Scanning Velocity Research Articles

Synchronized Multi-Laser Powder Bed Fusion (M-LPBF) Additive Manufacturing: A Technique for Controlling the Microstructure of Ti–6Al–4V

One of the technological hurdles in the widespread application of additive manufacturing is the formation of undesired microstructure and defects, e.g., the formation of columnar grains in Ti-6Al-4V—the columnar microstructure results in anisotropic mechanical properties, a reduction in ductility, and a decrease in the endurance limit. Here, we present the potential implementation of a hexagonal array of synchronized lasers to alter the microstructure of Ti–6Al–4V toward the formation of preferable equiaxed grains. An anisotropic heat transfer model is employed to obtain the temporal/spatial temperature distributions and construct the solidification map for various process parameters, i.e., laser power, scanning speed, and the internal distance among lasers in the array. Approximately 55% of the volume fraction of equiaxed grains is obtained using a laser power of P = 500 W and a scanning speed of v = 100 mm/s. The volume fraction of the equiaxed grains decreases with increasing scanning velocity; it drops to 38% for v = 1000 mm/s. This reduction is attributed to the decrease in absorbed heat and thermal crosstalk among lasers, i.e., the absorbed heat is higher at low scanning speeds, promoting thermal crosstalk between melt pools and subsequently forming a large volume fraction of equiaxed grains. Additionally, a degree of overlap between lasers in the array is required for high scanning speeds (v = 1000 mm/s) to form a coherent melt pool, although this is unnecessary for low scanning speeds (v = 100 mm/s).

Hardening mechanism and thermal-solid coupling model of laminar plasma surface hardening of 65 Mn steel

In the present work, the laminar plasma surface hardening method is employed to enhance the service life of metal components fabricated from 65 Mn steel. The mechanical and wear behaviors of the laminar plasma surface hardened 65 Mn steel were analyzed. The martensite transition transformation of the temperature of the laminar plasma-hardened 65 ferrite Mn steel was determined by a thermal-solid coupling model. Based on the orthogonal experimental results, the optimal hardening parameters were confirmed. The scanning velocity, quenching distance and arc current are 130 mm/min, 50 mm and 120 A, respectively. The pearlites and ferrites are transformed into martensites in the hardened zone, while the ratio of martensite in the heat-affected zone decreases with the increase in the hardening depth. Compared to the untreated 65 Mn steel, the average hardness increases from 220 HV0.2 to 920 HV0.2 in the hardened zone and the corresponding absorbed power increases from 118.7 J to 175.5 J. At the same time, the average coefficient of friction (COF) decreases from 0.763 to 0.546, and the wear rate decreases from 5.39×10−6 mm3/(N·m) to 2.95×10−6 mm3/(N·m), indicating that the wear resistance of 65 Mn steel could be significantly improved by using laminar surface hardening. With the same hardening parameters, the depth and width of the hardened zone predicted by the thermal-solid coupling model are 1.85 mm and 11.20 mm, respectively, which are in accordance with the experimental results; depth is 1.83 mm and width is 11.15 mm. In addition, the predicted hardness distributions of the simulation model are in accordance with the experimental results. These results indicate that the simulation model could effectively predict the microstructure characteristics of 65 Mn steel.

Dual-Function Femtosecond Laser: β-TCP Structuring and AgNP Synthesis via Photoreduction with Azorean Green Tea for Enhanced Osteointegration and Antibacterial Properties.

β-Tricalcium phosphate (β-TCP) is a well-established biomaterial for bone regeneration, highly regarded for its biocompatibility and osteoconductivity. However, its clinical efficacy is often compromised by susceptibility to bacterial infections. In this study, we address this limitation by integrating femtosecond (fs)-laser processing with the concurrent synthesis of silver nanoparticles (AgNPs) mediated by Azorean green tea leaf extract (GTLE), which is known for its rich antioxidant and anti-inflammatory properties. The fs laser was employed to modify the surface of β-TCP scaffolds by varying scanning velocities, fluences, and patterns. The resulting patterns, formed at lower scanning velocities, display organized nanostructures, along with enhanced roughness and wettability, as characterized by Scanning Electron Microscopy (SEM), optical profilometry, and contact angle measurements. Concurrently, the femtosecond laser facilitated the photoreduction of silver ions in the presence of GTLE, enabling the efficient synthesis of small, spherical AgNPs, as confirmed by UV-vis spectroscopy, Transmission Electron Microscopy (TEM), and Fourier Transform Infrared Spectroscopy (FTIR). The resulting AgNP-embedded β-TCP scaffolds exhibited a significantly improved cell viability and elongation of human bone marrow mesenchymal stem cells (hBM-MSCs), alongside significant antibacterial activity against Staphylococcus aureus (S. aureus). This study underscores the transformative potential of combining femtosecond laser surface modification with GTLE-mediated AgNP synthesis, presenting a novel and effective strategy for enhancing the performance of β-TCP scaffolds in bone-tissue engineering.

Crack analysis in laser powder bed fusion-fabricated 2195 Al-Li alloy: An in-depth examination of influential variables

Laser powder bed fusion (LPBF) of high-strength 2195 Al-Li alloys offers significant industrial potential, yet the process is hindered by a high susceptibility to hot cracking. This study systematically investigates the hot cracking mechanisms and the key processing parameters influencing crack formation in LPBF-fabricated 2195 Al-Li alloys. Extensive experimental analysis revealed that crack density is significantly affected by scanning velocity and laser power, with scanning velocity identified as the most critical factor through a neural network model and a crack susceptibility model. The study demonstrates that achieving crack-free samples requires extremely low scanning velocities, as higher velocities exacerbate crack formation, particularly at high-angle grain boundaries (HAGBs). The findings also highlight the limitations of preheating in reducing crack susceptibility, emphasizing the importance of precise control over processing parameters to mitigate cracking in LPBF-fabricated 2195 Al-Li alloys.

تأثير استعمال ليزر النيوديميوم ياك (Nd-YAG) على البنية الدقيقة وصلابة سطح الفولاذ AISI1012

The unique characteristics of the laser beam such as directionality, monochromaticity, and brightness make it a very important tool in the surface treatment engineering. The concentrated heat in the laser beam can be precisely directed toward the processed region on the surface. The laser beam power, beam size, and scanning velocity are easily controlled during the different processing methods. Laser surface modifications of metallic materials, such as laser surface melting, laser surface alloying, and laser cladding are some of the most important methods to improve the mechanical properties of the processed layer on the surface. A pulsed Nd-YAG laser surface melted specimens of low carbon steel with a maximum power of 90W at different processing parameters. The rapid melt and solidification of the treated layer produced a refinement in the microstructure. The original microstructure of this steel (Ferrite + Pearlite) has been transformed to new phases of martensitic and bainitic structures. The melted layer consists of the melted pool, the heat affected zone, and the substrate. The maximum hardness of the laser melted layer is more than 400 HV. The effect of different lasers such as high power CW CO2 laser on the mechanical properties and corrosion resistance of steel alloys will be carried out in future studies. Keywords: Nd-Yag Laser, Laser surface treatment, Microstructure and hardness of AISI1012 steel

On microstructure development during laser melting and resolidification: An experimentally validated simulation study

Integrating experiment and simulation provides invaluable insights into the critical parameters that determine the microstructure of alloys produced by additive manufacturing. Here, the grain structure formation due to solidification during single pass laser scans (mimicking bead-on-plate single tracks) on a 316L stainless steel is studied in situ inside a scanning electron microscope that is directly integrated with a continuous-wave laser. The grain size distribution before melting is used as an initial condition in a coupled phase-field/thermal multiphysics modeling framework. The predicted resolidified microstructures are found to agree favorably with those observed experimentally for multiple laser powers and scan velocities, indicating the validity of the overall model. Grain morphology is analyzed quantitatively, and the top surfaces are compared between the experiments and simulations. Analysis of the three-dimensional grain shapes predicted by the simulations shows that the length of the major axis of the resolidified grains is sensitive to laser power and scan speeds, while the length of the minor axis is not. Furthermore, the preferential alignment of the major axes of the grains depends on the melt pool geometry.

Statistical modeling and optimization of clad geometry in laser cladding of Amdry 365 on Hastelloy X superalloy with response surface methodology

The aim of this study is to statistically investigate and optimize the laser cladding process of Hastelloy X superalloy using NiCoCrAlY powder (Amdry 365). In this study, response surface methodology was used to investigate the influence of laser input variables such as scanning velocity, laser power, and duty cycle on the clad geometry (including height, width, and angle) and dilution ratio. The results indicate that with increasing duty cycle and laser power, the clad width increases significantly, while the clad height increases slowly. However, increasing the scanning velocity leads to a decrease in the width and height of the clad. Furthermore, the clad angle and dilution ratio increase with increasing input parameters. The results of variance analysis shows that laser scanning velocity had the most significant impact on clad height, angle and dilution ratio, while laser power had the greatest influence on clad width. The laser power of 321.3 W, the scanning velocity of 6.3 mm/s and the duty cycle of 76 % proved to be the optimal input parameters. An experimental test was carried out to validate the optimal conditions based on the optimization responses. The validation results show that the developed models are able to describe the responses with an accuracy of less than 9 % error. The EDS analysis performed in the cladding zone of the optimum specimen showed the presence of the β phase in the dendritic region and the γ phase in the interdendritic region.

Impact of melt pool geometry variability on lack-of-fusion porosity and fatigue life in powder bed fusion-laser beam Ti–6Al–4V

Powder bed fusion-laser beam (PBF-LB) parts experience a significant decline in fatigue performance when process-induced defects are present. In this work, a decline in 4-point bend fatigue life was observed in PBF-LB Ti–6Al–4V coupons fabricated at constant power with increasing scanning velocity and which underwent subsequent stress relief and surface machining. Specifically, the presence of pores that resemble lack-of-fusion (LoF) and a decline in fatigue life were observed at scanning velocities lower than that expected from prior published work. It was hypothesized that this unexpected presence of LoF pores resulted from melt pool geometry variability that was not considered in prior work when the LoF criterion was implemented. Further, these pores can be small in size and infrequent in their occurrence when the melt pool geometry variability is not severe. Such sparse pores are challenging to characterize using conventional 2D characterization methods. This work leverages tall and narrow coupon geometry and high-resolution X-ray micro computed tomography (X-μCT) to capture LoF porosity. The results show that a modified melt pool overlap-based LoF criterion considering melt pool geometry variability captures the unexpected occurrence of LoF pores observed in X-μCT. In addition, the LoF percent metric displays a strongly negative correlation with fatigue performance. The insights from this work provide guidance on characterizing melt pool geometry variability across scan lines to systematically evaluate processing parameters that generate LoF pores, which, in turn, could lower fatigue performance.

Analysis of co-relation on LPBF process parameter on wear characteristics of Cu-Cr-Zr alloy

Copper alloy bearings, gears, and fasteners have a significant impact on industrial sectors. However, due to the defect formation and void generation during the manufacturing of copper alloy parts using (Laser Powder Bed Fusion) LPBF technique, the wear resistance of the copper alloy was significantly affected. Hence, the prime novelty of the current research is enhancing wear resistance by analyzing the interaction of combined LPBF parameters. In order to decrease cavity forms and reduce the wear rate of the printed Cu alloy components, the important LPBF process parameters such as Scan Velocity (SV) of 550, 750, and 950 mm s−1, Laser Power (LP) of 460, 540, and 620 W, and Re-melting Range (RR) of 5, 25, and 45% were selected and studied. The results of the experimental investigation were supported by the use of Grey Relation Analysis (GRA). A comparative study was conducted with five distinct parameter combinations to investigate the relative influence of each parameter on the relative density, wear rate and elastic modulus. The research findings verify that the application of optimal SV of 750 mm s−1 and RR of 45% with maximum LP of 460 W resulted in the maximum relative density of 99.91%, minimal wear rate of 0.52 × 10−5 mm3/Nm, and maximum elastic modulus of 140.22 GPa.

Multiphoton Lithography of Interpenetrating Polymer Networks for Tailored Microstructure Thermal and Micromechanical Properties.

Multiphoton lithography (MPL), an emerging truly 3D microfabrication technique, exhibits substantial potential in biomedical applications, including drug delivery and tissue engineering. Fabricated micro-objects are often expected to undergo shape morphing or bending of the entire structure or its parts. Furthermore, ensuring precise property tuning is detrimental to the realization of the functionality of MPL microstructures. Herein, novel MPL materials based on interpenetrating polymer networks (IPNs) are presented that effectively combine the advantages of acrylate and epoxy systems. IPNs with varying component ratios are investigated for their microfabrication performance and structural integrity with respect to thermal and micromechanical properties. A variety of high-resolution techniques is applied to comprehensively evaluate IPN properties at the bulk, micron, and segmental levels. This study shows that the MPL laser scanning velocity and power, photoinitiator content, and multi-step exposure can be used to tune the morphology and properties of the IPN. As a result, a library of 3D MPL IPN microstructures with high 3D structural stability and tailored thermal and micromechanical properties is achieved. New IPN microstructures with Young's moduli of 3-4MPa demonstrate high-to-fully elastic responses to deformations, making them promising for applications in morphable microsystems, soft micro-robotics, and cell engineering.

A planar plume array emanating from an atmospheric pressure argon plasma jet employing floating electrodes

Large-scale plasma plumes downstream of plasma jets are in urgent need from a practical viewpoint. In this Letter, an argon plasma jet with floating electrodes is proposed to produce a large-scale planar plume array. Results indicate that with increasing peak voltage (Vp), the planar plume array elongates gradually and scales up in the lateral direction to an optimal value of 90.0 mm. There is only one discharge pulse per voltage half cycle, whose intensity and duration increase with increasing Vp. Moreover, there is a time lag between the initiations of individual plumes. Fast photography reveals that the planar plume array originates from the repeated process of some micro-discharge filaments stretching along the argon stream. By optical emission spectroscopy, the spatial distribution of plasma parameters is obtained, such as electron density, electron temperature, and gas temperature. At last, the planar plume array is employed to test the surface modification of polyethylene terephthalate, for which a uniform modification has been realized with a scan velocity of 1.0 cm/min. These results are of great significance for the development of large-scale atmospheric pressure plasma sources.

An experimental process parameter study on the identification of defects in additively fabricated Al6061 with laser powder bed fusion

Additively fabricated metal parts using laser powder bed fusion (L-PBF) possess sophisticated morphology due to the recurrent use of laser-induced metal powder melting and solidification. The surface and 3D morphology of these parts often include defects in the form of protrusions, depressions, pores, voids, keyholes, or cracks that are known to be influenced by laser scanning paths and layer-to-layer processing. Such inconsistent part quality hampers the extensive adoption of L-PBF. Pores and cracks are detrimental to the fatigue life of the parts and components. Quantifying and controlling part defects and optimizing processing and scanning strategy parameters adaptively in real-time through in situ monitoring systems are highly desired. This study investigates the optimization of experimental process parameters (power, scan velocity, and hatch spacing) and their effects on the cracking and porosity of Al6061 alloy using machine learning techniques. Multi-objective optimization is formulated and conducted to determine the L-PBF parameters that minimize both porosity and crack densities.

Experimental investigations on influence of processing parameters on the microstructure and properties of AM-printed stainless steel

ABSTRACT The current study has investigated the mechanical properties and microstructure of the DMLS processed 316L experimentally by varying process parameters and solution annealing as a post-processing technique. The feedstock material characteristics, laser power input, layer thickness, scanning velocity, hatch spacing, and building direction are important factors to consider. The modified microstructure not only affects mechanical performance and corrosion resistance but also alters the specimen's properties. An analysis of the powder feedstock and density measurement has been conducted. The samples were subjected to tensile testing, hardness testing, and microstructural analysis. According to the Taguchi analysis findings, the most significant parameter affecting product quality was layer thickness. The observation of grain boundary precipitation in a few samples could be reversed through solution annealing. The results of this study will assist in determining the optimal process parameters for achieving the desired mechanical properties.

Process mapping and anomaly detection in laser wire directed energy deposition additive manufacturing using in-situ imaging and process-aware machine learning

This work concerns the laser wire directed energy deposition (LW-DED) additive manufacturing process. The objectives were two-fold: (1) process mapping – demarcating the process states as a function of the processing parameters; and (2) process monitoring – detecting process anomalies (instabilities) using data acquired from an in-situ meltpool imaging sensor. The LW-DED process enables high-throughput, near-net shape manufacturing. Without rigorous parameter control, however, LW-DED often introduces defects due to stochastic process drifts. To enhance scalability and reliability, it is essential to understand how LW-DED parameters affect processing regimes, and detect deleterious process drifts. In this work, single-track experiments were conducted over 128 combinations of laser power, scanning velocity, and linear mass density. Four process states were observed via high-speed imaging and delineated as stable, dripping, stubbing, and incomplete melting regimes. Physically intuitive meltpool features were used to train simple machine learning models for classifying the process state into one of the four regimes. The approach was benchmarked against computationally intense, black-box deep machine learning models that directly use as-received meltpool images. Using only six intuitive meltpool morphology and intensity signatures, the approach classified the LW-DED process state with statistical fidelity approaching 90 % (F1-score) compared to F1-score 87 % for deep learning models.

Uniformity optimization of galvanometric illumination

Dual-axis galvanometer is used as a common beam steering component in diverse illumination and imaging approaches. In this paper, we propose an uncorrelated uniform illumination approach based on dual-axis galvanometric scanning. Specially, we analyze the mechanism of galvanometric illumination and elucidate three main factors affecting its uniformity properties. In this illumination module, the laser beam is deflected rapidly by the galvanometer which is driven by triangular voltage signals, and then focused by an f-θ lens to illuminate the object at an equal lateral scanning velocity. This method has lower coherent noise than extended laser illumination, higher brightness than partial coherent illumination and higher uniformity than galvanometric Lissajous trajectory driven by sinusoidal signals.

Numerical Investigation of the Effects of Process Parameters on Temperature Distribution and Cladding-Layer Height in Laser Cladding

To delve into the effects of process parameters on temperature distribution and cladding-layer height in laser cladding, as well as the interaction between these two aspects, a thermal–fluid coupling numerical model was established considering process parameters (i.e., laser power and scanning velocity), the Marangoni effect, molten pool dynamics, and solid–liquid transition. The numerical findings indicate that the Marangoni effect is the main factor for the growth of the cladding layer. The cladding-layer height increasingly influences heat-transfer efficiency as it develops. Higher laser power or lower scanning velocity, or a combination of both, can lead to higher cladding temperatures and greater cladding-layer height. Under the combination of laser power of 1750 W and scanning velocity of 4 mm/s, the numerical simulation predicts a cladding-layer height of 1.12 mm, which closely aligns with the experimentally determined height of 1.11 mm. Additionally, the comprehensive error being below 5% demonstrates the model’s considerable instructional value for practical applications.

Multi-fidelity surrogate with heterogeneous input spaces for modeling melt pools in laser-directed energy deposition

Multi-fidelity (MF) modeling is a powerful statistical approach that can intelligently blend data from varied fidelity sources. This approach finds a compelling application in predicting melt pool geometry for laser-directed energy deposition (L-DED). One major challenge in using MF surrogates to merge a hierarchy of melt pool models is the variability in input spaces. To address this challenge, this paper introduces a novel approach for constructing an MF surrogate for predicting melt pool geometry by integrating models of varying complexity, that operate on heterogeneous input spaces. The first thermal model incorporates five input parameters i.e., laser power, scan velocity, powder flow rate, carrier gas flow rate, and nozzle height. In contrast, the second thermal model can only handle laser power and scan velocity. A mapping is established between the heterogeneous input spaces so that the five-dimensional space can be morphed into a pseudo two-dimensional space. Predictions are then blended using a Gaussian process-based co-kriging method. The resulting heterogeneous multi-fidelity Gaussian process (Het-MFGP) surrogate not only improves predictive accuracy but also offers computational efficiency by reducing evaluations required from the high-dimensional, high-fidelity thermal model. The tested Het-MFGP yields an R2 of 0.975 for predicting melt pool depth. This surpasses the comparatively modest R2 of 0.592 achieved by a GP trained exclusively on high-dimensional, high-fidelity data. Similarly, in the prediction of melt pool width, the Het-MFGP excels with an R2 of 0.943, outshining the GP's performance, which registers a lower R2 of 0.588. The results underscore the benefits of employing Het-MFGP for modeling melt pool behavior in L-DED. The framework successfully demonstrates how to leverage multimodal data and handle scenarios where certain input parameters may be difficult to model or measure.

Double laser two-step process for creating interconnected frame microstructures' superhydrophobic surface with dual scales

Superhydrophobic surfaces have garnered significant attention for their unique wettability and extensive applications across various critical fields. In this paper, a two-step laser processing technique, involving infrared nanosecond laser patterning and ultraviolet picosecond laser surface modification, was employed to fabricate interconnected frame surfaces with dual-scale microstructures on Ti6Al4V substrates. After that, the microstructure surface was chemically modified with 1H,1H,2H,2H-perfluorodecyl trimethoxy-silane to achieve a superhydrophobic surface. An L32 (47) orthogonal experiment was used to analyze the effect of seven main factors (including the structure size, scanning velocity and the fluence, number of scans of infrared nanosecond laser and ultraviolet picosecond laser) on the wettability of the interconnected frame microstructures surface. After optimization, the surface strongly corresponded with the Cassie-Baxter model and demonstrated a water contact angle of 153.22±1.64° and roll-off angle of 4.43±1.70°. The experiments demonstrated that the optimized surface possesses excellent mechanical stability and corrosion resistance. Additionally, the optimized surface exhibits anti-adhesion, effective self-cleaning, and anti-fouling properties, which hold promise for addressing issues of liquid adhesion and dust pollution in industrial machinery.

Dynamic Characterization of Equatorial Plasma Bubble Based on Triangle Network‐Joint Slope Approach

AbstractThis paper introduces a Triangle Network‐Joint Slope (TN‐JS) approach to characterize the spatial and temporal dynamics of Equatorial Plasma Bubbles (EPBs) during geomagnetic storms. To collaboratively determine the EPB drift directions from multiple stations, a Delaunay triangle network is constructed, utilizing the distribution of Ionospheric Piercing Points (IPPs). The Time Difference of Arrival (TDOA) is extracted through cross‐correlating the Rate of Total Electron Content (ROT). The EPB drift direction can be approximately calculated by considering TDOA and IPP distances within each individual triangle of the network. This calculation is then refined through a joint statistical analysis. Using a reference station as the origin, the remaining stations within the network are projected along the estimated EPB drift direction. A spatial‐temporal color map illustrating regional ionospheric anomaly ROT observations is constructed. The EPB drift velocity among multiple stations can be collectively estimated by fitting the slope of this map, facilitating outlier exclusion. Accounting for satellite dynamic effects and the diverse orbit characteristics of GPS and BDS, corresponding IPP scan velocity compensation is performed and analyzed for EPB dynamic estimation. Using the geomagnetic storm event that occurred on September 8 as a case study, the spatial‐temporal kinetic properties of EPBs is characterized by analyzing Global Navigation Satellite System (GNSS) observations from 17 Hong Kong monitoring stations with the proposed TN‐JS approach. The results indicate during this magnetic event, that EPBs exhibit a westward drift trend with velocities ranging from a few tens to hundreds of meters per second in GPS and BDS observations.

Prediction of Femtosecond Laser Etching Parameters Based on a Backpropagation Neural Network with Grey Wolf Optimization Algorithm.

Investigating the optimal laser processing parameters for industrial purposes can be time-consuming. Moreover, an exact analytic model for this purpose has not yet been developed due to the complex mechanisms of laser processing. The main goal of this study was the development of a backpropagation neural network (BPNN) with a grey wolf optimization (GWO) algorithm for the quick and accurate prediction of multi-input laser etching parameters (energy, scanning velocity, and number of exposures) and multioutput surface characteristics (depth and width), as well as to assist engineers by reducing the time and energy require for the optimization process. The Keras application programming interface (API) Python library was used to develop a GWO-BPNN model for predictions of laser etching parameters. The experimental data were obtained by adopting a 30 W laser source. The GWO-BPNN model was trained and validated on experimental data including the laser processing parameters and the etching characterization results. The R2 score, mean absolute error (MAE), and mean squared error (MSE) were examined to evaluate the prediction precision of the model. The results showed that the GWO-BPNN model exhibited excellent accuracy in predicting all properties, with an R2 value higher than 0.90.