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The use of additive manufacturing in many branches of industry is increasing significantly because of its many advantages, such as being able to produce complex parts that cannot be produced by classical methods, using fewer materials, easing the supply chain with on-site production, being able to produce with all kinds of materials and producing lighter parts. The binder jetting technique, one of the additive manufacturing methods researched within the scope of this work, is predicted to be the additive manufacturing method that will grow the most in the next decade, according to many economic reports. Although additive manufacturing methods have many advantages, they can be slower than classical manufacturing methods regarding production speed. For this reason, this study aims to increase the manufacturing speed in the binder jetting method.

Adaptive slicing and variable binder amount algorithm (VBAA) were used to increase manufacturing speed in binder jetting. Taguchi method was used to optimize the layer thickness and saturation ratio in VBAA. According to the Taguchi experimental design, 27 samples were produced in nine different conditions, three replicates each. The width of the samples in their raw form was measured. Afterward, the samples were sintered at 1,500 °C for 2 h. After sintering, surface roughness and density tests were performed. Therefore, the methods used have been proven to be successful. In addition, measurement possibilities with image processing were investigated to make surface roughness measurements more accessible and more economical.

As a result of the tests, the optimum printing condition was decided to be 180–250 µm for layer thickness and 50% for saturation. A separate test sample was then designed to implement adaptive slicing. This test sample was produced in three pieces: adaptive (180–250 µm), thin layer (180 µm) and thick layer (250 µm) with the determined parameters. The roughness values of the adaptive sliced sample and the thin layer sample were similar and better than the thick layer sample. A similar result was obtained using 12.31% fewer layers in the adaptive sample than in the thin layer sample.

The use of adaptive slicing in binder jetting has become more efficient. In this way, it will increase the use of adaptive slicing in binder jetting. In addition, a cheap and straightforward image processing method has been developed to calculate the surface roughness of the parts.

An investigation was conducted into the impact of various process parameters on the surface and subsurface quality of glass-ceramic materials, as well as the mechanism of material removal and crack formation, through the use of ultrasonic-assisted grinding.

A mathematical model of crack propagation in ultrasonic-assisted grinding was established, and the mechanism of crack formation was described through the model. A series of simulations and experiments were conducted to investigate the impact of process parameters on crack depth, surface roughness, and surface topography during ultrasonic-assisted surface and axial grinding. Additionally, the mechanism of crack formation was explored.

During ultrasonic-assisted grinding, the average grinding forces are between 0.4–1.0 N, which is much smaller than that of ordinary grinding (1.0–3.5 N). In surface grinding, the maximum surface stresses between the workpiece and the tool gradually decrease with the tool speed. The surface stresses of the workpiece increase with the grinding depth, and the depth of subsurface cracks increases with the grinding depth. With the increase of the axial grinding speed, the subsurface damage depth increases. The roughness increases from 0.780um/1.433um.

A mathematical model of crack propagation in ultrasonic-assisted grinding was established, and the mechanism of crack formation was described through the model. The deformation involved in the grinding process is large, and the FEM-SPH modeling method is used to solve the problem that the results of the traditional finite element method are not convergent and the calculation efficiency is low.

Stereolithography (SLA) additive manufacturing (AM) technique has enabled the production of inconspicuous and aesthetically pleasing orthodontics that are also hygienic. However, the staircase effect poses a challenge to the application of invisible orthodontics in the dental industry. The purpose of this study is to implement chemical postprocessing technique by using isopropyl alcohol as a solvent to overcome this challenge.

Fifteen experiments were conducted using a D-optimal design to investigate the effect of different concentrations and postprocessing times on the surface roughness, material removal rate (MRR), hardness and cost of SLA dental parts required for creating a clear customized aligner, and a container was constructed for chemical treatment of these parts made from photocurable resin.

The study revealed that the chemical postprocessing technique can significantly improve the surface roughness of dental SLA parts, but improper selection of concentration and time can lead to poor surface roughness. The optimal surface roughness was achieved with a concentration of 90 and a time of 37.5. Moreover, the dental part with the lowest concentration and time (60% and 15 min, respectively) had the lowest MRR and the highest hardness. The part with the highest concentration and time required the greatest budget allocation. Finally, the results of the multiobjective optimization analysis aligned with the experimental data.

This paper sheds light on a previously underestimated aspect, which is the pivotal role of chemical postprocessing in mitigating the adverse impact of stair case effect. This nuanced perspective contributes to the broader discourse on AM methodologies, establishing a novel pathway for advancing the capabilities of SLA in dental application.

This study aims to compare the local climate characteristics of Angkor Wat, Borobudur and Prambanan parks and determine effective strategies for mitigating thermal conditions that could suit Borobudur and Angkor Wat.

The study employed local climate zone (LCZ) indicators and ten-year historical climate data to identify similarities and differences in local climate characteristics. Satellite imagery processing was used to create maps of LCZ indicators. Meanwhile, microclimate models were used to analyze sky view factors and wind permeability.

The study found that the three tropical large-scale archaeological parks have low albedo, a medium vegetation index and high impervious surface index. However, various morphological characteristics, aerodynamic properties and differences in temple stone area and altitude enlarge the air temperature range.

Based on the similarities and differences in local climate, the study formulated mitigation strategies to preserve the sustainability of ancient temples and reduce visitors' heat stress.

The local climate characterization of tropical archaeological parks adds to the number of LCZs. Knowledge of the local climate characteristics of tropical archaeological parks can be the basis for improving thermal conditions.

Unconventional machining processes, particularly ultrasonic vibration cutting (UVC), can overcome such technical bottlenecks. However, the precise mechanism through which UVC affects the in-service functional performance of advanced aerospace materials remains obscure. This limits their industrial application and requires a deeper understanding.

The surface integrity and in-service functional performance of advanced aerospace materials are important guarantees for safety and stability in the aerospace industry. For advanced aerospace materials, which are difficult-to-machine, conventional machining processes cannot meet the requirements of high in-service functional performance owing to rapid tool wear, low processing efficiency and high cutting forces and temperatures in the cutting area during machining.

To address this literature gap, this study is focused on the quantitative evaluation of the in-service functional performance (fatigue performance, wear resistance and corrosion resistance) of advanced aerospace materials. First, the characteristics and usage background of advanced aerospace materials are elaborated in detail. Second, the improved effect of UVC on in-service functional performance is summarized. We have also explored the unique advantages of UVC during the processing of advanced aerospace materials. Finally, in response to some of the limitations of UVC, future development directions are proposed, including improvements in ultrasound systems, upgrades in ultrasound processing objects and theoretical breakthroughs in in-service functional performance.

This study provides insights into the optimization of machining processes to improve the in-service functional performance of advanced aviation materials, particularly the use of UVC and its unique process advantages.

As an advanced manufacturing method, additive manufacturing (AM) technology provides new possibilities for efficient production and design of parts. However, with the continuous expansion of the application of AM materials, subtractive processing has become one of the necessary steps to improve the accuracy and performance of parts. In this paper, the processing process of AM materials is discussed in depth, and the surface integrity problem caused by it is discussed.

Firstly, we listed and analyzed the characterization parameters of metal surface integrity and its influence on the performance of parts and then introduced the application of integrated processing of metal adding and subtracting materials and the influence of different processing forms on the surface integrity of parts. The surface of the trial-cut material is detected and analyzed, and the surface of the integrated processing of adding and subtracting materials is compared with that of the pure processing of reducing materials, so that the corresponding conclusions are obtained.

In this process, we also found some surface integrity problems, such as knife marks, residual stress and thermal effects. These problems may have a potential negative impact on the performance of the final parts. In processing, we can try to use other integrated processing technologies of adding and subtracting materials, try to combine various integrated processing technologies of adding and subtracting materials, or consider exploring more efficient AM technology to improve processing efficiency. We can also consider adopting production process optimization measures to reduce the processing cost of adding and subtracting materials.

With the gradual improvement of the requirements for the surface quality of parts in the production process and the in-depth implementation of sustainable manufacturing, the demand for integrated processing of metal addition and subtraction materials is likely to continue to grow in the future. By deeply understanding and studying the problems of material reduction and surface integrity of AM materials, we can better meet the challenges in the manufacturing process and improve the quality and performance of parts. This research is very important for promoting the development of manufacturing technology and achieving success in practical application.

The purpose of this study is to investigate the influence of varying concentrations of nano-SiO₂ particle doping on the structure and properties of the micro-arc oxidation (MAO) coating of 7075 aluminum alloy. This research aims to provide novel insights and methodologies for the surface treatment and protection of 7075 aluminum alloy.

The surface morphology of the MAO coating was characterized using scanning electron microscope. Energy spectrometer was used to characterize the elemental content and distribution on the surface and cross section of the MAO coating. The phase composition of the MAO coating was characterized using X-ray diffractometer. The corrosion resistance of the MAO coating was characterized using an electrochemical workstation.

The results showed that when the addition of nano-SiO₂ particles is 3 g/L, the corrosion resistance is optimal.

This study investigated the influence of different concentrations of nano-SiO₂ particles on the structure and properties of the MAO coating of 7075 aluminum alloy.

The purpose of this paper was to prepare a ternary hierarchical rough particle to accelerate the anti-corrosive design for coastal concrete infrastructures.

A kind of micro-nano hydrophobic ternary microparticles was fabricated from SiO₂/halloysite nanotubes (HNTs) and recycled concrete powders (RCPs), which was then mixed with sodium silicate and silane to form an inorganic slurry. The slurry was further sprayed on the concrete surface to construct a superhydrophobic coating (SHC). Transmission electron microscopy and energy-dispersive X-ray spectroscopy mappings demonstrate that the nano-sized SiO₂ has been grafted on the sub-micron HNTs and then further adhered to the surface of micro-sized RCP, forming a kind of superhydrophobic particles (SiO₂/HNTs@RCP) featured of abundant micro-nano hierarchical structures.

The SHC surface presents excellent superhydrophobicity with the water contact angle >156°. Electrochemical tests indicate that the corrosion rate of mild steel rebar in coated concrete reduces three-order magnitudes relative to the uncoated one in 3.5% NaCl solution. Water uptake and chloride ion (Cl^-) diffusion tests show that the SHC exhibits high H₂O and Cl^- ions barrier properties thanks to the pore-sealing and water-repellence properties of SiO₂/HNTs@RCP particles. Furthermore, the SHC possesses considerable mechanical durability and outstanding self-cleaning ability.

SHC inhibits water uptake, Cl^- diffusion and rebar corrosion of concrete, which will promote the sustainable application of concrete waste in anti-corrosive concrete projects.

This paper aims to find the best method to predict the friction coefficient of textured 45# steel by comparing different machine learning algorithms and analytical calculations.

Five machine learning algorithms, including K-nearest neighbor, random forest, support vector machine (SVM), gradient boosting decision tree (GBDT) and artificial neural network (ANN), are applied to predict friction coefficient of textured 45# steel surface under oil lubrication. The superiority of machine learning is verified by comparing it with analytical calculations and experimental results.

The results show that machine learning methods can accurately predict friction coefficient between interfaces compared to analytical calculations, in which SVM, GBDT and ANN methods show close prediction performance. When texture and working parameters both change, sliding speed plays the most important role, indicating that working parameters have more significant influence on friction coefficient than texture parameters.

This study can reduce the experimental cost and time of textured 45# steel, and provide a reference for the widespread application of machine learning in the friction field in the future.

This paper is devoted to prepare micro-cone structure with variable cross-section size by Stereo Lithography Appearance (SLA)-based 3D additive manufacturing technology. It is mainly focused on analyzing the forming mechanism of equipment and factors affecting the forming quality and accuracy, investigating the influence of forming process parameters on the printing quality and optimization of the printing quality. This study is expected to provide a µ-SLA surface preparation technology and process parameters selection with low cost, high precision and short preparation period for microstructure forming.

The µ-SLA process is optimized based on the variable cross-section micro-cone structure printing. Multi-index analysis method was used to analyze the influence of process parameters. The process parameter influencing order is determined and validated with flawless micro array structure.

After the optimization analysis of the top diameter size, the bottom diameter size and the overall height, the influence order of the printing process parameters on the quality of the micro-cone forming is: exposure time (B), print layer thickness (A) and number of vibrations (C). The optimal scheme is A1B3C1, that is, the layer thickness of 5 µm, the exposure time of 3000 ms and the vibration of 64x. At this time, the cone structure with the bottom diameter of 50 µm and the cone angle of 5° could obtain a better surface structure.

This study is expected to provide a µ-SLA surface preparation technology and process parameters selection with low cost, high precision and short preparation period for microstructure forming.