Manganese is an indispensable strategic resource in the steel, chemical, electronics, and new energy sectors. As the primary solid waste generated during the production of electrolytic manganese metal, electrolytic manganese slag accumulates in massive quantities, yet its comprehensive utilization rate remains below 10 %. This slag is rich in characteristic pollutants such as high concentrations of manganese ions (Mn²⁺), ammonia nitrogen (NH₄⁺-N), and sulfates (SO₄²⁻), posing a severe challenge to the ecological environment. In recent years, technologies for the safe disposal of electrolytic manganese slag have primarily included water washing, high-temperature solidification, and chemical solidification; these methods can effectively reduce its leaching toxicity. In terms of resource recovery, research and applications have expanded into multiple directions, such as the production of construction materials (cement, concrete, unburned bricks, and roadbed materials), the development of agricultural fertilizers, the recovery of valuable elements, and the synthesis of high-value-added products.
This study evaluated the reliability of relative translucency parameter (RTP00) and whiteness index (WID) measurements of single-shade and multi-shade resin composites (RCs) with different thicknesses using a spectrophotometer and a mobile colorimeter application. A total of 192 specimens were prepared from six RCs, including three single-shade and three multi-shade materials, with 1 mm and 2 mm thicknesses. Color measurements were performed at baseline and after 7 days using a spectrophotometer and a mobile colorimeter application. RTP00 values were calculated using the CIEDE2000 formula, and WID values were calculated using the CIELAB-based formula. Reliability was assessed using intraclass correlation coefficients, and data were analyzed with robust ANOVA. Single-shade RCs showed higher RTP00 and WID values than multi-shade RCs. ColorMeter values were higher than spectrophotometer values. Material and method effects were significant for ΔRTP00 and ΔWID, with interactions. Reliability analysis showed higher consistency for the spectrophotometer. Mobile colorimeters provide practical and cost-effective measurements, while spectrophotometers remain a more reliable option for precise color assessment. Material type, thickness, and measurement method should be considered when evaluating optical properties for clinical use.
Friction Stir Spot Welding (FSSW) is a solid-state route for joining dissimilar aluminum-copper assemblies, but welding-induced softening and the brittle Al-Cu intermetallic layer limit joint reliability. This work investigates the integrated use of FSSW and Laser Shock Peening (LSP) as a post-weld surface treatment for 3 mm thick AA6061-T6/pure copper lap joints. A Taguchi L9 array with ANOVA was used to optimize rotational speed, dwell time, and tool geometry, identifying tool shape as the dominant factor; the optimum joint was then treated by LSP with a Q-switched Nd:YAG laser and compared with the as-welded baseline. The joint exhibited an asymmetric response: the aluminum side recovered its HAZ softening and exceeded its base-metal hardness, while the copper side softened slightly through laser-induced thermal recovery, yet the joint showed a net strengthening. XRD and FTIR supported grain refinement and the absence of thermal-oxidation damage. The integrated FSSW + LSP route is thus proposed as a viable post-weld strengthening strategy for thick dissimilar Al/Cu joints.
This study explores the fusion of traditional dyeing and weaving art of the Hainan Li nationality with modern textile design using a deep learning–based style transfer approach. The objective is to develop a reliable digital method for preserving traditional textile patterns while supporting sustainable and efficient design applications. Image data of traditional Li patterns and contemporary textile designs were systematically collected and processed to ensure cultural authenticity and visual diversity, forming a high-quality image dataset. A deep learning style transfer model based on adaptive feature transfer and hierarchical fusion (AFTH) was developed to integrate traditional dyeing and weaving patterns with modern textile design. Experimental results indicate that the proposed method demonstrates improved performance in pattern structure preservation, style representation accuracy, and overall visual quality when compared with representative existing methods. In addition, this study incorporates intelligent wastewater treatment and environmentally friendly dyeing technologies to evaluate the environmental and economic benefits of sustainable textile production. By combining machine learning–based process optimization with intelligent sewage treatment systems, resource consumption, chemical usage, and pollutant emissions are effectively reduced. The integrated results demonstrate that digital design innovation and intelligent environmental management can be jointly promoted within the textile industry.
To address the challenge of broadband noise control in electric vehicle doors under the constraints of narrow installation space and lightweight design, this study focuses on unreinforced glass fiber-melamine foam (GF-MF) composites and systematically investigates their acoustic performance regulation mechanisms and engineering structural design for vehicle door applications. Combining the Transfer Matrix Method (TMM) with impedance tube experiments, the effects of porosity, air backing layer thickness, and flow resistivity on the acoustic coefficients of the material were analyzed. A hybrid Finite Element-Statistical Energy Analysis (FE-SEA) model was established to evaluate the sound transmission loss (STL) of five door composite layup schemes under diffuse incidence conditions. The results demonstrate that high porosity significantly optimizes the impedance matching characteristics in the mid-to-high frequency range and enhances broadband sound absorption efficiency, while high flow resistivity effectively strengthens the viscous dissipation capacity in the mid-to-low frequency range. Among all structural layup schemes, the pure air layer scheme yields the highest STL across the full frequency band. Adding a 2 mm viscoelastic damping layer on the outer door panel side further improves low-frequency sound insulation performance. In contrast, positioning the damping layer adjacent to the GF-MF side or adopting a honeycomb sandwich structure leads to acoustic performance degradation. This research elucidates the acoustic parameter regulation laws of glass fiber-melamine foam (GF-MF) composites and the optimization strategies for vehicle door layup designs. A systematic comparative analysis of five layup schemes under identical thickness constraints is conducted. The findings provide practical engineering guidance for the development of lightweight, thickness-constrained acoustic packages in electric vehicle door systems.
