316L Stainless Steel Samples Research Articles

Void swelling in additively manufactured 316L stainless steel with hafnium composition gradient under self-ion irradiation

Compositionally-graded austenitic 316L stainless steel (SS) samples with five different Hafnium (Hf) concentrations (up to 1 wt.%) were additively manufactured by directed energy deposition and then were irradiated using 5 MeV Fe2+ ions to 50 displacements per atom (dpa) at 500, 550, and 600 °C, respectively. A rastering beam was used to ensure homogenous irradiations for the large areas of ∼1.40 cm2. Composition-dependent void evolution was evaluated. Void size, void number density, and void swelling all tend to decrease with increasing Hf concentration at all three temperatures. When the nominal Hf concentration increases to 1 wt.% in the doped additively manufactured (AM) 316L SS, the void swelling is over an order of magnitude lower than that in pure AM 316L. Atom probe tomography results showed that about 0.14 wt.% Hf dissolved in the matrix at the 1 wt.%. Hf nominal concentration. The suppression of void swelling by Hf addition shows qualitative agreement with the numerical calculation based on the vacancy trapping mechanism, indicating that the oversized Hf reduces the steady state vacancy concentration, and hence the incubation period of swelling is extended, resulting in a dramatic difference in void swelling. Other factors including grain boundaries, dislocation and dislocation cells, Hf-rich particles, and delta ferrite are secondary to this mechanism. This work shows that additive manufacturing enabled microalloying is promising for developing void swelling resistant materials.

Investigation of Causal Relationships between Printing Parameters, Pore Properties and Porosity in Laser Powder Bed Fusion

This work reports on employing X-ray computed tomography (XCT) and optical microscopy to investigate the causal relationships between printing parameters, pore properties, and porosity in 316L stainless steel samples additively manufactured by Laser Powder Bed Fusion (LPBF). The porosity is very similar for both investigation methods. XCT provides more accurate results for large lack of fusion pores, while optical results are more accurate for small keyhole pores. These results were employed to develop mathematical models to determine how printing parameters influence pore properties and overall porosity. The developed optical and XCT mathematical models reveal that power is the most significant factor affecting pore properties and overall porosity. Pore number and mean diameter decrease and sphericity increases with increasing power. Overall porosity is negatively correlated with power, indicating that the higher the power, the lower the overall porosity. Attention should also be paid to the quadratic effects of power, velocity and hatch spacing on porosity, revealing an inverse change in porosity after a certain threshold. Power interacts with velocity and hatch spacing, suggesting that changes in power affect the influence of velocity and hatch spacing on porosity, and vice versa. The interaction of velocity and hatch spacing is not significant. Both models successfully predicted optimal printing parameter sets as validated by experimental measurements.

An optimized single-crystal to polycrystal model of the neutron transmission of textured polycrystalline materials

The attenuation coefficient of textured materials presents a complex dependence on the preferred orientation with respect to the neutron beam. Presented here is an attenuation coefficient model to describe textured polycrystalline materials, based on a single-crystal to polycrystalline approach, aiming towards use in full-pattern least-squares refinements of wavelength-resolved transmission experiments. The model evaluates the Bragg contribution to the attenuation coefficient of polycrystalline materials as a combination of the Bragg-reflected component of a discrete number of imperfect single crystals with different orientations, weighted by the volume fraction of the corresponding component in the orientation distribution function. The proposed methodology is designed to optimize the number of single-crystal orientations involved in the calculation, considering the instrument resolution and the statistical uncertainty of the experimental transmission spectra. The optimization of the model is demonstrated through its application to experiments on calibration samples presenting random crystallographic textures, measured on two imaging instruments with different resolutions. The capability of the model to simulate textured samples in different orientations is shown with a copper sample used as a reference in texture studies of archaeological objects and a 316L stainless steel sample produced by laser powder-bed fusion. The ability of the model to predict the attenuation coefficient of polycrystalline textured materials on the basis of a reduced number of texture components opens the possibility of including it in a least-squares fitting routine to perform crystallographic texture analysis from wavelength-resolved transmission experiments.

Productivity Enhancement in Directed Energy Deposition: The Oscillating Scanning Strategy Approach

Directed Energy Deposition (DED) is an additive manufacturing process that enables the production of large metal components by melting the feedstock material while being deposited. An improvement of the production speed of this process would further increase its applicability in many industrial fields. The DED building rate is strictly related to the building parameters adopted, in particular to the laser spot diameter, which also affects the build accuracy and the surface quality of the components. The possibility of using a variable laser spot would result in a significant increase in the production rate in bulky zones, while also providing a good surface quality where needed. In the present work, an oscillating scanning strategy was used to create a large apparent laser spot (+ 170% of the nominal value) to produce 316L stainless steel samples via DED. The optimisation of the DED parameters with the oscillating strategy was performed using the single scan tracks (SSTs) approach. The morphologies of the SSTs obtained with different process parameters were assessed and the geometrical features related to the melt pools were analysed in order to select the most suitable X and Z displacements for the production of the cubic samples. The analyses of the cubes revealed that, if the correct overlap among nearby scans is selected, it is possible to obtain dense samples with all the oscillating diameters tested. Finally, comparing the building rate and powder efficiency values confirmed that this method can accelerate the building process and improve its overall performance.Graphical

A comprehensive investigation on application of machine learning for optimization of process parameters of laser powder bed fusion-processed 316L stainless steel

Metal 3D printing has gained a lot of attention among industries since it offers a practical solution to problems rising during the manufacturing of parts and components with complex geometry. This is an additive technology that eliminated several fabrication steps and at the same time reduces material waste during the manufacturing process. However, in all additive manufacturing technologies, the final properties of the parts are determined by the operational process parameters. In this study, several machine learning algorithms were examined to characterize the effects of the printing process parameters on relative density, hardness, yield strength, and tensile strength in manufactured parts. It was possible by using “Big Data” collected from a large number of previously published articles on the application of laser powder bed fusion (LPBF) for the 3D printing of 316L stainless steel samples. Among different process parameters, laser power, laser energy density, and scanning speed were proven to have the largest effects directly on the physical and mechanical properties of LPBF-processed parts. Six different classification models and five support vector machine regression-based models were tested to find the most accurate prediction algorithm. To validate the obtained results from the applied machine learning models, a set of 316L specimens were produced using LPBF technology using a random set of process parameters. The physical and mechanical properties of 3D printed samples were tested and compared to the ones predicted from the optimum models from machine learning analysis. The results were in great agreement, which shows the high accuracy of the developed machine learning algorithms in this study.

The role of heat treatments on wear behaviour of 316L stainless steel produced by additive manufacturing

• 316L samples were produced by Additive Manufacturing method. • Heat treatment was applied to the samples to examine the microstructure changes. • Heat treatments were found to affect the wear behavior of the samples. • The wear rate is reduced by heat treatment at 650 °C. • Increased heat treatment temperature deteriorates wear resistance. In this study, 316L stainless steel (SS) samples were produced using Direct Laser Metal Sintering (DMLS) method with standard parameters. Specimens were heat-treated at 650, 950, and 1150 °C for 2 h following the DMLS process. Effects of the heat treatments on the properties of DMLS parts were examined by microstructure, hardness, and wear tests. Microstructural properties were investigated by scanning electron microscopy (SEM), X-ray diffraction (XRD), and energy-dispersive X-ray (EDX) analysis. Hardness changes were determined by the Vickers hardness (HV) method. The results showed that the as-built microstructure of DMLS/316L SS deteriorated with the increase in heat treatment temperature. Moreover, heat treatment processes caused a decrease in hardness and wear resistance.

Predictive model to design for high cycle fatigue of stainless steels produced by metal additive manufacturing

This work develops a predictive model of S–N curves capable of proving the lower and upper bounds for fatigue behaviour of parts fabricated using different metal laser-based additive manufacturing (AM) and post-processing technologies. Alongside the ultimate strength of the material and its endurance limit, a surface factor and a defect factor are incorporated in the model to consider the effects of the AM process induced defects on the S–N curves. The model is correlated to comprehensive load-controlled fatigue experimental data from the literature for 316L stainless steel (SS) samples manufactured using metal laser-based AM technologies of various process and post-process conditions. It was demonstrated that the proposed model can capture and represent the effects of the induced defects as well as the mean stress effect. The value of the proposed model is that it can be integrated into existing industrial design workflows for fatigue assessment of AM 316L SS. Furthermore, it has the potential to be extended to other AM materials.

Origin, parameters, and underlying deformation mechanisms of propagating deformation bands in irradiated 316L stainless steel

Lüders-type propagating deformation bands were observed in specimens of irradiated 316L stainless steel samples removed from Spallation Neutron Source target vessels after service. Mechanical testing with digital image correlation (DIC) and in-situ tensile testing with scanning electron microscopy electron backscatter diffraction showed that the observed Lüders-type behavior was not related to the known transformation-induced plasticity or twinning-induced plasticity behavior. Instead, the phenomenon occurs at small local strain values before a significant amount of martensite or deformation twins appear in the microstructure. Microstructural analysis and in-situ mechanical test results suggest Lüders-type band formation and propagation were related to the appearance and evolution of defect-free channels—analogous to slip bands. A modified Swift equation with a Ludwigson-like component was offered to rationalize the phenomenon and model the strain-softening processes at small strain values. The results indicate complex microstructural processes and deformation mechanisms were active at small strain values and underline the benefits of advanced mechanical test approaches such as DIC.

Heat Treatment, Microstructure and Corrosion Relationship on 316L SS Produced by AM

ABSTRACT In this study, 316L stainless steel (SS) samples produced with standard parameters using the Additive Manufacturing method were heat treated with different parameters, and the effects of heat treatment on the microstructure, phase changes, hardness, porosity, and corrosion of the material were examined in detail. The results showed that the as-built microstructure of 316L stainless steel material produced by Additive Manufacturing deteriorated as the heat treatment temperature increased and the hardness decreased. The corrosion resistance of the material increased. The best corrosion resistance was obtained from heat treatment at 1150°C for 2 h.

(Digital Presentation) Comparison of Electrochemical Measurements to Atmospheric Corrosion Experiments on Additively Manufactured 316L

As interest in the commercial implementation of additively manufactured (AM) metal components increases, so does the need to understand the corrosion behavior of these materials. AM metals deviate in microstructure and surface quality from traditionally processed metals which impacts their corrosion properties. Currently there are no studies investigating the variation in corrosion behavior for AM components printed on different machines. This work compares the breakdown potential, an indication of stable pit growth and the loss of passivity, from 316L stainless steel samples printed on several machines. A correlation between breakdown potential and the surface microstructure, unique to parts printed on different machines, will be discussed. Additionally, the electrochemical measurements are correlated with salt fog experiments. Finally, pit morphology from accelerated atmospheric corrosion exposures (salt fog and constant humidity/contamination lab exposures) are compared to a real-world exposure (coastal environment) of AM 316L. SNL is managed and operated by NTESS under DOE NNSA contract DE-NA0003525. SAND2022-4063 A

Ultrasonic methods for the characterization of additively manufactured 316L stainless steel

This research utilizes linear and nonlinear ultrasonic techniques to establish a linkage between microstructure and macroscale mechanical properties of additively manufactured (AM) stainless steel 316L samples. The specimens are manufactured using two methods: laser-powder bed fusion and traditional wrought manufacturing. Using the nonlinear ultrasonic method of second harmonic generation, the acoustic nonlinearity parameter is estimated in samples with different heat treatment levels intended to alter microstructural and mechanical properties. Linear ultrasonic parameters including wave speed and resonant frequency are additionally measured. Mechanical properties are obtained through tensile testing of coupons corresponding to the test samples. Microstructural information for the samples is obtained using electron backscatter diffraction to help elucidate the relationships between microstructure, mechanical properties, and ultrasonic response. Results indicate correlations between the nonlinearity parameter and both ultimate tensile strength and yield strength, where nonlinearity generally decreases as sample strength increases, particularly in the AM samples. We hypothesize that microstructural evolution of grain characteristics across different heat treatments influences trends in measured nonlinearity, as well as substructures at smaller scales such as dislocations. These results show promising evidence for the feasibility of AM parts qualification using nondestructive nonlinear ultrasonic testing.

Eddy Current Testing of Artificial Defects in 316L Stainless Steel Samples Made by Additive Manufacturing Technology.

Additive manufacturing has many positives, but its incorporation into functional parts production is restricted by the presence of defects. Eddy current testing provides solutions for their identification; however, some methodology and measurement standards for AM (additive manufacturing) products are still missing. The main purpose of the experiment described within this article was to check the ability of eddy current testing to identify AM stainless steel parts and to examine the data obtained by eddy currents variation under the influence of various types of designed artificial defects. Experimental samples were designed and prepared with SLM (selective laser melting) technology. Artificial defects, included in the samples, were detected using the eddy current testing device, taking the important circumstances of this non-destructive method into account. The presented research shows significant potential for eddy current testing to identify defects in AM products, with a resolution of various types and sizes of defects. The obtained data output shows the importance of choosing the right measurement regime, excitation frequency and secondary parameters setup. Besides the eddy current testing conditions, defect properties also play a significant role, such as their shape, size, if they are filled with unmolten powder or if they reach the surface.

Synchronous-hammer-forging-assisted laser directed energy deposition additive manufacturing of high-performance 316L samples

Plastic-deformation-assisted method has positive effect on regulating microstructure and mechanical properties of additive manufacturing (AM) metal samples. However, when fabricating weakly rigid metal samples by laser directed energy deposition (LDED), there are great limitations in the applicability and process flexibility of the commonly used rolling deformation auxiliary methods, which needs to be further improved. In this study, a synchronous-hammer-forging-assisted laser directed energy deposition (SHLDED) method is developed, and the effect of synchronous-hammer-forging on the microstructure and mechanical properties of LDED-processed 316L stainless steel samples is investigated. The results show that large plastic deformation up to 21 % of deposited materials can be achieved using a small hammering force of 55 N. Compared with LDED sample, the microstructure of SHLDED sample shows obvious equiaxed grains and refinement effect. The maximum intensity of the pole figure decreases by 50 % and the average grain size decreases by 69 %. Owing to the combined effect of grain refinement and work hardening, the yield strength (YS), ultimate tensile strength (UTS), and microhardness of SHLDED sample reach 494 ± 19 MPa, 677 ± 7 MPa, and 243 ± 11 HV 0.2 , respectively, which are 41 %, 10 %, and 22 % higher than those of LDED sample. This study provides a new method for microstructure and mechanical properties regulation of LDED metal samples. • A synchronous-hammer-forging-assisted LDED device was developed. • 21 % large plastic deformation was achieved using small hammering force of 55 N. • The microstructure achieved 69 % grain refinement and 50 % anisotropy reduction. • The yield strength and tensile strength were improved by 41 % and 10 % respectively.

Plastic anisotropy evolution of SS316L and modeling for novel cruciform specimen

In this paper, the evolution of the plastic anisotropy of stainless steel 316L samples is investigated under proportional loading paths using a customized cruciform specimen. The determination of a novel cruciform specimen by a design of experiments approach integrated with finite element simulations is described. The mechanical properties of the material are characterized under uniaxial tension applied in every 15° from the rolling direction and equibiaxial tension from hydraulic bulge experiments. The results reveal that the plastic anisotropy shown in stress and strain significantly evolves with respect to the plastic work. Based on the experiments, the material behavior is modeled using a non-quadratic anisotropic yield function, Yld2004–18p, with parameters modeled as a function of the equivalent plastic strain, assuming plastic work equivalence, and with constant parameters for comparison. The Hockett-Sherby model is also used for the strain hardening behavior to extrapolate the results to higher strain values. The models are implemented into a user material subroutine for finite element simulations. To validate the model, in-plane biaxial tension experiments are performed, using a customized specimen, to achieve greater deformation than previous designs by introducing double-sided pockets for thickness reduction and notches in the corner areas. The results are compared with finite element simulations implemented with the plasticity models.

Formation mechanism of MnS inclusion during heat treatments and its influence on the pitting behavior of 316L stainless steel fabricated by laser powder bed fusion

The formation mechanism of MnS inclusions during heat treatment and its effect on the pitting behavior of laser powder bed fusion (L-PBF)-fabricated 316L stainless steel (SS) were investigated. MnS inclusions precipitated at the grain boundaries of the samples, and the spherical oxide particles can become nucleation sites. The quantity and size of the MnS inclusions increased with prolonged heating. Compared with the as-received sample, the pitting of heat-treated L-PBF-fabricated 316L SS samples was mainly induced by the newly generated MnS inclusions rather than the fabricated gas pores and extended along the grain boundaries; this caused the dramatic pitting resistance deterioration.

Application of nonlinear ultrasonic analysis for in situ monitoring of metal additive manufacturing

Nonlinear ultrasonic techniques have the benefit of high sensitivity to micro or early-stage defects. Among the various nonlinear techniques, the newly proposed sideband peak count (SPC) technique investigates defect-induced nonlinearity by counting the spectral sidebands from a broadband ultrasonic response in the frequency domain. In this study, SPC analysis is transformed into the time–frequency plane through synchrosqueezed wavelet transform (SWT) for transient nonstationary ultrasonic signals. The proposed new SPC technique was then adopted for in situ porosity monitoring in directed energy deposition (DED)—a typical metal additive manufacturing process. Porosity is one of the most critical defects in DED and has detrimental effects on the mechanical properties and fatigue performance of products. For in situ porosity monitoring, a fully noncontact ultrasonic measurement was achieved with a laser ultrasonic system, and its detectability was improved by laser polishing. Time and frequency windows were properly selected to suppress the effects of wave characteristic variations on the SPC analysis in the SWT domain. The performance of the proposed technique was verified by monitoring porosity in stainless steel 316L samples manufactured in the DED process. The test results demonstrated that the proposed nonlinear technique is much more sensitive to porosity than conventional linear techniques, and hence, is more suitable for in situ porosity monitoring.

Experimental investigation on the fatigue behavior of laser powder bed fused 316L stainless steel

Additive manufacturing of metal powder materials through Laser Powder Bed Fusion (LPBF) allows for a single-step fabrication process of complex geometries. However, the introduction of such an innovative technology opens new questions about the fatigue life of functional components especially intended for applications where the products are subjected to severe time-varying loading conditions. In this context, the present work aims at evaluating the fatigue strength of 316L stainless steel samples fabricated through laser powder bed fusion by controlling the building orientation and the volumetric energy density. The work at first presents the response of the LPBF fabricated samples to a monotonic tensile load for varying building orientations. It follows the presentation of their fatigue response to a reverse bending loading condition. Quasi-static tensile tests show that LPBF specimens have lower elastic modulus but higher ultimate and yield strength than the original bulk material, whereby the results evidence a strong anisotropy related to the building orientation. Porosity and building orientation are found to strongly affect the fatigue behavior, with the fatigue limit which lowers from 50% of the ultimate strength of the bulk material down to 20% for the LPBF-ed specimens. Finally, the observation of the failure surfaces suggests that the early fracture of the samples is due to the concomitant initiations of cracks at different sites that eventually coalesce and promote the failure.

In-situ study of microstructural evolution and strain distribution during single axis tension of 316L stainless steel prepared by selective laser melting

A combined digital image correlation (DIC) and electron backscatter diffraction (EBSD) study of the multi-scale strain distribution and microstructure evolution during tensile loading has been carried on 316L stainless steel samples prepared by selective laser melting (SLM). The initial material shows a range of microstructural heterogeneity. Macro- and micro-DIC results reveal a non-uniform distribution of plastic strain over several length scales, including the formation of localized slip-bands at the intra-grain level. No obvious correlation is found between the heterogeneity in plastic strain and either grain size, grain morphology or the orientation of the cellular structures formed during SLM. Intragranular orientation subdivision and the evolution of local misorientation have also been investigated by EBSD during tension, where a complex pattern of heterogeneity in both microstructure and plastic strain is found.

3D In-situ Stop Action Study of Recrystallization in Additively Manufactured 316L Stainless Steel: Reconstruction Optimization and Observations

A volume of an additively manufactured 316L stainless steel sample has been tracked during its recrystallization using near- and far-field High Energy Diffraction Microscopy (HEDM) and absorption tomography at Advanced Photon Source beamline 1-ID. A near-field compatible in situ furnace allows monitoring of Bragg diffraction signals as they evolve out of a weak and diffuse background while the sample temperature is ≈ 1250° C. The sample is rapidly cooled to room temperature after observation of significant signal evolution and ∼ 0.035 mm3 is mapped by the near-field method. Four cycles of heat treatment follow the structure from a state of small, isolated grains through impingement of domains to near completion of recyrstallization. Here, the experiment and reconstructions are described, and recrystallized fractions, twin domains, and distributions of grain boundary types are discussed.

Influence of Build Angle and Polishing Roughness on Corrosion Resistance of 316L Stainless Steel Fabricated by SLM Method.

Metal parts formed by laser additive manufacturing methods usually have large surface roughness, which affects the corrosion resistance of the parts. This study reported the reason for and mechanism of the large surface roughness of 316L stainless steel samples manufactured by selective laser melting (SLM) at different build angles. Through the study, the reason for the large top surface roughness (average surface roughness is 15.3 ) is due to the molten channel structure formed on the surface. The large side surface roughness (average surface roughness is 19.1 ) is due to the incomplete fused particles adhering to the surface. Through electrochemical experiments, the influence of the build angle and polishing treatment on the corrosion resistance of the sample was studied. The different roughness of the top and side surfaces results in different corrosion resistances (the top surface pitting potential is 0.317 and the side surface pitting potential is 0.148 ), and polishing can improve the surface corrosion resistance of specimens by reducing the surface roughness, especially for the side surface (from 0.148 to 0.351 ). Therefore, parts manufactured by SLM can be post-treated to reduce roughness and improve surface corrosion resistance.