative locations in the YRB. According to the local climate characteristics and food demand, diversified multi-cropping systems were designed, and the main local winter crops were selected as the previous crops of the corn–soybean strip compound cropping system, with the local traditional double-cropping model as the control (CK). The emergy evaluation method was introduced to quantitatively compare the efficiency and sustainability of diversified multi-cropping systems in the YRB. The results showed that by incorporating soybean by intercropping with corn, compared with the CK, the total energy input, annual energy output, and annual economic output increased by 15.80%, 9.78%, and 33.12% on average, respectively. The unit emergy value (UEV) and unit non-renewable value (UNV) increased by 6.03% and 5.98%, respectively; the emergy yield ratio (EYR) and environmental loading ratio (ELR) decreased by 0.91% and 0.44%, respectively; the emergy sustainability index (ESI) was the same. In the third mature crop selection, compared with that of corn, the ELR of soybean decreased by 14.32%, and the ESI increased by 18.55%. In addition, the choice of winter crops plays a vital role in the system’s efficiency and sustainability. Compared with those of other winter crops, the annual economic outputs of potato (upper reaches of the YRB), potato or forage rape (middle reaches of the YRB), and wheat (lower reaches of the YRB) increased by 51.02%, 32.27%, and 0.94%, respectively; their ESI increased by 71.21%, 47.72%, and 12.07%, respectively. Potato–corn/soybean or potato/corn/soybean (upper reaches of the YRB), forage rape–corn/soybean or potato/corn/soybean (middle reaches of the YRB), and wheat–corn/soybean (lower reaches of the YRB) were chosen to facilitate the coexistence of high economic benefits and environmental sustainability. Additionally, promoting mechanization and reducing labor input were essential to improve the efficiency and sustainability of multi-cropping systems. This study would provide a scientific basis and theoretical support for the development of efficient and sustainable multiple-cropping systems in the dryland of the YRB.

Sustainability in Long-Term Surface Mine Planning: A Systematic Review of Operations Research Applications

The mining industry, critical for global resource supply, has historically been linked to significant environmental degradation and social challenges, including habitat disruption, water and soil contamination, as well as fatalities. But recently, the industry has been undergoing a transformative change to meet evolving environmental and societal expectations. Operations Research (OR) provides essential tools and techniques to optimize decision-making processes in this context. This paper presents a comprehensive review of different OR methods and their applications in balancing economic, social, and environmental objectives in surface mine planning. Of the 63 papers reviewed, 45 were published by researchers from three main countries: Canada, the United States, and Australia, with 73% of these papers appearing in journals. This review highlighted that linear programming (LP), dynamic programming (DP), Lagrangian relaxation (LR), stochastic programming, and metaheuristics are among the most widely applied methods in surface mine planning within a sustainable development (SD) context. By evaluating the strengths and limitations of these techniques, this review offers valuable insights for researchers and practitioners aiming to improve production efficiency and sustainability through advanced planning strategies.

Intelligent agricultural mechanization: A new era engine for agricultural development

Abstract. In recent years, the rapid advancement of technology and the increasing demand for efficient agricultural practices have propelled significant progress in the field of intelligent agricultural mechanization. This paper aims to comprehensively explore this important topic by analyzing the key role of intelligent agricultural mechanization in modern agriculture, examining its technological applications, and identifying prevailing challenges. Intelligent agricultural mechanization involves the integration of cutting-edge technologies such as artificial intelligence, machine learning, and the Internet of Things (IoT) into agricultural machinery and processes, revolutionizing traditional farming methods. Through an in-depth study of relevant literature, it elucidates how intelligent agricultural mechanization can significantly enhance agricultural production efficiency by minimizing resource waste, reducing labor costs, and increasing crop yields. Furthermore, the paper explores the broader implications of these advancements for sustainable development. The research results presented herein seek to provide robust theoretical support and practical guidance for advancing agricultural modernization. In this paper, future development trends are also discussed, including the potential for further innovations and the role of policy and regulatory frameworks in facilitating the adoption of intelligent agricultural mechanization.

Plastic Injection Molding Process Analysis: Data Integration and Modeling for Improved Production Efficiency

This paper presents a comprehensive analysis of the plastic injection molding process through the integration of data acquisition technologies and classification models. In collaboration with a company specializing in plastic injection, data were extracted directly from the machine during a specific period at the beginning of a shift change. These data were subjected to exploratory analysis to identify correlations between important variables, such as injection time, cycle time, and mold pressures. Additionally, classification models, including Random Forest and Logistic Regression, were constructed to predict and classify the process state based on these variables. The model results demonstrated high predictive performance, with 99.5% accuracy for Random Forest and 97% for Logistic Regression. These results provide a strong foundation for the early identification of potential problems and informed decision making to improve the efficiency of the plastic injection molding process. This study contributes to the advancement of the integration of intelligent technologies in industrial process optimization, aligned with the principles of Industry 4.0.

The application of electroflocculation (EC) technology in printing and dyeing wastewater

Abstract. Industrial wastewater contains a large number of toxic pollutants, and the total consumption of dyes in the global textile printing and dyeing industry exceeds 587,000 tons per year. Duo to the process of dye production is more complex, the application of processes and materials are more, so many production links will produce a variety of waste, garbage, and the relevant waste dye into the river, lake and sea is up to millions of kilograms. It can be seen that textile printing and dyeing wastewater is the main source of water environmental pollution. If not treated in time, it will not only affect the production efficiency, but also harm the surrounding ecological environment and pose a serious threat to human survival. Scientific and effective intervention of textile industry wastewater and reasonable selection of textile industry wastewater intervention mode are related to the sustainable development of the industry. In recent years, electroflocculation (EC) technology has gradually become a research hotspot due to its advantages of high removal rate, simple operation, small dosage of chemicals, and small impact on the environment, including the intervention of wastewater. This paper will describe the main mechanism of EC and the application status of EC technology is discussed in detail, the limitations and future development trend of this technology are also proposed.

Inactivation of sacB Gene Allows Higher 2,3-Butanediol Production by Bacillus licheniformis from Inulin

Bacillus licheniformis 24 (BL24) is an efficient, non-pathogenic producer of 2,3-butanediol (2,3-BD). However, during inulin fermentation, the strain produces large amounts of exopolysaccharides (EPS), which interfere with the process’ performance. The present study aims to investigate the effect that inactivation of the sacB gene, encoding levansucrase in BL24, has on 2,3-BD production efficiency. Knockout of the sacB gene was accomplished via insertional inactivation. The sacB-knockout variant formed 0.57 g/L EPS from sucrose and 0.7–0.8 g/L EPS from glucose and fructose, a 15- and 2.5-fold reduction relative to the wild type, respectively. Likewise, during batch fermentation with soluble inulin Frutafit® CLR, the mutant BLΔsacB produced significantly less EPS than the wild type, allowing the maintenance of pH at values favoring 2,3-BD synthesis. At pH 6.50, BLΔsacB reached a record titer of 128.7 g/L 2,3-BD, with productivity of 1.65 g/L/h, and a yield of 85.8% of the theoretical maximum. The obtained concentration of 2,3-BD is two-fold higher compared to that of the wild type. Subsequent RT-qPCR assays confirmed a successful sacB knockout. Three of the genes involved in inulin hydrolysis (sacA, sacC, and fruA) maintained their expression levels compared to the wild type, while that of levB increased. Although total EPS accumulation could not be completely eliminated via sacB gene knockout alone, the overall reduction in EPS content has enabled the highest yield of 2,3-BD from inulin to date, a promising result for the industrial production from inulin-rich substrates.

A promising direction of development of out-of-furnace vacuuming processes of steel

Secondary furnace processing of steel is a key link in modern steelmaking production and will simultaneously solve the problems of improving steel quality and production efficiency. At the same time, there is a variant of secondary evacuation of steel with a simplified bottomless vacuum chamber, which has a number of technological and design advantages. The article discusses the main parameters of this process and proposals for its industrial application

Indium Oxide Layer Dual Functional Modified Bismuth Vanadate Photoanode Promotes Photoelectrochemical Oxidation of Water to Hydrogen Peroxide.

The photoelectrochemical (PEC) dual-electron pathway for water oxidation to produce hydrogen peroxide (H2O2) shows promising prospects. However, the dominance of the four-electron pathway leading to O2 evolution competes with this reaction, severely limiting the efficiency of H2O2 production. Here, we report a In2O3 passivator-coated BiVO4 (BVO) photoanode, which effectively enhances the selectivity and yield of H2O2 production via PEC water oxidation. Based on XPS spectra and DFT calculations, a heterojunction is formed between In2O3 and BVO, promoting the effective separation of interface and surface charges. More importantly, Mott-Schottky analysis and open-circuit potential measurements demonstrate that the In2O3 passivation layer on the BVO photoanode shifts the hole quasi-Fermi level towards the anodic direction, enhancing the oxidation level of holes. Additionally, the widening of the depletion layer and the flattening of the band bending on the In2O3-coated BVO photoanode favor the generation of H2O2 while suppressing the competitive O2 evolution reaction. In addition, the coating of In2O3 can also inhibit the decomposition of H2O2 and improve the stability of the photoanode. This work provides new perspectives on regulating PEC two/four-electron transfer for selective H2O2 production via water oxidation.

From waste to resource: Hydrogen generation and antimicrobial activity of Ag-based photocatalysts recovered from biomedical waste

Electrocardiogram (ECG) disposable electrodes contain a substantial amount of silver (Ag), which can be extracted and recycled. Most current methods for recovering Ag from waste are expensive and environmentally harmful. This study investigated a sustainable chemical process for extracting Ag from discarded medical electrodes using a simple Cu(II) solution under moderately acidic conditions. Using response surface methodology (RSM) based on a three-level, full-factorial design, the optimized extraction conditions were determined as pH = 4.78, T = 80°C, [Cu(II)]₀ = 8.0 × 10⁻³ M, and [NaCl]₀ = 3.72 M. Under these conditions, a process efficiency approaching 100 % was achieved. Moreover, the recovery of metallic silver exceeded 85 %, even when using real matrices. (i.e., discarded ECG electrodes). As a result, the Ag-containing leachate solutions were utilized to synthesize silver-based materials with varying Ag content. These materials demonstrated (i) excellent photocatalytic activity for hydrogen production in aqueous solutions containing organic compounds and (ii) significant antipathogenic properties. In summary, effective Ag/TiO₂ photocatalytic materials with high efficiency for hydrogen production and antimicrobial activity were successfully prepared through a novel, sustainable, and cost-effective chemical recovery process of silver from discarded ECG electrodes.

Boron-Nitrogen Compounds in Luminescent Materials: A Review of Applications and Synthesis Methods

Boron-nitrogen compounds (B-N) have emerged as a promising material due to their unique electronic structure and excellent luminescent properties, showing great potential in organic light-emitting diodes (OLED) and electroluminescent devices. This paper systematically reviews the molecular structure, optical, and electronic properties of B-N compounds, discusses their applications in luminescent materials, and explores synthesis methods, including Friedel-Crafts-type reactions, borohydride reduction reactions, and olefin metathesis. Additionally, the paper analyzes key factors in controlling the performance of luminescent materials, investigating the impact of synthesis conditions, doping, and the preparation of composite materials on luminescent efficiency and stability. Despite significant progress in B-N compound research, challenges remain in synthesis precision, luminescent efficiency, and industrial production. Future research should focus on improving targeted synthesis capabilities, optimizing electronic structure and luminescent performance, and exploring more efficient, cost-effective production processes. With continued innovation, B-N compounds are poised to become a foundation for the next generation of high-efficiency luminescent materials, driving advancements in optoelectronic technology.

Efficiency and Heat Production of Ultrasonic Osteotome Strategy in Robot-Assisted Laminectomy.

A biomechanical study. We aimed to assess temperature fluctuations when applying the ultrasonic osteotome during laminectomy and identify the most appropriate cutting method for robot-assisted laminectomy to mitigate the risk of heat-related injuries. Utilizing a robotic system for laminectomy, the study implemented the ultrasonic bone scalpel to cut both artificial polyurethane bones and animal spinal bones. The research focused on comparing and analyzing the maximum temperature of the inner surface of four types of artificial bones through three different cutting techniques: vertical constant cutting at speeds of .5mm/s and 1mm/s, as well as robot-assisted vertical reciprocating cutting. After the initial results, two optimal vertical cutting approaches were selected for subsequent trials, evaluating the effectiveness and temperature impact of various ultrasonic osteotome modes on 10 isolated spinal bones from pigs. When cutting polyurethane bones, reciprocating cutting demonstrated the lowest maximum temperature in contrast to constant speed cutting at .5mm/s and 1mm/s. In the animal bone trial, direct cutting registered an average maximum temperature of 43.25°C with an average cutting duration of 688.3s, while reciprocating cutting recorded an average maximum temperature of 34.20°C with an average cutting time of 713.0s. The reciprocating cutting strategy utilized in robot-assisted ultrasonic osteotome is effective in reducing heat generation and maintaining high cutting efficiency.

3D NiCoW Metallic Compound Nano-Network Structure Catalytic Material for Urea Oxidation

Urea shows promise as an alternative substrate to water oxidation in electrolyzers, and replacing OER with the Urea Oxidation Reaction (UOR, theoretical potential of 0.37 V vs. RHE) can significantly increase hydrogen production efficiency. Additionally, the decomposition of urea can help reduce environmental pollution. This paper improves the inherent activity of catalytic materials through morphology and electronic modulation by incorporating tungsten (W), which accelerates electron transfer, enhances the electronic structure of neighboring atoms to create a synergistic effect, and regulates the adsorption process of active sites and intermediates. NiCoW catalytic materials with an ultra-thin nanosheet structure were prepared using an ultrasonic-assisted NaBH4 reduction method. The results show that during the OER process, NiCoW catalytic materials have a potential of only 1.53 V at a current density of 10 mA/cm2, while the UOR process under the same conditions requires a lower potential of 1.31 V, demonstrating superior catalytic performance. In a mixed electrolyte of 1 M KOH and 0.5 M urea, overall water splitting also shows excellent performance. Therefore, the designed NiCoW electrocatalyst, with its high catalytic activity, provides valuable insights for enhancing the efficiency of water electrolysis for hydrogen production and holds practical research significance.

Computational Fluid Dynamics Analysis and Optimization of a Doublesuction Turbine Agitator

Background: As one of the essential pieces of chemical equipment, a reactor provides the necessary reaction space and conditions for the materials involved in the reaction during the stirring process. However, under typical operating conditions, issues such as uneven gas distribution, suboptimal gas-liquid mixing, and low product yield often arise in gas-liquid phase reactors. Purpose: To address the issues prevalent in current stirred reactors, a new design for a stirred reactor equipped with a double-suction turbine agitator was developed. Method: In this paper, a stirred reactor equipped with a double-suction turbine agitator was designed, and its three-dimensional modeling was conducted using SolidWorks. Computational Fluid Dynamics (CFD) simulations, based on the Euler-Euler two-phase approach with the RNG k −ε turbulence model, were performed to assess variables such as stirring speed, installation height, blade diameter and agitator inner diameter. The dispersion characteristics and flow field behaviors of the gas-liquid two-phase under varying conditions were comparatively analyzed. Optimizations were conducted across various parameters to enhance the gas mixing efficiency in the liquid phase. Result: The results show that a diameter of 370mm for the double-suction turbine agitator, an installation height of 640mm, a blade diameter of 500mm, and an inner hole diameter of 200mm yield optimal gas-liquid two-phase mixing performance. This configuration results in a broad and uniform gas distribution within the reactor, maintaining a desired high level of gas holdup at specific positions. Conclusion: The double suction turbine agitator is a type of radial agitator. During operation, it induces significant centrifugal forces in the liquid, exerts a robust shear effect, and enhances the mixing of the gas-liquid phases, thereby increasing the production efficiency of the product.

Design and Application of Fuzzy PID Controller Based on MATLAB

In an era where the development of intelligent technology is a pivotal force propelling economic advancement, enhancing production efficiency, diminishing costs, and reshaping daily life, the field of intelligent vehicle control technology has garnered significant attention among automotive researchers. The dynamics of smart cars during driving often exhibit nonlinearity and are susceptible to external environmental disturbances, such as wind resistance and road surface inequality. Traditional PID controllers have limited ability to suppress these interferences, so this study uses fuzzy PID algorithms to solve the inherent challenges in intelligent vehicle control. Through comprehensive analysis of the current landscape and technological advancements in intelligent vehicle control systems, coupled with rigorous MATLAB/Simulink simulations and real-world testing, the study showed that the overshoot of the adaptive fuzzy PID was reduced by 86% compared to the traditional PID. Consequently, it markedly enhances the precision and stability of speed control in intelligent vehicles, providing a groundbreaking perspective and practical methods for the enhancement of intelligent vehicle control systems with considerable application potential.

Innovation and Utilization of Functional Feed Additives from Maize By-Products in Broiler Chickens

Supplementation with spent mushroom substrate (SMS) as an exogenous enzyme in broiler diets represents a promising nutritional strategy to enhance production efficiency and reduce costs. To assess the effects of SMS enzyme products on various parameters, including growth performance, blood chemistry, carcass and meat quality, and gut health, a study was conducted with one-day-old broilers (n = 500). The broilers were separated into five groups: a control diet (CON) and an antibiotic group (AGP) which were added to the diet at 0.25 g kg−1, and SMS from Flammulina velutipes supplementation groups which were added to the diet at 0.5 g kg−1 (SMS0.5), 1.0 g kg−1 (SMS1.0), and 2.0 g kg−1 (SMS2.0). Final body weight and average daily gain in broilers which were fed the AGP diet were higher than in broilers which were fed the CON, SMS0.5, and SMS1.0 diets. Broilers in the CON group had a decreased average daily feed intake compared to other groups. The addition of AGP and SMS2.0 diets improved the feed conversion ratio and reduced the feed cost per gain in broilers. Broilers that were fed the CON diet had the highest serum cholesterol, while the AGP diet increased triglyceride. Dietary supplementation of SMS improved some carcass characteristics and ceacum microbial content in broilers, especially with the SMS2.0 diet. Broiler fed CON and SMS0.5 worsened the villus height/crypt depth ratio of duodenum histology. In conclusion, SMS supplementation at 1.0 and 2.0 g kg−1 can improve productive performance and health in broiler diets; however, SMS2.0 had the best efficiency.

Production Technological Design for 500,000 Tonnes Per Year of Ethylene Glycol

Effective and reasonable chemical design of ethtlene glycol production process is of vital significance for the further improvement of our ethylene glycol production capacity. This paper carried out reasonable design of ethylene glycol water lawful production process, using reaction rectifying tower device, and optimizing calculation for each link of production, so as to obtain satisfactory products. In the comprehensive consideration of production efficiency and cost saving and other aspects of the relevant equipment is reasonable selection, and draw the PID process flow chart. It is expected to produce 500,000 tons of pharmaceutical grade glycol with mass fraction of 99.89%.

Spatiotemporal variation in grain production performance and efficiency of the cultivated landscapes in Upper Blue Nile Basin of Ethiopia: the impact of residual moisture-based farming on water and food security

Analysis of grain production performance can provide reference information to explore multiple cropping options and further improve the resource use efficiency of farming methods. This study investigated the spatiotemporal dynamics of grain production performance and efficiency of major crop production systems (CPS) in the Ethiopia’s Blue Nile Basin. The results show that only 39% of the basin is currently cultivated, although a significant cropland expansion (10%) was recorded between 1985 and 2020. The study identified 11 major CPS, mostly practiced in the basin. Of these, single cropping based on the main rainy season (Meher-Only) covers the largest area (26%), followed by Meher-Residual-Intermittent (12%) and Meher-Belg-Dependable (11%). Extended-Meher, Meher-Residual-Dependable, Meher-Residual-Intermittent, and Meher-Belg-Dependable are the four more powerful CPS with higher efficiency. Comparatively, CPS practiced in Wet-Woyna-Dega and Wet-Dega have better overall performance. Findings confirm that agricultural space management (land) and green-water (rainfall) utilization are the most influential factors, followed by land use planning and land use systems (CPS) invention. As landscape suitability for grain production governs future performance, in the low elevation and flood plains parts of the basin, the possibility of creating additional space into the food system is very high. In mountainous and high-altitude regions, the efficiency of grain production will decrease because incorporating additional arable land into the food system is trivial. In the last three decades, in BNB, only 10% of arable land (equivalent to 30 million quintals of food) has been added to the good system, which can support approximately 6 million people. Compared to the population growth of the basin (12 million 1985–2020), its contribution to the food system was less than 50%. This confirms that multiple cropping systems, such as Residual moisture-based CPS, have played a significant role in boosting the food system in the basin. Therefore, improving grain production performance/efficiency requires targeted investments, including the invention of more adaptable crop varieties, efficient cropping practices, and the introduction of advanced agricultural space and water management technologies. The results of the study will help identify important policy gaps and suggest possible options to enhance residual farming and other multiple cropping systems.

Exploring advanced microwave strategy for the synthesis of two-dimensional energy materials

The rapid pace of technology and increasing energy demands underscore the urgent need for eco-friendly materials with exceptional energy conversion and storage capabilities. Two-dimensional (2D) energy materials, characterized by unique physicochemical properties, hold great promise in renewable energy conversion, catalysis, and electronics. Nevertheless, conventional synthesis methods often falter in balancing high quality, high yield, and cost-effectiveness, presenting substantial obstacles to their large-scale application. Microwave-assisted synthesis, characterized by its rapid and efficient process, emerges as a promising approach to surmount these limitations. This review meticulously examines the pivotal role of microwave-assisted synthesis in the preparation of 2D materials, highlighting its profound impact on enhancing material quality and production efficiency. By scrutinizing the unique physical properties of microwaves and their applications in material synthesis, the review elucidates the innovative contributions of microwave technology to materials science. Furthermore, it delves into the intricate influence of microwave parameter control on the synthesis process and resultant material properties, offering insight into the potential of microwave technology for the precise modulation of material structure and functionality. This comprehensive analysis underscores microwave-assisted synthesis as a viable solution for overcoming current challenges, thereby advancing the development of high-performance 2D energy materials.