316L Stainless Steel Samples Research Articles

Studies on the Effect of Laser Shock Peening Intensity on the Mechanical Properties of Wire Arc Additive Manufactured SS316L

This study examines the impact of laser shock peening (LSP) on the mechanical properties, microstructural features, and elemental distribution of stainless steel 316L (SS316L) produced using wire arc additive manufacturing (WAAM). The investigation focuses on significant changes in mechanical behavior, surface topography, and porosity following LSP treatment, comparing these results to the untreated condition. LSP treatment significantly enhanced the ultimate tensile strength (UTS) and yield strength (YS) of WAAM-fabricated SS316L samples. The UTS of the as-manufactured WAAM specimen was 548 MPa, which progressively increased with higher LSP intensities to 595 MPa for LSP-1, 613 MPa for LSP-2, and 634.5 MPa for LSP-3, representing a maximum improvement of 15.8%. The YS showed a similar trend, increasing from 289 MPa in the as-manufactured specimen to 311 MPa (LSP-1) and 332 MPa (LSP-2), but decreasing to 259 MPa for LSP-3, indicating over-peening effects. Microstructural analysis revealed that LSP induced severe plastic deformation and reduced porosity from 14.02% to 4.18%, contributing to the improved mechanical properties. Energy dispersive spectroscopy (EDS) analysis confirmed the formation of an oxide layer post-LSP, with an increase in carbon (C) and oxygen (O) elements and a decrease in chromium (Cr) and nickel (Ni) elements on the surface, attributed to localized pressure and heat impacts. LSP-treated samples exhibited enhanced mechanical performance, with higher tensile strengths and improved ductility at higher laser intensities. This is due to LSP effectively enhancing the mechanical properties and structural integrity of WAAM-fabricated SS316L, reducing porosity, and refining the microstructure. These improvements make the material suitable for critical applications in the aerospace, automotive, and biomedical fields.

Significance of the electrochemical passive layer during the wear tests of surface finished SLM stainless steel features

Tribology, the study of friction, wear, and lubrication, plays a critical role in the performance of manufactured components, particularly in the emerging field of additive manufacturing (AM). While AM allows for the fabrication of complex geometries, the as-built components often suffer from surface roughness and suboptimal mechanical properties, necessitating post-processing treatments to enhance their usability. In this paper, a specific heat treatment sequence, including main quenching, intermediate quenching, and tempering, was applied to stainless steel 316L samples to improve their mechanical characteristics. The main quenching involved heating the samples to 1000°C for 30minutes, followed by water quenching. The intermediate quenching followed a similar process at 750°C. The heat-treated samples (HT-1 and HT-2) underwent different tempering stages. The HT-1 samples were selected for tribological testing due to their lower residual stresses and higher hardness compared to HT-2 samples, with both samples demonstrating similar ductility. HT-1 samples were tested against six different hard counter body materials under varying surface roughness conditions achieved through electrochemical polishing. The electrochemically fully finished (ECP) samples achieving the lowest coefficient of friction (COF) compared to as-built samples. Wear mechanisms varied with the counter body materials: adhesive wear and tribo-oxidation were dominant against hardened steel, alumina (Al2O3), boron carbide (B4C), and silicon carbide (SiC), while abrasive wear was predominant against tungsten carbide (WC) and titanium carbide (TiC).

Mass finishing of additively manufactured AISI 316L using pecan nutshells as sustainable abrasive media

Abrasive processes represent the main methods for obtaining high-quality surface finish in metal parts. As one main characteristic, these processes have a relatively high consumption of energy per material volume removed, as well as many inputs, such as abrasive tools and equipment, and, consequently, a high associated environmental impact. Additive manufacturing is becoming a competitive method to produce customized parts, but the surface finish is often not good enough for the application, and post-processing is needed. In this work, a mass finishing process using a planetary mill with abrasive media made of sustainable materials (pecan nutshells) was used on AISI 316L stainless steel samples manufactured by selective laser melting (SLM). The main goal was to perform a multicriteria analysis of the sample surface before and after post-processing. Through the analysis, it could be observed that the nutshell abrasive media has results close to those of traditional ceramic media. The increase in the rotation speed of the planetary mill, increase of finishing time, and use of abrasive pastes can further increase the effectiveness of the process.

Thermal Conductivity of 3D Printed Metal using Extrusion-based Metal Additive Manufacturing Process

Abstract In this study, the thermal conductivity of 3D-printed 316L stainless steel parts using the bound metal deposition (BMD) method, an extrusion-based 3D printing technology, were examined experimentally and validated numerically using finite element analysis (FEA). Various critical printing parameters were examined, including infill density, skin overlap percentage, and print sequence to study their effect on the printed thermal conductivity. A heat conduction experiment was performed on the 3D-printed samples of 316L stainless steel followed by a FEA. The results from this investigation revealed that an increase in 3D printing infill density correlated with a rise in effective thermal conductivity. Conversely, a substantial decrease in thermal conductivity was observed as porosity increased. For instance, at a porosity level of 16.5%, the thermal conductivity experienced a notable 33% reduction compared to the base material. The skin overlap percentage, which governs how much the outer shell of adjacent layers overlaps, was found to impact heat transfer across the overall part surface. A higher overlap percentage was associated with improved thermal conductivity, although it could affect the surface finish of the part. Furthermore, the study explored the print sequence, focusing on whether the outer wall or infill was printed first. Printing the outer wall first resulted in higher thermal conductivity values than that obtained from printing the infill first. Therefore, it is crucial to carefully consider these factors during the BMD 3D printing process to achieve the desired thermal conductivity properties.

Deep Learning-Driven Prediction of Mechanical Properties of 316L Stainless Steel Metallographic by Laser Powder Bed Fusion.

This study developed a new metallography-property relationship neural network (MPR-Net) to predict the relationship between the microstructure and mechanical properties of 316L stainless steel built by laser powder bed fusion (LPBF). The accuracy R2 of MPR-Net was 0.96 and 0.91 for tensile strength and Vickers hardness predictions, respectively, based on optical metallurgy images. Feature visualisation methods, such as gradient-weighted class activation mapping (Grad-CAM) and clustering, were employed to interpret the abstract features within the MPR-Net, providing insights into the molten pool morphology and grain formation mechanisms during the LPBF process. Experimental results showed that the optimal process parameters-190 W laser power and 700 mm/s scanning speed-yielded a maximum tensile strength of 762.83 MPa and a Vickers hardness of 253.07 HV0.2 with nearly full densification (99.97%). The study marks the first application of a convolutional neural network (MPR-Net) to predict the mechanical properties of 316L stainless steel samples manufactured through laser powder bed fusion (LPBF) based on metallography. It innovatively employs techniques such as gradient-weighted class activation mapping (Grad-CAM), spatial coherence testing, and clustering to provide deeper insights into the workings of the machine learning model, enhancing the interpretability of complex neural network decisions in material science.

Microstructure and mechanical properties of 316L stainless steel manufactured by multi-laser selective laser melting (SLM)

The microstructure and mechanical properties of 316L stainless steel samples manufactured by dual-laser selective laser melting technology, were investigated in compare with that of the single-laser scanning samples. It was found that the porosity of the dual-laser overlap samples was lower than that of single laser forming samples due to the different laser energy density absorbed by the powders. Furthermore, it was found that the crystal structure and crystal orientation of both zones were similar. From the TEM observation, it was noted that the number density of nano-oxides in the overlap zone was higher than that in the single laser forming zone. This reason was suggested as the difference of the oxygen content inside the melt pool during the forming process. The strength and microhardness of the single-laser samples was lower than that of the dual-laser overlap samples, but the elongation was higher. By analyzing the strengthening mechanism, it was revealed that Orowan strengthening was the main reason for the difference. These results could guide the large-size component manufactured using the muti-laser selective laser melting technology.

Influence of print-chamber oxygen content on the microstructure and properties of 3D-printed 316L

Abstract Samples of 316L stainless steel have been prepared using laser-powder bed fusion from the same batch of powder using different print-chamber oxygen levels, ranging from 50 ppm to 1500 ppm. The oxide particle density is found to increase with oxygen content, while the cell structure is invariant with oxygen level and the grain size shows a relatively sharp transition for measured oxygen levels of above 450 ppm. Based on the microstructural observations it is suggested that the increasing oxygen levels leads to a transition in the solidification pattern. Samples printed at the higher oxygen level show higher strength and lower mechanical anisotropy than samples with a coarser grains structure printed at lower oxygen levels. The main influence of the higher oxide particle content on thermal stability is on the kinetics of recrystallization during isothermal annealing at 1000 °C.

Bioinspired Self-Adhesive Multifunctional Lubricated Coating for Biomedical Implant Applications.

In the realm of clinical applications, the concern surrounding biomedical device-related infections (BDI) is paramount. To mitigate the risk associated with BDI, enhancing surface characteristics such as lubrication and antibacterial efficacy is considered as a strategic approach. This study delineated the synthesis of a multifunctional copolymer, embodying self-adhesive, lubricating, and antibacterial properties, achieved through free radical polymerization and a carbodiimide coupling reaction. The copolymer was adeptly modified on the surface of stainless steel 316L (SS316L) substrates by employing a facile dip-coating technique. Comprehensive characterizations were performed by using an array of analytical techniques including Fourier transform infrared spectroscopy, X-ray photoelectron spectroscopy, optical interferometry, scanning electron microscopy, and atomic force microscopy. Nanoscale tribological assessments revealed a notable reduction in the value of the friction coefficient of the copolymer-coated SS316L substrates compared to bare SS316L samples. The coating demonstrated exceptional resistance to protein adsorption, as evidenced in protein contamination models employing bovine serum albumin and fibrinogen. The bactericidal efficacy of the copolymer-modified surfaces was significantly improved against pathogenic strains such as Staphylococcus aureus and Escherichia coli. Additionally, in vitro evaluations of blood compatibility and cellular compatibility underscored the remarkable anticoagulant performance and biocompatibility. Collectively, these findings indicated that the developed copolymer coating represented a promising candidate, with its facile modification approach, for augmenting lubrication and antifouling properties in the field of biomedical implant applications.

Experimental Study on Parameters Optimization of Selective Laser Melting 316L Stainless Steel Based on the Response Surface Methodology

Abstract The use of 3D printing technology can prepare flexible and varied special-shaped complex structures while realizing resource-saving and cost reduction. For this purpose, a 316L stainless steel sample was formed by selective laser melting technology, and the quality of samples was optimized by the Box–Behnken surface response method. Taking the surface roughness Sa as the response value, a regression analysis of four parameters of selective laser melting (laser power, scanning speed, scanning spacing, and scanning strategy) was designed using design expert software. The results showed that the scanning spacing and scanning speed have the greatest influence on the surface roughness, while the laser power and scanning strategy have no significant influence on the surface roughness. Meanwhile, the established surface roughness response surface model is effective and can be used for quality optimization of 316L structural trim. When the laser power was 185 W, the scanning speed was 615 mm/s, the scanning spacing was 110 μm and concentric scanning strategy was adopted, the surface adhesion powder was less, and the minimum surface roughness Sa was 9.001 μm.

Scaling of damage mechanism for additively manufactured alloys at very high cycle fatigue

A comparative analysis of fracture mechanisms in high- and very high- cycle fatigue (HCF, VHCF) regimes was carried out based on the results of multifractal analysis of the fracture surfaces of additively manufactured 316L stainless steel samples. In terms of scale invariants, the morphology of fracture surfaces in HCF and VHCF regimes inside and outside the fine granular area is shown. The analysis demonstrated that chaotic patterns of relief formation prevail in the crack initiation zone of VHCF samples. However, there is a self-similar relief with a pronounced correlation in the crack propagation area. The relief of the crack growth areas for HCF and VHCF samples are similar to each other.

Effect of Anisotropy on Residual Stress Measurement of 316L Stainless Steel by Ultrasonic Surface Wave

Fe–Cr alloys are widely used in power, petroleum, and manufacturing industries for their good resistance to corrosion and oxidation at high temperatures. Ultrasound is the only nondestructive method so far to measure the residual stress of in-service components. However, for parts with material anisotropy, such as materials processed by rolling, the measurement accuracy is highly restrained. In this paper, a rolled 316L stainless steel sample is used to study the influence of texture on the measurement of residual stress by ultrasonic surface wave. The experimental results show that the propagation velocity of surface waves in the sample has anisotropic characteristics. The wave velocity parallel to the rolling direction (0°) is the maximum, and the wave velocity perpendicular to the rolling direction (90°) is the minimum, thereby affecting the measurement accuracy. It is found that reducing the frequency of surface waves can reduce the influence of anisotropy. Therefore, a low-frequency method and modified formula are used to improve the measurement accuracy. The maximum error in the rolling direction is reduced from 21.3 to 3.6 MPa, and the maximum relative error is also reduced from 45.4 to 9.0%. The modified formula can further reduce the influence of anisotropy, with the maximum error value further reduced to 2.3 MPa, the maximum relative error reduced to 4.9%, and the surface wave detection accuracy effectively improved.

A ribbed strategy disrupts conventional metamaterial deformation mechanisms for superior energy absorption

ABSTRACT Enhancing energy absorption in mechanical metamaterials has been a focal point in structural design. Traditional methods often include introducing heterogeneity across unit cells. Herein, we propose a straightforward ribbed strategy to achieve exceptional energy absorption. We demonstrate our concept through modified body-centered cubic (BCC) and face-centered cubic (FCC) ribbed truss-lattice metamaterials (BCCR and FCCR). Using stainless-steel 316L samples, compression tests indicate a 111% and 91% increase in specific energy absorption (SEA) for BCCR and FCCR, respectively, along with an enhancement in compression strength by 61.8% and 40.7%. Deformation mechanisms are comprehensively elucidated through both finite element analysis and theoretical calculations. The mitigation of stress concentration at nodes, redistribution of load transfer pathways within struts, and introduction of multiple plastic hinges collectively contribute to increased energy absorption and higher compression strength. Using rein-based polymer samples, the ribbed truss-lattice metamaterials also exhibit exceptional damage tolerance, experiencing only a 15% loss in maximum strength after cyclic compression at 20% strain, while maintaining a 73% higher SEA compared to their non-ribbed counterpart. This strategy extends beyond the discussed structures, presenting itself as a generic approach to enhance plateau strength and SEA.

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.

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.

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.

The effect of the vibratory surface finishing process on surface integrity and dimensional deviation of selective laser melted parts

Selective laser melting (SLM) is an additive manufacturing method used in aerospace and biomedical industries due to its ability to fabricate complex geometries with excellent mechanical properties. However, achieving the desired surface quality can be challenging. Vibratory surface finishing (VSF) is a widely used post-processing technique in engineering industries to improve surface quality. In this study, SLM-produced stainless steel 316L samples with different geometries, including samples with flat surfaces (SFS), samples with bulged surfaces (SBS), and samples with concave surfaces (SCS), were processed using triangular, spherical, and cylindrical media shapes for different processing times. The research aimed to analyze the surface integrity and dimensional deviation of each sample type after VSF. Our study employed a full factorial design of experiments (DoE) to assess the influences on the surface integrity, dimensional deviations, surface morphology, and surface hardness of 316L stainless steel parts produced via SLM. After VSF, the average Ra value was reduced by 75% after 9 h of operation, achieving the lowest Ra value (1.68 μm) using spherical media. Spherical media also reduced Ra values on concave surfaces by approximately 71%, with a reduction from 14.55 to 4.15 μm. The study found that VSF helps improve surface roughness while affecting the components’ average dimensional deviation and subsurface microhardness. The microhardness measurement showed a value of 220 HV, which was approximately 6.4% higher than the bulk hardness.

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.

Influence of Surface Finish on the Dry Sliding Wear and Electrochemical Corrosion Behaviour of 316L Stainless Steel

316L stainless steel is known for its high corrosion resistance and extensively being used for biomedical implants and for the fabrication of the parts in nuclear reactors, and fuel cells. In the current study, 316L stainless steel samples were grounded using different grades of surface grits (400, 1200, and mirror-finished) by mechanical polishing, and influence of surface finish on the wear and corrosion characteristics was studied. The dry sliding wear experiments were carried out on ball-on-plate setup against hardened steel ball and the corresponding friction curves were obtained and specific wear rates were measured. The wear mechanisms were identified by examining the worn-out surface using scanning electron microscope and Raman spectrometer. It was evident that the formation and removal of iron oxides is the dominant mechanism for material loss from the samples during wear tests. The higher wear resistance of the mirror-finished sample was attributed to the formation of stable chromium oxide layer on the wear track. Potentiodynamic polarization tests were performed on the samples and better corrosion resistance was observed for the mirror-finished sample.

Effects of the thermal history on the microstructural and the mechanical properties of stainless steel 316L parts produced by wire-based laser metal deposition

Laser metal deposition with coaxial wire feeding is a novel technology for additively manufacturing near-net-shape metal parts, as well as for repairing and modifying existing components. The microstructure and, thus, the mechanical properties of the deposited material significantly depend on the thermal history of the part, which is influenced by the process parameters and the amount of dissipated heat energy. In order to investigate these correlations, stainless steel 316L samples were produced under different thermal conditions and thoroughly characterized. Solid cuboids were built on a substrate plate at room temperature as well as on a preheated substrate plate. Subsequently, the influence of the different thermal conditions on the melt pool temperatures was evaluated, and the microstructures, the microhardness, and the tensile properties were analyzed. It was found that the mean melt pool temperatures and the primary dendrite arm spacing (PDAS) increased with the build height, while the cooling rates showed an inverse relationship with the build height. The determined PDAS values were correlated with the microhardness profile of the specimens using a Hall-Petch type relationship. An increased heat accumulation in the parts was thereby associated with a coarser microstructure and diminished mechanical properties. The presented results pave the way for tailoring the properties of additively manufactured components to specific requirements.