Surface Roughness Measurements Research Articles

Experimental investigation and optimization of the effect garnet vibratory tumbling as a post-process on the surface quality of 3D printed PLA parts

The method known as additive manufacturing causes high surface roughness between layers depending on the technique used at the end of the product development process. This can be an important problem in three-dimensional (3D) manufacturing depending on the usage area. To solve this problem, in this experimental study, the effect of vibratory tumbling (VT) on surface roughness in 3D printing was investigated using garnet abrasive particles. Optimization with the best parameters was also performed and the results were analyzed. This experimental study investigated the effect of vibratory tumbling on surface roughness in 3D printing produced from Polylactic acid (PLA) material using garnet abrasive particles. The surface roughness (Ra) values were measured at different vibration durations for each mesh size. The results provide insights into the impact of vibratory tumbling on surface roughness in 3D-printed parts. The study involved subjecting the printed parts to vibratory tumbling using garnet abrasive particles of various mesh sizes (80, 90, 100, 120, 150, 180, and 220 mesh). Surface roughness measurements were taken at different vibration durations (2, 4, 6, 8, 10, and 12 hours) for each mesh size. A surface roughness measuring device was used to obtain the roughness values. The findings reveal that vibratory tumbling with garnet abrasive particles effectively reduces surface roughness in 3D printed parts. As the vibration duration increased, smoother surfaces were achieved. The data collected for each mesh size and vibration duration offer valuable insights into the relationship between vibratory tumbling and surface roughness in 3D printing. The surface roughness of the printed samples was reduced by 60% on average by using the optimum values after post-process. This research highlights the potential of vibratory tumbling as a viable method for improving surface roughness in 3D printing applications. Emphasis is placed on optimizing the vibration duration and selecting the appropriate mesh size to achieve the desired surface quality. Overall, this study contributes to our understanding of the effect of vibratory tumbling on surface roughness in 3D printing and provides considerable insights for enhancing surface quality in additive manufacturing processes.

Electrochemical polishing, characterisation and in vitro evaluation of additively manufactured CoCr stents with personalised designs

Additive manufacturing (AM) technology has paved the way for manufacturing personalised stents. However, there is a notable gap in comprehensive microstructure analyses and in vitro evaluations of the AM CoCr stents using advanced methodologies. To address this gap, this study focuses on investigating the microstructure and in vitro performance of personalised CoCr stents manufactured through micro-laser powder bed fusion (μ-LPBF). The evaluation process begins with the measurements of dimensions and surface roughness, followed by in-depth microstructural analyses. To improve surface roughness and reduce excessive strut size, the μ-LPBF stents undergo electrochemical polishing. Importantly, in vitro stent deployments are carried out in artificial arteries manufactured based on actual patients' data. Compared to the commercial MULTI-LINK VISION CoCr stent, the μ-LPBF personalised stents have rough surface finish (average roughness: 1.55 μm for μ-LPBF vs. 1.09 μm for commercial) and compromised grain microstructures (elongated for μ-LPBF vs. equiaxed for commercial). However, the personalised stents demonstrate better performances in in vitro tests. Notably, compared to the commercial stent in the two studied cases, they deliver larger lumen gains (up to 11.24 %) and reduced recoils (up to 4 times). This study validates the merit of the lesion-specific designs and the feasibility of using AM technology for stent fabrication.

Effects of a new magnetostrictive ultrasonic scaler and a traditional piezoelectric ultrasonic scaler on root surfaces and patient complaints

Tooth wear and pain are the primary concerns of patients undergoing periodontal scaling. The aims of this study were to compare the effects of a new magnetostrictive ultrasonic scaler and a traditional piezoelectric ultrasonic scaler on tooth surface roughness and calculus removal and to determine their impacts on patient discomfort during supragingival cleaning. This article had two parts: an in vitro study and a clinical study. In the in vitro study, thirty teeth with subgingival calculus were randomly assigned to two scaling treatment groups: magnetostrictive scalers (n = 15) and piezoelectric scalers (n = 15). Surface roughness measurements were taken at baseline and after scaling, and the root samples were visualised by SEM after scaling. Additionally, a single-centre randomised split-mouth clinical trial was conducted. Eighty-five participants diagnosed with chronic gingivitis or periodontitis were randomly assigned to receive supragingival scaling. The magnetostrictive scaler was used in half of the mouths (n = 85), and the piezoelectric scaler was used in the other half of the mouths (n = 85). Data on pain, noise, and vibration were collected using a VAS questionnaire, and the operating time was recorded. In both in vitro and clinical studies, magnetostrictive scalers were reported to be more effective than piezoelectric scalers in removing dental deposits (P < 0.05). Additionally, the root surface after scaling with the magnetostrictive scaler was smoother than that after scaling with the piezoelectric scaler in the in vitro study (P = 0.02). SEM examination also revealed that fewer dental materials were lost after instrumentation with the magnetostrictive scaler than after instrumentation with the piezoelectric scaler. Piezoelectric scalers caused less discomfort to patients in terms of pain, noise, and vibration than magnetostrictive scalers (P < 0.05). According to this clinical study, the magnetostrictive scaler caused more discomfort during supragingival scaling than the piezoelectric scaler. Moreover, the magnetostrictive scaler was also more efficient and produced a smoother root surface with less material loss after scaling than the piezoelectric scaler, as demonstrated in the in vitro study.

Relationship between topographic parameters and BRDF for tungsten surfaces in the visible spectrum

In metallic fusion devices, parasitic light originating from multiple reflections on the wall is a major problem for the interpretation of optical diagnostics. Strong stray light affects several optical diagnostics in ITER. One possibility to cope with this reflected light is to use photonic simulation, which can accurately predict the behavior of light within complex 3D geometry. A prerequisite is to get a good description of the reflection model, represented by the Bidirectional Reflectance Distribution Function (BRDF), based on optical measurements of in-vessel materials. To avoid complicated measurements using goniophotometer to get the BRDF, one possibility is to link surface optical properties and topography characteristics, such as roughness measurements, for example, using the classical Bennett’s formula. Measurements were performed using two experimental goniophotometers to fully characterize the BRDF of tungsten samples with different roughness values. Surface topography was measured using a three-dimensional laser scanning confocal microscope. Several parameters were extracted from these measurements including the arithmetic average roughness (Ra), the root mean square roughness (RMS), the Surface Inclination Angle Distribution and furthermore its mean value δm and the power spectral density (PSD). The correlations of BRDF model parameters deduced from the measurements are compared with the previous topographic parameters. The initial results on several tungsten samples show that Ra, which is the usual measure of surface roughness, is not the most suitable metric to link with the reflection behavior of the surface. In contrast, the PSD and the surface inclination angle are interesting metrics for describing the reflected light.

A new intelligent approach of surface roughness measurement in sustainable machining of AM-316L stainless steel with deep learning models

Due to the manufacturing sector's digitalization and ability to combine quality measurement and production data, machine learning and deep learning for quality assurance hold enormous potential. In this situation, industries may process data to inform data-driven estimates of product quality, thanks to predictive excellence. This research investigates the machinability of Laser Powder Bed Fusion (LPBF) − 316L stainless steel specimens, focusing on the impact of cutting parameters and cooling conditions (Dry, MQL, CO2 and CO2 + MQL) on surface roughness. The research employs advanced data augmentation techniques, incorporating TransGAN and multi-head attention (MHA) based Alexnet model for surface imperfection classification. The results highlight the effectiveness of the proposed methodology in accurately classifying surface conditions and underscore the superior performance of the MHA-Alexnet algorithm compared to alternative models (Alexnet and AE-Alexnet). Overall, the study contributes valuable insights into optimizing machining parameters and cooling strategies for enhanced surface finish in additively manufactured alloys.

Multi-Objective Optimization of Cutting Parameters for Polyethylene Thermoplastic Material by Integrating Data Envelopment Analysis and SWARA-Based CoCoSo Approach

This paper presents a comprehensive study on the multi-objective optimization of cutting parameters for Polyethylene (PE) thermoplastic material utilizing a CO2 laser. Recognizing the pivotal role of precise and efficient cutting in various sectors, from packaging to biomedical engineering, we integrate two potent analytical methodologies - Data Envelopment Analysis (DEA) and Step-Wise Weight Assessment Ratio Analysis (SWARA)-based Comprehensive Criteria Score Optimization (CoCoSo) approach. The cutting parameters chosen for the study were material thickness, power, and cutting speed. The experiments were conducted according to the Taguchi L18 orthogonal array. Measurements of surface roughness and kerf width were performed to examine the cutting quality. Additionally, another response variable, material removal rate, was calculated. By integrating Data Envelopment Analysis and SWARA-Based CoCoSo approach, the experimental condition that yielded the lowest surface roughness, kerf width, and the highest material removal rate was determined. The optimum experimental condition was found to be 4 mm material thickness, 80 W laser power, and 15 mm/s cutting speed. This work, therefore, paves the way for the innovative application of these combined methodologies in enhancing the production processes of PE and other thermoplastic materials, with clear implications for cost-effectiveness and sustainability in the manufacturing sector.

HVOF-sprayed surface coating with various compositions of Co-NiCrAlY-Al2O3 to minimize sediment erosion in hydraulic turbines

The components of hydropower plants are susceptible to sediment erosion caused by hard particles in the water. These hard particles cause substantial material loss and a reduction in the performance of the hydraulic turbines. The present study deals with the mitigation of sediment erosion in hydraulic turbines by developing a protective coating (CoNiCrAlY-Al2O3 metal-ceramic composite) using a high-velocity oxygen-fuel (HVOF) coating technique. Hardness measurement, surface wettability analysis, and surface roughness measurement were conducted to characterize the coatings, whereas scanning electron microscopy (SEM), X-ray diffraction (XRD), and energy-dispersive X-ray spectroscopy (EDS) were performed for metallurgical characterization. The slurry/sediment erosion behavior of bare and coated substrate was investigated using a slurry erosion tester. Experiments were performed for five coating compositions at different impact angles (30° ≤ ϴ ≤ 90°) and velocities (6 ≤ v ≤ 12 m/s). The maximum improvement in erosion performance (reduction in erosion rate compared to bare substrate ≈ 28.12 % at 30°, 9.29 % at 45°, and 11.69 % at 90° impact angle) was obtained for the coating having 12 wt% alumina doped into Co-NiCrAlY. The coating's performance was improved due to increased hardness, high shielding effect, and reduction in impact energy on Al2O3 by using CoNiCrAlY-Al2O3 deposition. The empirical correlation between erosion rate and velocity for both bare and coated substrates has also been proposed.

The effect of beverage temperature on the surface roughness, microhardness, and color stability of the monoshade composite resin: An in vitro study

ObjectiveThis study assessed the impact of beverage temperature on the surface roughness, microhardness, and color stability of monoshade composite resin. Materials and MethodsA batch of 70 monoshade composite resin specimens manufactured by Charisma Diamond ONE (Kulzer, Hanau, Germany) was prepared. Initial readings for surface roughness, microhardness, and color were recorded. The specimens were then divided into seven groupings of ten each: Distilled water (control group), Nescafe coffee at 70 °C and 5 °C, Arabic coffee at 70 °C and 37 °C, and cola at 7 °C and 24 °C. These samples underwent 30-min daily immersion in their respective beverages for a duration of 30 days. Final measurements were then taken. A non-contact profilometer was used for measuring surface roughness, a Vickers microhardness machine from Contour GT-I (Bruker Nano GmbH, Berlin, Germany) for microhardness, and a Color-Eye 7000A Spectrophotometer (X-Rite, GretagMacbeth, Michigan USA) for color stability. Statistical analyses, including repeated measure ANOVA for microhardness, roughness, and color, were executed using SPSS version 23. ResultsAll beverages led to changes in composite color and properties. Notably, coffee at 70 °C resulted in significant discoloration of the composite resin surface (p < 0.0001). The beverage that most affected the surface hardness and roughness of the monoshade composite resin was cola at 7 °C (p = 0.008) ConclusionThe inherent chemicals in beverages, coupled with their temperatures, can influence the composite properties of resin, specifically surface discoloration, hardness, and roughness. Clinicians may, therefore, consider instructing patients about the potential negative effects of these beverages.

Grinding Surface Roughness Measurement Combined with Simulation Data and Transfer Learning

AbstractThe surface‐roughness machine vision measurement method requires training numerous samples with uniform roughness values to construct a prediction model. Insufficient actual sample size will make the model lack generalization ability. So, a grinding surface‐roughness measurement method combined with simulation data and transfer learning is proposed. First, through surface simulation, inverse fitting, and three‐dimensional (3D) modeling, more realistic simulation samples are obtained, real samples are prepared, and a simulation imaging system and an actual imaging experiment to acquire surface images are designed. Second, the data distribution difference between the simulation domain and the actual domain through transfer component analysis and the use of the adjusted simulation‐domain data and its label to train a support vector regression model is adjusted. Finally, the model predicts the surface roughness of the uncalibrated actual‐domain sample. For shared features of transferable simulation images and actual images, using the high sensitivity of color information, image features are enhanced and a proportion of pure color region index is designed, strongly correlated within the domain but less differentiated between domains. The results show that the transfer learning prediction accuracy based on this index exceeds 90%, verifying the feasibility of the proposed method and providing a new improvement strategy for sample expansion in visual roughness measurement.

Experimental Analysis of Surface Roughness of Steel by Considering Variable Cutting Parameters for Turning

This paper presents results of experiment conducted in order to analysis of surface roughness of steel by considering variables cutting parameters for turning. Surface roughness measurement is a critical aspect of quality control in manufacturing processes, particularly in the context of lathe and milling machine operations. This abstract provides an overview of the methods, tools, and significance of surface roughness measurement in turning processes. It explores the key techniques, such as stylus profilometry and optical interferometry that are commonly employed for assessing surface roughness. The abstract also highlights the importance of surface roughness measurement in ensuring product quality, functionality, and performance. Furthermore, it emphasizes the relevance of this research in optimizing machining processes, enhancing product aesthetics, and reducing material waste. This investigation contributes to the field of precision manufacturing by presenting an in-depth analysis of surface roughness measurement in lathe machine applications, offering valuable insights for industry professionals and researchers alike.

Chatter Identification of Vibration Signals and Surface Roughness using Wavelet Transform and I-kazTM Methods

The paper describes the method to identify chatter in low-cutting-speed operations. It is based on vibration and surface roughness measurements. Tool chatter is the self-excited relative motion between the cutting tool and work piece. Tool chatter leads to poor surface quality and tool wear. The LMS Scadas testing system and accelerometer were used to measure the vibration signals during the turning operation, and Marsuft Psi was used to measure the surface roughness. When various cutting parameter combinations, such as cutting speed, feed rate, and depth of cut, were employed throughout the machining process, chatter and vibrating phenomena occurred. After the recorded signals were analyzed using the wavelet transform (WT), a chatter index (CI) was produced to determine how severe the chatter was. According to the results analysis, the experimental study demonstrated the close relationship between the surface roughness values and the chatter index when evaluating chatter identification.

Friction and wear behavior of a mechanical oscillating strip system used for interproximal enamel reduction: a quantitative and qualitative scanning electronic microscope evaluation.

To evaluate wear and friction properties of oscillating strips in order to validate the importance of a standardized interproximal enamel reduction (IPR) sequence to preserve their efficiency and lifetime. Fifteen complete oscillating IPR sequences were tested by means of tribological tests (Linear Reciprocating Tribometer, C.S.M. Instruments, Peseaux, Switzerland). Fifteen single 0.2-mm metallic strips underwent a long continuous cycle of 240 minutes. Strip surface roughness and waviness measurements were assessed by means of a contact probe surface profiler (TalySurf CLI 2000; Taylor Hobson, Leicester, UK) and TayMap software. Statistical analysis was performed with independent-samples t-test. Significance was at the P < .05 level. Scanning electronic microscopy analysis of strip surfaces was conducted with an FEI Quanta 200 (Hillsboro, Ore) in high vacuum at 30.00 kV. Resin strips revealed a significant reduction in surface roughness (Ra, Rt, RDq) and a significant increase in waviness parameters (Wa, Wt). Rt and RDq values significantly decreased upon use of the metallic strips. Significantly higher values of Wa (+ 2.84 µm) and Wt (+0.1 µm) were observed only for the 0.2-mm metallic strips. Higher friction values were observed when the metallic strips were tested singularly rather than within the entire sequence. Lower Ra and Rt values were revealed when 0.2-mm metallic strips were tested up to 240 minutes. The application of a standardized oscillating sequence allows for more efficient wear performance of the strips with a significant impact on their abrasive power and lifetime.

Overprinting of TPU onto PA6 Substrates: The Influences of the Interfacial Area, Surface Roughness and Processing Parameters on the Adhesion between Components.

The hybridisation of injection moulding (IM) and additive manufacturing (AM) offers the opportunity to combine the high productivity of IM and the high flexibility of AM into a single process. IM parts can be overprinted through fused filament fabrication (FFF) to allow for the customisation of parts or to add new functionalities. However, the right material pair must be chosen, and processing parameters must be optimised to achieve suitable adhesion between the components. The present study dealt with the investigation of the influence of the interfacial area, substrate surface roughness and overprinting processing parameters on the adhesion between the polyamide 6 (PA6) substrate and thermoplastic polyurethane (TPU) rib overprinted via FFF. PA6 substrates were produced through the IM of plates into a mould with different textures to obtain substrates with three different surface roughnesses. The ribs with varied interfacial areas were overprinted onto produced substrates using a desktop FFF 3D printer. To study the effect of overprinting processing parameters, the ribs were overprinted under varying printing and substrate temperatures and printing speeds according to the Box-Behnken design of experiments (DoE). The chemical composition and thermal properties of used materials were determined via attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR), thermogravimetric analysis (TGA), differential scanning calorimetry (DSC) and dynamic mechanical analysis (DMA). The surface properties of prepared substrates were studied via digital optical microscopy (OM), through surface roughness measurements using a confocal microscope, through contact angle (CA) measurements and through the determination of free surface energy (SFE). The adhesion between the components was determined by evaluating the tear-off strength using a universal testing machine (UTM). With an increasing interfacial area, the tear-off strength decreased, while substrate surface roughness had no statistically significant effect. Overprinting parameters influenced the tear-off strength in the order of printing speed > printing temperature > substrate temperature. High values of tear-off strength were found for the lowest printing speed, while there were no important differences found between the middle and upper values. With increasing printing and substrate temperatures, the tear-off strength increased linearly. The highest value of tear-off strength (0.84 MPa) was observed at a printing temperature, substrate temperature and printing speed of 250 °C, 80 °C and 2 mm/s, respectively.

Surface Degradation of Ion-releasing Restorative Materials With Cariogenic Challenge.

This study examined the influence of cariogenic environments on the surface roughness of ion-releasing restorative materials (IRMs). Custom-made stainless steel molds with holes of 5 mm × 2mm were used to fabricate 60 disc-shaped specimens of each of the following materials: Activa Bioactive (AV), Beautifil Bulk Restorative (BB), Cention N (Bulk-fill) (CN), and Filtek Z350XT (FZ) (Control). Baseline surface roughness (Ra) measurements were obtained using an optical 3D measurement machine (Alicona Imaging GmbH, Graz, Austria). The specimens were then randomly divided into five subgroups (n=12) and exposed to 10 ml of the following mediums at 37°C: distilled water (DW), demineralization solution (DM), remineralization solution (RM), pH cycling (PC) and air (AR) (control). Ra measurements were again recorded after one week and one month, followed by statistical evaluations with two-way analysis of variance (ANOVA) to determine interactions between materials and mediums. One-way ANOVA and post hoc Games Howell tests were performed for intergroup comparisons at a significance level of 0.05. Mean Ra values ranged from 0.085 ± 0.004 (µm) to 0.198 ± 0.001 µm for the various material-medium combinations. All IRMs showed significant differences in Ra values after exposure to the aqueous mediums. The smoothest surfaces were observed in the AR for all materials. When comparing materials, AV presented the roughest surfaces for all mediums. All IRM materials showed increased surface roughness over time in all cariogenic environments but were below the threshold value for bacterial adhesion, except for AV 1-month post immersion with pH cycling. Therefore, besides AV, the surface roughness of IRMs did not deteriorate to an extent that it is clinically relevant.

Effect of an Effervescent Multivitamin on Color and Surface Roughness of Micro-Hybrid Dental Resin Composites.

The use of multivitamins has become widespread globally, yet there is a scarcity of studies investigating their impact on resin composite restorations. This study aimed to evaluate the effect of an effervescent multivitamin tablet on micro-hybrid dental resin composites' surface roughness and color. Fifty disc-shaped samples (8 × 2 mm, shade A2; n = 10) were prepared and polished using five different micro-hybrid resin composites (Pergamon, Dentac, Turkey; Estelite Posterior, Tokuyama, Japan; Geanial Anterior, GC, Japan; Charisma Opal, Kulzer, Germany; Beautifil II, Shofu, USA). Samples were immersed in 200 mL water to one effervescent multivitamin tablet (Redoxon Triple Action, Bayer) at 24 °C for 2 min a day in 24 h intervals for 30 days. All samples' surface roughness (Ra) and ΔE(L*a*b) measurements were recorded at the beginning and end of the 30 days. The Wald chi-square and a two-way ANOVA were used for statistical analysis (significance level p < 0.05). The resin composite type and exposure to the multivitamin had a statistically significant effect on Ra values (p < 0.05). The resin composite type had a statistically significant effect on ΔE values, likely due to the higher mean value of BII (p = 0.040). The surface roughness and color of resin composites can be affected by multivitamins with a pH value of 3.0. Therefore, it is important to consider the patient's routine vitamin intake during resin composite selection. Additional research is required to explore the properties of different dental restorative materials.

Wear performance of short fiber added polyamide composites produced by additive manufacturing: Combined impacts of secondary heat treatment, reinforcement type, and test force

AbstractIn recent years, the number of studies focusing on the additive manufacturing has increased seriously to elucidate the critical points such as physical, chemical, and mechanical properties. Contrary to common trends and for the first time in the literature, this experimental endeavor aims to comprehend the combined impact of reinforcement type and heat treatment on the wear features of additively manufactured polyamide 6 (PA6) composites. As reinforcement materials, glass, and carbon fibers were utilized and all samples were created through the fused filament fabrication. Half of the samples were subjected to annealing treatment after the main production, and characterization works were performed using a fused emission scanning electron microscope, differential scanning calorimetry, and dynamic mechanic analysis. From the outcomes, it is seen that heat treatment has a positive effect on the hardness, and wear resistance of the composites. Besides, glass fiber‐reinforced samples display lower friction coefficient and lower volume loss results than other samples. For all samples, secondary annealing causes a positive impact on wear endurance in most cases. On the other side, the wear mechanism of the tested samples changes with the test force level and reinforcement type. At lower test forces, abrasive wear‐induced debris parts are detected on the deformed surfaces of PA6 and carbon‐added samples, but this case is opposite for the highest force of 40 N.Highlights Additive manufacturing was underlined as a promising way to create polymer composites with high dimensional accuracy. The combined effect of secondary annealing and reinforcement type on the wear resistance of 3D‐printed PA6 composites was examined for the first time in the literature. Carbon and glass fibers were compared to explore their effect on friction coefficient and wear behavior of polymer composite samples produced via FFF technology. Hardness and surface roughness measurements were used to comprehend the dry sliding wear results. Depending on the increasing test force levels and reinforcement type, deformation, and abrasion mechanisms were analyzed.

Investigating the Impact of Productivity on Surface Roughness and Dimensional Accuracy in FDM 3D Printing

Over the past three decades, 3D printing technologies have undergone significant advancements, revolutionizing various industries, such as automotive. Additive manufacturing has played a crucial role in reducing product development time and enabling the direct printing of functional parts. One of the key advantages of additive manufacturing is its ability to provide greater design freedom compared to traditional manufacturing methods. This means that complex geometries and varying material properties can be easily printed. In this research paper, the author focused on investigating the impact of layer thickness and part orientation on the surface roughness and accuracy of printed parts. The main objective was to identify the optimal combination of layer thickness and part orientation that would yield the best results in terms of surface roughness and accuracy, considering printing time as a variable. The results from printing time, accuracy and surface roughness measurements showed that the vertical orientation is the superior for cylindrical orientation.

Tribological improvement of potential lubricants for electric vehicles using double functionalized graphene oxide as additives

The aim of the present research is to analyze thermophysical and tribological properties of PAO4 nanolubricants containing functionalized (GO-polyethyleneimine-oleic acid, GO-PEI-OA) and non-functionalized (GO) graphene oxide. Nanodispersions of these NPs were prepared, observing a better stability for the GO-PEI-OA nanolubricants. As for the tribological properties, significant improvements in coefficient of friction were obtained comparing with the base oil, being 28% for GO-PEI-OA (0.10 wt%). Concerning the anti-wear behavior, better results were obtained for GO-PEI-OA nanolubricants (0.15 wt%) with improvements of about 27%, 54% and 60% for the diameter, depth, and area of the wear track, respectively. Finally, Raman spectroscopy and surface roughness measurements were used to identify the tribological mechanisms of tribofilm formation and repairing.

Surface characteristics of additively manufactured CoCr and Ti6Al4V dental alloys: The effects of carbon and gold thin film coatings, and alkali-heat treatment.

This study investigates the impact of surface modifications on additively manufactured CoCr and Ti6Al4V dental alloys, focusing on surface properties. Thin film carbon (C) and gold (Au) coatings, as well as alkali-heat treatment, were applied to the high- and low-polished specimens. Scanning electron microscopy (SEM) showed that thin film coatings retained the underlying surface topography, while the alkali-heat treatment induced distinct morphological changes. Energy-dispersive x-ray spectroscopy (EDS) analysis revealed that C-coating enriched surfaces with C, and Au-coating introduced detectable amounts of Au. Nevertheless, signs of coating delamination were observed in the high-polished specimens. Alkali-heat treatment led to the formation of a sodium titanate layer on Ti6Al4V surfaces, confirmed by sodium presence and Fourier transform infrared spectroscopy (FTIR) results showing carbonate bands. Surface roughness measurements with atomic force microscopy (AFM) showed that C-coating increased surface roughness in both high- and low-polished alloys. Au-coating slightly increased roughness, except for low-polished Au-coated Ti6Al4V, where a decrease in roughness was observed compared to low-polished bare Ti6Al4V, likely due to surface defects present in the latter resulting from the additive manufacturing process. Alkali-heat treatment led to a pronounced increase in roughness for both alloys, particularly for Ti6Al4V. Both thin film coatings decreased the water contact angles in all specimens in varying magnitudes, indicating an increase in wettability. However, the alkali-heat treatment caused a substantial decrease in contact angles, resulting in a highly hydrophilic state for Ti6Al4V. These findings underscore the substantial impact of surface modifications on additively manufactured dental alloys, potentially influencing their clinical performance. RESEARCH HIGHLIGHTS: Thin film coatings and chemical/heat treatment modify the surface properties of additively manufactured dental alloys. The surfaces of the alloys get rougher and more hydrophilic after alkali-heat treatment. Thin gold coatings exhibit potential adhesion challenges.

A visual measurement method of grinding surface roughness based on aliasing region index and neural network

Most existing vision-based roughness measurements primarily rely on statistical information from grayscale images or intensity information from color images. However, the structural information of images has not been fully and effectively utilized. To more accurately measure the roughness of grinding surfaces, a visual measurement method of grinding surface roughness based on aliasing region index and neural network is proposed. Firstly, color images of grinding surface are obtained under red and green illumination. Secondly, aliasing regions of red and green images are extracted through fuzzy clustering segmentation and morphological processing. Then the aliasing width and the aliasing dispersion of aliasing region can be calculated as indices for roughness measurement. Thirdly, the relationship model between aliasing region index and grinding surface roughness is constructed using the back propagation (BP) neural network. The results demonstrate that the aliasing dispersion index has a better correlation with grinding surface roughness than the aliasing width index. The method based on the aliasing dispersion index and BP neural network is feasible and accurate for grinding surface roughness measurement.