Search Results (562)

High-precision rolling bearing applications are widely used in aerospace, new energy vehicles and high-end equipment. However, high-precision bearing manufacturing has always been one of the hot topics of research. The main problem is that the grinding accuracy of rolling bearings is too divergent. In this study, the improvement of grinding accuracy of high-precision rolling bearings was mainly studied. An on-line roundness measurement system was developed and its accuracy was analyzed. The same bearing precision grade, different bearing brands, different bearing sizes and different measurement methods were mainly used for cross-precision measurement comparison. Meanwhile, a static analysis was conducted on the measuring claw. Results indicate that the on-line measurement system can achieve an accuracy of 3 µm. The error rate was less than 11% compared with the current mature measurement technology. Under the action of the same normal measuring force, the deformation of the measuring claw of invar was larger than that of the measuring claw of 45 steel, which was relatively increased by 31%. The conclusion of this study will provide reliable data analysis and a theoretical basis for research in the field of bearing. Full article

Edible powders are important food ingredients, and their quality strongly affects processability, stability, and nutrient delivery. Compared with conventional grinding, superfine grinding enables particle-size reduction to the micron or submicron scale and has shown considerable potential for improving the physicochemical and functional properties of food powders. This review summarizes five representative superfine grinding technologies and discusses how different mechanical force fields regulate powder quality through changes in particle size, specific surface area, cell-wall integrity, and macromolecular structure. Current evidence indicates that superfine grinding can improve hydration behavior, dissolution, the release of bioactive compounds, antioxidant activity, and in vitro bioaccessibility, but these effects are highly dependent on raw-material characteristics and processing conditions. At the same time, excessive micronization may induce particle agglomeration, thermal degradation of sensitive components, sensory deterioration, high energy consumption, and potential safety concerns related to ultrafine particles. Therefore, the performance of a single grinding technology is often constrained by intrinsic physicochemical and engineering limitations. Recent studies suggest that combining superfine grinding with pretreatment, interfacial stabilization, or encapsulation strategies can improve powder stability and functionality more effectively than grinding alone. Future research should focus on standardized evaluation systems, mechanistic clarification across food matrices, and integrated process design for industrial application. Full article

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

Intelligent caving mining requires not only equipment automation, but also the coordinated regulation of production timing, spatial structure, ore output, ore-flow quality, and energy consumption across the mining-processing chain. In caving mines, the state of broken ore flow, drawpoint activation, fragmentation distribution, dilution, ore loss, and ore-waste mixing affects not only underground production stability, but also downstream mineral processing performance, including feed-grade stability, particle-size distribution, pre-concentration potential, and the energy consumption of crushing, grinding, and separation. However, existing studies remain fragmented, with insufficient integration among production scheduling, spatial configuration, ore-flow and ore-output control, mineral-processing-oriented feed quality, and energy efficiency. To address this gap, this review systematically examines the time-space-quantity-energy collaborative feedback framework for intelligent caving mines. The four dimensions are defined as production timing, structural space, ore output and ore-flow quality and energy-consumption constraints, respectively. Recent advances are summarized in production rhythm analysis, spatial modeling, ore-flow and ore-output characterization, fragmentation recognition, energy monitoring and evaluation, digital-twin support, and intelligent control methods. On this basis, this review further reveals the coupling mechanisms by which time organization shapes spatial utilization, spatial structures constrain ore output and ore-flow quality, ore-output and ore-quality fluctuations affect energy-consumption evolution, and energy feedback reshapes production scheduling and spatial allocation. Key challenges are identified in multi-source data integration, mechanism modeling, evaluation methodology, and closed-loop execution. Future research directions are proposed toward digital twin-enabled, data-driven, mineral-processing-oriented, and human-machine collaborative regulation. Compared with existing reviews that discuss intelligent mining technologies, digital-twin architectures, ore-flow control, or underground production planning separately, this review clarifies their shared regulatory logic within a time-space-quantity-energy coupling framework oriented toward mining and processing. Overall, the unified time-space-quantity-energy framework provides a theoretical basis for transforming caving mines from isolated underground production optimization toward intelligent, efficient, low-energy, and mineral-processing-responsive collaborative operation. Full article

Liquid-phase mineralization of CO₂ using coal fly ash (CFA) is an efficient approach to permanent CO₂ sequestration. To address the low leaching efficiency of calcium ions (Ca²⁺) in carbon mineralization, this study systematically investigates the leaching performance and leaching mechanism of calcium ions from CFA by using a sequential alkaline-acid processing (i.e., alkaline activation followed by acid leaching). The effects of NaOH concentration, acid concentration, acid type (HCl/CH₃COOH), reaction time, and grinding duration on leaching efficiency are studied. The reaction products are characterized by X-ray diffraction (XRD) and scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDS). A kinetic model is proposed to analyze the reaction dynamics and leaching mechanisms. The results show that the maximum Ca²⁺ leaching efficiency for untreated CFA is 43.7% after 40-min acid leaching with 7 mol/L HCl and 1:1.5 S/L ratio. The leaching efficiency can be enhanced to 72.1% after 50-min alkaline activation with 11 mol/L NaOH. Grinding the CFA can further increase the leaching performance of Ca²⁺. It is shown that the leaching efficiency can be enhanced to 58.75% and 82.3% after 90-min grinding, respectively, for cases without and with 50-min alkaline activation using 9 mol/L NaOH. It is also shown that a peak leaching efficiency of 86.51% can be obtained when 8 mol/L CH₃COOH is used for the acid system. The mechanism for the enhancement of leaching efficiency is that both NaOH activation and mechanical grinding can break down the calcium and aluminum silicate vitreous matrix of CFA, facilitating calcium release. Ca²⁺ leaching performance exhibits two regimes. The leaching efficiency is significantly time-dependent in the first regime, and it remains almost constant in the second regime after the efficiency reaches a pseudo-maximum value. The contribution of this study is that a theoretical foundation is provided for enhancing the Ca²⁺ recovery from CFA, which makes it practical for large-scale CFA utilization and permanent CO₂ sequestration in industry applications. 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

A comprehensive and systematic study was conducted to address a series of key technical challenges encountered in the grinding process at a copper mine. These issues included the complex mechanical properties of the feed ore, which led to low grinding efficiency, difficulty in achieving the required grinding fineness for flotation, uneven particle size distribution in the grinding products, and severe occurrences of overgrinding and undergrinding. Based on the semi-theoretical ball diameter formula, the optimal initial ball size distribution for the ball mill was precisely calculated as Φ70:Φ50:Φ40:Φ30 = 15:25:35:25. Through laboratory-scale grinding tests and Discrete Element Method (DEM) simulations, a systematic analysis of multiple indicators under three different ball loading schemes was performed, including the motion state of particles inside the mill, the collision behavior of the grinding media, and the energy distribution. This analysis confirmed the rationality and effectiveness of the literature scheme. Industrial trial results showed the following: the yield of the +0.20 mm fraction decreased by 4.15 percentage points, and the yield of the −0.010 mm fraction and its proportion relative to the −0.074 mm fraction decreased by 10.17 and 19.10 percentage points, respectively. Conversely, the yields of the intermediate separated fraction (−0.20 + 0.010 mm), the easily separated fraction (−0.074 + 0.018 mm) and the −0.074 mm qualified fraction increased by 14.32, 14.13, and 7.29 percentage points, respectively. The grinding technical efficiency improved by 19.55 percentage points. Furthermore, the specific steel ball consumption decreased by 46 g/t, a reduction of 5.07%. The copper concentrate recovery increased by 0.65 percentage points, resulting in an annual increase of 40.51 tons of copper metal, additional revenue of CNY 3.2483 million, and steel ball cost savings of CNY 603,500. Collectively, this optimization generated a total economic benefit of CNY 3.8518 million. By optimizing the ball size distribution, the particle size composition of the grinding products was significantly improved, the flotation indicators were enhanced, and the grinding media consumption cost was reduced, achieving quality improvement and efficiency increase in the mineral processing. This study provides a valuable reference for solving similar grinding problems. Full article

Coal-fired power units remain integral to electricity supply in many regions while facing increasingly stringent environmental expectations. Bridging reliable generation with sustainability requires more than end-of-pipe controls; it demands continuous intelligence embedded in plant operations. This study introduces an industry-oriented monitoring framework that transforms historical operational records into actionable foresight, enabling on-the-fly orchestration of combustion conditions to anticipate sulfur oxide (SOx) concentrations. Leveraging 919 empirical data points collected in 2019 from Unit 8 of the Taichung Thermal Power Plant, the framework integrates robust data governance, targeted feature curation, and a neural network-based analytics core. Eight process variables—sulfur content, coal feed rate, fixed carbon, grinding rate, calorific value, excess air, air flow, and boiler efficiency—emerge as the most influential drivers through systematic selection and feature importance attribution. The resulting forecasting module exhibits near-perfect alignment with observed emissions (R² = 0.99), enabling near-real-time guidance for setpoint adjustments and facilitating compliance strategies under varying load and fuel-quality conditions. Beyond accuracy, the system is architected for scalability and portability, aligning with Industry 4.0 paradigms by coupling continuous sensing, data-driven decision support, and stakeholder transparency. By reframing emission oversight as a proactive, intelligent service rather than a static reporting function, the proposed approach advances operational resilience, regulatory compliance, and community trust, with direct implications for resource efficiency and circular economy initiatives across heavy industry. The framework reduces potential SOx emissions and improves energy utilization efficiency under varying operational conditions. This approach contributes to environmental sustainability by enabling proactive emission reduction and cleaner production practices. It supports regulatory compliance and aligns with global sustainability goals, including SDG 7 and SDG 13. Full article

Rapid urbanization and escalating demands for pollution and carbon reduction pose significant challenges to the cement industry in China, characterized by high energy consumption and emissions. However, a multidimensional framework to assess the synergies and trade-offs between environmental, carbon, and economic effects for various decarbonization technologies in cement production is still lacking. Here, six application scenarios of new suspension preheater dry process cement production were developed and evaluated using a life cycle assessment (LCA) framework to quantify environmental impacts, synergistic reduction of pollution and carbon emissions (SRPC), and economic performance. A multi-attribute decision-making model, Analytic Hierarchy Process–entropy–TOPSIS (AHP–entropy–TOPSIS), was applied to assess environmental–economic trade-offs. The results indicate that biomass fuel substitution and high grinding efficiency achieved the best SRPC and environmental–economic trade-off scores (S_norm: 0.17–0.22). Alternative raw materials moderately reduced carbon but increased pollutant emissions and economic uncertainty (S_norm: 0.14–0.20). Mono-ethanolamine absorption and calcium looping provided substantial carbon reduction but weaker overall performance due to environmental trade-offs and higher costs (S_norm: 0.12–0.16). These findings provide quantitative guidance for prioritizing and combining decarbonization strategies to support the green transition and sustainable development of the cement industry. 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

Background: This study proposes a cascade strategy for the comprehensive valorization of Rosa canina L. leaves, considered an underutilized agricultural by-product. Methods: The approach is based on a combination of optimized Ultrasound-assisted extraction (UAE) followed by High-pressure homogenization (HPH) of the residual biomass from both whole and ground leaves. UAE parameters (temperature, process duration, and ethanol concentration) were optimized to maximize the yield of total phenolic content (TPC), total flavonoid content (TFC), and antioxidant activity (DPPH, FRAP). Results: The optimal conditions (55.5 °C, 69.7 min, 40.8% ethanol) yielded extracts with a high TPC (289.55 mg GAE/g) and TFC (177.88 mg CE/g), reducing the processing time by 22% while increasing the TPC yield by 31% compared to the conventional solid–liquid extraction (SLE). It was found that primary extraction from whole leaves is more efficient than extraction from ground leaves, suggesting that the energy-intensive preliminary grinding step could be eliminated. The application of HPH to the residual biomass provided a significant secondary release of bioactive compounds, exceeding high-shear mixing (HSM) by up to 1.5 times for whole leaves. Kinetic analysis showed a higher release of bioactive compounds from whole leaves compared to ground leaves. Conclusions: The proposed UAE + HPH cascade process is a sustainable approach, ensuring rational use of resources and a significant increase in the total yield of antioxidants from Rosa canina L. leaves. Overall, the study may contribute to the circular economy by promoting valorization of agricultural by-products through an energy-efficient, sustainable cascade approach. Full article

To remove the oxide layer of TC1 titanium alloys in an environmentally friendly and efficient manner, this study conducted experiments using a nanosecond pulsed laser to systematically investigate the influence of different laser energy densities on the cleaning effect. The results showed that the oxide layer could be completely removed at an energy density of 6.37 J/cm², with the surface oxygen element content reduced to 4.87%. The macroscopic surface presented a silvery metallic luster. Moreover, the roughness decreased significantly with the increase in energy density. At 6.37 J/cm², the surface roughness dropped to 0.37 µm. The mechanism of removing the oxide layer of TC1 titanium alloy mainly includes laser ablation and plasma impact. At energy densities ranging from 2.55 J/cm² to 6.37 J/cm², the cleaning mechanism was mainly laser ablation. When the energy density exceeded 6.37 J/cm², the cleaning mechanism gradually shifted from laser ablation to plasma impact as the dominant factor. Meanwhile, the microhardness of the samples after laser cleaning was basically consistent with that of the samples subjected to mechanical grinding, which provides a basis for a nanosecond pulsed laser to replace traditional methods for oxide layer cleaning. Full article

High-performance cutting materials are central to modern production engineering. Cemented carbides dominate industrial tooling, while polycrystalline boron nitride (PcBN) is established for hard turning and finishing nickel-based alloys. The associated tool manufacturing chains are energy- and effort-intensive, motivating approaches that reduce material losses and primary energy demand. This study quantifies energy consumption across the production of solid carbide cutting tools with a focus on near-net-shape green machining, its impact on subsequent grinding and material recirculation. It also quantifies energy consumption for regrinding PcBN cutting tools. Power measurements were recorded during green machining and tool grinding of cylindrical versus pre-contoured (green-machined) blanks, including coolant units for the carbide tools during operation. Tool performance of the carbide tools was assessed via milling tests in 42CrMo4; PcBN reground tools were evaluated in Inconel 718. In the process chain of carbide tool production, specific energy decreased from 6.98 to 6.36 kWh/kg (−8.88%) despite +0.461 kWh/kg for green machining; direct recirculation of green-machined material saved an additional 5.861 kWh/kg. Reground PcBN inserts achieved comparable tool life to new tools while reducing energy by ≈85% per insert. The dominant levers for energy reduction are shorter grinding times in the presence of high machine and coolant base loads and systematic regrinding of high-embodied-energy tools. Full article

SAG grinding mills represent critical energy-intensive operations in copper concentrators, accounting for 30%–50% of total plant energy consumption. The accurate prediction of mill power draw and production rate under varying operational conditions is essential for real-time control, production planning, and energy management. This study presents a comprehensive comparison of ML algorithms for modeling Production and Power in a Chilean copper mining industry. Deterministic and stochastic models were fitted and validated using industrial data from a Chilean copper operation. More representative models were re-estimated and subsequently evaluated under different operating regimes to examine their predictive performance under aggregated conditions of the feeding variables. This procedure allowed for the identification of the modeling approaches that provide the most robust performance across varying operational regimes. The results show that XGB achieved the best predictive performance, with test RMSE and R² values of 87.98 and 97.35% for SAG Production, and 431.11 and 95.11% for SAG Power, respectively. Stochastic approaches provided complementary uncertainty quantification, supporting risk-informed decision making under variable operating conditions. The analysis by operational regime indicates that XGB presents better fit in the Thick hydraulic regime, for both responses’ variables, which could be explained why a dense pulp operation provides more predictable grinding dynamics. The comparative analysis reveals trade-offs between model complexity, interpretability, computational requirements, and predictive performance, offering practical guidance for selecting appropriate modeling frameworks based on specific operational objectives and data availability in mineral processing applications. Full article

The progressive phase-out of coal-fired power plants in Portugal has significantly reduced the availability of fly ash (FA) as a supplementary cementitious material (SCM), reinforcing the need for sustainable alternatives. Waste glass powder (WGP), characterized by its high amorphous silica content, has emerged as a promising candidate; however, most studies focus on ultrafine particles or isolated performance indicators, lacking an integrated technical, environmental, and economic assessment. This study evaluates cement pastes incorporating 25% WGP (by volume) with different particle size distributions, including fineness levels comparable to cement and FA. Mechanical performance, grinding energy demand, carbon footprint, and cost were systematically analyzed. The results indicate that WGP is technically viable as an SCM, with a median particle size (D₅₀) of approximately 48 µm providing the most balanced performance. Although finer particles enhance pozzolanic reactivity, the associated increase in grinding energy and economic cost offsets these gains. The findings demonstrate that optimizing particle size, rather than maximizing fineness, enables a technically robust and industrially realistic use of WGP. This approach supports circular economic strategies and contributes to the decarbonization of the construction sector by identifying an efficient replacement pathway for FA under resource-scarcity conditions. Full article