Surface Method Research Articles

Recent advances in biomimetic superhydrophobic surfaces: focusing on abrasion resistance, self-healing and anti-icing.

Superhydrophobic materials have been widely used in the fields of materials engineering and the coating industry due to their excellent abrasion resistance, corrosion resistance, anti-icing and antibacterial properties and have also attracted the attention of many researchers. However, in the process of application, their superhydrophobic surface is susceptible to external factors such as physical or chemical effects, resulting in the loss of low surface energy materials or the destruction of micro- and nano-rough structures, thus losing their superhydrophobic properties. This review describes the research progress in three aspects of superhydrophobic surfaces: abrasion resistance, self-healing, and anti-icing. Firstly, the definition and application of superhydrophobic surfaces, as well as the basic principle and mechanism of superhydrophobic surfaces are introduced. Then, the research status and improvement methods of superhydrophobic surfaces are presented in detail from three aspects, such as abrasion resistance, self-healing, and anti-icing. Finally, the research process of superhydrophobic surfaces is evaluated and prospected in order to provide a new perspective for the preparation of superhydrophobic surfaces with a wide range of applications and better performance.

Heat transfer characteristic and optimization design of alter diameter array impingement cooling structure

The fine design of blade cooling is one of the leading directions in the development for blade manufacturing technology, attaining optimal and consistent cooling efficiency is the common research concern in the field of fine design. In the current work, the alter diameter hole arrays are applied to reasonably regulate the distribution of cold air flow, which aims to achieve uniform cooling performance of impinging cooling technology. Experiment involving temperature sensitive paint technology and simulation based on SST k-w turbulence model are conducted. Subsequently, the mechanism of cooling performance increasement is investigated; the impact of structural elements on the heat transfer properties is discussed. Moreover, the correlation between the Nu number of the target surface and the comprehensive influence factors was fitted based on response surface method; the optimal structure in the range of the structural parameters is calculated based on NSGA-II and TOPSIS method. The results reveal that the influence of d and x on average surface Nusselt number is remarkable. In addition, the response surface model fitting model is accurate to predict the structure parameter effect on cooling performance of alter impingement cooling, with the prediction error less than 2.67 %. Compared with the basic EDI, the Nu of the ADI structure with ∇T constraint is increased by 5.2 %, the temperature inhomogeneity is reduced by 53.4 %. The significant improvement of temperature inhomogeneity indicates the practicality of ADI structure and optimized procedure used in improving impingement cooling efficiency which shows promising performance increasement.

Effect of high-density-polyethylene (HDPE) and waste tire rubber (WTR) on laboratory performance of styrene butadiene styrene (SBS) modified asphalt

To reduce the cost of SBS modified asphalt, we incorporated waste high-density polyethylene (HDPE) and waste tire rubber (WTR) as partial substitutes for SBS modifier. The performance parameters for HDPE, WTR, and SBS synergistic modified asphalt were designed using the response surface method. Specifically, modified asphalt groups with excellent conventional properties were identified through penetration, softening point, and ductility tests. The high/low-temperature rheological properties and anti-aging properties of the selected modified asphalt were investigated. The modification mechanism of the composite modified asphalt was studied using fluorescence microscopy (FM). Subsequently, a cost analysis of the modified asphalt was conducted. Based on the aforementioned studies, we recommend a composition of 1.5% SBS, 3% HDPE, and 10% WTR, which demonstrated superior performance compared to 4% SBS modified asphalt. Furthermore, the cost of the modified asphalt was found to be 13.3% lower than that of SBS modified asphalt.

Eco-friendly iron extraction from fe-containing copper smelting slag via reduction roasting with coal and magnetic separation: Experimental and mechanism insights

Copper smelting slag (CSS) is a byproduct produced during the thermal smelting of copper and poses a considerable environmental challenge, particularly in China, where its accumulated volume surpasses 1.8 billion tons. This study utilized the response surface method (RSM) to optimize experimental procedures and reduce costs, the results showed that the effects of each factor on iron recovery were in the following order: roasting temperature > roasting time > coke dosage. The optimized iron recovery of iron extraction from CSS by Magnetization-roasting reached 78.87 %, while the actual iron recovery was 78.84 %. The relative error is very small, indicating that the model is effective. Conducted the thermodynamic computational analysis to understand the migration of metal phases in CSS, employed XPS analysis to identify valence changes in key elements, and the clever combination of restricted reduction kinetics and SEM-EDS analysis shows that the reduction reaction of CSS is mainly controlled by interfacial chemistry and carbon gasification at low temperatures. By processing CSS, the study successfully produced environmentally friendly iron that can be recycled, offering a sustainable solution for managing toxic waste from copper production.

A new formulation for predicting the ultimate capacities of FRP-confined concrete using advanced machine learning framework: Developed structural reliability analysis

Maintaining the safety levels of concrete structures is critical, where boosting the strength and deformability of such components utilizing Fibre Reinforced Polymer (FRP) composites is well adopted. However, the outside environment and applied loads can influence the FRP confined concrete. Therefore, accurate assessment of the ultimate capacities of FRP-confined concrete is highly essential. This paper proposes an advanced machine-learning framework using a novel approach called Group Method Data Handling Neural Network (GMDH-NN) for developing novel formulations that properly predict the ultimate capacities of FRP-confined concrete. The GMDH-NN ability in terms of tendency, agreement, and accuracy is compared to the existing empirical correlations and well-known machine-learning methodologies, notably Artificial Neural Network (ANN) and Response Surface Method (RSM). Furthermore, to address the failure modes of strength and ductility, the reliability analysis of FRP-confined concrete using combined Monte Carlo simulation (MCS) with the proposed GMDH-NN is examined for three types of composite sheets: Aramid, Carbon, and Glass. Results prove the GMDH-NN outperformance for modeling the ultimate strength (R2 =0871) and strain (R2 =0.79) capacities for FRP-confined concrete. The structural reliability analysis indicated that the choice of FRP sheets had a substantial influence on the increase of the safety levels of confined concrete cores, as well as the requirement for early prediction of these parameters to avoid failures.

Anti-corrosion and anti-icing properties of superhydrophobic laser-textured aluminum surfaces

Superhydrophobic surfaces have favorable properties in simultaneously reducing the negative effects of corrosion and ice accumulation. In this study, laser-texturing was employed as a facile and environmentally friendly surface method to prepare a surface with hierarchical roughness for subsequent grafting by immersion in an ethanol solution containing 1H,1H,2H,2H-perfluorodecyltriethoxysilane (FAS-10). Various analytical techniques were utilized to assess the characteristics of the laser-textured aluminum surfaces before and after grafting, such as a contact profilometer, optical tensiometer, scanning electron microscope with energy-dispersive spectroscope, and X-ray photoelectron spectroscope. These methods were used to evaluate surface roughness, wettability, morphology, and composition. The corrosion properties were evaluated through potentiodynamic and impedance measurements in a dilute Harrison's solution (DHS) composed of 0.35 wt% (NH4)2SO4 + 0.05 wt% NaCl. Additionally, freezing delay tests at various surface temperatures were performed to assess the surface's ability to prevent the freezing of water droplets on the treated surface. The laser-textured aluminum surface, featuring micro/nanostructures and a grafted nanoscopic perfluoroalkyl silane film, exhibited outstanding superhydrophobicity and enhanced corrosion protection. The developed surface has been shown to significantly delay the onset of ice nucleation and extend the freezing delay.

Improving the Performance of Natural Gas Engine at High Altitude Based on Response Surface Method and NSGA-II Optimization

Improving the Performance of Natural Gas Engine at High Altitude Based on Response Surface Method and NSGA-II Optimization

Response Surface Design Models to Predict the Strength of Iron Tailings Stabilized with an Alkali-Activated Cement

Tailing storage facilities are very complex structures whose failure generally leads to catastrophic consequences in terms of casualties, serious environmental impacts on local biodiversity, and disruptions in the mineral supply. For this reason, structures at risk must be reinforced or decommissioned. One possible option is its reinforcement with compacted filtered tailings stabilized with binders. Alkali-activated binders provide a more sustainable solution than ordinary Portland cement but require an optimization of the tailing–binder mixture, which, in some cases, can lead to a substantial experimental effort. Statistical models have been used to reduce the number of those experiments, but a rational design methodology is still lacking. This methodology to define the right mixture for a required strength should consider both the mixture components and in situ conditions. In this paper, response surface methods were used to plan and interpret unconfined compression strength test results on an iron tailing stabilized with alkali-activated binders. It was concluded that the fly ash content was the most important parameter, followed by the liquid content and sodium hydroxide concentration. From the obtained results, several statistical models were defined and compared according to the definition of a strength prediction model based on a mixture index parameter. It was interesting to observe that models with the porosity cement index still provide reasonable adjustment even when different tailings’ water contents are considered.

Atomistic simulation on the deposition behavior of cold spray

Cold spray is an effective method for surface coating, which has been applied in various engineering areas. However, it is difficult to directly observe the dynamic deformation process in experiments. This paper applies the molecular dynamics simulation to model the deposition of a monocrystalline Cu particle onto a Cu substrate and, subsequently, carries out a systematic study on the deposition mechanism and microstructure evolution. The results indicate that the deposition process consists of an impact stage and a relaxation stage. It is mainly the high speed collision and the friction following the collision that lead to particle deposition, which, under different circumstances, can be defined as surface deposition or penetration deposition. Two methods, namely, drastic shear deformation and cooling in the relaxation stage, can help form nanocrystallines. Jetting and melting are not the necessary factors for the deposition of nano-sized particles. The formation of dislocation lines is influenced by impact velocities. At lower impact velocities, the dislocation lines are mainly distributed near the contact surface. However, when the impact velocity is higher, dislocation lines are almost uniformly distributed in the particle.

ANALYSIS OF IGNITABILITY AND COMBUSTION RATE OF SELECTED INTERIOR FURNISHING MATERIALS

The first part of the article presents the issue of apartment fires and describes materials used inthe final stage of interior finishing. The second part discusses the research method and procedureas well as the stand where, using two surface and edge methods in accordance with the PN-ENISO 11925-2:2020 standard, the ignitability and burning rate of selected eight finishing materials,such as: laminated chipboard, varnished MDF, PVC wall panel, pine wooden board, ash woodenpanel, carpet, laminated panel and vinyl panel, were determined. The test results are summarizedin a table with the following values or answers to questions (Yes or No) for both methods used:whether ignition after 15 s, or ignition after 30 s, whether combustion was self-sustained, whetherthere were drops or waste, whether they caused ignition of the tissue paper, flame height after20 s and 2 min. The last column contains the general characteristics of smoke released duringcombustion. Moreover, a separate table lists the average lengths of the burned sample and theirlinear burning velocities in the surface and edge methods for selected interior finishing materials.The study comprises an analysis of the obtained results, based on which several conclusions wereformulated important from the viewpoint of fire safety of apartments. For example, it turned outthat the highest combustion speed was observed in carpet samples and an ash wooden panelprotected with clear varnish, while the lowest flame spread speed was recorded in the case ofa vinyl panel and a varnished MDF board.

Optimization of pre-oxidation enhanced coagulation for micro-polluted water treatment by response surface method

Optimization of pre-oxidation enhanced coagulation for micro-polluted water treatment by response surface method

Study on design optimization, road performance verification and preparation process selection of hybrid fiber reinforced asphalt mixture composite

To achieve long-lasting, high-strength, and sustainable asphalt pavement, this study prepared a hybrid fiber asphalt mixture using micron-scale calcium sulfate whiskers (CSW) and millimeter-scale basalt fibers (BF). The response surface method was employed to optimize the mix design, develop a prediction model, and verify road performance. The preparation process was refined based on the optimal mix design. The findings revealed that the best overall road performance was obtained with 5 % CSW content, 6 mm BF length, and 0.32 % BF content. The mixture demonstrated optimal performance with CSW wet mixing and BF dry mixing. Additionally, testing the fiber asphalt mixture at the mixture level was found to be crucial, as results can vary from those obtained at the mastic level. This study provides an in-depth analysis of the hybrid fiber asphalt mixture’s action mechanisms in material optimization, performance verification, and preparation processes, offering valuable insights for related research and engineering applications of hybrid fibers.

Analysis of ultra-high concentration solar cells integrated with a confined microjet impingement cooling

The high solar concentration levels result in an intense influx of energy onto the concentrated triple-junction solar cell, leading to elevated temperatures that can degrade the cell’s performance and overall lifespan. This necessitates the development of innovative and efficient cooling strategies to mitigate temperature-induced losses and ensure optimal energy conversion. This study introduces an innovative micro jet impingement cooling system designed for ultrahigh concentrated solar cells, addressing the critical challenge of temperature management under high solar concentration levels. Furthermore, structural modifications were proposed, including reducing ceramic layer thickness to decrease the thermal resistance and using thermal interface materials to improve the cell temperature uniformity. A three-dimensional computational fluid dynamics model was developed to evaluate the proposed system’s performance and compare it with the traditional jet impingement heat sink. The model was verified and validated using empirical data in the literature. In addition, the Response Surface Method was employed to provide a comprehensive understanding of the system’s behavior under various weather conditions and cooling fluid effects. The results showed that concentration ratio and direct normal irradiance significantly affect the system’s performance. Moreover, the new cooling system maintains temperatures below the recommended operating temperature. Finally, the environmental assessment indicated substantial energy payback time reductions at 20,000 Suns, which is significantly lower than at 1000 Suns. The CO2 emissions analysis shows a marked potential for emissions mitigation, particularly at higher CRs and longer sunshine hours. These insights offer a comprehensive overview of ultrahigh concentrated solar cell thermal system performance, highlighting its efficiency and environmental sustainability in solar energy applications.

Research on Alkali-Activated Slag Stabilization of Dredged Silt Based on a Response Surface Method.

To improve the resource utilization of dredged silt and industrial waste, this study explores the efficacy of using ground granulated blast furnace slag (GGBS), active calcium oxide (CaO), and sodium silicate (Na2O·nSiO2) as alkali activators for silt stabilization. Through a combination of addition tests, response surface method experiments, and microscopic analyses, we identified key factors influencing the unconfined compressive strength (UCS) of stabilized silt, optimized material ratios, and elucidated stabilization mechanisms. The results revealed the following: (1) CaO exhibited the most pronounced stabilization effect, succeeded by Na2O·nSiO2, whereas GGBS alone displayed marginal efficacy. CaO-stabilized silt demonstrated rapid strength augmentation within the initial 7 d, while Na2O·nSiO2-stabilized silt demonstrated a more gradual strength enhancement over time, attributable to the delayed hydration of GGBS in non-alkaline conditions, with strength increments noticeably during later curing phases. (2) Response surface analysis demonstrated substantial interactions among GGBS-CaO and GGBS-Na2O·nSiO2, with the optimal dosages identified as 11.5% for GGBS, 4.1% for CaO, and 5.9% for Na2O·nSiO2. (3) X-ray diffraction (XRD) and scanning electron microscopy (SEM) analyses clarified that the hydration reactions within the GGBS-Na2O·nSiO2 composite cementitious system synergistically enhanced one another, with hydration products wrapping, filling, and binding the silt particles, thereby rendering the microstructure denser and more stable. Based on these experimental outcomes, we propose a microstructural mechanism model for the stabilization of dredged silt employing GGBS-CaO-Na2O·nSiO2.

The effect of weighting on the color appearance of dyed silk fabric

The weighting process may change the color appearance of silk. The objective of the present study is to evaluate the effect of weighting with methyl methacrylate (MMA) on the color appearance of silk fabric using the response surface method. For this purpose, a CCD design was used to investigate the effect of methyl methacrylate monomer concentration and dye concentration on color appearance and percentage of weight gain of silk fabric. Analysis of variance, response surface, and contour plots of the colorimetric characteristics of the weighted silk fabric show that the methyl methacrylate concentration has a significant effect on color parameters such as L*, a*, b*, C*, and hue angle of the weighted silk fabric. The results indicate that the weighting process changes the color of silk fabric.

A Direct Contour Control Method for Free-Form Surface Machining Trajectories Based on Coordinate Transformation

The requirement for high-speed and high-precision contouring with free-form surfaces in the CNC machining process is increasing. The contour error is an essential criterion for the quality of CNC machining. For the problem of contour error control, the present research is mainly based on position tracking, and the control method directly aiming at contour control has not been well studied. This paper proposed a new type of coordinate transformation-based direct contour control method (CT-DCC) for free-form surface machining trajectories. By real-time monitoring of the contour error and the foot point of the free-form parametric trajectory, the contouring task is decomposed into the contour error control task in the normal direction and the velocity control problem in the feed direction. Using coordinate transformation, the output commands of the two tasks are converted to the axial motion command. CT-DCC completely eliminates position tracking in the traditional control to achieve direct control of the contour error, which provides a new solution for the contour control problem of free-form surface machining. Both the axial velocity control and the axial torque control-based CT-DCC scheme were studied, and the two-axis and three-axis direct contour controllers were tested. The simulation and experiment results show the feasibility of the proposed method.

Multi-objective optimization of seawater mixing in cement-based materials with supplementary cementitious materials using response surface methodology

Seawater instead of freshwater to produce concrete is an effective measure to save freshwater resources. However, the presence of harmful ions in seawater restricts its broader application. The incorporation of supplementary cementitious materials (SCMs) has the potential to significantly mitigate these adverse effects. Consequently, there is a growing interest in understanding the mechanisms by which SCMs function in seawater-mixed cementitious systems. In this study, a quadratic polynomial prediction model with the mechanical properties and dry shrinkage of the composite matrix as the response target was analyzed by the response surface method (RSM). Tests and analytical techniques elucidated the effects of metakaolin (MK) and ground granulated blast-furnace slag (GGBS) on the hydration process of the pastes after seawater mixing. The results revealed that the compressive strength and dry shrinkage were influenced by single-factor or multi-factor interactions. The optimal mix design (MK=20.2 % and GGBS=10.0 %) was experimentally validated, showing an absolute error of 1.5 %. The microstructural analysis indicated that MK and GGBS expedited essential pozzolanic reactions. Enhanced strength in mixtures before 3 d was attributed to cation exchange and initial flocculation. In the 28 d specimens, the increase in strength was related to the growth of Friedel’s salt crystals and C-(A)-S-H gels. Due to the presence of the C-(A)-S-H gels and AFm phases, chloride ions were efficiently immobilized, and the shrinkage of the matrix was reduced.

Integrated study of prediction and optimization performance of PBI-HTPEM fuel cell using deep learning, machine learning and statistical correlation

This paper uses 3D modeling and artificial intelligence methods to predict, and find optimal point in high-temperature proton exchange membrane (HTPEM) fuel cells. The main objective is to obtain maximum power and current density at the optimum node of the HTPEM fuel cell. The response surface method (RSM) is used to prevent excessive duplication and ensure adequate data coverage for determining input parameters. Also, for the first time, the correlation presented was compared with AI-based metaheuristic optimization methods i.e., including support vector regression (SVR), Gaussian process regression (GPR), and deep neural networks (DNN) with a dropout layer, alongside metaheuristic algorithms such as whale optimization algorithm (WOA), Grasshopper optimization algorithm (GOA), firefly algorithm (FF), and the genetic algorithm (GA). The results show that SVR, GPR, and DNN methods have excellent performance, with mean absolute percentage error (MAPE) of 0.81 % for DNN, 0.83 % for SVR, and 2.24 % for GPR. Most optimization algorithms exhibit errors below 8 %. The DNN-GOA, SVR-WOA, SVR-GA, and GPR-GOA algorithms have the lowest errors among them. Correlations have a lower computational cost for obtaining maximum power and current density at the optimum node compared to optimization algorithms, with a relative error of less than 6 % in most cases.

Treatment of bio-treated coking wastewater in a 3DEF system with Fe-loaded needle coke particle electrodes

As one of the most representative hard-to-biodegrade industrial wastewater, coking wastewater is poor in biodegradability and has a high concentration of organic matter. Consequently, even after treatment using biochemical technology, the discharge standards cannot be reached. We used the self-developed Fe-loaded needle coke electrodes (Fe-NCPEs) as particle electrodes and established a three-dimensional electro-Fenton (3DEF) system for the treatment of bio-treated coking wastewater (BTCW) in this study. The 3DEF system's conditions for treating BTCW were optimized using Response Surface Method (RSM). When the initial pH was 4.69, the applied voltage was 11.1 V, the Fe-NCPE dosage was 11.63 g L−1, and the COD was reduced from 387 to 57.3 mg L−1 and the colour removal rate reached 99 % after 3 h of reaction, meeting local coking wastewater discharge standards. The power consumption is only 15 kWh per ton of BTCW, indicating that this system can treat the BTCW with high efficiency and low energy consumption. UV-Vis, FTIR, and GC-MS analysis illustrated that cyclic aromatic compounds, esters, and ethers can be efficiently degraded to alkanes and olefins by the 3DEF system. The ·OH quenching experiments showed that in the 3DEF system, the ·OH is the main reactive group, which can oxidize the large hard-to-degrade organic compounds in BTCW to small organic compounds, and even to CO2 and H2O. Dynamic experiments showed that the 3DEF system can successfully remove pollutants from BTCW under continuous flow conditions with an HRT of 3 h, allowing it to meet emission standards.

Ultrasound-assisted extraction of withanolides from Tubocapsicum anomalum: Process optimization, isolation and identification, and antiproliferative activity

Tubocapsicum anomalum, a Chinese medicinal plant rich in anti-tumor withanolides, requires efficient extraction methods. In this paper, an HPLC method was first established for the detection of withanolides, and gradient elution was carried out using a methanol–water solvent system. It was found that the content of withanolides was the highest in the leaves of T. anomalum, followed by the stems and fruits, and almost none in the roots. During the actual picking process, the quantity of leaves collected was relatively small, while the number of stems was the highest. Therefore, the Box-Behnken response surface method was used to optimize the ultrasonic-assisted extraction process of withanolides from the stems of T. anomalum. The optimal extraction conditions were determined as follows: the liquid–solid ratio was 20:1, the extraction solvent was 70 % ethanol, the ultrasonic power was 250 W, the ultrasonic time was 40 min, and the ultrasonic temperature was 50 °C. Under these conditions, the average yields of tubocapsenolide A (Te-A) and tubocapsanolide A (Ta-A) can reach 2.87 ± 0.12 mg/g and 1.18 ± 0.05 mg/g, respectively. We further compared extraction rates of two withanolides from different parts of T. anomalum using ultrasonic and traditional extraction methods. Ultrasonic extraction significantly increased rates, with the highest yields from leaves, followed by stems and fruits. The results show that ultrasonic optimization can improve extraction rate, reduce time, lower costs, enhance quality, and increase yield. Therefore, the optimized ultrasonic-assisted extraction process was adopted to extract the aerial parts of T. anomalum and separate the components. After optimization, the extract underwent several chromatographic separations to isolate eight previously undescribed withanolides (1–8) and two artificial withanolides (9–10), in addition to fifteen known compounds (11–25). Their structures were established through extensive spectroscopic data analysis. The compounds were evaluated for their antiproliferative effects against multiple cancer cell lines, including human hepatocellular carcinoma cells (HepG2, Hep3B, and MHCC97-H), human lung cancer cells (A549), human fibro-sarcoma cancer cells (HT1080), human chronic myeloid leukemia cells (K562), and human breast cancer cells (MDA-MB-231 and MCF7). Compounds 1–3, 5, 7, 11, 13, 15–16, and 22 displayed significant activity with IC50 values of 5.14–19.87 μM. The above results indicate that ultrasonic-assisted extraction technology can be used to obtain new withanolides more efficiently from T. anomalum, thereby enhancing the utilization rate of T. anomalum resources.