Surface Roughness Factor Research Articles

Sponge-shaped Au nanoparticles: a stand-alone metallic photocatalyst for driving the light-induced CO2 reduction reaction

Coinage metal nanoparticles (NPs) enable plasmonic catalysis by generating hot carriers that drive chemical reactions. Making NPs porous enhances the adsorption of reactant molecules. We present a dewetting and dealloying strategy to fabricate porous gold nanoparticles (Au-Sponge) and compare their CO2 photoreduction activity with respect to the conventional gold nanoisland (Au-Island) morphology. Porous gold nanoparticles exhibit an unusually broad and red-shifted plasmon resonance which is in agreement with the results of finite difference time domain (FDTD) simulations. The key insight of this work is that the multi-step reduction of CO2 driven by short-lived hot carriers generated by the d → s interband transition proceeds extremely quickly as evidenced by the generation of methane. A 3.8-fold enhancement in the photocatalytic performance is observed for the Au-Sponge in comparison to the Au-Island. Electrochemical cyclic voltammetry measurements confirm the 2.5-fold increase in the surface area and roughness factor of the Au-Sponge sample due to its porous nature. Our results indicate that the product yield is limited by the amount of surface adsorbates i.e. reactant-limited. Isotope-labeled mass spectrometry using 13CO2 was used to confirm that the reaction product (13CH4) originated from CO2 photoreduction. We present the plasmon-mediated photocatalytic transformation of 4-aminothiophenol (PATP) into p,p'-dimercaptoazobenzene (DMAB) using Au-Sponge and Au-Island samples.

Quantitative Study of Dislocation Density Effects on (100)-Orientated Cu in CO2RR

For the electrochemical CO2 reduction reaction, (CO2RR) structural defects have been reported to create key active sites. Previous reports have demonstrated the relationship between structural defects and CO2RR activities. However, an in-depth understanding of the connection between defect structure and selectivity study has proved challenging. In this presentation, we elucidate the relationship between dislocation density, activity, and selectivity on Cu in CO2RR. To accomplish this, we successfully synthesized (100)-oriented Cu samples with dislocation densities varying by a factor of 9, and we quantitatively studied the relationship between dislocation density and CO2RR performance.In this work, we employ (100)-oriented Cu prepared by physical vapor deposition. This approach creates an atomically smooth surface that eliminates the differences in the relative influence based on differences in surface reconstruction and roughness factor. A suite of X-ray-based methods are applied to characterize the defect structure. Here, X-ray diffraction pole figures confirm the good epitaxial growth of Cu (100). X-ray diffraction (XRD) θ/2θ symmetrical scan are applied to facilitate calculation of the dislocation density. Unlike TEM and metallographic etching, this method provides precise structure information over large areas of the Cu catalyst.It is demonstrated that under the potential of -1.04 V vs. RHE, the sample with the largest dislocation density favors HER more. With high dislocation density, HER and C1 products are dominant. The situation changes with the dropping dislocation density, and the best CO2RR performance is achieved at a medium dislocation density changing from 1.668 x 1015 m-2 to 1.106 x 1015 m-2, indicating a favorable catalyst surface for C-C coupled products. Here, a combination of mechanistic study via electrochemical methods and X-ray absorption spectroscopy suggests that a combination of low- and full-coordinated Cu sites is more beneficial for C-C coupling. Figure 1

Spreading dynamics of a microgel particle-laden thermosensitive polymer drop along smooth and nanofiber surfaces

The research focuses on the influence of 300-μm microgel particles in an aqueous solution of a thermosensitive biopolymer on the spreading and deformation of 3.7-mm drops. The drops impact a smooth hydrophilic and a rough hydrophobic surface. A mass fraction of microgel particles varies in a range of 0–0.2. A universal physical model of the spreading of thermosensitive polymer drops laden with microgel particles along surfaces with significantly different roughness is proposed. It explains the strong inhomogeneity of the contact line stretching due to the deceleration of the continuous phase flow by microgel particles and the increased flow vorticity because of the addition of the surface roughness factor. The validity of the proposed physical model is proven by qualitative and quantitative assessments of the contact line deformation when spreading. An empirical expression for the maximum spreading factor is derived, taking into account the properties of liquids, wall roughness, and microgel particle concentration; it reliably predicts when Re≈110−3100, the surface roughness is 0.5–125 nm, Ca=4.5×10−7, and the number of microgel particles in drops is up to 100. The expression was successfully tested during the modeling of arbitrary surface roughness and the increased concentration of microgel particles relative to those considered in experiments during the formation of a biopolymer layer. When developing the method of additive manufacturing of a functional layer, a practical correlation was established between the volume content of microgel particles, acting as potential containers for living cells, in a drop and the area of the biopolymer layer.

Titanium surface treatments and their effects on the roughness factor

The surface pretreatment of a Ti substrate to produce metal oxide electrodes with electrocatalytic properties is of fundamental importance. The preparation of the substrate prior to the application of the coating critically affects the properties of the coating, including its surface roughness, adhesion, and corrosion resistance. In this work, different treatments were applied to the surfaces of Ti discs and their effects on surface roughness were studied. The treatments applied to Ti consisted of three stages: (1) mechanical treatment, (2) degreasing, and (3) chemical treatment. The first stage was carried out with 120 grit SiC abrasive sandpaper, the second stage was carried out with acetone (group A) or sodium hydroxide (NaOH) solution (group B), and the third stage was conducted using hydrochloric acid (HCl), oxalic acid, a mixture of hydrofluoric acid (HF)/phosphoric acid (H3PO4), or a sequence of all three chemical treatments (i.e., HCl, oxalic acid, and HF/H3PO4). The morphological properties, surface composition, and electrochemical behavior of the treated Ti discs were characterized by scanning electron microscopy (SEM), X-ray diffractometry (XRD) and cyclic voltammetry (CV) in a 0.5 M H2SO4 solution, respectively. The electroactive surface area (Aes) and roughness factor (frs) of each Ti disc were estimated from capacitance measurements of the electrochemical double layer. The morphology and voltammetric behavior of Ti varied markedly depending on the surface treatment applied. In addition, the XRD results showed that Ti surfaces subjected to different treatments exhibited different crystallographic planes. The trend in surface roughness with respect to the chemical reagent used was as follows: Group A: oxalic acid > HF/H3PO4 > global treatment > acetone > HCl; Group B: oxalic acid > HF/H3PO4 > NaOH > HCl > global treatment. The most severe chemical attack on the substrate was induced by oxalic acid, which led to the largest electroactive area and roughness factor among the treated Ti samples investigated in this study.

Terahertz-based optoelectronic properties of ZnS quantum dot-polymer composites: For device applications

Terahertz (THz) technology integration with nanomaterials is receiving excellent attention for next-generation applications, including enhanced imaging and communication. The excellent optical properties in THz domain can lead to preparation of low-cost CMOS camera which can convert THz radiation into optical signal in very efficient manner. In the present study, we have studied the properties of Zinc Sulfide quantum dots (ZnS QDs) embedded with Polyvinyl Alcohol (PVA) composites films using THz Signal at room temperature. The optical characterizations such as refractive index, absorption coefficients and dielectric constants of these samples were measured in the 0.1–2.0 THz range. Additionally, optical impedance, surface roughness, and reflection coefficient in TE and TM mode between 0.1 and 2.0 THz range were determined for these samples based on surface roughness-based reflection and scattering properties. The surface roughness factor was used to measure the optical impedance of the ZnS QDs based polymer films. The measured values of the absorption coefficient at 266 nm are compared with THz radiation, and the refractive indices of these samples range from 1.75 to 2.0. Finally, these samples were subjected to UV light excitation (λexe = 266 nm) of 0.15 ns duration and 400 nm for the fluorescence and corresponding life time measurements. We observed two numbers of fluorescence lines in nanosecond based excited domain whereas 400 nm excitation-based fluorescence life time lies between 13.8–11.39 ns range along with shift in fluorescence lines between 538.7 to 560.7 nm, respectively.

Parametric analysis, modeling and optimization of the process parameters in electric discharge machining of aluminium metal matrix composite

Optimizing electric discharge machining (EDM) for aluminum/SiCp metal matrix composites poses challenges due to intricate machine parameters and process complexity, impacting process economy and elevating product costs. The research aims to find the optimal combination of process parameters which include pulse on-time, pulse current, duty cycle (%), gap voltage, sensitivity and flushing pressure for EDM of Al/SiCp-MMC using a copper electrode for the selected response factors such as material erosion rate and surface roughness, Ra. The experiments were designed using the central composite design of response surface methodology and an advanced optimization technique known as Teaching–learning-based optimization (TLBO), is applied to find the optimal combination of process parameters to obtain maximum material erosion rate subject to the desired range of surface roughness (SR), Ra. The combination of the high pulse on-time (i.e. 150 μs) and high pulse current (i.e. 12A) results in high material removal rate with deep craters on the machined surface clearly visible in SEM images contrasting the minimized surface roughness at lower values of pulse on-time (50 μs) and the pulse current (4A). Pulse on - time (Ton) is found to be the most significant factor for material erosion rate and surface roughness with percentage contribution of 70.86 and 54.9 respectively for optimization of the response. The regression models were developed at 95% confidence level for material removal rate and surface roughness with R2 value of 0.93 and 0.95 respectively signifying high degree of accuracy in predicting the response. Confirmation tests conducted to check the adequacy of the established models revealed that the percentage error between the predicted and experimental responses is found to be within acceptable levels. Electron discharge machining of the aluminium metal matrix composite at the optimized conditions could provide economical aspect in the aerospace and automobile industry.

Numerical Study of Drilling Parameters with Al 356 Alloy Using Bacterial Foraging Optimization

Numerical Study of Drilling Parameters with Al 356 Alloy Using Bacterial Foraging Optimization

Numerical analysis of rotating scans’ effect on surface roughness in laser-powder bed fusion

The rotating scanning strategy is a critical factor for top surface roughness in laser-powder bed fusion (L-PBF), yet the underlying mechanism remains elusive. This study introduces an integrated L-PBF model, encompassing powder packing and molten pool fluid dynamics analysis, to investigate how surface roughness accumulates across layers with non-rotating scans but is mitigated with rotating scans. To address computational complexity and prediction errors associated with multi-layer simulations, the model utilizes an experimentally built part as substrate and simulates single-layer depositions with varying scanning rotation angles. Additionally, an as-machined surface representing ideal flat substrate is included for comparative analysis. Results indicate that on as-built surfaces featuring alternating peak-valley patterns, both powder packing structure and fusion zone shape are location-dependent. To effectively characterize the packing structure on such non-flat surfaces, an effective packing density is proposed. Specifically, peak locations exhibit a thinner powder layer, a 14.5% increase in effective packing density, and a 7% decrease in penetration depth compared to valley locations. The circulation flow, driven by recoil pressure and Marangoni force, is responsible for the reduced surface roughness with rotating scans. Specifically, the circulation flow intersects with multiple peaks and valleys, effectively promoting material redistribution among these tracks and disrupting the peak-valley patterns. Conversely, the peak-valley patterns are preserved and may propagate to subsequent layers with non-rotating scans.

Evaluation and Multi-Objective Optimisation of Cutting Parameters in Turning of AISI 1020 Mild Steel using Formulated Cutting Fluid

Input parameter like the cutting fluid is one of the requirements for minimal surface roughness, cutting temperature, tool wear and optimal material removal rate coupled with improved machinability and productivity. The evaluation of the optimal factors of surface roughness, material removal rate, cutting temperature and tool wear in the turning of AISI Mild Steel with the use of eco-friendly fluids. Concerns has been raise globally about the non - biodegradability and non-recyclability of the conventional fluids in the research space. This prompted the research interest in replacing the mineral oil based fluids with eco-friendly cutting fluid such as castor seed oil based cutting fluid (CBCF). The locally sourced castor seed oil was investigated for its physiochemical properties as well as its fatty acid composition (FAC). The cutting fluid was formulated using ratio 1:9 of oil with additives to distilled water and then characterized. In turning of AISI 1020 Mild Steel, the evaluation of surface roughness, material removal rate, cutting temperature and tool wear under the CBCF compared to the mineral oil based cutting fluid (MBCF) were carried out using Taguchi experimental design and Grey Relational Analysis (GRA) for multi-response optimization. The formulated cutting fluid showed pH value of 8.47, viscosity of 0.830 mm2/s, good resistance to corrosion, good stability and milkfish in colour. From the GRA, the multi-response optimal factor combination under the CBCF is (1250 rev/min) spindle speed, (0.6 mm/rev) feed rate and (1.0 mm) depth of cut, all at level 3 while under the MBCF, it also shows (1250 rev/min) spindle speed, (0.6 mm/rev) feed rate and (1.0 mm) depth of cut all at level 3. The parameters from Taguchi and GRA results are in agreement with results from other vegetable oil based fluids and this study also contributes and improves the science of machining.

Machinability investigation of natural fibers reinforced polymer matrix composite under drilling: Leveraging machine learning in bioengineering applications

The growing demand for fiber-reinforced polymer (FRP) in industrial applications has prompted the exploration of natural fiber-based composites as a viable alternative to synthetic fibers. Using jute–rattan fiber-reinforced composite offers the potential for environmentally sustainable waste material decomposition and cost reduction compared to conventional fiber materials. This article focuses on the impact of different machining constraints on surface roughness and delamination during the drilling process of the jute–rattan FRP composite. Inspired by this unexplored research area, this article emphasizes the influence of various machining constraints on surface roughness and delamination in drilling jute–rattan FRP composite. Response surface methodology designs the experiment using drill bit material, spindle speed, and feed rate as input variables to measure surface roughness and delamination factors. The technique of order of preference by similarity to the ideal solution method is used to optimize the machining parameters, and for predicting surface roughness and delamination, two machine learning-based models named random forest (RF) and support vector machine (SVM) are utilized. To evaluate the accuracy of the predicted values, the correlation coefficient (R2), mean absolute percentage error, and mean squared error were used. RF performed better in comparison with SVM, with a higher value of R2 for both testing and training datasets, which is 0.997, 0.981, and 0.985 for surface roughness, entry delamination, and exit delamination, respectively. Hence, this study presents an innovative methodology for predicting surface roughness and delamination through machine learning techniques.

Preparation of Tunable Cu−Ag Nanostructures by Electrodeposition in a Deep Eutectic Solvent

AbstractThe green transition requires new, clean, inexpensive, and sustainable strategies to prepare controllable bimetallic and multimetallic nanostructures. Cu−Ag nanostructures, for example, are promising bimetallic catalysts for different electrocatalytic reactions such as carbon monoxide and carbon dioxide reduction. In this work, we present the one‐step preparation method of electrodeposited Cu−Ag with tunable composition and morphology from choline chloride plus urea deep eutectic solvent (DES), a non‐toxic and green DES. We have assessed how different electrodeposition parameters affect the morphology and composition of our nanostructures. We combine electrochemical methods with ex‐situ scanning electron microscopy (SEM), energy dispersive X‐ray spectroscopy (EDS), and X‐ray photoelectron spectroscopy (XPS) to characterize the nanostructures. We have estimated the electrochemically active surface area (ECSA) and roughness factor (R) by lead underpotential deposition (UPD). The copper/silver ratio in the electrodeposited nanostructures is highly sensitive to the applied potential, bath composition, and loading. We observed that silver‐rich nanostructures were less adherent whereas the increase in copper content led to more stable and homogenous films with disperse rounded nanostructures with tiny spikes. These spikes were more stable when the deposition rate was fast enough and the molar ratio of Cu and Ag was no greater than approximately two to one.

Enhancing efficiency in photo chemical machining: a multivariate decision-making approach

Non-Traditional Machining (NTM) outperforms traditional processes by offering superior geometric and dimensional accuracy, along with a better surface finish. Photo Chemical Machining (PCM) represents one such NTM process, using chemical etching for material removal. PCM finds substantial application in the creation of microchannels in pharmaceutical, chemical and energy industries. Several input parameters—such as etchant concentration, etching time and etchant temperature—profoundly influence the machining’s quality and efficiency. Therefore, the optimization of these parameters is crucial. This study presents a comparative analysis of five Multiple Criteria Decision Making (MCDM) techniques—Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Multi-Objective Optimization on the basis of Ratio Analysis (MOORA), Additive Ratio Assessment (ARAS), Weighted aggregated sum product assessment method (WASPAS) and Multi-Attributive Border Approximation Area Comparison Method (MABAC)—for the optimization of the PCM process. Key performance metrics considered are Material Removal Rate (MRR), Surface Roughness (SR), Undercut (Uc) and etch factor (EF). The weights of these criteria were calculated using the Criterion-Induced Aggregation Technique (CRITIC) and was compared with other popular methods like MEREC, Entropy and equal weights. MRR and EF are seen as beneficial criteria, while SR and Uc are perceived as cost criteria. Optimum process parameters were identified as 850 g/L etchant concentration, 40 min etching time and 70°C etchant temperature. Two of the three employed MCDM techniques agreed on these optimal parameters, reinforcing the findings. Furthermore, a strong correlation was observed amongst the employed MCDM techniques, further validating the results.

Surface roughness and cutting force in turning of alkaline-treated banana fibre-reinforced polymer composite: Compressed air cutting

Banana fibre-reinforced polymer (BaFRP) composite can ensure environmentally friendly decomposition of waste material and reduction of cost in comparison with traditionally used fibre material. This article emphasizes the influence of various machining constraints on surface roughness (Ra) and cutting force (Pz) in turning alkaline-treated banana fibre-reinforced polymer (T-BaFRP) composite. 30% weight fraction yields satisfactory mechanical properties. Taguchi orthogonal array L25 is used to design experiments and optimization using DFA and TOPSIS. An experimental investigation was conducted under compressed cooling air-cutting conditions where pressure was kept at 8 bar. Analysis of variance depicts that depth of cut and feed rate are the most prominent factors for surface roughness and cutting force. The predicted and experimental values error is 0.517% for surface roughness and 1.181% for cutting force. The optimization using DFA and TOPSIS reported optimal depth of cut, cutting speed, and feed rate at 0.362 mm, 55 m/min, and 0.113 mm/rev, and at 0.8 mm, 154 m/min, and 0.12 mm/rev, respectively. Ra of 2.594 µm and Pz of 14.258 N by DFA and 3.02 µm and 25.83 N by TOPSIS method have been attained. Moreover, confirmation test suggests that both response parameters (surface roughness and cutting force) are in close alignment with the results from the DFA and TOPSIS.

Thermo-hydraulic performance evaluation through experiment and simulation of additive manufactured Gyroid-structured heat exchanger

Following the breakthrough of additive manufacturing in overcoming machining limitations, triply periodic minimal surface (TPMS), governed by mathematical implicit functions, has emerged as a highly promising configuration for heat exchanger. Current study evaluates the thermo-hydraulic characteristics of a 316L stainless steel Gyroid-structured heat exchanger, manufactured by selective laser melting (SLM), through experimental and numerical methods. The experiment was conducted on a single-phase test rig with water as the working medium. The measured performance is affected by surface roughness and other factors, resulting in deviations from the theoretical performance. Specifically, at a flow rate of 500 kg/h, the experimentally measured overall heat transfer coefficient and cold-side differential pressure exhibit a 9.70 % and 69.82 % increase, respectively, compared to their theoretical values. In comparison to various heat exchangers reported in the literatures, this experimental model possesses a notable advantage concerning the power density achievable per unit length of pressure drop consumed. In addition, a nonlinear regression method based on the least squares approach and the thermal resistance separation method is proposed to obtain the Nu ∼ Re correlation. The fitting effect is satisfactory, as all the points fall within the deviation range of (-7.5 %, 7.5 %). Moreover, this experimental model outperforms four conventional heat exchanger configurations in terms of performance evaluation criteria.

Assessment of Machinability of Ti6Al4V Alloy Under Dry Conditions

Titanium alloys pose significant challenges during machining, necessitates a thorough investigation into the impact of process parameters on machining Ti6Al4V alloy. This study investigates into the machinability of Ti6Al4V alloy under dry machining conditions using uncoated tools. The experimental design studiedthe effect of process parameters on the cutting power, surface roughness and material removal rate during dry machining of Ti6Al4V alloy. Utilizing Taguchi design of experiments, unified cutting experiments were conducted under dry conditions employing uncoated tools. The study findings revealed that optimal cutting parameters lead to improved cutting energy consumption, reduced tool wear, and enhanced surface finish and material rates. Analysis of Variance (ANOVA) and regression modelling were employed to obtain an objective function capable of predicting the best cutting conditions. ANOVA showed that cutting speed is the main factor for an increase in the cutting power with major contribution of 73 % whereas feed rate is the key factor for surface roughness with the contribution of 80 %. These results help to gain the advantages of dry machining under optimal conditions, facilitating clean production with minimal energy consumption and improved surface quality.

Immersion polishing post-treatment of PLA 3D printed formed parts on its surface and mechanical performance

Steps were taken to improve the surface and mechanical performance of PLA 3D printed formed parts, reduce the “step texture” produced by the fused deposition process, and improve the quality of 3D printing by means of post-treatment. The PLA 3D formed parts were immersion polished with chloroform solution to investigate the effects of immersion polishing on the surface roughness, surface gloss, mechanical properties, and other factors of PLA formed parts. The results of the pre-experiment showed that 90% of the effect was due to the optimal concentration value of chloroform solution and 10% was the optimization of time for immersion polishing. Under the pre-experimental conditions, the surface roughness of the formed parts was reduced by 87%, and the surface gloss was increased by 510%, the surface quality and gloss were significantly improved, and the “step texture” was significantly reduced; meanwhile, the tensile and compressive ultimate strength of the formed parts were increased by 9.41% and 13.09%, respectively, and the mechanical performance were improved, and the quality of 3D printing post-treatment was significantly improved.

Extension of the revised wind erosion equation (RWEQ) to calculate grassland wind erosion rates based on the 137Cs tracing technique

The commonly used wind erosion models, including the Revised Wind Erosion Equation (RWEQ), are mainly based on data from loose soils, for which the erodibility factor (EF) reflects the abundance of erodible aggregates, and cannot be applied to simulate erosion of compacted soils such as some grassland soils. Taking the Inner Mongolia Autonomous Region in northern China as the study area, we used the 137Cs tracing technique to estimate the soil loss of grassland by wind erosion from 1963 to 2021, and used the results as criteria to verify the wind erosion rate (WER) predicted by RWEQ for the same period. We found that RWEQ accurately calculated the WER of cultivated farmland, but overestimated grassland WER. We believe that the main reason is that the equation did not consider the impact of soil compaction (SC) on EF, since the calculation methods for the weather factor, vegetation factor, surface roughness factor, and soil crust factor in RWEQ are applicable for grasslands. Therefore, we used the 137Cs tracing results to extrapolate the grassland EF while keeping the climate, soil crust, vegetation cover, and roughness factors constant, and combined SC and the proportion of aggregates smaller than 0.84 mm in diameter to develop an empirical equation for grassland EF. Compared with the original model, the extended model (RWEQext) that included the factor of SC more accurately estimated the WER of compacted grassland soil and could be applied to the whole study area. The RWEQext results showed that tolerable and slight levels of wind erosion dominated the grassland and gobi surfaces in the study area, whereas moderate wind erosion occurred in grasslands with sparse vegetation cover, and severe, very severe, and destructive wind erosion mainly occurred on loose surfaces such as sandy land with low vegetation cover.

Effect of drilling parameters on hole quality in drilling of pultruded GFRP composite material: Surface roughness, thrust force and delamination factor

Fiber reinforced polymer (FRP) composites are being used in a variety of areas. These materials need to be processed with some machining methods according to their usage areas, but their machinability is difficult. In this study, drilling is performed on glass fiber reinforced polymer (GFRP) composite produced by pultrusion with coated and uncoated drill. Then, surface roughness (SR), delamination factor (Fd) and thrust forces were investigated. Microstructures of chips formed during drilling were investigated and their effects on surface roughness were determined. Three distinct feed rates and cutting speeds were selected as machining parameters. Investigations showed that feed rate had a more significant effect on surface roughness, delamination factor and thrust force. It was understood that when the cutting speed increased, the surface roughness, thrust force and delamination factor decreased. Better results were obtained with TiN coated drills compared to uncoated drills.

Analysis of surface roughness and delamination factor applied to the drilling of hybrid polymeric composite materials by the Taguchi method

This research studies the impact of drilling parameters, namely spindle speed (V), feed rate (f) and drill bit type (Diamond inlay drill bit DD and special carbide drill bit for Kevlar KD), on roughness (Ra) and delamination factors (Idf and Odf) generated when drilling composite materials. To design and evaluate the experiment, the orthogonal matrix L18 of Taguchi's method was used. An ANOVA analysis was performed to verify the statistical effect of the control variables in the experiment with a significance level of α = 0.05. Linear and quadratic regression equations were used to predict the values of the response variables at acceptable levels, with quadratic regression showing the best predictive result (R2 = 0.85). The analysis revealed that tool type was the most significant controlling factor affecting Ra and Odf, and feed rate had the greatest effect on Idf. The results indicated that the DD bit performed better than the KD bit for Ra. Increasing V reduced the surface quality of Ra, Idf and Odf. Conversely, increasing f increased Ra and Idf, but decreased Odf. Therefore, the use of a KD bit is more efficient when drilling this type of hybrid composite material. This assertion is further corroborated by SEM images that validate the extent of surface damage caused by the drilling process.

Comparative Evaluation of Coated Carbide and CBN Inserts Performance in Dry Hard-Turning of AISI 4140 Steel Using Taguchi-Based Grey Relation Analysis

Dry hard-turning is a vital manufacturing method for machining hardened steel due to its low cost, high machining efficiency, and green environmental protection. This study aims to analyze the effect of various machining parameters on cutting forces and surface roughness by employing RSM and ANOVA. In addition, multi-objective optimization (Grey Relation Analysis: GRA) is performed to determine the optimum machining parameters. Dry hard-turning tests were carried out on AISI 4140 steel (50 HRC) using coated carbide and CBN inserts with different nose radii. The results show that the cutting force components are greatly affected by the cutting depth and cutting speed for both cutting inserts. As the level of cutting depth and cutting speed rise, the cutting forces also increase. However, the feed rate was the main factor in surface roughness. A low feed rate and high cutting speed lead to good surface quality. According to the results, CBN inserts exhibited better performance compared to carbide inserts in terms of minimum cutting forces and surface roughness. The lowest radial force (Fx = 55.59 N), tangential force (Fy = 15.09 N), cutting force (Fz = 30.49 N), and best surface quality (Ra = 0.28 µm, Rz = 1.8 µm) were obtained using a CBN tool. Finally, based on the GRA, the (V = 120 m/min, f = 0.04 mm/rev, a = 0.06 mm, r = 0.8 mm) have been chosen as optimum machining parameters to minimize all responses simultaneously in the machining of AISI 4140 steel using both carbide and CBN inserts.