Stainless Steel Samples Research Articles

Effect of grain size on fatigue strength of 304 stainless steel

Abstract In this study, three types of 304 stainless steel samples with different strengths were prepared by refining the grain size through rolling. The microstructure of the samples was observed by electron microscopy. The influence of grain size on the static tensile properties and fatigue strength of the material is mainly attributed to changes in the plastic deformation fracture mechanism and micro-deformation mechanism. In addition, a new fatigue strength prediction model is proposed based on the influence of tensile strength and work-hardening capacity. Compared with the staircase method and Basquin formula models, the proposed model maintains the accuracy of fatigue strength prediction while reducing the cost of fatigue experiments. This provides a new approach for predicting the fatigue strength of specific materials and improving anti-fatigue design capabilities.

K-MEANS AND AGGLOMERATIVE HIERARCHY CLUSTERING ANALYSIS ON THE STAINLESS STEEL CORROSION PROBLEM

Stainless Steel (SS) is a material that is widely used in various fields because it is resistant to corrosion. However, if SS is exposed to heat at high temperatures for a long period of time, a sigma phase, namely the Fe-Cr compound, will form, which indicates that corrosion has begun. The appearance of this corrosion can be detected through color changes on the SS surface, ranging from light brown to dark blue. Corrosion events will be observed through the distribution of color on the sample surface at the location selected through the SS microstructure image. Cluster analysis will be used to group the colors on the surface of the SS sample through the images used. The results of cluster analysis can be used to identify SS color which indicates the appearance of corrosion in the sample. In this research, we will examine the determination of many clusters for K-Means and Agglomerative Hierarchy with Ward's Criterion, Single, Average, and Complete Linkages. In addition, the model quality measure was tested with Silhouette Coeficient. Single linkage gives the worst results because it gives the impression that only one dominant color appears so it can be said that it is unable to distribute each color to the specified cluster. Likewise with Average because the number of clusters cannot be determined with certainty. On the other hand, the K-Means results are similar to Ward's results, this is reasonable because the basic idea of both is to find the minimum distance between each object and its center, in this case the average is used as the measure of the center, while the results that are most similar to the original image are clustering uses complete linkage. These results can be used as recommendations for academics and practitioners in the fields of Statistics, Mathematics and Materials Engineering in the subsequent analysis process to solve SS corrosion problems.

Modelling the Evolution of Phases during Laser Beam Welding of Stainless Steel with Low Transformation Temperature Combining Dilatometry Study and FEM

In this study, the evolution of volume fractions during laser beam welding (LBW) of stainless steel, with a specific focus on incorporating the low transformation temperature (LTT) effect using the dilatometer, has been proposed. The LTT effect refers to the phase transformations that occur at lower temperatures and lead to the formation of a martensitic microstructure, which will significantly influence the residual stresses and distortion of the welded joints. In this research, the LTT conditions are achieved by varying the Cr and Ni content in the weld seam by varying the weld parameter, including laser power, welding speed and filler wire speed. The dilatometer analysis technique is employed to simulate the thermal conditions encountered during LBW. By subjecting the stainless steel samples to controlled heating and cooling cycles, the kinetics of the volume fractions can be measured using the lever rule and empirical method (KOP and Lee). The phase transformation simulation model is computed by integrating the thermal and metallurgical effects to predict the volume fractions in LBW joints and has been validated using dilatometer results. This provides valuable insight into the relationship between welding parameters and phase transformations in stainless steel with the LTT effect during laser beam welding. Using this relationship, the weld quality can be improved by reducing the residual stresses and distortion.

Plasma electrolytic polishing of additively manufactured metal parts: Optimizing the post processing workflow

Additive manufacturing of metal parts is gaining acceptance in industry due to its unique manufacturing capabilities. Higher surface roughness of printed parts is one of the major challenges of this advanced manufacturing technique, which requires a crucial post-processing stage before the components can be used in practice. This study investigates the influence of plasma electrolytic polishing (PeP) and the combination of PeP and particle blasting as a post processing technique for additively manufactured stainless steel samples. The results show a 70% improvement in surface roughness after 10 minutes of particle blasting and 3 minutes of PeP in sequence and presents the possibility of optimizing processing time to achieve better surface qualities with minimal post processing time.

Silicon nanowires analyzed by x-ray photoelectron spectroscopy

Silicon nanowires were characterized by x-ray photoelectron spectroscopy with an Al Kα (1486.6 eV) excitation source. The sample was fixed to a stainless-steel sample holder with a copper double-sided adhesive tape. Survey spectrum and C 1s, O 1s, and Si 2p core-level spectra were acquired.

A method for rapid estimation of residual stresses in metal samples produced by additive manufacturing

The mechanical methods for measuring residual stresses typically rely on so-called destructive techniques where some stress components can be determined based on part deflection after material removal (cutting, etching, drilling, etc.). While these methods don't provide a comprehensive representation of residual stresses within the entire part, they can be readily applied in most manufacturing labs. In this study, we propose an efficient method for determining residual stress within additively manufactured cylindrical samples of stainless steel. The method is based on the assumption of a relation between the axial component of residual stress (normal to cross-section) and the cylinder radius. The general form of this relation is proposed based on data from numerical simulations using linear, parabolic or piecewise approximations. The parameters for the proposed relation are defined using equilibrium equations for total force and moment. The proposed method relies on an experiment with a mechanical cut along the cylinder. Consequently, the deflection of the cylinder halves after the cut allows for obtaining the equivalent bending moment.

Investigation of electromagnetic shielding effectiveness of nano silver coated stainless steels

This paper presents the shielding effectiveness (SE) of various nanosilver-coated stainless steels (201, 304, 316 and 430), using a coaxial transmission line setup with waveguides and a vector network analyzer (VNA) in accordance with ASTM 4935 standards. The conducted experiments revealed excellent SE outcomes, indicating that the silver-coated stainless steel samples exhibited notably superior SE performance compared to their uncoated counterparts. The importance of SE in electromagnetic compatibility (EMC) applications, particularly in minimizing electromagnetic interference (EMI) and safeguarding sensitive electronic devices, is well acknowledged. This study further explored the shielding effectiveness of a novel hybrid material, nano silver (Ag) coated different stainless steels, with a focus on its potential for improved EMI shielding capabilities. Experimental measurements were conducted in the 5G frequency domain.It was found that nanosilver coating increased the SE of stainless steels by between 5 and 12 dB. This enhancement attributed to the incorporation of nanostructured silver particles on the stainless steel surface, which facilitates enhanced reflection of electromagnetic waves, resulting in superior shielding performance. Moreover, this study underlying the mechanisms of SE through various analyses, including X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), and scanning electron microscopy (SEM). In summary, this research has demonstrated that nano silver coating increases the SE value of materials. This result suggests that all other materials can be used to increase the SE value. The results have implications for advancing electromagnetic shielding technologies and promoting the development of robust EMI shielding solutions in various industrial applications where effective shielding is of paramount importance.

High resolution magnetic field imaging probe with two rows of TMR sensors for small defects inspection

It is still a challenging problem to detect small defects for eddy current array probes, which requires the probes to possess excellent sensitivity, as well as high spatial resolution. This paper presents a novel high-resolution magnetic field imaging probe with two rows of tunneling magnetoresistance (TMR) array sensors. The bare die sensors are integrated on a printed circuit board by golden wire bonding technology. The two rows of sensors are placed staggered with each other. The data of the two arrays are merged into a matrix, in which way the image pixel pitch is increased to 0.25 mm. The probe employs a differential scheme to suppress the noise, so as to detect the weak signal of small defects. To highlight the weak defect indications, feature extraction and segmentation algorithms are developed. The experimental results confirm that the proposed method can inspect a small defect with dimensions 1 mm (length) × 0.1 mm (width) × 0.1 mm (depth) on a stainless-steel sample.

Improved surface properties of AISI-420 steel by Ti[sbnd]C based coating using graphite cathodic cage with titanium lid in plasma deposition

In this work, titanium‑carbon (TiC) based coating is deposited on AISI-420 martensite stainless steel samples to improve surface properties. The coating is deposited using a graphite cathodic cage equipped with a titanium lid, which acts as a source of carbon and titanium. The hardness of samples (untreated hardness of 220 HV0.25) is increased up to 1337 HV0.25 and 1524 HV0.25 by coating deposition at cathodic (base plate connected with cathodic cage) and floating potential (with no external potential). The sample treated at cathodic potential exhibits expanded martensitic phase due to diffusion of carbon atoms. In contrast, additional TiC and chromium carbide Cr23C6 peaks are formed while treated at floating potential. The thickness of carburizing layer is 80 and 77 μm, when the coating is deposited at cathodic and floating potential, respectively. The wear volume of the untreated sample (1200 × 10−4 mm3) is reduced to ∼ (20 × 10−4 mm3) after the coating deposition, and the friction coefficient is also reduced due to the coating deposition. A significant decrease in corrosion rate is also observed, specifically at floating potential. It suggests that Ti-C-based coating using this modified cathodic cage plasma deposition (CCPD) is beneficial for the hardness, wear, and corrosion resistance of AISI-420 steel.

Cr-Co Oxide Coatings Resistant to Corrosion, Electrodeposited on 304 SS Using an Ethylene Glycol-Water Solvent

The electrochemical co-deposition of Cr-Co oxide coatings at room temperature on 304 stainless steel (SS) was studied using an electrolyte composed of a mixture of ethylene glycol (EG), hydrated metal chloride salts (MCln∙YH2O), and water as a secondary hydrogen donor (HBD). Metallic Cu and Ni undercoats were applied to improve the adhesion of a posterior Cr-Co metallic and oxide layer. The electroactive events that took place during both electrodeposition processes were studied using cyclic voltammetry (CV) and chronoamperometry. The microstructure and composition of the surface layers were studied using scanning electron microscopy (SEM/EDS), X-ray diffraction (XRD) and cross-sectional elemental mapping via transmission electron microscopy (TEM). The surface of steel with the Cr-Co:EG-H2O coating showed greater resistance to pitting corrosion (123.93 mV) compared to untreated stainless steel (62.3 mV). This sample showed a large hystere-sis area, which is associated with high resistance to pitting corrosion by the occurrence of a re-passivation of the sample at a Erep value of 24.31 mV. After the cyclic potentiodynamic polariza-tion (CPP) test, the lowest specific mass loss (0.001 mg/cm2) was achieved for the AISI 304 SS sample coated using EG-water solvents (Cr-Co:EG-H2O), while the untreated AISI 304 SS reached a higher specific mass loss (0.01 mg/cm2). The Electrochemical Impedance Spectroscopy (EIS) tests showed that the uniform corrosion resistance varied significantly from the untreated AISI 304 SS (35 kΩ) to the coated sample (57 kΩ), which is attributed to the protection provided by the chromium and cobalt oxides coating. The best corrosion resistance achieved was correlated with a superhydrophobic character (with a contact angle of 158.41°) of the Cr-Co coatings. This was in turn a consequence of a needle-like morphology characteristic of these oxides.

Cluster Mo2C deposited on graphene nanowalls by x-ray photoelectron spectroscopy

Molybdenum deposited on carbon graphene nanowalls was characterized by x-ray photoelectron spectroscopy with an Al Kα (1486.6 eV) excitation source. The sample was fixed to a stainless-steel sample holder with copper double-sided adhesive tape. Survey spectrum, C 1s, O 1s, Si 2p, and Mo 3d core levels spectra were acquired.

A new laser remelting strategy for direct energy deposition of 316L stainless steel

At present, components produced by Direct energy deposition (DED) still have many shortcomings, such as rough surfaces, many internal pores, and the formation of long columnar grains that will lead to anisotropy due to large temperature gradients. Laser remelting (LR) is an effective method to improve the top surface quality and densification of samples. In the present work, in the process of manufacturing 316L stainless steel samples with DED, an additional LR process without powder conveying is added after each deposition layer of the samples is deposited. The smoothness of the sample surface has been greatly improved, and the density of the samples has been increased to nearly fully dense. The number and size of pores inside the samples are significantly decreased. By changing laser power and spot size, the effect of the LR process with different energy densities on microstructure and mechanical properties was studied. After the LR process, the coarse and long columnar grains in samples are transformed into fine equiaxed grains and fine columnar grains. Experimental results show that the LR process with appropriate energy density can reduce the residual stress of the samples made by DED and significantly improve the tensile strength and elongation of the samples. LR with the same processing parameters as the deposition has the most obvious effect on refining the microstructure and improving tensile properties. However, the LR process with low energy density will increase the residual stress of the sample, resulting in poor mechanical properties.

Corrosion behavior of selective laser melted biomaterials in a physiological environment

Medical applications are today the most important areas that use additively manufactured parts. The choose of the convenient biomaterial during implant design depends on several criteria such as biocompatibility, osteointegration and processing cost. The purpose of this work is to compare the corrosion behavior of AISI 316L austenitic stainless steel and Titanium TiAl6V4 orthopedic implants manufactured by selective laser melting. For each material the process parameters were varied to obtain comparable surface states mainly evaluated by microgeometric quality and porosities distribution. The electrochemical interaction between biomaterial and the physiological environment was simulated by corrosion tests performed in a Ringer type solution. From the obtained results it can be seen that selective laser melted Titanium TiAl6V4, despite its higher roughness, exhibits the highest corrosion resistance compared to AISI.316L stainless steel samples. In fact, for comparable porosities distribution density, enhanced corrosion properties, such as corrosion rate, pitting potential (Epp) and corrosion potential (Ecorr) were achieved for Titanium alloy.

An energy resolved neutron imaging detector based on boron doped nMCP coupled with a time stamping optical camera

Energy resolved neutron imaging has developed rapidly due to its advantage on testing the inner structure of crystal samples. Neutron detector is one of the key components to determine the imaging results quality. The neutron sensitive microchannel plate (nMCP) has been widely used in energy resolved neutron imaging experiments because of the high spatial and timing resolution. However, the ability to adjust field-of-view (FOV) and spatial resolution has not been realized in the nMCP detector, which is an attractive capability in energy resolved neutron imaging experiments. In this paper, an energy resolved neutron imaging detector was developed by coupling nMCP with a time stamping camera. The neutrons were absorbed by nMCP and converted into light through a phosphor screen. Then the light was focused on the camera by optical lens. A data algorithm was designed to improve the data quality. By changing the magnification of the optical lens, large FOV (46mm diameter) and high spatial resolution (26 μm) were realized in the experiments at CSNS beamline 20. The energy resolved ability was demonstrated by a Bragg-edge transmission imaging experiment for aluminum and stainless-steel samples. The performance of this detector makes it a promising candidate used in energy resolved neutron imaging.

Evaluation of wear behavior on AISI 431 by vaccum annealing method for sustainable applications

In this research work, the vacuum annealed stainless steel samples were subjected to a constant load. The wear behavior of AISI 431 sample were examined by using pin on disc wear tester. The vacuum annealing were used to preserve the stability between ductility and brittleness. The samples were created in cylindrical shape with a length of 40 mm and diameter 8mm. For this current research, 3 samples are treated at 600°C, 660°C, 820°C temperatures and they were assigned asA1, A2 and A3 respectively. The outcome of vacuum annealing is that to reduce the hardness and increase in ductility, to overcome the material from defects and release internal stress. The hardness, wear behavior were measured for the treated and untreated samples. To evaluate the wear behavior, comparison of results, wear test studies and scanning electronic microscope analysis were done.

Effect of sterilization on the corrosion behavior of orthopedic implants coated and uncoated

The impact of sterilization on the corrosion behavior of orthopedic implants produced via Laser Powder Bed Fusion is analyzed in a biologically relevant environment. In a controlled environment at 37 °C, experiments were conducted to mimic a natural biological state. In a controlled oven at 50 °C for 20 min, AISI 316L stainless steel samples were prepped before primary testing. The experiment showed that sterilization leads to the development of a more efficient passive layer, resulting in improved corrosion resistance. The improvement in corrosion potential, pitting potential, and corrosion rate was substantial. A decrease in corrosion resistance is observed when TiN (Titanium Nitride) is applied. The findings suggest that sterilization can enhance the corrosion performance of 316L L-PBF implants, although this improvement may not apply equally to all coated components, such as those with TiN coatings.

Investigation of low-cycle fatigue in adhesively-bonded single-lap joints

Adhesively bonded joints are used as an alternative to classical mechanical joining methods, e.g., bolts, rivets, welding, and soldering, due to their advantages such as high strength, uniform stress distribution, and good fatigue resistance. These adhesively bonded joints are becoming more and more important, especially in fields where weight is critical, such as aviation and aerospace. Adhesively bonded joints are preferred because they offer highly reliable connections. In the present study, the low-cycle fatigue of materials joined together as adhesively bonded single-lap joints were investigated experimentally and numerically. Joints of aluminum and steel samples were subjected to variable loads that were lower than the experimentally obtained average breaking loads, and the number of cycles was determined. As a result, the fatigue life of adhesively bonded single-lap stainless steel samples was observed to be higher than that of aluminum samples. In addition, it was also observed that smudging adhesive around the endpoints of the joint significantly increased the fatigue life of steel samples.

Spall strength of additively repaired 304L stainless steel

Additive manufacturing has the potential to repair damaged parts, but the performance of additive materials under high strain rate loading is still uncertain—especially with the added complexity of an interface with an existing wrought material. In this work, 304L stainless steel samples were intentionally damaged and then repaired with wire-fed laser additive manufacturing. The samples were subjected to shock loading to generate incipient spall. Velocimetry and post-mortem metallography results show that when the additive repair process parameters are optimized to reduce porosity and match the equation of state of the original material, the influence of the repair region on the shock propagation is negligible. The free-surface velocity profile and internal damage morphology of the repaired sample are shown to be practically identical to the pristine material.

Quasi-in-Situ Analysis of Electropolished Additively Manufactured Stainless Steel Surfaces

Progress in additive manufacturing is leading to the emergence of new areas of application. Laser Powder Bed Fusion (L-PBF) is increasingly used for the development of metallic medical implants, but for high-risk implants like vascular support structures (stents), surface quality is critical to ensure successful implantation without harming the surrounding tissue and ensure the patients’ health. Therefore, enhancing the surface quality is crucial. Electropolishing is a method for removing surface roughness by smoothing out micro-peaks and valleys. However, L-PBF structures have a high surface roughness due to metal particles adhering on the surface. To achieve a smooth surface for additively manufactured implants like stents using electropolishing, the removal of these particles needs to be studied in more detail.The objective of this study is to examine the electropolishing mechanism of 316L stainless steel samples additively manufactured through Laser Powder Bed Fusion (L-PBF). The main objective is to investigate the removal properties and surface characteristics during electropolishing. To achieve this, various surfaces were characterized for morphology and roughness during Hull cell experiments. Markings are utilized on the Hull cell sample surfaces to identify points of interest during quasi-in-situ measurements. The surfaces are then analyzed after multiple time steps, applying different currents to investigate particle dissolution. The surface characteristics are analyzed through scanning electron microscopy, and surface roughness is analyzed using laser scanning microscopy.The results show that the electropolishing process preferentially removes the adhering particles present on the surface of the samples. Increasing the current density results in faster particle dissolution and a smoother surface (see Figure 1a and b). The mechanism of material removal of various surface features, as shown in Figure 1 (red circle, yellow arrow and red square), was assessed based on the experimental results of the surface structures seen on the SEM images. It was found that different surface features were removed during the experiment at different polishing times and current densities. The amount of charge flowed was found to correlate with surface morphology.Based on the obtained results, various surface features (such as large adherent particles, agglomerates of smaller particles, and valleys) and their changes with increasing test duration and current density were observed by quasi-in situ analyses. A reduction in the diameter of round particles adhering to the surface was observed at both low and higher current densities (see Figure 1a red circle a). Increasing the polishing time resulted in leveling of both large particles and valleys (see Figure 1b red square). Also, dissolution of agglomerates of smaller particles occurred at different polishing times as a function of current density and polishing time (see Figure 1a yellow arrow) are observed.Smoothed surface structures can be observed in regions with equivalent surface charge density (see Figure 2). As a result, comparable surface morphologies may appear at the same area charge density, irrespective of a specific current density. So, it may be adequate to only consider the amount of charge flowed to describe the electropolishing of additive materials.In conclusion, comprehending the dissolution characteristics of particles on L-PBF surfaces is essential for attaining satisfactory surface finish in electropolishing. The results of this study offer valuable perspectives into the electropolishing mechanism of additively manufactured 316L stainless steel and can guide future investigations on surface finishing and polishing of additive manufactured implants like stents. Figure 1

Grain and grain boundary segmentation using machine learning with real and generated datasets

We report a significantly improved accuracy in grain boundary segmentation using Convolutional Neural Networks (CNN) trained on a combination of real and generated data. Manual segmentation is accurate but time-consuming, and existing computational methods are faster but often inaccurate. To combat this dilemma, machine learning models can be used to achieve the accuracy of manual segmentation and have the efficiency of a computational method. An extensive dataset of from 316L stainless steel samples is additively manufactured, prepared, polished, etched, and then microstructure grain images were systematically collected. Grain segmentation via existing computational methods and manual (by-hand) were conducted, to create ”real” training data. A Voronoi tessellation pattern combined with random synthetic noise and simulated defects, is developed to create a novel artificial grain image fabrication method. This provided training data supplementation for data-intensive machine learning methods. The accuracy of the grain measurements from microstructure images segmented via computational methods and machine learning methods proposed in this work are calculated and compared, and also provide benchmarks in grain segmentation. Over 400 images of the microstructure of stainless steel samples were manually segmented for machine learning training applications. This data and the artificial data is available on Kaggle.