Demand For Industrial Products Research Articles

Non-noble metal catalysts for electrooxidation of 5-hydroxymethylfurfural.

2,5-Furandicarboxylic acid (FDCA) is a class of valuable biomass-based platform compounds. The creation of FDCA involves the catalytic oxidation of 5-hydroxymethylfurfural (HMF). As a novel catalytic method, electrocatalysis has been utilized in the 5-hydroxymethylfurfural oxidation reaction (HMFOR). Common noble metal catalysts show catalytic activity, which is limited by price and reaction conditions. Non-noble metal catalyst is known for its environmental friendliness, affordability and high efficiency. The development of energy efficient non-noble metal catalysts plays a crucial role in enhancing the HMFOR process. It can greatly upgrade the demand of industrial production, and has important research significance for electrocatalytic oxidation of HMF. In this paper, the reaction mechanism of HMF undergoes electrocatalytic oxidation to produce FDCA are elaborately summarized. There are two reaction pathways and two oxidation mechanisms of HMFOR discussed deeply. In addition, the speculation on the response of the electrode potential to HMFOR is presented in this paper. The main non-noble metal electrocatalysts currently used are classified and summarized by targeting metal element species. Finally, the paper focus on the mechanistic effects of non-noble metal catalysts in the reaction, and provide the present prospects and challenges in the electrocatalytic oxidation reaction of HMF.

Design of locally cooled step-less fan for industrial use using Arduino programming

Under the background of the development of domestic and foreign manufacturing industries and the increasing demand for industrial products at home and abroad, and under the premise of ensuring and even further reducing the manufacturing cost of manufacturers, how to effectively detect and cool the local temperature of industrial parts is a problem worth studying. After analyzing the advantages and disadvantages of traditional manual control and gear adjustment to adjust the fan, the design will be programmed using Arduino. The fan combines infrared sensor technology to detect the presence and position of parts. A temperature sensor is also set up to detect local temperatures in real-time. A fan with automatic step-less speed change according to temperature is obtained. This fan is used for heat dissipation control of local parts in industrial production, thereby reducing the cost of manual control. It further improves control accuracy and efficiency, improves product quality, and ensures production safety.

Enhanced trace NO2 gas sensing with functionalized graphene-based nanofibers

The development of trace nitrogen dioxide (NO2) gas sensors has recently garnered widespread attention. This interest arises not only from the demand for industrial production and environmental monitoring but, more importantly, due to the inherent health hazards associated with trace NO2 levels. In this study, we introduce a graphene-based nanofiber functionalized with a conductive polymer and metal nanoparticle, namely the AgPGNFs, for trace NO2 detection. We employ a combination of supramolecular assembly and oriented lyophilization technique to manufacture these nanofibers. These nanofibers harness the synergistic effects of functionalization and three-dimensional structuring involving graphene, conductive polymers, and metal nanoparticles, significantly enhancing NO2 adsorption and charge variation to improve sensing performance. Consequently, the as-prepared sensor exhibits high sensitivity to NO2, rapid response and recovery speed, excellent gas selectivity and stability, and notably, a low limit of detection of 20 ppb. This work underscores the potential of a new approach for designing advanced trace gas sensors.

Effect of Electrochemical Aryl Diazonium Salt Modification on Interfacial Properties of CF/PEEK Composites.

The interfacial properties between carbon fiber (CF) and thermoplastic resin are relatively weak, which can be problematic for composites in structural applications. Improving the surface roughness of CF is regarded as an effective way to enhance the interface of composites. However, most CF modifying methods are complex and time-consuming, which cannot meet the demand for industrial production. Therefore, it is of great significance to research a fast technique of CF surface modification to strengthen the interface of composites. Herein, a one-pot reaction based on the aryl diazonium salt modification was applied to enhance the interface between CF and poly ether ether ketone (PEEK) resin. Carbon nanotubes (CNTs) were linked to CF by p-phenylenediamine (PPD) via cyclic voltammetry (CV). The surface morphology, chemical characteristics and surface energy of modified CF illustrated the effectiveness of this method, and the interfacial properties of as-prepared modified CF/PEEK demonstrated the increased tendency. All the CF was treated within 5 min and the interfacial shear strength (IFSS) of CF/PEEK was increased to the maximum of 99.62 MPa by aryl diazonium salt modification. This work may shed some light on the industrialized application of CF reinforced high-performance engineering thermoplastic composites.

Error analysis and compensation for Mini LED mass transfer visual positioning system

The accuracy of the visual positioning system directly impacts the production efficiency of Mini/Micro LED display panels. This paper aims to enhance the precision of the mass transfer visual positioning system to meet the increasing demands of industrial production. Firstly, we conducted an error analysis of the mass transfer visual positioning system to understand the impact of different error sources on positioning accuracy. Subsequently, based on the results of the error analysis, we proposed an error compensation method that utilizes a high-precision motion positioning platform and laser displacement sensor to calculate the pose of the camera. Additionally, we introduced a Kalman filter with a forgetting factor to iteratively optimize the subsequent calculation of camera pose parameters. Ultimately, through simulation experiments and transfer experiments, we demonstrated that our proposed method can effectively enhance the accuracy of the visual positioning system for mass transfer devices while maintaining high robustness.

Catalysts and electrolyzers for the electrochemical CO2 reduction reaction: from laboratory to industrial applications.

To cope with the urgent environmental pressure and tight energy demand, using electrocatalytic methods to drive the reduction of carbon dioxide molecules and produce a variety of fuels and chemicals, is one of the effective pathways to achieve carbon neutrality. In recent years, many significant advances in the study of the electrochemical carbon dioxide reduction reaction (CO2RR) have been made, but most of the works exhibit low current density, small electrode area and poor long-term stability, which are not suitable for large-scale industrial applications. Herein, combining the research achievements obtained in laboratories and the practical demand of industrial production, we summarize recent frontier progress in the field of the electrochemical CO2RR, including the fundamentals of catalytic reactions, catalyst design and preparation, and the construction of electrolyzers. In addition, we discuss the bottleneck problem of industrial CO2 electrolysis, and further present the prospect of the essential issues to be solved by the available technology for industrial electrolysis. This review can provide some basic understanding and knowledge accumulation for the development and practical application of electrochemical CO2RR technology.

Precise redesign for improving enzyme robustness based on coevolutionary analysis and multidimensional virtual screening.

Natural enzymes are able to function effectively under optimal physiological conditions, but the intrinsic performance often fails to meet the demands of industrial production. Existing strategies are based mainly on the evaluation and subsequent combination of single-point mutations; however, this approach often suffers from a limited number of designable residues and from low accuracy. Here, we propose a strategy (Co-MdVS) based on coevolutionary analysis and multidimensional virtual screening for precise design to improve enzyme robustness, employing nattokinase as a model. Using this strategy, we efficiently screened 8 dual mutants with enhanced thermostability from a virtual mutation library containing 7980 mutants. After further iterative combination, the optimal mutant M6 exhibited a 31-fold increase in half-life at 55 °C, significantly enhanced acid resistance, and improved catalytic efficiency with different substrates. Molecular dynamics simulations indicated that the reduced flexibility of thermal and acid-sensitive regions resulted in a significantly increased robustness of M6. Furthermore, the potential of multidimensional virtual screening in enhancing design precision has been validated on l-rhamnose isomerase and PETase. Therefore, the Co-MdVS strategy introduced in this research may offer a viable approach for developing enzymes with enhanced robustness.

ACD‐YOLO: Improved YOLOv5‐based method for steel surface defects detection

AbstractSince the quality of steel is of paramount importance in modern production, the defects detection of steel surface is significantly crucial. In this field, two‐stage detection algorithms have encountered issues about low detection speed, while one‐stage detection algorithms have room for improvement in detection accuracy. How to trade‐off between accuracy and speed of detection to better meet the demands of industrial production remains a challenge. To address this problem, this paper proposes a You Only Look Once version 5 (YOLOv5)‐based improved method ACD‐YOLO. ACD‐YOLO model incorporates anchors optimization, context augmentation module, and efficient convolution operators. In anchor optimization, the boundaries of anchors are optimized using an improved genetic algorithm. Moreover, to improve detection accuracy, a context augmentation module is incorporated into both the head and the backbone end of the network. Additionally, efficient convolution operators are adopted to address the increase of computation complexity caused by the context augmentation module. Experimental results show that ACD‐YOLO achieves mean average precision of 79.3%, with frames per second of 72. Compared to reference methods, ACD‐YOLO achieves the best balance between accuracy and speed of detection, and is more suitable for practice industrial production.

Magnetic phosphazene porous organic polymer for efficient and selective recovery of rare earth elements from acidic wastewater

Efficient recovery of rare earth elements (REEs) from secondary resources is highly recommended to meet industrial production demand and maximize resource utilization. Herein, a magnetic porous organic polymer, termed MTAP, was developed by choosing natural polyphenol tannic acid as a monomer and hexachlorocyclotriphosphazene as a crosslinker. The integration of magnetic nanoparticles further enhanced its advantages since it can be rapidly isolated using an external magnetic field, simplifying the overall operation. Batch adsorption experimental results showed that MTAP can quickly capture REEs including Ce, Nd, Eu, and Gd, achieving the adsorption equilibrium just in 2 min. Furthermore, the adsorption isotherms exhibited an excellent fit with the Langmuir model with the maximum adsorption capacities ranging from 145.5 to 164.2 mg/g at 25 °C. What’s more, MTAP was successfully applied to recycle REEs in industrial wastewater with high recovery efficiencies. These characteristics including low cost, easy preparation, rapid adsorption kinetics, and high adsorption capacities highlight the outstanding application prospects of MTAP for the recovery of REEs.

METHODOLOGY FOR DETERMINING THE NEED FOR ECONOMIC RESOURCES OF THE ROAD TRANSPORT COMPLEX

The article is devoted to the development of a methodology for determining the need for economic resources of the road transport complex. A mathematical model is proposed for forecasting the demand for various types of resources, based on the demand for industry products.

Detection of Anomalous Behavior of Manufacturing Workers Using Deep Learning-Based Recognition of Human–Object Interaction

The increasing demand for industrial products has expanded production quantities, leading to negative effects on product quality, worker productivity, and safety during working hours. Therefore, monitoring the conditions in manufacturing environments, particularly human workers, is crucial. Accordingly, this study presents a model that detects workers’ anomalous behavior in manufacturing environments. The objective is to determine worker movements, postures, and interactions with surrounding objects based on human–object interactions using a Mask R-CNN, MediaPipe Holistic, a long short-term memory (LSTM), and worker behavior description algorithm. The process begins by recognizing the objects within video frames using a Mask R-CNN. Afterward, worker poses are recognized and classified based on object positions using a deep learning-based approach. Next, we identified the patterns or characteristics that signified normal or anomalous behavior. In this case, anomalous behavior consists of anomalies correlated with human pose recognition (emergencies: worker falls, slips, or becomes ill) and human pose recognition with object positions (tool breakage and machine failure). The findings suggest that the model successfully distinguished anomalous behavior and attained the highest pose recognition accuracy (approximately 96%) for standing, touching, and holding, and the lowest accuracy (approximately 88%) for sitting. In addition, the model achieved an object detection accuracy of approximately 97%.

Insight into the anti-corrosion mechanism of Chinese mahonia leaves as a green and bio-degradable against copper corrosion in sulfuric acid medium

BackgroundMetal corrosion not only leads to significant economic losses for the country but also poses a considerable threat to human safety. The majority of corrosion inhibitors available in the market today fail to meet the demand of industrial production for green and sustainable development. Therefore, it is the pursuit of numerous researchers to find efficient, eco-friendly and low-cost methods for metal protection. MethodsIn this work, the information on the main components in extracts of Chinese mahonia leave (MLE) was determined by liquid chromatography-mass spectrometry (LC-MS). The functional groups of MLE were investigated using Fourier transform infrared spectroscopy (ART-FTIR). X-ray electron spectroscopy (XPS) was selected to detect bonding information between MLE and the surface of copper. The mechanism of the anti-corrosion in the Cu/H2SO4 system has been explored by theoretical calculation and electrochemical measurement. Significant findingsThe electrochemical results showed that MLE could prevent corrosion of copper in the H2SO4 system, and the inhibition efficiency (IE) was 91% at 300 mg/L, MLE predominantly forms a protective film on the copper surface by employing both weak interactions (electrostatic adsorption) and strong interactions (chemical coordination). These interactions effectively isolate the copper substrate from the corrosive medium, resulting in a reduction in the corrosion rate. Combining molecular dynamics simulations with theoretical calculations, we have further confirmed that the N, O, and other heteroatoms in MLE molecules play a crucial role in their corrosion inhibition performance.

From Local to Global: Reconsidering Material Experience in the Age of Global Regionalism

Abstract: Global design tends to simplify and homogenize the discourse of architectural practice. Global practices typically avoid concrete solutions addressing the specific needs of the local. Global production is concerned with solving not a single problem but the same problem at high volume. Global design leads to an estrangement of local tradition and material history, delivering unfitting contextual insertions that progressively impoverish local memory in material, cultural, and ultimately, social terms. The global is not context antagonistic; it is acontextual by definition, because its concerns are related to abstract systems of economic value and the demands of industrial production. Conversely, the local celebrates the idiosyncrasies that relate to a specific location. Local architectural strategies promote a connection between material work and sensory experience, providing an architectural framework for the collective memory that avoids compromising contextual responses with uprooted designs. The tactile experience of materials over time contributes to construct the memory of places, ultimately building up its identity. Material memory opposes the homogenizing and alienating dimension of generic global design. The associations between material perception and collective memory facilitate a foundation for contemporary architectural production through sensory experience, while incorporating regional idiosyncrasies that embody contextual continuities. The connections between material memory and tactility can in fact reveal pathways to productive models of responsible globalism. The qualities embodied in the material memory of a place speak to a common history that embodies the very traces of how and why a place is what it is. Material memory and the direct experience of tactility oppose many of the homogenizing and alienating conditions of generic global design, providing a model that provides continuity between the local and the global, between past and future. This essay reflects on local techniques and material tactility as a potential path to grounding interventions that oppose the homogenizing discourses implemented by global trends. In proposing a model based on Global Regionalism, materials are considered the canvas upon which the intimacy of contextual traces connects memory with innovation, incorporating experience and tradition into the global mainstream.

Nexus between Macroeconomic Factors and Corporate Investment: Empirical Evidence from GCC Markets

The current study aims to explore the role of various macroeconomic factors in determining corporate investment. Using firm-level data of six Gulf Cooperation Council (GCC) region countries for a 14 year period (2007–2020), the current study establishes the empirical analysis by employing the system generalized method of moments (GMM) technique. The empirical results reveal the negative impact of foreign direct investment whilst the positive impact of economic growth, financial development, and inflation rate on corporate investment decisions. Due to high market competition, foreign direct investment can hamper the growth of domestic industrial sectors. However, economic growth, financial development, and inflation rate positively drive the investment by enhancing the demand for industrial products, cheap financing, and price appreciation effect on production enrichment respectively. Based on results, it is suggested that corporate managers should consider the economic sensitivity of investment. The novelty of study can be listed, as the current analysis presents the dynamic role of various economic factors in determining the corporate investment decisions specifically in GCC region countries.

Tandem expression of Ganoderma sinense sesquiterpene synthase and IDI promotes the production of gleenol in E. coli.

Ganoderma sinense, with more than 2000years of medicinal history, is a fungus of the basidiomycetes that is rich in polysaccharides and terpenoids. However, the biosynthesis of terpenes, especially sesquiterpenes, has been little studied. The functional identification of sesquiterpene synthases from G. sinense is of great significance to the study of fungal terpenoid biosynthesis and regulation. Our research group has completed the functional characterization of 21 sesquiterpene synthase genes from G. sinense. It was found that gleenol, biosynthesis of which is catalyzed by the sesquiterpene synthase GsSTS26 and GsSTS27, has the functions of killing termites, antihelminth, and plant growth regulation. In the unmodified E. coli Rosetta (DE3) strain, the content of gleenol produced by sesquiterpene synthase from G. sinense is low, which makes it difficult to meet the demand of industrial production and the market. Therefore, it is of great significance to obtain high-yielding strains by means of synthetic biology. In this study, we constructed eight recombinant strains by using tandem gene expression and promoter engineering, and the content of gleenol was increased by up to 23-fold. In this study, we realized the de novo synthesis of gleenol in E. coli and provided a basis for the biosynthesis of terpenoids in basidiomycetes. KEY POINTS: • Eight recombinant expression systems were constructed by using tandem genes and promoter engineering. • The recombinant strain promoted the efficient production of gleenol in E. coli Rosetta (DE3). • The recombinant strain achieved de novo production of gleenol in E. coli.

Robust energy management for industrial microgrid considering charging and discharging pressure of electric vehicles

The growing number of electric vehicles (EVs) has resulted in increasing availability of battery storage capacities. The energy storage capacity of EVs is used to provide demand flexibility for the supply side. However, the different preferences of EV users will affect the charge and discharge decision of EVs. To overcome this problem, the concept of charging and discharging pressure is proposed to restrict the charging and discharging behavior of EVs. It is mainly dominated by the electricity price. Simultaneously, the charging and discharging time anxiety and state of charge (SoC) of EVs also affect the charging and discharging mode of EVs. This paper proposes a novel industrial microgrid (IMG) structure, which is mainly composed of power demand of industrial production, renewable energy sources (RES), energy storage systems (ESS), EVs and thermal power generation units. The aim of the proposed model is to minimize the operation cost of IMG and maximize the income of EV users. For the management of demand side, the strategy of time of use (ToU) price is adopted. In addition, considering the uncertainty of RES and industrial load, a robust optimization algorithm is proposed, and the operation of IMG under different uncertain scenarios is analyzed. Finally, the robust mixed integer quadratic programming (MIQP) of IMG is studied. The detailed simulation and comparison results verify the effectiveness of the proposed energy system under different charging and discharging pressures based on EVs.

A Review on the Impact of Heavy Metals on Female Fertility

In human health status, the quality of the environment plays an important role. With increased demand for industrial products, food, consumption by continuous growth of human population leads to excessive environmental contamination. The heavy metal group represents pollutants and in natural conditions these elements are not only decompose resistant but may also bio-magnify and bio-accumulate in the food chains which concerns with health problems, seriously connected with a annual emission rate globally. Environment exposure to the most comprehensively distributed pollutants like Cd, Pb, Hg and their contamination causes the main health hazards and at the same time heavy metals exhibits a high level of toxicity against living organisms. According to the considerable toxicological study report from the recent decades, the heavy metals adverse effect on human beings as immunodeficiency, kidney & other organ failures, neurotoxicity, osteoporosis as well as latent involvement in impaired fertility. Epidemiologically and clinically, it is difficult to interpret the metal-induced effect on female reproduction as other factors are also involved. Toxic manifestations depend on intensity of exposure, timing and duration. The eco-toxicological and risk evaluation needs further critical investigation. Along with the implementation of law regulations for the emission limits, the development of awareness campaigns are also required to decrease the harmful habits & lifestyle to develop the successful techniques for fertility protection.

Economic, environmental, exergy (3E) analysis and multi-objective genetic algorithm optimization of isopropyl acetate production with hybrid reactive-extractive distillation

Isopropyl acetate (IPAC) is an important fine chemical intermediate with a great demand for industrial production. In view of the high energy consumption in the traditional reactive distillation (RD) process of IPAC production, this study further proposed three enhanced processes of reactive-extractive distillation (RED), reactive-extractive dividing wall column (REDWC) and reactive-extractive distillation coupled pervaporation (REDPV) process. Firstly, the surface charge density distribution between components is calculated by COSMO-SAC model to screen a variety of potential solvents. Combined with the empirical screening method, relative volatility is used to determine the optimal solvent. Then, the conceptual design of RD, RED and REDWC three processes are completed based on reaction kinetics, and the operating conditions of processes are optimized by multi-objective genetic algorithm. Furthermore, REDPV process using pervaporation module instead of solvent recovery column is proposed. Finally, the total annual cost (TAC), gas emissions and exergy efficiency are used to evaluate the proposed process. The results show that compared with RD process, the TAC and gas emission of RED process are reduced by 42.69% and 49.82%. While those of REDWC process are reduced by 45.06% and 52.93%. The thermodynamic efficiency of these two processes is increased by 63.28% and 62.67%. Compared with RED process, REDPV process further reduces the cost by 14.45% and the gas emissions by 34.55%, but obtain the lowest thermodynamic efficiency.

Estimation of CO2 Emissions Embodied in Domestic Trade and Their Influencing Factors in Japan

CO2 emissions embodied in domestic trade between Japanese prefectures are gradually increasing and becoming an important growth point in the country’s CO2 emissions. The primary objective of this study is to evaluate the CO2 emissions embodied in Japan’s domestic imports and exports to visualize the carbon transfer paths between prefectures according to the attributes of production and consumption: also to identify the influencing factors of the carbon flow. This study estimated the CO2 emissions embodied in domestic imports and exports by prefectures using input–output analysis, followed by the log-mean Divisia index decomposition approach, which is used to quantify the influencing factor of net export CO2 emissions across prefectures. The results show substantial regional differences in the CO2 emissions embodied in domestic imports and exports across prefectures. Manufacturing prefectures satisfy most of Japan’s domestic demand for industrial products and are the main net exporters of CO2 emissions. Carbon flow is more obvious in economically advanced regions (such as the Kanto and Kansai regions) and covers more prefectures through carbon transfer. Consumer prefectures import the most CO2 emissions and export large amounts of CO2 emissions to other prefectures. Among the three factors influencing net export CO2 emissions, the technology effect has the most significant impact through the carbon intensity of domestic trade flows. These findings highlight the substantial differences in CO2 emissions embodied in domestic trade and the influencing factors across prefectures in Japan. The responsibility for emission reduction is attributable to both manufacturing and consumer prefectures.

Study on polyetheretherketone prepreg manufactured by aqueous system of powder impregnation

AbstractAiming to improve safety and stability in manufacturing poly‐ether‐ether‐ketone (PEEK) prepreg by powder impregnation, the aqueous system combined with surfactant and thickener was proposed in this paper. Based on surface tension method, the effects of surfactants and concentration on dispersion efficiency of PEEK powders were studied, and concentration of surfactants was determined. The effect of thickener concentration on suspension stability was analyzed, and ingredients of aqueous system were optimized by mechanical tests. The results show that, dispersion efficiency would reach maximum when surfactant concentration at critical micelle concentration, but not affected by the type of surfactant. Network association mechanism of thickener could improve stability of suspension, which holding time was increased from 40 min to 4 h. The good dispersion effect and long times stable system improved the coefficient variation of resin mass fraction, which was reduced from 7% to 4%. Compared with circulating system, the mechanical test results showed that the tensile strength kept unchanged, but interlayer properties were associated with carbon residue mass, the lower the residue carbon mass, the higher the interlayer strength retention rate, the optimized ingredient was Aerosol OT 75%E solution. Aqueous system has characteristics of safety, green, and low cost, which fits the demands of industrial production of prepreg.