Surface Roughness Measurements Research Articles

Shot peening effects on Cr-Mo-V steel: a comprehensive study of microstructure, surface roughness, residual stress, and mechanical behavior

This study presents a comprehensive study of the microstructure, mechanical characteristics, and surface roughness of Cr-Mo-V low alloy steels and a detailed investigation of the overall impact of shot peening (SP). The microstructure was examined using the optical and scanning electron microscope, showing a significant grain size decrease after shot peening. Evaluations of mechanical characteristics, such as microhardness and tensile strength, showed a noteworthy rise, suggesting enhanced material strength. Studies using fragmentography shed more light on changed fracture tendencies. X-ray diffraction technique (XRD) was used to measure residual stress distribution, and the outcomes displayed an increase after SP, which suggests that internal stresses were created. Surface roughness measurements also showed a noticeable decline, indicating better surface quality. The transformational effects of shot peening on Cr-Mo-V low alloy steels were highlighted by comparative investigations with base metals, providing insights into enhancing material performance for various engineering applications.

Scale-independent model based on fractal theory for calculating the adhesion force between a particle and rough surfaces.

The elimination of the scale-dependent statistical parameters is a challenge in the estimation of the van der Waals force between a particle and rough surfaces. Herein, a scale-independent parameter, the fractal dimension, was introduced into the Rabinovich model to calculate the microadhesion force. First, a Weierstrass-Mandelbrot function is proposed to generate a random 2D contour, which has a simplified form and is more reasonable for spectrum analysis. And then, the roughness scale extraction method was employed to calculate the fractal-dimension value of the real aluminum (Al) surface. And last, the proposed scale-independent Rabinovich-Fractal model was used to calculate the adhesion forces, which are consistent with the results of the atomic force microscopy adhesion test. Aside from providing a more accurate estimation of the van der Waals forces, the proposed model is not influenced by the sampling scale of the surface roughness measurement, which eliminates the related error in van der Waals force estimation.

Sand blasting for hydrophobic surface generation in polymers: Experimental and machine learning approaches

Wettability is a crucial surface feature of polymers due to their numerous interaction-destined applications. This study focuses on the application of sand blasting process for investigating the wettability of polymeric materials to produce hydrophobic behavior. Four different polymeric materials, Acrylonitrile Butadiene Styrene (ABS), Poly(methyl methacrylate) (PMMA), Polypropylene (PP), and Polycarbonate (PC) underwent sand blasting with varying process parameters, following a comprehensive plan for the design of experiments. Subsequent analyses included surface roughness measurement and wettability tests, supplemented by scanning electron and confocal microscopy observations to gain deeper insights into the blasted surfaces. A predictive model based on a machine learning algorithm was developed using the backpropagation technique to correlate the surface treatment parameters to surface roughness and wettability indexes. From the experimental results sand blasting proved to be efficient in creating hydrophobic surfaces on all the tested materials. The developed neural network demonstrated high fitting degrees between the predicted and measured values. ABS exhibited the most hydrophobic behavior and emerged as a strong candidate for further investigations.

The Abrasive Effect of Moon and Mars Regolith Simulants on Stainless Steel Rotating Shaft and Polytetrafluoroethylene Sealing Material Pairs.

For space missions to either the Moon or Mars, protecting mechanical moving parts from the abrasive effects of prevailing surface dust is crucial. This paper compares the abrasive effects of two lunar and two Martian simulant regoliths using special pin-on-disc tests on a stainless steel/polytetrafluoroethylene (PTFE) sealing material pair. Due to the regolith particles entering the contact zone, a three-body abrasion mechanism took place. We found that friction coefficients stabilised between 0.2 and 0.4 for all simulants. Wear curves, surface roughness measurements, and microscopic images all suggest a significantly lower abrasion effect of the Martian regoliths than that of the lunar ones. It applies not only to steel surfaces but also to the PTFE pins. The dominant abrasive micro-mechanism of the disc surface is micro-ploughing in the case of all tests, while the transformation of the counterface is mixed. The surface of pin material is plastically transformed through micro-ploughing, while the material is removed through micro-cutting due to the slide over hard soil particles.

Effect of Bond Coating Surface Morphology on the TBC System Lifetime

AbstractA study on the effect of bond coating (BC) surface modifications prior to ceramic deposition is presented. Grit blasting and polishing were used to modify the BC surface finish. Thermal barrier coating (TBC) systems were made of a commercial yttria-stabilized zirconia (YSZ) deposited by electron beam physical vapor deposition on a β-(Ni,Pt)Al-coated Ni-based single crystal superalloy. Surface roughness measurements and scanning electron microscopy observations, before and after thermal cycling at 1100 °C, were performed to investigate the influence of the initial surface treatment on the YSZ/BC interface morphology and top coat spallation resistance. Surface states enhancing TBC spallation resistance have been found. In particular, it is shown that rumpling can be avoided even in the presence of phase transformations in the BC, by grinding samples with P600 SiC paper or by applying an “heavy” grit blasting leading to a thinner BC.

Effect of acidic media on surface characteristics of highly filled flowable resin-based composites: An in vitro study.

To analyze and compare the impact of acidic media on the surface characteristics of highly filled flowable resin-based composites. Two hundred fifty-six specimens were divided into four groups: GUF (G-aenial Universal Flo), GUI (G-aenial Universal Injectable), TEF (Tetric EvoFlow), and FSF (Filtek Supreme Flowable Restorative). Surface characteristics were analyzed before (T0) and after specimens immersion in different media, such as gastric juice (GJ), fizzy drink (FD), citric juice (CJ), or artificial saliva (AS), for 9 h (T1) and 18 h (T2). The analyses included surface roughness (SR) measurements, where average roughness (Ra) was obtained, scanning electron microscopy (SEM) analysis, and surface hardness (SH) evaluation, with Vickers numbers (HV) reported. The differences in values among groups/subgroups within the same stage were assessed using two-way ANOVA and Tukey's post hoc test, whereas repeated measures ANOVA with Bonferroni post hoc test was performed to compare the changes in values through the stages. Data were presented as mean ± standard deviation (SD). At T0, GUI and GUF revealed lower Ra values (p < 0.05), more evenness in SEM micrographs, and higher HV values (p < 0.05) than FSF and TEF. At T1 and T2, specimens of all groups/subgroups demonstrated an increase in Ra and a decrease in HV compared with T0 (p < 0.05), as well as the changes in surface morphology on SEM micrographs. The lowest Ra and highest HV values were observed in GUI group, in contrast to FSF group, and in specimens immersed in GJ. GUI revealed lower SR and higher SH compared to GUF and FSF both before and after exposure to acidic media. The presence of acidic media, especially GJ, significantly increases SR and decreases SH of tested materials. Information on the changes in the surface characteristics of highly filled resin-based composites after exposure to acidic media may be essential for the longevity of restorations like composite veneers fabricated from these materials.

Hole quality geometrical measurement and surface roughness for α-Phase titanium alloy (α-Ti-6Al-4V) materials by using L-PBF (laser powder bed fusion) orthopedic implant application

This study examines the quality of circular-hole 3D-printed objects using laser powder bed fusion (L-PBF) on Ti-6Al-4V titanium alloy that typically used for orthopedic implants. Meanwhile measuring surface roughness and hole dimension deviations in AM specimens is very challenging. Thus, the specimens were printed with varying process parameters, followed by an L9 orthogonal array experiment, where parameters included laser power (LP) at 175, 185, and 195 W; scanning speed (SS) at 600, 900, and 1200 mm/s; and hatch distance (HD) at 70, 90, and 110 µm. Thus the, minimum surface roughness values are Ra 2.4 µm for the top surface and Ra 16.06 µm for the inside hole curve. Whereas the smallest hole deviations are 0.1102 mm for external and 0.2094 mm for internal diameters. Therefore, this analysis include FESEM, EDX, XRD, profilometry and stereomicroscopy. Where the best settings are LP 195 W, SS 900 mm/s, and HD 70 µm, producing well-fused, uniform α-phase Ti-6Al-4V specimens that are suitable for biomedical applications.

Evaluation of the anticorrosive painting procedure with reused abrasive for surface preparation – a case study

Atmospheric corrosion is a relevant cause of failure for many metallic structures. Its aggressiveness depends on environmental factors such as relative humidity, salinity, and contaminants. Anti-corrosion paint is the most used technique to minimize this problem, and surface preparation is a fundamental step for suitable paint adhesion. Abrasive blasting can remove oxides and old paint and texture the surface for receiving a new coating. An alternative to reduce costs is reusing abrasive particles to make the process more sustainable. In this investigation, an paint system was qualified through tests in its current environment. The influence of reused abrasives on the painting process by the paint layer’s thickness and its adhesion to the substrate was evaluated. Samples blasted with new and reused abrasives were prepared to evaluate the surface preparation process, allowing surface roughness measurements and incrustation analysis. It was possible to observe that the layers of paint were thin and not uniform, had approximately 155 μm thick, and defects such as pinholes. Reusing the abrasive did not affect the surface average roughness, which was 9.4 ± 2.5 μm. Abrasive incrustation and other contaminants such as Na, P, K, S, and Cl were found on new and reused abrasive surfaces. Recommendations for improvement and suggestions for changing the process were possible to assess.

Study on the impact of grinding variables on surface grinding of inconel 800

ABSTRACT Surface grinding is a widely employed finishing process in industrial sectors dedicated to achieve desired Surface characteristics of components. This study experimentally investigates the impact of the grinding parameters pertaining to the surface characteristics of Inconel 800, which is a nickel-iron-chromium alloy extensively used in high-temperature applications. Various commercially available grinding wheels were employed to grind Inconel800 under different grinding conditions. The ground surfaces were comprehensively analyzed using surface roughness measurements, Three-dimensional profilometry, optical microscopy, findings from XRD and SEM reveal that grinding parameters and wheel characteristics significantly impact the surface texture, topographical features, residual stress, and surface morphology of the machined nickel alloy.. The insights from this investigation contribute to the understanding of the grinding behavior of nickel-based superalloys and provide a basis for optimizing the grinding process for enhanced surface integrity. The findings are valuable for industries dealing with the machining of high-performance nickel alloy components.

Surface roughness of different types of resin composites after artificial aging procedures: an in vitro study

BackgroundThe temperature changes, chemical agents, and brushing activity that resin composite restorations are exposed to in the oral environment can cause changes in surface roughness. In this study, the aim was to investigate in vitro the clinical one-year surface roughness changes of different types of composites (flowable or conventional) from the same companies by subjecting them to immersion in solutions, brushing, and thermal cycling procedures to simulate intraoral conditions.MethodsFour different resin composite brands were included in the study using both their conventional (Charisma Smart, 3M Filtek Ultimate Universal, Omnichroma, Beautifil II) and flowable resin composites (Charisma Flow, 3M Filtek Ultimate Flowable, Omnichroma Flow, Beautifil Flow Plus F00), giving 4 groups with 2 types of resin composite in each. 40 samples were prepared for each group/resin type, for a total of 320 samples. After initial surface roughness measurements by a mechanical profilometer, the samples were divided into 4 subgroups (n = 10) and immersed in solutions (distilled water, tea, coffee, or wine) for 12 days. The samples were then subjected to 10,000 cycles of brushing simulation and 10,000 cycles of thermal aging. Surface roughness measurements were repeated after the procedures. For statistical analysis, the 3-way analysis of variance and the Tukey test were used (p < 0.05).ResultsIt was concluded that composite groups and types had an effect on surface roughness at time t0 (p < 0.001). At time t1, the highest surface roughness value was obtained in the Beautifil-conventional interaction. When the surface roughness values between time t0 and t1 were compared, an increase was observed in the Beautifil II and Beautifil Flow Plus F00, while a decrease was observed in the other composite groups.ConclusionComposite groups, types, and solutions had an effect on the surface roughness of resin composites. After aging procedures, it was concluded that the Beautifil group could not maintain the surface structure as it exceeded the threshold value of 0.2 μm for bacterial adhesion.

Study of structural, surface energies, and tribomechanical properties of thermoplastics irradiated by electron beam

This study investigates the effects of electron irradiation on the structural, surface energy, and tribomechanical properties of two key thermoplastics: polyetheretherketone (PEEK) and polytetrafluoroethylene (PTFE). The experimental methods included electron beam irradiation using the ILU-10 pulsed linear accelerator, Fourier transform infrared spectroscopy (FT-IR), x-ray diffraction (XRD), microhardness testing, surface roughness assessment, tribology tests, and contact angle measurements.The FT-IR analysis revealed significant chemical changes on the surfaces of the polymers, including oxidation processes and the breaking of molecular bonds. XRD analysis showed an increase in the crystallinity of PTFE after irradiation, while the structure of PEEK remained stable. Microhardness testing indicated a notable increase in hardness for both polymers, particularly for PTFE, suggesting cross-linking of molecular chains. Surface roughness measurements demonstrated a decrease in roughness for both irradiated polymers. Tribology tests revealed that electron irradiation increased the coefficient of friction for PTFE and PEEK under various loads, which can be attributed to the alterations in their surface properties. Contact angle measurements indicated improved wettability of the irradiated surfaces, especially for PEEK, due to the formation of new functional groups. The total surface energy increased for both polymers post-irradiation, as determined using the Owens-Wendt-Rabel-Kaeble method. Electron irradiation leads to significant modifications in the surface and bulk properties of PEEK and PTFE, enhancing their tribomechanical and adhesive properties. These changes open new opportunities for the application of these materials in various engineering fields where specific performance characteristics are required.

Surface quality evaluation through new optical imaging system-based objective speckle for additive manufactured titanium samples

Laser cladding is an effective additive manufacturing technology used for materials’ surface modification to enhance their surface and mechanical properties. Surface roughness is a crucial feature that affects the materials’ quality and lifespan. Additionally, it is a real indicator of hardness and wear resistance. Although the existing methods may precisely measure surface roughness, they require delicate adjustment, can damage surfaces, and have limited working distances. This study presents a novel optical imaging system to quantitatively estimate the quality modifications of additive manufacturing samples by measuring their surface roughness based on objective speckle and advanced multivariate analysis methods. The raw speckle patterns are generated from deposited layers on Ti6Al4V titanium alloys obtained at different laser processing parameters. The proposed analysis approach produces collections of local statistical matrices from which histogram features are extracted. Canonical correlation analysis (CCA) is then proposed to distinguish the most significant features. The correlation between the features (with and without applying CCA) and surface roughness is established by using two machine learning regression algorithms, nonlinear support vector regression (SVR), random forest regression (RF), and k-nearest neighbor regression (kNN). The results confirmed that combining RF and CCA provided a feasible regression model to estimate the surface roughness, with 0.998 for R2 in training samples and maximum values of 0.258, 0.484, and 4.593 %, respectively, for MAE, RMSE, and MAPE in test samples. This demonstrates that the proposed objective speckle imaging system is effective in estimating the quality modification of additive manufacturing samples by measuring their surface roughness.

Controlled Porosity of Selective Laser Melting-Produced Thermal Pipes: Experimental Analysis and Machine Learning Approach for Pore Recognition on Pipes Surfaces.

This study investigates the methods for controlling porosity in thermal pipes manufactured using selective laser melting (SLM) technology. Experiments conducted include water permeability tests and surface roughness measurements, which are complemented by SEM image ML-based analysis for pore recognition. The results elucidate the impact of SLM printing parameters on water permeability. Specifically, an increase in hatch and point distances leads to a linear rise in permeability, while higher laser power diminishes permeability. Using machine learning (ML) techniques, precise pore identification on SEM images depicting surface microstructures of the samples is achieved. The average percentage of the surface area containing detected pores for microstructure samples printed with laser parameters (laser power (W) _ hatch distance (µm) _ point distance (µm)) 175_ 80_80 was found to be 5.2%, while for 225_120_120, it was 4.2%, and for 275_160_160, it was 3.8%. Pore recognition was conducted using the Haar feature-based method, and the optimal patch size was determined to be 36 pixels on monochrome images of microstructures with a magnification of 33×, which were acquired using a Leica S9 D microscope.

Surface roughness measurement using microscopic vision and deep learning

Due to the self-affine property of the grinding surface, the sample images with different roughness captured by the micron-scale camera exhibit certain similarities. This similarity affects the prediction accuracy of the deep learning model. In this paper, we propose an illumination method that can mitigate the impact of self-affinity using the two-scale fractal theory as a foundation. This is followed by the establishment of a machine vision detection method that integrates a neural network and correlation function. Initially, a neural network is employed to categorize and forecast the microscopic image of the workpiece surface, thereby determining its roughness category. Subsequently, the corresponding correlation function is determined in accordance with the established roughness category. Finally, the surface roughness of the workpiece was calculated based on the correlation function. The experimental results demonstrate that images obtained using this lighting method exhibit significantly enhanced accuracy in neural network classification. In comparison to traditional lighting methods, the accuracy of this method on the micrometer scale has been found to have significantly increased from approximately 50% to over 95%. Concurrently, the mean squared error (MSE) of the surface roughness calculated by the proposed method does not exceed 0.003, and the mean relative error (MRE) does not exceed 5%. The two-scale fractal geometry offers a novel approach to image processing and machine learning, with significant potential for advancement.

Deep-learning-assisted sidewall profiling white light interferometry system for accurately measuring 3D profiles and surface roughness on the groove sidewalls of precision components.

The accurate measurement of surface three-dimensional (3D) profile and roughness on the groove sidewalls of components is of great significance to diverse fields such as precision manufacturing, machining processes, energy transportation, medical equipment, and semiconductor industry. However, conventional optical measurement methods struggle to measure surface profiles on the sidewall of a small groove. Here, we present a deep-learning-assisted sidewall profiling white light interferometry system, which consists of a microprism-based interferometer, an optical path compensation device, and a convolutional neural network (CNN), for the accurate measurement of surface 3D profile and roughness on the sidewall of a small groove. We have demonstrated that the sidewall profiling white light interferometry system can achieve a measurement accuracy of 2.64 nm for the 3D profile on a groove sidewall. Moreover, we have demonstrated that the CNN-based single-image super-resolution (SISR) technique could improve the measurement accuracy of surface roughness by over 30%. Our system can be utilized in cases where the width of the groove is only 1 mm and beyond, limited only by the size of the microprism and the working distance of the objective used in our system.

Influence of discrete laser surface melting on hot cracking behavior and mechanical properties of Q235 steel

Modern industries demand higher mechanical properties from components. Traditional heat treatment methods often suffer from drawbacks such as high production costs, time-intensive processes, and labor-intensive procedures. The integration of bionic engineering with laser surface melting has given rise to Discrete Laser Surface Melting (DLSM) technology, effectively mitigating these shortcomings. Previous research has substantiated the capability of this technology to significantly enhance various metal properties. This study employed an Nd:YAG pulsed laser for the DLSM treatment of Q235 steel. The discrete laser surface melted (DLSMed) units were prepared on Q235 steel samples. Subsequent analysis utilized scanning electron microscopy (SEM), X-ray diffraction (XRD), and energy-dispersive spectroscopy (EDS) to examine the microstructure and chemical composition of the DLSMed samples. Surface profilometry, hardness testing, and X-ray stress testing were conducted to measure surface roughness, microhardness, and residual stress, respectively. Mechanical properties were evaluated using tensile and impact testing machines. Experimental findings revealed that the DLSMed sample's surface could be divided into three regions: the melting zone, the heat-affected zone (HAZ), and the substrate. The microstructure of the melting zone consisted of refined martensite. The depth and width of the DLSMed units exhibited a certain regularity with variations in the defocus distance. Increasing the defocus distance positively impacted grain refinement and hardness but also led to an increase in surface roughness. Residual stress increased within a specific defocusing range, but beyond this range, its variation lost regularity. Hot cracking behavior within the DLSMed unit encompassed four stages: crack nucleation, propagation, healing, and decomposition. Different defocusing distances and the distribution of DLSMed units significantly affected the tensile strength and impact toughness of the samples. As the defocusing distance increased, the tensile and yield strength of DLSMed samples with transverse units gradually decreased. In contrast, samples with longitudinal units showed a trend of first decreasing and then increasing in tensile and yield strength. The distribution of DLSMed units played a significant role in improving the tensile properties of Q235 steel. The contribution of three factors to the impact performance of DLSMed samples was ranked from high to low as hardness, grain size, and yield strength ratio. The soft phase (substrate) could absorb impact energy and convert it into strain energy stored in the DLSMed sample. Only when the distribution of DLSMed units (hard phases) aligned with the tensile direction could they effectively limit the plastic deformation and enhance the mechanical properties of Q235 steel. However, an increase in defocusing distance led to increased brittleness, deteriorating the mechanical properties of the DLSMed samples. Finally, this study unveiled the strengthening mechanisms of DLSMed samples, providing valuable insights for future applications in enhancing the mechanical properties of metals.

Comparative analysis of surface roughness level for bearing coating using VMD of vibration signal

Degradation in surface finish of the material is an important concern in engineering applications. However, most of the conventional techniques available to monitor the surface roughness requires dismantling of the machine element. Though in rotary components like bearing, it is practically not feasible. Therefore, in this work, an on-board technique is proposed to compare the level of surface roughness based on vibration signature. To demonstrate, five different industrial standard coatings (Nickel, Copper, Zinc phosphate (ZnP), Silver, and Black oxide) were carried out on raw five ball bearings (NBC6205). Two sets of coated bearing were prepared, where first set was utilised for experimentation and second for the purpose of measuring surface roughness of bearing surface. These coated bearings were tested at five different RPMs ranging from 300 RPM to 1500 RPM and their vibration signals were recorded. The recorded vibration signals must be having characteristics originated from ball rolling on different level of surface roughness and hence distributed in nature. Further, to target distributed characteristics present in the signal, commonly used statistical parameters for vibration signature analysis (RMS, Crest factor, Variance, Skewness, Kurtosis, Shannon entropy and Log energy) were calculated. Then, correlation of the parameters was checked in relation to the different levels of surface roughness but no relation was found. The signals were then decomposed into six intrinsic mode functions (IMFs) using Variational Mode Decomposition (VMD) method. Again, same statistical parameters were calculated for these decomposed levels, it has been noted that Shannon entropy have shown correlation to surface roughness in at least one decomposed level between 900 to 1500 RPM with minimum value of chain index as 176.65. Moreover, in this RPM range, responsive frequency bands found to be shifted towards higher side i.e. from 567 to 4590 Hz.

Exploiting Turmeric’s Coloring Capability to Develop a Functional Pigment for Wood Paints: Sustainable Coloring Process of Polyamide 11 Powders and Their Strengthening Performance

Currently, the wood coatings industry is focusing on creating unique, vibrant finishes using new functional pigments. Simultaneously, there is a growing adoption of eco-friendly bio-based materials, reflecting trends in other sectors and supporting the circular economy. Thus, the aim of this study is to unveil a straightforward, cost-effective, and notably sustainable process for exploiting the coloring potential of turmeric powder and coloring polyamide 11-based fillers, employed as multifunctional pigments for wood coatings. Through the incorporation of this additive into a wood paint, the study demonstrates its dual effect of enhancing the aesthetics of the final composite layer while leveraging the beneficial protective properties inherent to polyamide 11. The impact of these additives on sample aesthetics is assessed through optical observations, as well as measurements of color, gloss, and surface roughness. The strengthening contribution of the functional pigment is evaluated using the Taber abrasion resistance test, static friction coefficient measurements, and Buchholz surface hardness test. Finally, the aesthetic consistency of the bio-based filler and the coloring efficiency of the sustainable process are tested by subjecting the samples to aggressive conditions, including the UV-B chamber exposure test, cold liquids resistance tests, and water uptake test. Ultimately, the study illustrates how this functional bio-based pigment not only provides sufficient protection but also meets current eco-requirements, thereby contributing to the sustainability of the wood coatings industry.

The 1st Step of Surface Roughness Measurement and Filtering

The 1st Step of Surface Roughness Measurement and Filtering

Influence of heating temperature and time on mechanical-degradation, microstructures and corrosion performances of Teflon/granite coated aluminum alloys used for non-stick cookware

This study explores the functional characteristics (erosion, corrosion, mechanical damage, and microstructural features) of non-stick cookware made from aluminum alloys. Typically coated with polytetrafluoroethylene (PTFE-Teflon) or ceramic for non-stick properties, we conducted a systematic investigation using corrosion, abrasion, and mechanical tests on six types of cookware from different manufacturers (Manuf-1-6). The cookware was heated at various temperatures [Room temperature (RT), 100, 175, 250, & 350 °C] and times (45 & 120 min). Tests included Taber wear, Adhesive Pull-off, hot & RT corrosion, and surface roughness measurements. Characterization involved optical microscopy, scanning electron microscope (SEM) with electron backscattered diffraction (EBSD), and x-ray diffraction (XRD). Ceramic-coated cookware from Manuf-4 demonstrated superior mechanical strength, wear, and corrosion resistance due to refined microstructures. Manuf-1's PTFE-coated cookware also performed well. Optimal results were observed when heating below 250 °C for up to 45 min. Prolonged heating and temperatures beyond 250 °C adversely affected internal structures of all cookware. Thus, it is advisable to use Al-based non-stick cookware below 250 °C for a maximum of 45 min.