Search Results (524)

The urgent need to mitigate rising global CO₂ emissions demands the development of efficient carbon capture technologies. This study addresses the persistent challenge of sintering-induced performance degradation in CaO-based sorbents during high-temperature CO₂ capture. A novel solvent/nonsolvent synthetic strategy to fabricate CaO/CaAl-layered double oxide (LDO) composites was developed, where CaAl-LDO serves as a nanostructural stabilizer. The CaAl-LDO precursor enables atomic-level dispersion of components, which upon calcination forms a Ca₁₂Al₁₄O₃₃ “rigid scaffold” that spatially confines CaO nanoparticles and effectively mitigates sintering. Thermogravimetric analysis results demonstrate exceptional cyclic stability; the composite achieves an initial CO₂ uptake of 14.5 mmol/g (81.5% of theoretical capacity) and retains 87% of its capacity after 30 cycles. This performance significantly outperforms pure CaO and CaO/MgAl-LDO composites. Physicochemical characterization confirms that structural confinement preserves mesoporous channels, ensuring efficient CO₂ diffusion. This work establishes a scalable, instrumentally simple route to high-performance sorbents, offering an efficient solution for carbon capture in energy-intensive industries such as power generation and steel manufacturing. Full article

The article presents a comprehensive review of key issues and challenges related to enhancing the durability of hot forging tools. It discusses modern strategies aimed at increasing tool life, including modifications to tool materials, heat treatment, surface engineering, tool and die design, die geometry, tribological conditions, and lubrication. The review is based on extensive literature data, including recent publications and the authors’ own research, which has been implemented under industrial conditions at the modern forging facility in Forge Plant “Glinik” (Poland). The study introduces original design and technological solutions, such as an innovative concept for manufacturing forging dies from alloy structural steels with welded impressions, replacing traditional hot-work tool steel dies. It also proposes a zonal hardfacing approach, which involves applying welds with different chemical compositions to specific surface zones of the die impressions, selected according to the dominant wear mechanisms in each zone. General guidelines for selecting hardfacing material compositions are also provided. Additionally, the article presents technological processes for die production and regeneration. The importance and application of computer simulations of forging processes are emphasized, particularly in predicting wear mechanisms and intensity, as well as in optimizing tool and forging geometry. Full article

The global transition towards a low-carbon energy system urgently demands efficient and safe energy storage solutions. Aqueous zinc-ion batteries (AZIBs) are considered a promising alternative to lithium-ion batteries due to their inherent safety and environmental friendliness. However, conventional manufacturing methods are costly and labor-intensive, hindering their large-scale production. Recent advances in 3D printing technology offer innovative pathways to address these challenges. By combining design flexibility with material optimization, 3D printing holds the potential to enhance battery performance and enable customized structures. This review systematically examines the application of 3D printing technology in fabricating key AZIB components, including electrodes, electrolytes, and integrated battery designs. We critically compare the advantages and disadvantages of different 3D printing techniques for these components, discuss the potential and mechanisms by which 3D-printed structures enhance ion transport and electrochemical stability, highlight critical existing scientific questions and research gaps, and explore potential strategies for optimizing the manufacturing process. Full article

The European Union promotes decarbonization in energy-intensive industries like glass manufacturing. Collaboration between industry and researchers focuses on reducing CO₂ emissions through hydrogen (H₂) integration as a natural gas substitute. However, to the best of the authors’ knowledge, no updated real-world case studies are available in the literature that consider the on-site implementation of an electrolyzer for autonomous hydrogen production capable of meeting the needs of a glass manufacturing plant within current technological constraints. This study examines a representative hollow glass plant and develops various decarbonization scenarios through detailed process simulations in Aspen Plus. The models provide consistent mass and energy balances, enabling the quantification of energy demand and key cost drivers associated with H₂ integration. These results form the basis for a scenario-specific techno-economic assessment, including both on-grid and off-grid configurations. Subsequently, the analysis estimates the levelized costs of hydrogen (LCOH) for each scenario and compares them to current and projected benchmarks. The study also highlights ongoing research projects and technological advancements in the transition from natural gas to H₂ in the glass sector. Finally, potential barriers to large-scale implementation are discussed, along with policy and infrastructure recommendations to foster industrial adoption. These findings suggest that hybrid configurations represent the most promising path toward industrial H₂ adoption in glass manufacturing. Full article

The Industrial Internet of Things (IIoT), a key enabler of Industry 4.0, integrates advanced communication technologies with the industrial economy to enable intelligent manufacturing and interconnected systems. Secure and reliable identity authentication in the IIoT becomes essential as connectivity expands across devices, systems, and domains. Blockchain technology presents a promising solution due to its decentralized, tamper-resistant, and traceable characteristics, facilitating secure and transparent identity verification. However, current blockchain-based cross-domain authentication schemes often lack a lightweight design, rendering them unsuitable for latency-sensitive and resource-constrained industrial environments. This paper proposes a lightweight cross-domain authentication scheme that combines blockchain with Chebyshev chaotic mapping. Unlike existing schemes relying heavily on Elliptic Curve Cryptography or bilinear pairing, our design circumvents such computationally intensive primitives entirely through the algebraic structure of Chebyshev polynomials. A formal security analysis using the Real-Or-Random (ROR) model demonstrates the scheme’s robustness. Furthermore, performance evaluations conducted with Hyperledger Fabric and the MIRACL cryptographic library validate the method’s effectiveness and superiority over existing approaches in terms of both security and operational efficiency. Full article

Catalysts are ubiquitous in manufacturing industries and gas phase pollutant abatement but are not widely used in wastewater treatment, as high temperatures and concentrated waste streams are needed to achieve the reaction degradation rates required. Heating water is energy intensive, and alternative, low temperature solutions have been investigated, collectively known as advanced oxidation processes. However, many of these advanced oxidation processes use expensive oxidants such as perchlorate, hydroxy radicals or ozone to react with contaminants, and therefore have high running costs. This study has investigated microwave catalysis as a low-energy, low-cost technology for water treatment using NiO catalysts that can be heated in the microwave field to drive the decomposition of azo-dye contaminants. Using this methodology for the microwave-assisted degradation of two azo dyes (azorubine and methyl orange), conversions of >95% were achieved in only 10 s with 100 W microwave power. Full article

Digitization and green low-carbon are the main directions of China’s economic development in the future. This paper aims to explore the relationship between improvements in the digital level of manufacturing industry segments and carbon emissions. It is found that the digitization level of China’s manufacturing industry segments is still at a low level, which needs to be further improved, and the digitization level of technology-intensive industries is higher than that of capital-intensive and labor-intensive industries. There is a serious misallocation of production factors and R&D factors among manufacturing industries, which is mainly caused by capital factors. Improvement in the digital level of manufacturing industry segmentation can significantly improve the double-layer factor allocation efficiency of the manufacturing industry, and can synchronously realize carbon emissions reduction through improvements in the double-layer factor allocation efficiency of the manufacturing industry; in other words, the improvement in the digital level of China’s manufacturing industry has the dual effects of improving factor allocation efficiency and carbon emissions reduction. Further analysis shows that this effect has significant heterogeneity of ownership. Therefore, China should focus on accelerating the digital transformation of the manufacturing industry, improve the allocation efficiency of traditional and R&D factors in the manufacturing industry through this digital transformation, and accelerate the realization of green and low-carbon development. Full article

Against the backdrop of increasingly severe global climate change, the automotive industry, as a carbon-intensive sector, has found its low-carbon transformation crucial for achieving the “double carbon” goals. This paper constructs manufacturer decision-making models under an oligopolistic market scenario for the single dual-credit policy and the “dual-credit + carbon cap-and-trade” policy, revealing the nonlinear impacts of new energy vehicle (NEV) credit trading prices, carbon trading prices, and credit ratio requirements on manufacturers’ pricing, emission reduction effort levels, and profits. The results indicate the following: (1) Under the “carbon cap-and-trade + dual-credit” policy, manufacturers can balance emission reduction costs and NEV production via the carbon trading market to maximize profits, with lower emission reduction effort levels than under the single dual-credit policy. (2) A rise in credit trading prices prompts hybrid manufacturers (producing both fuel vehicles and NEVs) to increase NEV production and reduce fuel vehicle output; higher NEV credit ratio requirements raise fuel vehicle production costs and prices, suppressing consumer demand. (3) An increase in carbon trading prices raises production costs for both fuel vehicles and NEVs, leading to decreased market demand; hybrid manufacturers reduce emission reduction efforts, while others transfer costs through price hikes to boost profits. (4) Hybrid manufacturers face high carbon emission costs due to excessive actual fuel consumption, driving them to enhance emission reduction efforts and promote low-carbon technological innovation. Full article

In an era defined by rapid technological advancements, the intersection of artificial intelligence and industrial innovation has garnered significant attention from both academic and industry stakeholders. The emergence of Industry 4.0, characterized by the integration of cyber–physical systems, the Internet of Things, and smart manufacturing, demands the evolution of operational methodologies to ensure processes’ sustainability. One area of focus is the development of wearable systems that utilize artificial intelligence for the estimation of arm movements, which can enhance the ergonomics and efficiency of labor-intensive tasks. This study proposes a Random Forest-based regression model to estimate upper arm kinematics using only shoulder orientation data, reducing the need for multiple sensors and thereby lowering hardware complexity and energy demands. The model was trained on biomechanical data collected via a minimal three-IMU wearable configuration and demonstrated high predictive performance across all motion axes, achieving R² > 0.99 and low RMSE scores on training (1.14, 0.71, and 0.73), test (3.37, 1.97, and 2.04), and unseen datasets (2.77, 0.78, and 0.63). Statistical analysis confirmed strong biomechanical coupling between shoulder and upper arm motion, justifying the feasibility of a simplified sensor approach. The findings highlight the relevance of our method for sustainable wearable technology design and its potential applications in rehabilitation robotics, industrial exoskeletons, and human–robot collaboration systems. Full article

The advancement of high-tech industries, notably in semiconductor manufacturing, pharmaceuticals, and precision instrumentation, has imposed stringent requirements on cleanroom environments, where strict control of airborne particulates, microbial presence, temperature, and humidity is essential. However, these controlled environments incur significant energy consumption, with air conditioning systems accounting for 40–60% of total usage due to high air circulation rates, intensive treatment demands, and system resistance. In light of global carbon reduction goals and escalating energy costs, improving the energy efficiency of cleanroom heating, ventilation, and air conditioning (HVAC) systems has become a critical research priority. Recent efforts have focused on optimizing airflow distribution, integrating heat recovery technologies, and adopting low-resistance filtration to reduce energy demand while maintaining stringent environmental standards. Concurrently, artificial intelligence (AI) methods, such as machine learning, deep learning, and adaptive control, are being employed to enable intelligent, energy-efficient system operations. This review systematically examines current energy-saving technologies and strategies in cleanroom HVAC systems, assesses their real-world performance, and highlights emerging trends. The objective is to provide a scientific basis for the green design, operation, and retrofit of cleanrooms, thereby supporting the industry’s transition toward low-carbon, sustainable development. Full article

This paper presents an analysis of the abrasive wear influence on the tooth flank geometry of plastic gear wheels, emphasizing the contribution of tooth stiffness to the observed changes. The study examined gear wheels made from polylactic acid (PLA) with wall thicknesses of 0.6 mm, 1.0 mm and 2.4 mm, manufactured using FDM technology. A standard layer height of 0.2 mm was chosen as it offers a balance between good precision and reasonable printing times. The PLA gear wheels were tested for wear in a meshing configuration with a metallic reference gear. The results indicate that wear intensity increases as tooth stiffness decreases, suggesting an inverse proportionality between abrasive wear and tooth stiffness. In all tested cases, the tooth tip was more affected by abrasive wear compared to the rest of the profile. The analysis establishes that sliding velocity has the greatest influence on the abrasive wear characteristics of the evaluated gears. Based on experimental findings, a mathematical model was developed for simulating abrasive wear in plastic gears, with scalability across various manufacturing technologies. For PLA gears, both experimental and simulated data confirm that full tooth infill is essential for functional durability. Full article

Single-lip deep-hole drilling is a key technology for the precision machining of high-temperature nickel-based alloy pore structures in aero engines. However, the intense thermo-mechanical coupling effects during machining can easily lead to surface integrity deterioration, and the correlation mechanism between microstructure and properties remains unclear. By adjusting the spindle speed and feed rate, a series of orthogonal experiments were carried out to study the integrity characteristics of the machined surface, including surface morphology, roughness, work hardening, and subsurface microstructure. The results reveal gradient structural features along radial depth: a dynamic recrystallized layer (RL) at the surface and a plastically deformed layer (PDL) containing high-density subgrains/distorted grains in the subsurface. With the increase in the spindle speed, the recrystallization phenomenon is intensified, the RL ratio of the machined-affected zone (MAZ) is increased, and the surface roughness is reduced to ~0.5 μm. However, excessive heat input will reduce the nanohardness. Low feed rates (<0.012 mm/rev) effectively suppress pit defects, whereas high feed rates (≥0.014 mm/rev) trigger pit density resurgence through shear instability. Progressive material removal rate (MRR) elevation drives concurrent PDL thickness reduction and RL proportion growth. Optimal medium MRR range (280–380 mm³/min) achieves synergistic RL/PDL optimization, reducing machining-affected zone thickness (MAZ < 35 μm) while maintaining fatigue resistance. These findings establish theoretical foundations for balancing efficiency and precision in aerospace high-temperature component manufacturing. Full article

Under the background of globalization and the latest technological changes, many enterprises ensure corporate competitiveness and sustainable development by deploying production globalization and transforming production modes. This paper proposes a task-based enterprise model to study how enterprises’ production mode transformation toward intelligent manufacturing affects corporate offshoring production. Intelligent manufacturing forms relative push–pull forces on corporate offshoring production through reshoring effects and offshoring effects on the extensive margin of task sets while promoting corporate offshoring production through productivity effects on the intensive margin. Empirically, this paper constructs a staggered quasi-natural experiment using China’s Intelligent Manufacturing Pilot Demonstration Projects (IMPDP), adopts the heterogeneity-robust nonlinear Difference-in-Differences (DID) method, and confirms that intelligent manufacturing has significant positive causal effects on Chinese manufacturing enterprises’ offshoring production. The reshoring effect of intelligent manufacturing is stronger than the offshoring effect, but its powerful productivity effect masks the reshoring effect in overall empirical results. The positive effects of intelligent manufacturing are more significant in non-state-owned enterprises (non-SOEs) and capital-intensive enterprises. Further considering host country selection for corporate offshoring, this study finds that intelligent manufacturing simultaneously promotes corporate offshoring production to both developed and developing countries, but enterprises prefer Belt and Road Initiative countries. Additionally, intelligent manufacturing also promotes corporate offshore trade activities while causing the reshoring of offshore R&D activities. Overall, the transition of production modes toward intelligent manufacturing in Chinese manufacturing enterprises generally leads to a further expansion of corporate offshoring production. Full article

Epoxy resin paper-impregnated bushings, as critical insulating components in power transformers, are subjected to complex electric fields, thermal fields, and mechanical stresses over extended periods. Their performance stability is directly linked to the safe operation of transformers. Given the significant costs associated with their production, reliability verification is a crucial aspect of their design and manufacturing process. This study employs the finite element simulation technology to systematically investigate the electric field distribution characteristics, thermal field distribution characteristics, and seismic performance reliability verification methods of epoxy resin paper-impregnated bushings. The simulation and calculation results indicate that for bushings with rated voltages of 40.5 kV, 72.5 kV, and 126 kV, the maximum radial electric field strengths are 1.38 kV/mm, 2.74 kV/mm, and 3.0 kV/mm, respectively, with axial electric field strengths all below allowable values. The insulation margin meets the 1.5 standard requirements. Under short-circuit conditions, the thermal stability analysis of the bushings reveals that the final conductor temperatures are all below 180 °C, indicating sufficient safety margins. All three types of bushings comply with the design requirements for an 8-degree earthquake intensity and are capable of effectively withstanding seismic loads. This research provides a theoretical foundation for the development and application of epoxy resin paper-impregnated bushings, offering a significant engineering application value in enhancing the safety and stability of transformers and power systems. Full article

This study examines the impact of research and development (R&D) on productivity outcomes across South African industries. Drawing on an industry-level panel dataset covering 66 industries (6 mining, 37 manufacturing, and 23 services) stretching from 1993 to 2023, the study estimates how a change in the initial R&D stock affects labor and capital productivity over a five-year horizon using the Feasible Generalized Least Squares (FGLS) method. The results reveal a positive but weak elasticity of labor productivity to R&D stock (0.01–0.02%), consistent with existing literature. The effects on capital productivity are even lower (0.003–0.005%), suggesting that R&D more directly enhances labor productivity than capital. Sectoral estimations indicate that R&D has no significant effect on labor productivity in mining but a strong productivity effect in manufacturing and services—twice as large in the latter. In contrast, capital productivity gains are only evident in mining. Additionally, the study finds that R&D effects are larger in technology-intensive industries, and the productivity benefits increase with the share of skilled workers, underscoring the importance of absorptive capacity. Overall, the findings suggest that while R&D matters for productivity, its returns are stronger in human capital- and technology-intensive industries. Full article