Search Results (779)

Pebbles are competent ore fragments that are difficult to further reduce in size in conventional comminution circuits, and their efficient treatment is essential for improving circuit stability and lowering downstream grinding energy consumption. In this study, pebbles from the Julong Copper Mine were used to optimize the key operating parameters for high-pressure grinding roll (HPGR)-based pebble treatment. A uniaxial piston compression device was employed to simulate the confined particle-bed breakage process in HPGR, and the effects of feed volume, moisture content, applied pressure, loading speed, and roll surface profile on pebble compression performance were systematically investigated. The compressed products were characterized by particle size distribution, fine fraction yields, and grinding energy indices. The results indicated that the optimal compression conditions were a feed volume of 240 cm³, a moisture content of 6%, a loading speed of 0.2 mm/s, and an applied pressure of 1000 kN. Under these conditions, the products exhibited higher fine fraction yields and lower grinding energy indices, indicating improved subsequent grindability. Moreover, among the tested roll surface profiles, the cylindrical studded platen with 60% coverage produced the best compression performance. The findings provide a useful basis for optimizing HPGR operating parameters for copper ore pebble treatment. Full article

To investigate how the process parameters of ultra-thin diamond grinding wheel dicing affect the dicing quality of silicon carbide (SiC) wafers, single-factor experiments were designed. This study examined the influence of key process parameters, including spindle speed, feed rate, and first dicing depth, on the maximum chip width on the front side W₁ and the maximum chip width on the back side W₂, thereby determining their optimal parameter ranges. Subsequently, a quadratic polynomial prediction model was established using response surface analysis to analyze the interactive effects among the grinding wheel dicing process parameters. Finally, the prediction model was optimized using the genetic algorithm NSGA-II, and the optimal parameter combination for the two response variables was determined: a spindle speed of 31,960 r/min, a feed rate of 2.0019 mm/s, and a first dicing depth of 197.51 μm, yielding an average W₁ of 4.8852 μm and W₂ of 18.5360 μm. The relative errors between the predicted and average experimental values are 2.83% for W₁ and 4.43% for W₂. Both errors are below 5%, confirming the validity of the model. Therefore, the model serves as a practical reference for planning subsequent dicing processes using ultra-thin diamond grinding wheels. Full article

This study proposes a water-jet guidance–ultrasonic grinding hybrid process for drilling holes in ceramic matrix composites to address issues such as cracking, chipping, thermal damage, and low machining efficiency, thereby achieving high-efficiency, high-quality processing of such components. With final surface quality as the constraint, three methods—water-jet guidance, ultrasonic grinding, and the combined water-jet guidance–ultrasonic grinding—were applied to drill holes in SiC_f/SiC composite materials. The study investigated how different processes and parameters affect hole surface quality and machining efficiency. Results demonstrate that the hybrid process effectively overcomes defects inherent to single-process grinding (crazing, chipping) and laser processing (heat-affected zones, recast layers), while significantly removing surface oxides generated by water-jet-guided machining. The hole diameter deviation (<0.017 mm), hole wall surface roughness (Sa < 1.837 μm), and processing efficiency (5.25 min/hole) achieved by this composite process all outperformed those of either ultrasonic grinding or water-jet-guided processing alone. This composite process significantly enhances both processing efficiency and hole wall quality, providing a viable solution for high-quality, efficient machining of ceramic matrix composite components. Full article

The objective of the grinding process is to obtain a better surface finish (roughness, accuracy, etc.) or a high material removal rate of the workpiece. These grinding process response variables depend largely on both the grinding conditions and the topography of the grinding wheels formed during dressing. In this regard, the paper focuses on determining the optimal dressing conditions for grinding wheels dressed with diamond roller dressers during rough and finish grinding. A new multi-objective optimization approach for determining dressing conditions has been proposed, which leads to Pareto-optimal solutions for increasing the grinding process production rate, reducing roughness, and increasing the accuracy of ground surfaces. To demonstrate the performance of this approach, one process of dressing electrocorundum grinding wheels with novel diamond rollers made of medium- and high-strength synthetic diamonds with mixed grain sizes has been selected. Empirical models have been developed to examine the production rate of the grinding process, the roughness of the ground surfaces, and the accuracy of the machined parts. Multi-objective optimization based on a genetic algorithm has been performed by applying two methods: determining an optimal compromise area for the dressing process conditions, and the weighted utility function method. The novelty of the implementation is due to the process of identifying the precise optimal dressing parameters specifically for the investigated mixed-grit diamond rollers. The optimization results show that rough grinding requires uni-directional dressing with a diamond roller AC32 at a feed rate of 1.4 mm/min, a dressing speed ratio of 0.8, a dress-out time of 1.0 s, and a grit size ratio of 2.56, ensuring a production rate of 875 mm³/min, a surface roughness Ra up to 1.25 µm, and a cylindricity deviation up to 12.5 µm. For fine grinding, optimal counter-directional dressing parameters include a feed rate of 0.26 mm/min, a speed ratio of 0.23, a dress-out time of 5.0 s, and a grit size ratio of 2.2, which guarantee a minimum surface roughness Ra of 0.38 µm, a cylindricity deviation of 8.1 µm, and a production rate of at least 600 mm³/min. Full article

In this study, In_0.40Mn_0.15Co_3.85Sb₁₂ was synthesized by the ceramic method, using a traditional melting–annealing treatment (MA), followed by grinding and sintering via the hot-pressing (HP) technique. Rietveld refinement of the powder diffraction (PXRD) data confirms that the resulting phase has a cubic crystal structure in space group Im-3, which is isostructural with the pristine Co₄Sb₁₂ phase. The cell parameter a of the filled In_0.40Mn_0.15Co_3.85Sb₁₂ increases after hot pressing compared with the Co₄Sb₁₂ phase. This suggests that the partial substitution of cobalt atoms with manganese (Mn) alters the cell size of the resulting material. The PXRD pattern of the In_0.40Mn_0.15Co_3.85Sb₁₂ phase of the MA sample shows a low-intensity line (~30°), which is related to elemental antimony (~4%, by Rietveld refinement). Rietveld refinements support a second model which implies the pressure-induced self-insertion of remanent antimony from the (MA) phase into the void sites after (HP) treatment, leading to a new phase: In_0.30Sb_0.10Mn_0.15Co_3.85Sb_11.90 (HP). The vibrational Raman modes of the obtained phases, In_0.40Mn_0.15Co_3.85Sb₁₂ (MA and HP), are correlated with those of the pristine phase, Co₄Sb₁₂. A strong primary signal at 185 cm⁻¹ in the Raman spectrum of In_0.40Mn_0.15Co_3.85Sb₁₂ (MA) is associated with antimony impurities, which is confirmed by Rietveld refinement. Raman spectra of the HP sample are well correlated to the (SPS) Co₄Sb₁₂ phase, which reveals structural changes due to self-insertion of antimony into the voids. The band-gap energy values of both the In_0.40Mn_0.15Co_3.85Sb₁₂ (MA) phase and the (HP) phase are 0.750 ± 0.006 eV and 0.650 ± 0.004 eV, respectively. These values are higher than those of the Co₄Sb₁₂ phase, which has a band-gap energy of 0.55 eV. This indicates that the electronic band structure is modified by the partial substitution of cobalt with manganese and the introduction of indium in the icosahedral cages. Electrical transport properties at room temperature show that In_0.40Mn_0.15Co_3.85Sb₁₂ (MA) and In_0.30Sb_0.10Mn_0.15Co_3.85Sb_11.90 (HP) are n-type semiconductors. Full article

Robotics optimization is essential for improving the performance, efficiency, and reliability of robotic systems, especially when dealing with complex engineering problems involving multiple conflicting objectives. Algorithm-specific parameter-free metaheuristic algorithms have gained attention in such applications because they eliminate the need for problem-specific parameter tuning. However, their performance can be further enhanced by improving convergence and maintaining solution diversity in multi-objective optimization. This paper proposes three multi-objective variants—archive, opposition, and self-adaptive multi-population (SAMP)—for the algorithm-specific parameter-free BxR algorithms such as Best–Mean–Random (BMR), Best–Worst–Random (BWR), and Best–Mean–Worst–Random (BMWR). The proposed variants are evaluated on five robotic optimization problems spanning two to six objectives, including Autonomous Underwater Vehicle shape optimization, power line inspection robot design, inverse kinematics of a 4-DOF manipulator, wall-building robot trajectory planning, and optimization of a reconfigurable parallel cutting and grinding mechanism. Their performance is compared with several established multi-objective algorithms using metrics such as GD, IGD, SPC, and HV, supported by rigorous statistical testing involving Friedman tests, Conover post hoc analysis with Holm correction, and Vargha–Delaney A₁₂ effect sizes over 30 independent runs. The results show that archive variants achieve the best IGD rank in four of the five case studies and the best HV rank in three of them, with the five-objective trajectory planning problem being the sole exception where SAMP and base BxR variants show improved IGD performance. The base BxR algorithms prove to be strong competitors, consistently outperforming established parameter-dependent methods on IGD across all five problems. The opposition variants do not provide consistent improvement; however, they also do not cause catastrophic degradation, suggesting that refined opposition strategies warrant further investigation. The study demonstrates the effectiveness of the proposed algorithms as practical optimization tools for complex robotic optimization problems. Full article

HT250 grey cast iron is a material of significance in the manufacture of precision machine tool guideways. The performance of guideways is significantly affected by the wear resistance of the machined surface. The present paper studies comparative grinding experiments conducted on HT250 using CBN and SiC wheels. The aim was to investigate the potential benefits of CBN grinding in enhancing surface wear resistance and to illuminate the underlying mechanisms. The results of these experiments demonstrate that, compared with SiC grinding, CBN grinding produces guideway specimens’ subsurface layer with finer grains (refined by approximately 15%) and notably higher microhardness (peak value of 382 HV). These microstructural improvements directly enhance the wear resistance of the ground surface. Within the tested parameter range, the optimal wear-resistant surfaces were obtained at a grinding speed of v_s = 30 m/s, a feed rate of v_f = 2000 mm/min, and a depth of cut of a_p = 6 μm. Under these conditions, surface roughness is better than R_a 0.4 μm, and surface microhardness achieves its maximum value. The wear tests were conducted using a ball-on-disk configuration under room temperature, oil lubrication, and applied loads ranging from 20 N to 80 N. The results show that, under the same loading and wear testing conditions, the wear depth of specimens machined with CBN wheels is reduced to 80–50% of that of specimens processed with conventional SiC wheels. Full article

PCBN tools are widely used in the machining of ferrous metals. Tool edge preparation is a crucial procedure in the tool preparation process that directly affects tool performance. In this paper, tool chamfer grinding and edge blunting were conducted on the PCBN tool to investigate the effect of material microstructures. In tool chamfer grinding, the PCBN tool with larger particles exhibits a larger chamfer width error and roughness than that of smaller particles, and the PCBN tool with higher Al content exhibits a larger chamfer width error and roughness than that with lower Al content. The optimal tool chamfer grinding speed is 24 m/s for the PCBN tool with larger particles, and 27 m/s for smaller particles. The optimal feed rate is 70 mm/min for both PCBN materials. In edge blunting, PCBN tools with larger particles or lower Al content are more difficult to passivate, and the optimal blunting time is about 30 s for an edge radius of 30 μm. The PCBN tools were prepared using the obtained machining parameters and used in the turning of brake pads. It is found that the PCBN tool with smaller particles exhibits longer life than that of larger particles. Although it exhibits the same wear characteristics, the tool life of the PCBN tool with lower Al content is longer than that of the tool with higher Al content. Full article

Matcha, a finely milled powdered green tea originating from Japan, is characterized by a unique cultivation method in which tea plants are shaded prior to harvest. This practice enhances the accumulation of chlorophyll, caffeine, L-theanine, and other bioactive compounds. In addition, specialized post-harvest processing, including careful hand-picking, gentle steaming, drying, and traditional stone grinding, helps preserve the nutritional and biochemical integrity of the tea leaves. This review examines the relationship between cultivation and processing techniques and the resulting bioactive composition of matcha. It also summarizes current scientific evidence regarding the potential health-promoting properties of matcha and its major constituents. The analysis is based on available scientific literature, including both in vitro and in vivo studies investigating the biological activity of matcha and green tea catechins. Particular attention is given to studies evaluating their effects on metabolic parameters such as glucose levels, lipid profile, body weight regulation, and gut microbiota composition. In addition, the potential influence of matcha-derived compounds on neurological function, systemic physiological processes and anticancer potential is discussed. Furthermore, matcha is increasingly recognized as a functional food ingredient and has been incorporated into a variety of products, including bakery goods, dairy products, functional beverages, and nutraceutical formulations. The collected findings suggest that matcha may exert a broad spectrum of beneficial biological effects due to its high concentration of polyphenols, amino acids, and antioxidants. Nevertheless, despite promising experimental and preclinical data, further well-designed clinical studies are needed to better understand the mechanisms of action, bioavailability, and long-term health effects associated with regular matcha consumption. Full article

Silicon carbide particle-reinforced aluminum matrix (SiCp/Al) composites are prone to surface defects during grinding owing to the heterogeneous deformation of the aluminum matrix and SiC particles, rendering conventional two-dimensional roughness parameters inadequate for precise surface characterization. In this study, three-dimensional surface roughness parameters were adopted to assess the ground surface quality of SiCp/Al composites. Orthogonal grinding experiments were carried out with four key process parameters (grinding wheel grit size, spindle speed, feed speed, and grinding depth), and the quantitative relationships between processing parameters and 3D roughness parameters, including arithmetical mean height (Sa), root mean square height (Sq), skewness (Ssk), kurtosis (Sku), surface bearing index (Sbi), core fluid retention index (Sci), and valley fluid retention index (Svi), were analyzed. The results reveal that the machined surface presents typical features including grooves from abrasive–matrix interaction, pits induced by SiC particle pull-out, scratches caused by dragged SiC particles, and tailing phenomena due to aluminum matrix melting under grinding heat. Grinding parameters exert distinct effects on surface topography: grinding wheel grit size shows the most significant influence on the Sa index, with its weight decreasing from 34% to 13% as grit becomes finer, while the combined influence weight of spindle speed, feed speed and grinding depth increases from 22% to 29%. Based on the comprehensive 3D roughness evaluation index, the optimal grinding parameter combination is determined as 320# grinding wheel, 4000 r/min spindle speed, 20 mm/min feed speed and 20 μm grinding depth. Additionally, the PSO-BP neural network achieves higher accuracy and better stability in predicting Sa and Sci than the conventional BP neural network. Full article

Repurposing mineral processing waste offers both environmental and economic benefits, reducing the disposal burden while enabling mineral resource recovery. A magnetic adsorbent, with an Fe₃O₄ content of 71.0%, collected from waste copper converter slag was utilized to recover gold (Au³⁺) from chloride solution. The adsorbent was separated from the slag samples by crushing, grinding to an average particle size of 30 μm, and magnetic separation. Batch adsorption experiments were performed to evaluate the effects of pH, contact time, chloride concentration, and initial gold concentration on gold uptake amount. The material recovered over 99% of gold from chloride solution under acidic conditions and in the near-neutral pH range. The gold sorption rate was also relatively fast and over 98% recovery was achieved after just 15 min of contact time. Increasing chloride concentration did not influence gold uptake. Parameter studies and spectrometric analyses suggest that chalcocite (Cu₂S) and metallic copper present in magnetite slag reduced the gold chloride complex to metallic gold. These results suggest that converter magnetite slag is a potentially effective sorbent to recover gold from secondary sources due to its selectivity and low cost. Moreover, gold-loaded magnetite slag can be easily separated from the solution by magnetic separation and then recirculated to the smelting stage of copper processing to recover the deposited gold and other precious metals. Overall, this work highlights a pathway to transform waste into opportunity, reinforcing sustainability in mineral processing operations. Full article

Additively manufactured lightweight lattice structures typically consist of thin walls with thicknesses ranging from hundreds of micrometers to millimeters. Within this range, such thin walls exhibit a pronounced size effect. Despite extensive research on the topic, a clear mapping between key influencing factors and mechanical properties remains lacking. This gap makes it challenging to accurately predict mechanical performance across different wall thicknesses, especially for those below 500 μm. In this work, Ti-6Al-4V thin-walled tensile specimens with thicknesses ranging from 0.2 mm to 1.0 mm were fabricated via laser powder bed fusion (LPBF). The variations in mechanical properties, microstructure, surface defects, and internal defects were investigated. The results indicate that yield strength (YS) and ultimate tensile strength (UTS) decreased significantly as thickness decreased, dropping from 794.1 MPa to 471.7 MPa and from 910.7 MPa to 485.2 MPa, respectively. Printing defects were identified as the dominant factors governing the size effect: strength was jointly affected by surface and internal defects, whereas failure mode and ductility were primarily governed by internal defects. By introducing an effective thickness ratio parameter, a semi-empirical predictive model was developed to characterize the strength-thickness relationship and to quantify the individual contributions of surface defects and other coupled interior factors. Subsequently, ultra-thin specimens were subjected to surface grinding and polishing to alleviate surface defects, leading to improvements in YS and UTS of approximately 27–39% and 22–45%, respectively. The model-predicted strengths of the surface-treated specimens were in good agreement with the measured values, further validating the effectiveness of the proposed model. Full article

Tungsten carbide and cobalt cutting tools require low surface roughness to improve cutting performance by reducing the wear from machining friction. While this is achieved by conventional manufacturing processes (pressing and sintering, grinding), with additive manufacturing processes it is more difficult (layer height, printing strategy). Since less costly and more sustainable solutions (without lubricants) are being studied as alternatives to conventional processes, a complementary technology (laser ablation) is suggested for the additive manufacturing of green WC-10Co. In this study, material extrusion (MEX) was used to produce green WC-10Co 3D objects, followed by laser ablation (50 W ytterbium fiber laser, 800–1100 nm wavelength) on their surface. Different laser strategies and parameters (power, speed, frequency, distance between lines, number of passages) were tested to find the most suitable. Most combinations were excluded by initial visual inspection, while the best ones were measured with a contact and non-contact profilometer. Further analysis was made on the composition and microstructure (with techniques such as Raman spectroscopy, scanning electron microscope, x-ray diffraction, and hardness indentation) to study what the interaction with the laser changed on the surface. Results show that with a combination of 50 W laser power, 1000 mm/s laser speed, 2000 kHz laser frequency, 0.1 mm distance between lines and three laser passages, it was possible to achieve a surface roughness of 0.6 µm (Sa) for the sintered WC-10Co, produced by MEX. No η-phase and graphite were detected, as well as microporosity and fissures. Full article

The occurrence of short-wave corrugation with wavelengths of 32–44 mm on curved sections of urban express railway lines is particularly pronounced, yet the underlying initiation mechanisms have remained insufficiently understood. Furthermore, conventional mitigation strategies—including the installation of rail dampers and passive grinding—entail substantial maintenance expenditures, thereby hindering their large-scale application. To elucidate the initiation mechanisms of rail corrugation and to formulate effective control measures, the characteristic corrugation parameters under various track structure configurations across an entire alignment were first measured and systematically analyzed. Dynamic interaction models between vehicles and three distinct track typologies were subsequently developed, together with a comprehensive analytical framework for corrugation evolution. The wheel–rail dynamic response characteristics and corrugation growth rates corresponding to each track type were examined, and the wheel–rail coupled vibration modes that exacerbate corrugation propagation in urban express lines were identified. The instantaneous wear behavior of the rail under differing creep regimes was also investigated, leading to the proposal of a novel self-mitigating approach for rail corrugation. The results demonstrate that the excitation frequency of rail corrugation is predominantly confined to the 600–700 Hz range, exhibiting a fixed-frequency characteristic that remains invariant with respect to curve radius, track structure type, and operational speed. An interesting finding is that, although the intrinsic vibration properties of different track structures diverge significantly, the third-order bending resonance of the rail segment situated between bogie wheels is largely unaffected by track-borne vibrations and manifests as a localized wheel–rail resonance within the vehicle–track coupled system. This particular resonance markedly accelerates corrugation development and is identified as the critical governing factor for corrugation initiation in urban express lines, regardless of the underlying track configuration. Furthermore, rail instantaneous wear displays a substantial phase shift under varying creep conditions, with the wear profiles under creep saturation (full sliding) and low creep (rolling–sliding) exhibiting a distinct anti-phase relationship. This insight underpins a novel self-wear suppression strategy: by intentionally mixing rolling–sliding and full-sliding operational regimes, destructive interference between the out-of-phase wear contributions is achieved, resulting in a considerably attenuated corrugation growth rate compared with exclusive rolling–sliding operation. This methodology thus offers a promising and fundamentally new alternative for the long-term management of rail corrugation through intrinsic wheel–rail interaction. Full article

Based on the separate grinding process for raw meals in the cement industry, raw meal samples with different particle size characteristics were prepared by controlling the fineness of calcareous components. The results show that the fineness of the calcareous components has a significant influence on the burnability of the clinker and that a critical threshold exists (80 μm sieve residue (R_80μm) = 15%). When the particle size exceeds this critical value, the particle size effect becomes dominant, leading to a nonlinear and sharp increase in f-CaO content. As the proportion of coarse particles larger than 200 μm increases, the f-CaO content rises markedly, with a greater impact than that of 80 μm particles. Microscopic analysis of the clinker reveals that with coarsening of the calcareous components (increase in R_80μm), alite (C₃S) content decreases, whereas belite (C₂S) and f-CaO contents gradually increase and exhibit enrichment. Based on diffusion-controlled kinetics, a semi-empirical reaction kinetics model, $f\text{-}\mathit{CaO} = A·\mathit{exp}{\displaystyle \frac{(E_{a,0}+k·R_{80 \mathsf{\mu }\mathrm{m}})}{\mathit{RT}}}·({R_{80\mathsf{\mu }\mathrm{m}})}^n$, was developed by introducing the apparent activation energy parameter E_a(R_80μm) as a function of particle size. The model exhibited excellent goodness of fit (R² > 0.95), with an intrinsic activation energy E_a,0 = 18.7 kJ·mol⁻¹ and an incremental coefficient k = 0.28 kJ·mol⁻¹·%⁻¹. Validation experiments yielded a relative error of 4.3%. This model quantifies the coupled effects of temperature and particle size, providing quantitative guidance for balancing grinding energy consumption and sintering energy consumption. Full article