Manufacture Of Materials Research Articles

Mechanisms of interaction between banking institutions and aviation enterprises

It is shown that the main mechanisms of interaction between banks and aviation enterprises are: loans, leasing, collateral financing, risk hedging, project financing, financial consultations and services, factoring, guarantees and insurance. The global aerospace market has been proven to have significant growth potential due to an increase in global GDP, growth in global air traffic and record numbers of new aircraft orders. Innovation, efficiency gains and the development of new markets contribute to the sector's long-term positive outlook. It is shown that the aviation industry is subject to strict regulation at the national and international levels, including requirements for safety, ecology, product quality, data protection and many other aspects. Failure to comply with these requirements can result in serious legal consequences, financial loss and reputational damage. Long supply chains have been found to be an integral part of the aviation industry, ensuring the supply of components and materials for aircraft manufacturing. They have their own advantages and challenges that require effective management and coordination. The use of modern technologies, the development of partnership relations and strategic risk management contribute to increasing the efficiency and sustainability of these chains. It has been determined that the management of the risks of execution of key contracts is extremely important for aviation enterprises. Implementation of effective risk management strategies helps reduce the possibility of problems, ensure timely and high-quality fulfillment of obligations to customers, as well as maintain financial stability and competitiveness in the market. It has been proven that the interaction of banks and aviation companies brings numerous advantages to both parties. Aviation enterprises get access to the necessary financing, risk management and consulting services, which contributes to their development and increased efficiency. Banks, in turn, expand their customer base, increase profitability, develop new products and strengthen their reputation. Such cooperation is an important component of the success of both the aviation industry and the banking sector.

Understanding the Hazards of Hexane and Short-Term Exposure to Air Contaminated with Hexane Affects the Nervous System and can Cause Dizziness

Abstract: The term ‘hydrocarbon’ is self-explanatory which means compounds of carbon and hydrogen only. Hydrocarbons play a key role in our daily life. You must be familiar with the terms ‘LPG’ and ‘CNG’ used as fuels. LPG is the abbreviated form of liquified petroleum gas whereas CNG stands for compressed natural gas. Another term ‘LNG’ (liquified natural gas) is also in news these days. This is also a fuel and is obtained by liquifaction of natural gas. Petrol, diesel and kerosene oil are obtained by the fractional distillation of petroleum found under the earth’s crust. Coal gas is obtained by the destructive distillation of coal. Natural gas is found in upper strata during drilling of oil wells. The gas after compression is known as compressed natural gas. LPG is used as a domestic fuel with the least pollution. Kerosene oil is also used as a domestic fuel but it causes some pollution. Automobiles need fuels like petrol, diesel and CNG. Petrol and CNG operated automobiles cause less pollution. All these fuels contain mixture of hydrocarbons, which are sources of energy. Hydrocarbons are also used for the manufacture of polymers like polythene, polypropene, polystyrene etc. Higher hydrocarbons are used as solvents for paints. They are also used as the starting materials for manufacture of many dyes and drugs. Thus, you can well understand the importance of hydrocarbons in your daily life. In this unit, you will learn more about hydrocarbons

Optimizing sheet metal edge quality with laser-polishing: surface characterization and performance evaluation

Dual-phase (DP) steels are widely used in the automotive industry due to their exceptional performance. It offers excellent strength, ductility, formability, and weldability. However, there is a high risk of edge cracking, particularly in materials like DP1000 steel, caused by residual damage from blanking, such as microcracks and burrs, which needs further investigation. In this study, the transformative potential of laser-polishing on DP1000 steel was investigated. The goal was to reduce edge crack sensitivity and enhance edge formability. In this work, laser-polished samples produced by various pre-manufacturing techniques such as sawing, punching, and waterjet cutting were examined. Various evaluations were performed on laser-polished samples. Those included white-light-confocal microscopy, scanning electron microscopy, and Electron Backscatter Diffraction (EBSD) analysis. Those evaluations aimed to analyze the microstructural transformation, surface roughness, and micro grain size distribution resulting from laser-polishing. Laser-polishing is a process in which the edge of the sample is remelted locally. Hence, residual damage vanishes, and surface defects disappear, which should be beneficial for edge formability. On the other hand, the cooling rate during re-solidification is high, leading to high strength and reduced ductility compared to the initial DP steel. Therefore, hole expansion tests were conducted to evaluate the edge formability of the steel. The results indicated a significant improvement in the hole expansion ratio of the laser-polished samples compared to samples with conventional manufactured edges. These findings will help to assess the advantages and limitations of laser-polishing in sheet material manufacturing.

Impact of the partial substitution of cement and sand by ash from several types of wood species in cementitious materials manufacture: valorization in the industrial field

The main objective of this article is to evaluate the potential use of wood ash as a substitute for cement and sand in mortars. Three types of wood were selected: Ayous, Sapelli and Fraké, all of which were sourced from carpentry in Cameroon. The sawdust was dried and combusted to obtain ash, then ground and sieved. Six types of mortar were produced, with cement substitution at 0%, 5%, 10%, 15%, 20% and 25%. The physico-mechanical properties of these substitutions were determined after 7, 28 and 56 days. The results of the cement paste consistency show that it increases with the addition of ash, due to the fact that sawdust ash requires a large quantity of water. The addition of ash caused an increase in setting time due to the fact that sawdust ash is less reactive than Ordinary Portland cement, resulting in a delay in the rate of cement hydration. Apparent density values decreased with the addition of sawdust ash, probably due to the hygroscopic behavior of type of ash in mortar specimens. The highest pozzolanic index is that of 5% replacement by ash and almost identical absorption for all mortars at this substitution percentage. Acid attack results revealed a higher durability of mortar specimens with the higher percentage of ash substitution. Optimum compressive strengths for the different substitution percentages were observed at 5%, 15% and 10% respectively for Ayous, Sapelli and Fraké. The best wood ash is Sapelli because of its chemical composition and resistance to compression in mortars. At 56 days, compressive strength values exceed those of the reference composition. This may be due to pozzolanic reactions in the mortars of ash.

Osteoclast-Driven Polydopamine-to-Dopamine Release: An Upgrade Patch for Polydopamine-Functionalized Tissue Engineering Scaffolds.

Polydopamine, a mussel-inspired self-adherent polymer of dopamine, has impressive adhesive properties and thus is one of the most versatile approaches to functionalize tissue engineering scaffolds. To date, many types of polydopamine-functionalized scaffolds have been manufactured and extensively applied in bone tissue engineering at the preclinical stage. However, how polydopamine is biodegraded and metabolized during the bone healing process and the side effects of its metabolite remain largely unknown. These issues are often neglected in the modern manufacture of polydopamine-functionalized materials and restrict them from stepping forward to clinical applications. In this study, using our bioinspired polydopamine-laced hydroxyapatite collagen calcium silicate material as a representative of polydopamine-functionalized tissue engineering scaffolds, we discovered that polydopamine can be metabolized to dopamine specifically by osteoclasts, which we termed "osteoclast-driven polydopamine-to-dopamine release". The released dopamine showed an osteoinductive effect in vitro and promoted bone regeneration in calvarial critical-sized defects. The concept of "osteoclast-driven polydopamine-to-dopamine release" has considerable application potential. It could be easily adopted by other existing polydopamine-functionalized scaffolds: just by recruiting osteoclasts. Once adopted, scaffolds will obtain a dopamine-releasing function, which enables their modulation of osteoblast activity and hence elevates the osteoinductive effect. Thus, "osteoclast-driven polydopamine-to-dopamine release" serves as an upgrade patch, which is useful for many existing polydopamine-functionalized materials.

Material selection and manufacturing for high‐temperature heat exchangers: Review of state‐of‐the‐art development, opportunities, and challenges

Material selection and manufacturing for high‐temperature heat exchangers: Review of state‐of‐the‐art development, opportunities, and challenges

Study of stress-assisted nano-cutting mechanism of gallium arsenide

The high-performance manufacturing of hard-brittle materials by single-point diamond turning (SPDT) is a very active and challenging research area. The stress-assisted nano-cutting is a promising method for improving the machinability of hard-brittle materials. However, the simulation results in the existing stress-assisted nano-cutting model would contradict the actual condition due to the pre-stress being released before tool entry into the workpiece. A modified stress-assisted nano-cutting model with a virtual boundary between the workpiece and tool is proposed for the first time in this paper to investigate the nano-cutting process of GaAs material under different external stresses. The emergence of an atomic flow vortex during stress-assisted nano-cutting significantly enhances the quality of the machined surface, leading to a substantial reduction in both machined surface roughness (34.4 %) and subsurface damage (56.2 %), compared to the normal nano-cutting. By evaluating surface roughness, subsurface damage depth, morphological accuracy, cutting force, and removal efficiency, a pre-strain of 0.06 is determined to be the optimal pre-strain for stress-assisted nano-cutting. Moreover, the selection of optimal pre-strain remains unaffected by variations in the nano-cutting depth. TEM results demonstrate that the nano-cutting mechanism elucidated by the MD analysis accurately reflects the genuine deformation of the GaAs material.

Automated optimization for steel mold of precast components based on multi-objective evolutionary algorithm

Designing an economical and reliable steel mold for precast concrete (PC) components can accelerate the promotion of prefabricated buildings. This paper presents an automated design framework for a steel mold of PC components to generate manufacturing information, including dimensions and location of each plate. The profile and dimensions of PC components are extracted from the shop drawings, and a finite element model of the steel mold is established and initialized. A multi-objective optimization model considering material usage and manufacturing convenience is developed to determine the geometry and quantity of plates in steel molds. The non-dominated sorting genetic algorithm II (NSGA-II) is applied to obtain a Pareto solution set for steel mold design. The production information in DXF format can be automatically generated by parsing Industry Foundation Classes (IFC) model. The cost-effectivity and practicality of the proposed framework were verified via the design case for a real PC stair mold.

Green pathways for biomass transformation: A holistic evaluation of deep eutectic solvents (DESs) through life cycle and techno-economic assessment

The utilization of renewable biomass resources to manufacture biofuels, chemicals, and materials has garnered considerable attention. Deep eutectic solvents (DESs) have surfaced as a promising instrument within the realm of biomass conversion, owing to their distinctive attributes such as biodegradability, negligible toxicity, easier fabrication, liquid-phase stability and renewability as opposed to ionic liquids (ILs). Research into DESs, particularly those derived from natural sources, is expanding to advance affordable and sustainable biomass conversion. However, the bottlenecks of DES are its limited solubility for certain biomass constituents, cost and availability. To overcome these hurdles, ongoing research and technological innovations strive to tap into the complete potential of DESs in biomass conversion. This review underscores the importance of evaluating DESs' eco-friendly potential comprehensively, encompassing ecological, financial, and technological standpoints which aims to illuminate how DESs can effectively contribute to sustainable biomass utilization, fostering an environmentally conscious circular bio-based economy.

Multi-objective optimization design of a circular core paper sandwich panel

Abstract Ensuring sufficient mechanical performance while enabling lightweight design is critical for utilizing paper sandwich panels in the furniture industry. To design lightweight sandwich panels that balance mechanical properties and cost, this study developed a circular core paper sandwich panel (CCPSP) and investigated its structural efficiency using multi-objective optimization. The response surface method (RSM) based on Box–Behnken design was utilized to establish mathematical models relating the paper tube spacing, inner diameter, and height to the out-of-plane compressive strength, density, and cost. The resulting models effectively revealed the coupled effects of the parameters on the responses. Subsequently, the models were optimized using the non-dominated sorting genetic algorithm II (NSGA-II) to find the Pareto optimal trade-offs between maximizing compressive strength while minimizing its density and cost. The optimization solution resulted in an optimal set of paper tube geometries that maximized the structural efficiency of CCPSP. Overall, lower tube height conferred superior structural efficiency, while tube spacing and diameter were constrained. The results highlight the potential of CCPSP as an efficient and sustainable material for furniture manufacturing, enabled by multi-objective optimization of its structure.

Reinforcing Efficiency of Recycled Carbon Fiber PLA Filament Suitable for Additive Manufacturing.

The use of 3D printing technology for manufacturing new products based on sustainable materials enables one to take advantage of secondary raw materials derived from recycling. This work investigates the structural performances of 3D printing composite filaments based on polylactic acid (PLA), as a matrix, reinforced by recycled carbon fiber (rCF). Carbon fibers were recovered from industrial scraps by a patented thermal process and used to produce thermoplastic composite filaments for additive manufacturing without any additional treatment and additives. The influence of the recovered carbon fiber (rCF) content on the thermal properties, mechanical properties and microstructure of the composites was studied in the range of 3-20 wt%. The recorded TGA curves exhibited a one-stage weight loss within the temperature range 290-380 °C for all samples and the residual rCF content was in good agreement with the theoretical fiber loading. The Young modulus of the extruded filaments strongly increased below a critical content (5 wt%), while at higher content the improvement was reduced. An increase in the storage modulus of 54% compared to neat PLA 3D printed sample resulted in a printed specimen with a higher rCF content. SEM images highlighted a strong rCF prevailing alignment in the direction of the extrusion flow, creating almost unidirectional reinforcement inside the filament. These findings suggest that homogeneous composite filaments reinforced with well-dispersed recycled CF without additional chemical modification and additives are suitable materials for additive manufacturing. The effect of rCF topological distribution within the material on the mechanical performances has been discussed, highlighting that the isolated fibers could efficiently transfer loads with respect to the percolated 3D network and have been correlated with the microstructure.

Directed evolution of material-producing microorganisms

Nature is home to a variety of microorganisms that create materials under environmentally friendly conditions. While this offers an attractive approach for sustainable manufacturing, the production of materials by native microorganisms is usually slow and synthetic biology tools to engineer faster microorganisms are only available when prior knowledge of genotype-phenotype links is available. Here, we utilize a high-throughput directed evolution platform to enhance the fitness of whole microorganisms under selection pressure and identify genetic pathways to enhance the material production capabilities of native species. Using Komagataeibacter sucrofermentans as a model cellulose-producing microorganism, we show that our droplet-based microfluidic platform enables the directed evolution of these bacteria toward a small number of cellulose overproducers from an initial pool of 40,000 random mutants. Sequencing of the evolved strains reveals an unexpected link between the cellulose-forming ability of the bacteria and a gene encoding a protease complex responsible for protein turnover in the cell. The ability to enhance the fitness of microorganisms toward a specific phenotype and to unravel genotype-phenotype links makes this high-throughput directed evolution platform a promising tool for the development of new strains for the sustainable manufacturing of materials.

Application of CNN for multiple phase corrosion identification and region detection

Corrosion is a significant issue that contributes negatively to the degradation of materials most especially metals. To ensure proper maintenance, enhance reliability and prevent breakdown, it is very essential to not only effectively detect corrosion but to also understand its locations and distributions on the materials. A Multiple phase Convolutional Neural Network (CNN) model is created for this purpose. The Multiple phase CNN model consists of custom designed deep learning algorithms at various stages. This created the opportunity to make use of binary classification, multi-label classification and patch distribution algorithm to detect and identify corrosion regions on metallic materials. Six (6) different labels of corrosion were modelled to represent different levels of degradation using 600 anonymized images. The images were used in the various stages of the framework for training the respective models. Results at the binary level shows 94.87 % of corrosion detection. The multiclass stage of the Multiple phase CNN records the highest accuracy of 92.1 %. The patch distribution stage recorded a highest accuracy of 96.5 % and 94.6 % for the Average Image and Average Pixel ROCAUC (Region of Concentration Area Under Cover). It also shows a region segment average accuracy detection of 91.5 % (image level) and 89.2 %(pixel level) for 9 distinct regions. The research provides a comprehensive and detailed reliability and maintenance information for Aerospace, Transport and Manufacturing Materials experts and non-experts. The framework shows a robust approach to detecting corrosion which is essential for critical and safety applications as well as preventing economic loss due to corrosion. This can also be extended to other domains beyond the corrosion case study.

Obtaining materials for additive manufacturing based on modified oligomeric products of glycolysis of recycled polyethylene terephthalate with diethylene glycol

A technology has been developed for producing a photopolymerizing composition based on modified glycolysis products of recycled polyethylene terephthalate with diethylene glycol. The effect of dimethacrylic ether of triethylene glycol (TGM-3), used as an active diluent monomer, on the physical and mechanical characteristics of finished products is analyzed.

Advanced Manufacturing Transformation: A Strategic Framework for the Smart Factory

This paper presents a comprehensive strategy for implementing advanced manufacturing operations within a Smart Factory framework for a large consumer electronics manufacturer. By leveraging digital twin technology, additive manufacturing, robotics, automation, and advanced materials, this strategy aims to enhance operational efficiency, implement advanced analytics, integrate smart technologies, and sustain competitive advantage. The approach includes ecosystem partner identification, technology integration, process optimization, data management, continuous improvement, governance, and compliance.

The use of mining and metallurgy waste in manufacture of building materials

The use of mining and metallurgy waste in manufacture of building materials

Exploring Basalt: A Methodological Framework for Analysing Wear Traces on Basalt Tools

Basalt is a widely used raw material for tool manufacture at prehistoric sites, but a unified methodology for assessing how hominfins used basalt in prehistory is lacking. A comprehensive experimental investigation of basalt tools is, thus, necessary to establish a reliable methodological framework that can be used to explore the functional properties of archaeological basalt assemblages.The aim of this study is to contribute to the development of a methodological framework for the analysis of use-wear on basalt tools. Basalt, characterised by its distinct mechanical and structural properties and unique response to mechanical stress, requires specialised treatment and investigation.To address this, our basalt varieties were characterised using SEM–EDS analysis. Sequential experiments were conducted, using the experimental basalt tools in different activities, including butchery, hide, bone and woodworking to determine use-wear formation patterns. Subsequentially, various analytical tools, including optical and scanning electron microscopes, were used to analyse macro- and micro-wear traces on basalt.Our results provide useful information on methodological aspects of use-wear formation on basalt. The inclusion of detailed cleaning and experimental protocols enhanced the robustness of our methodology. Furthermore, the combined utilisation of various microscopes enabled to compile a comprehensive and complementary information on such a complex raw material such as basalt and to characterise thoroughly the diagnostic features of the micro-wear traces (e.g. edge damage, rounding, polish).

Advancements in atomic-scale interface engineering for flexible electronics: Enhancing flexibility and durability.

Flexible electronics, such as wearable displays, implantable electronics, soft robots, and smart skin, have garnered increasing attention. Despite notable advancements in research, a bottleneck remains at the product level due to the prevalent use of polymer-based materials, requiring encapsulation films for lifespan extension and reliable performance. Multilayer composites, incorporating thin inorganic layers to maintain low permeability towards moisture, oxygen, ions, etc., exhibit potential in achieving highly flexible barriers but encounter challenges stemming from interface instability between layers. This perspective offers a succinct review of strategies and provides atomic-scale interface modulation strategy utilizing atomic layer integration technology focused on enhancing the flexibility of high-barrier films. It delves into bendable multilayers with atomic-scale interface modulation strategies, encompassing internal stress and applied stress modulation, as well as stretchable composite structural designs such as gradient/hybrid, wavy, and island. These strategies showcase significant improvements in flexibility from bendable to stretchable while maintaining high barrier properties. Besides, optimized manufacturing methods, materials, and complex structure design based on atomic-scale interface engineering are provided, better aligning with the future development of flexible electronics. By laying the groundwork for these atomic-scale strategies, this perspective contributes to the evolution of flexible electronics, enhancing their flexibility, durability, and functionality.

In situ SEM fatigue testing technology for metallic materials: a review.

Fatigue failure is one of the most common fracture modes of structural materials in the industrial field. The study of material fatigue mechanisms and methods for predicting fatigue life has always been of significant interest to researchers due to the abrupt and catastrophic failure mode. In recent decades, the performance and functionality of scanning electron microscopy (SEM) have been continuously improved and expanded. Based on this, the development of in situ fatigue testing in SEM has been rapidly developed. This technology plays a crucial role in providing insights into the deformation behavior of materials under fatigue. Keeping this in view, a comprehensive review of the development and application methods of in situ SEM fatigue testing technology is provided here. The development of in situ SEM fatigue testing devices is provided in brief overview, and the application and research progress of this technology in some representative metal structural materials (nickel-based single-crystal superalloys, steel, aluminum alloys and additive manufacturing materials) are analyzed in detail. Moreover, the perspectives on evaluating fatigue damage, particularly about small cracks and the plastic accumulations fatigue behavior, are presented in this study, utilizing the latest advancements in in situ SEM fatigue testing. Remarks about the present and outlook for future work to be done are then provided.

Artificial intelligence enabled smart design and manufacturing of advanced materials: The endless Frontier in AI+ era

AbstractFuture‐oriented Science & Technology (S&T) Strategies trigger the innovative developments of advanced materials, providing an envision to the significant progress of leading‐/cutting‐edge science, engineering, and technologies for the next few decades. Motivated by Made in China 2025 and New Material Power Strategy by 2035, several key viewpoints about automated research workflows for accelerated discovery and smart manufacturing of advanced materials in terms of AI for Science and main respective of big data, database, standards, and ecosystems are discussed. Referring to classical toolkits at various spatial and temporal scales, AI‐based toolkits and AI‐enabled computations for material design are compared, highlighting the dominant role of the AI agent paradigm. Our recent developed ProME platform together with its functions is introduced briefly. A case study of AI agent assistant welding is presented, which is consisted of the large language model, auto‐coding via AI agent, image processing, image mosaic, and machine learning for welding defect detection. Finally, more duties are called to educate the next generation workforce with creative minds and skills. It is believed that the transformation of knowledge‐enabled data‐driven integrated computational material engineering era to AI+ era promotes the transformation of smart design and manufacturing paradigm from “designing the materials” to “designing with materials.”