Scanning Speed Research Articles

Data analysis and visualization of electric vehicle engineering

We have visualized data using Excel to understand the relationship between battery chemistries and capacity. Examined Python code for tuning a Proportional – Integral – Derivative (PID) controller to understand its role in improving control accuracy. The challenges and benefits of PID tuning are discussed, highlighting the importance of precise tuning for optimal performance, efficiency, and safety. Analysing the impact of various battery form factors, including cylindrical, pouch, and prismatic options, on system cost, safety, and durability. Furthermore, the paper explores design trade-offs in electric vehicle development, emphasizing the need for balancing competing parameters such as performance, durability, and cost-effectiveness. The characteristics of various battery form factors (cylindrical, pouch, and prismatic) and Light Detection and Ranging (LiDAR) sensors (mechanical, solid-state, and hybrid) are compared, providing insights into their suitability for different applications. Overall, this article offers a comprehensive overview of the intricate relationships between battery chemistries, PID controllers, and design trade-offs in the development of efficient and sustainable electric vehicles. Conducted a comprehensive cost-benefit analysis for different LiDAR sensor models, comparing mechanical scanning, solid-state, and hybrid LiDAR sensors, with a focus on durability, scanning speed, and cost implications. Beside the aforementioned, we have also presented technical findings in a concise format using tables, aiding the engineering division in making informed decisions for various projects.

The influence of selective laser melting (SLM) parameters on physical, and mechanical properties of AlSi10Mg cylindrical specimen

Abstract AlSi10Mg cylindrical specimens were fabricated using the Laser-based Powder Bed Fusion (L-PBF) process, focusing on optimizing scanning speed, hatch spacing, and layer height through the box-behnken design (BBD). The study aimed to minimize surface roughness and maximize relative density. The analysis involved ANOVA, regression analysis, and composite desirability, revealing that hatch spacing and layer height significantly influence relative density and surface roughness. Under optimized conditions (scanning speed: 500 mm s−1, hatch spacing: 100 microns, layer height: 30 microns), the L-PBF specimen achieved a 96.70% relative density, 2.07 microns surface roughness (Ra), and an average microhardness of 124.9 HV0.5 (longitudinal) and 120.5 HV0.5 (transverse).

Aging-Induced Microstructural and Property Changes in Direct Laser Energy Deposited NiCrFeSiBC Hardfacing Alloy Bushes

Abstract Wear resistant NiCrFeSiBC hardfacing alloy bushes for fast breeder reactor applications are fabricated through direct laser energy deposition (DLED) using CO2 laser with optimized parameters for laser power (2.5 kW), scan speed (4.2 mm/s), powder feed rate (4 g/min) and 60% of track to track overlap. DLED bushes have significantly different microstructure than weld deposited ones. As-deposited bushes have predominantly uniform fine dendritic solidification structure of γ-Ni + Ni3B, γ-Ni + Ni3B + Cr3C2 and Ni-B-Si eutectics with low volume fractions of Cr-rich borides and carbides. Microstructural heterogeneity is observed only in layer overlap regions characterized by coarsening of carbides that resulted in lower hardness (625 ± 11 HV0.1) compared to layer interiors (740 ± 19 HV0.1). Effect of aging at 550 °C on the microstructure and properties of the bushes is investigated using experimental and thermo-kinetic simulation techniques. Microstructure of the bushes remains stable without significant coarsening of the γ-Ni + Ni3B eutectic structures even after heat treatment for 4000 h. However, precipitation and coarsening behavior of Cr7C3 and Cr23C6 carbides are affected by aging which is reflected in the variation in hardness. Hardness of the bushes increases up to 100 h of aging due to the precipitation of fine Cr-rich carbides, and with increase in the duration of aging, carbides coarsen thereby reducing the hardness. Based on the study, it is concluded that direct laser energy deposited bushes may have better stability with respect to microstructure and properties at service temperatures.

Effect of Porosity on Tribological Properties of Medical-Grade 316L Stainless Steel Manufactured by Laser-Based Powder Bed Fusion

The potential of laser-based powder bed fusion (L-PBF) technology for producing functional components relies on its capability of maintaining or even improving the mechanical properties of the processed material. This improvement is associated with the microstructure resulting from the high thermal gradient and fast cooling rate. However, this microstructural advantage may be counterbalanced by the lack of full density, which could be tolerated to a certain degree for applications such as biomedical implants and medical equipment. In this study, medical-grade 316L stainless steel specimens with porosities ranging from 1.7 to 9.1% were additively manufactured by L-PBF using different combinations of laser power and scanning speeds. Tribological properties were evaluated by pin-on-disc testing in dry conditions against a silicon nitride test body and analyzed in the context of microstructural characterization by optical and electron microscopy. The results reveal that higher porosity allows for a diminishing wear rate, which is explained by the capacity of the pores to retain wear debris related with the three-body abrasion. This research provides practical insights into the design of medical wear-resistant components, thereby enhancing our understanding of the potential of L-PBF in the fields of materials science and biomedical engineering.

Investigation on multiple bending using laser forming of mild steel plate and its bend angle prediction

In manufacturing industries like shipbuilding, automotive, microelectronics, and aerospace, laser forming is a potential new technology. Laser forming is an intricate thermo-mechanical process in which the process mechanisms are determined by the temperature profile across the sheet thickness, which is influenced by laser power, scan speed, number of passes, laser beam diameter, and workpiece geometry. During the process, the material deforms because of compressive stress generated in the underneath region due to the thermal expansion of the irradiated region. This study focuses on the multiple bending and the effect of different process parameters on the laser bending of the sheet. Experiments were performed on 4 mm and 8 mm thick sheets of mild steel sheet of grade IS 2062 E250 using a 2-kW fiber laser with various influencing parameters such as power, scan speed, and laser spot diameter. Hardness and grain size measurements of laser-formed surfaces at different combinations of influencing parameters were performed and the features formed due to laser irradiation were analyzed. An artificial neural network (ANN) model is proposed to predict the bend angle value.

Micro-engraving on modified nickel-base superalloy using a short-pulsed laser source

ABSTRACT The modified nickel-base superalloy is micro-engraved with short pulsed laser with different parameter. The dimensional accuracy of the micro-profiles engraved through laser energy is evaluated through a scanning electron microscope. For the minimum speed of 50 mm per sec, the profile length and breadth have high dimensional stability compared to the average and high scan speed. The optical microscope is used to measure the depth of the micro-profile and the same has been metallurgically processed to read the microstructural changes. A maximum depth of 632 µm for the micro-profile is found with a maximum scan speed of 100 mm per sec at a low power of 2 watts and an average laser frequency of 7 kHz. Therefore, the input process parameters are invariant for the different responses on micro-engraving.

Multi-Physics Modeling in Curved Surface Laser Cladding: Impact of Scanning Trajectories and Cladding Parameters on Temperature Field and Coating Thickness

In order to apply laser cladding technology to the complex surface processing of hot-working dies, this study developed a numerical model for curved surface laser cladding along various scanning trajectories under multi-physics coupling considering the dynamics of the molten pool, cladding parameters (scanning speed and laser power), Marangoni effect, and solid–liquid phase transition. Utilizing this model and by altering cladding parameters, the temperature field and the variation in coating thickness along various scanning trajectories were studied as well as the interaction between the two. The following discoveries were made. Variations in scanning trajectories lead to differences in the coating thickness of curved surface laser cladding. Regardless of the combination of cladding parameters, the coating thickness of scanning from top to bottom is always less than that from bottom to top, with a difference of approximately 0.05 mm. The temperature field and coating thickness influence each other. The Marangoni effect induced by the temperature field is the primary cause of coating thickness growth, while the coating thickness affects thermal transfer from the thermal source, ultimately influencing the temperature field. Employing a greater laser power or a slower scanning speed, or a combination of greater laser power and slower scanning speed, can increase the coating thickness and its maximum temperature in curved surface laser cladding. The model, when contrasted with experimental data, exhibits a comprehensive discrepancy of 3.49%, signifying its high precision and practical engineering applicability.

Cold-Spray Deposition of Antibacterial Molybdenum Coatings on Poly(dimethylsiloxane).

Despite their widespread utilization in biomedical applications, these synthetic materials can be susceptible to microbial contamination, potentially compromising their functionality and increasing the risk of infection in patients. In this study, molybdenum (Mo), an essential metal in biological systems, was investigated as a Mo-based cold-sprayed coating on poly(dimethylsiloxane) (PDMS) for its potential use as biocompatible and antimicrobial surfaces for biomedical applications. Various cold-spray parameters were employed in the fabrication of Mo-embedded PDMS surfaces to alter the surface structure of the substrate, Mo loading density, and embedding layer thickness. Specifically, relatively low nozzle scanning speeds were used to develop high-density Mo-embedded PDMS surfaces. A comprehensive analysis was conducted to investigate how cold-spray processing parameters affect the surface topography, wettability, and chemical properties. The ability of the Mo-embedded PDMS to inhibit the colonization of Staphylococcus aureus, Staphylococcus epidermidis, Escherichia coli, and Pseudomonas aeruginosa bacterial species was demonstrated by both live/dead staining and disk diffusion methods. Surfaces with higher Mo loading densities significantly reduced the level of bacterial attachment and enhanced the bactericidal activity upon contact. Also, the level of Mo ion release over a 14-day period was measured and correlated to the properties of the substrate surface. Furthermore, attachment, viability, and proliferation of osteoblast-like MG63 cells were assessed to investigate the effect of Mo ion release on the biocompatibility of fabricated coatings. A notable decrease in cell viability and delayed growth of MG63 cells became evident after 7 days of incubation with the highly Mo-loaded samples. While this study enhanced our understanding regarding the engineering of composite materials for combatting microbial infections, the findings also suggest that the release of Mo ions may detrimentally affect osteoblast survival, potentially compromising the long-term functionality of orthopedic implants produced using this technique.

Wear and corrosion resistant iron-based amorphous coating in diluted biodiesel environment

Biodiesel is an eco-friendly source of energy that is synthesized from plant or animal-based oils and fats. However, the commercial use of biodiesel is limited due to its drawbacks such as auto-oxidation and moisture absorption, leading to accelerated corrosion of the metallic parts and degradation of wear resistance. In this work, a novel amorphous metal coating was proposed to promote the wear and corrosion resistance under multigrade diesel engine oil (15W-40) diluted with 7% palm oil-based biodiesel (B30). The coating was performed using laser cladding technique at different scanning speeds (40 and 60 mm/s) and constant laser power 280 W. Microstructure investigation and X-ray diffraction confirmed amorphous structure and crystalline phase (FeCr). It was found that the wear rate was reduced for the coated specimens by about 90% compared to the uncoated samples. The corrosion rates decreased by 54.74% and 69.96% for scanning speeds 40 and 60 mm/s, respectively. Thanks to the reduced microstructural defects such as grain boundaries in the amorphous structure of the coating. These findings showed that amorphous metal coating provides promising solutions to increase the reliability of using biodiesel without the need for corrosion inhibitors which reduce the combustion efficiency.

Optimizing two-photon polymerization for rapid and high-resolution prototyping of low-friction microtextured surfaces

Abstract Low-friction surfaces enhance performance across various sectors, such as boosting fuel efficiency in transportation and augmenting precision, safety, and comfort in medical devices. Given these benefits, there is a pressing need to investigate how the geometric characteristics of microtextured surfaces can effectively reduce friction, a process that demands precise geometric control. This study explores the application of Two-Photon Polymerization (TPP) as a high-resolution additive manufacturing technique for prototyping microtextured surfaces used in friction studies. TPP’s ability to create precise microstructures makes it an ideal tool for understanding the impact of geometrical factors on friction. However, a significant trade-off exists between print time and quality, particularly for large samples. The TPP parameters, including laser power, scan speed, hatch, and slice distances, were fine-tuned to cater to friction application and achieve a balance between resolution and efficiency. A hybrid fill mode combining solid, shell and scaffold printing was developed to reduce print time while maintaining surface integrity. Friction tests demonstrated that the TPP-printed microdimpled samples effectively reduced friction, highlighting the potential of TPP as a prototyping tool for tribological applications.

Different post-heat treatment responses on microstructure and mechanical characteristics of maraging steel 1.2709 samples produced by LPBF

Abstract The study focuses on the enhancement of microstructural and microhardness characteristics of Laser-Based Powder Bed Fusion (LPBF) maraging steel 1.2709 with the effect of different heat treatment (HT) conditions including aging (AT), double aging (DAT), and solutioning (ST) and compared with the as-built (AB) condition. The samples were fabricated with the LPBF process parameters, utilizing 120 W of laser power, 500 mm s−1 of scanning speed, maintaining 20 μm layer thicknesses, with the laser spot width and hatch spacing of 0.0550 mm and 100 μm respectively in the argon environment with the 45° rotating raster scanning pattern. Further the as-built and heat treated samples were evaluated utilizing electron backscatter diffraction (EBSD), Field Emission Scanning Electron Microscope (FESEM), microhardness, x-ray diffraction (XRD) and relative density. The FESEM analysis indicated that the DAT samples exhibit a more refined and uniform interdendritic grain growth of precipitates Ni3 (Al, Ti) compared to the as-built sample, which exhibited porosity and lack of fusion. Aging reduces the presence of interlayer defects, while the solution-heat-treated sample reveals the formation of lath martensite. The microhardness exhibited an increase following three distinct heat treatment conditions: AB, AT, DAT, and ST, measuring 450 HV, 650 HV, 760 HV, and 520 HV, respectively. The ferrite content was recorded at 99.6%, 87.4%, 99%, and 99.4%, while the austenite content was 0.4%, 12.6%, 1%, and 0.6%. The grain size in the ferrite phase was 8.72 μm, 6.087 μm, 6.86 μm, and 0.32 μm, and in the austenite phase the grain size was 0.26 μm, 0.86 μm, 2.51 μm, and 6.89 μm.

Research on Laser Cleaning of Graphite Lubrication Coating on the Magnesium Alloy Surface

The lubricating coating must be removed from the forged or stamped workpieces. Developing environment-friendly and high-precision cleaning technology is necessary. In this study, a nanosecond pulsed laser was used to clean the graphite lubricating coating of 15 μm thickness on the surface of an MB15 magnesium alloy. The effects of various laser cleaning parameters on the cleaning quality and the cleaning mechanism were studied. When the laser fluence (F) increases from 1.27 to 7.64 J/cm2, the clearance rate increases, and the surface roughness initially decreases before increasing. When the pulse frequency (f) increases from 10 to 30 kHz, the single-pulse energy decreases, the clearance rate decreases, and the surface roughness increases. When the scanning speed (v) increases from 1000 to 5000 mm/s, the spot overlap rate decreases, the clearance rate decreases, and the surface roughness firstly decreases and then increases. The optimal cleaning parameter combinations are F = 3.82 J/cm2, f = 10 kHz, and v = 3000 mm/s. The graphite lubrication coating was almost completely removed without damaging the substrate surface, and the surface carbon content of the sample was decreased to 6.42%. The laser cleaning mechanism of the graphite lubricating coating on the magnesium alloy surface is dominated by thermal ablation. As the laser fluence increases, the physical and chemical reactions become more violent.

Understanding and control of gas porosity in metal laser powder-bed fusion additive manufacturing

ABSTRACT The presented study discusses mechanism leading to gass porosity formation during additive manufacturing (AM) process. The method employs numerical scheme, which includes fluid dynamics of the melt pool and on-the-fly ray-tracing implemented within a phase field framework where the liquid/vapor interface is captured within volume of fluid approach. The emission of pores in the middle or the stripe happens only for relatively low scan speed (less than 0.6 m/s for IN718). The stripe edges (laser turning points) are identified as potential source of gas pores at scan speeds as high as 1 m/s. Simulations of laser turning, representative of the edge of a stripe, suggest the way the process parameters can be altered to avoid local porosity formation, while still ensuring a deep melt pool suitable for high build rates. The laser power modulation around the edge can lead to over 50% reduction of the pores emission. The proposed numerical framework requires only moderate computational resources, thus providing a holistic tool to decrease defect density and thus further improve quality of additive manufactured components.

Comparison between ZenoTOF 7600 system and QTOF for plant metabolome: an example of metabolomics applied to coffee leaves.

ZenoTOF is new class of high-resolution mass spectrometer that combines resolution and sensitivity. This mass spectrometer is well designed to perform metabolomics. In this context, we compared the performance of ZenoTOF 7600 system (Sciex) with QTOF6520 (Agilent Technologies) through the leaf metabolome analysis of two Coffea species, namely C. anthonyi and C. arabica. Both species were used to compare both TOF systems. Our results showed that the ZenoTOF 7600 system provided more features (3146 vs 2326 metabolites) and more nodes (1410 vs 379 metabolites) by molecular network in only one injection. These performances were attributed to the scan speed and sensitivity of the ZenotTOF and demonstrates its added value in the context of metabolomics.

Oscillatory nature in melt-gas-powder interactions during laser powder bed fusion process revealed by CFD-DEM coupled modelling

ABSTRACT The laser powder bed fusion (LPBF) process encompasses interactions between different material states, including melt, gas, and powder. While observational techniques can capture specific states, they cannot be combined to produce a comprehensive monitoring how they are mutually interacted. Thus, an integrated modelling approach is a crucial solution for revealing their interactions. This study investigates melt-gas-powder dynamics under varying laser scan speeds through a coupled CFD-DEM multiphase model. Findings reveal that metal vapour consistently transitions from an initialisation phase to a processing phase, exhibiting consistent behaviour in the former but varied responses in the latter. A relationship is identified between scan speed and vapour flow angle (VFA), with higher speeds broadening the VFA. Significantly, three oscillatory behaviours are observed: first, the oscillation of locally intensified pressure (LIP) sites on keyhole walls, where vapour ejection modes shift and may become periodic at intermediate scan speeds; second, the oscillation of two induced argon vortex flows with opposite swirling directions; and third, a simultaneously induced varying drag force on powder spatter. These oscillations clarify various spatter mechanisms, offer insights for process optimisation, and suggest implications for process stability. The study also proposes future research directions to further elucidate these mechanisms.

Trans-scale live-imaging of an E5.5 mouse embryo using incubator-type biaxial light-sheet microscopy.

During mouse embryonic development, the embryonic day (E) 5.5 stage represents a crucial period for the formation of the primitive body axis, where the symmetry breaking of cellular states influences the multicellular system. Elucidating the detailed mechanisms of this process necessitates a trans-layered dynamic observation of the embryo and all internal cells. In this report, we present our success in achieving in-toto single-cell observation in a whole hemisphere of an E5.5 embryo for 12 h, using a newly developed incubator-type biaxial light-sheet microscope. To achieve the success, we optimized our microscope system, including an incubator for culture stability, and refining the observation protocol to reduce phototoxicity. Our key discovery is that the scan speed during light-sheet formation plays a critical role in reducing phototoxicity, rather than the irradiation intensity or the interval time between frames. This innovative system not only enabled in-toto single-cell tracking but also led to the discovery of the abrupt shrinking of embryos whose contractile center was located at the extraembryonic ectoderm during monotonous growth up to the E6.5 stage.

Process capability analysis of additive manufacturing process: a machine learning−based predictive model

Purpose Predicting dimensional and geometrical errors in 3D printing parts during the design stage can significantly enhance the product’s quality. This study aims to predict the form deviation and process capability in additive manufacturing (AM) specimens considering layer thickness, laser power and scan speed parameters in the laser powder bed fusion (LPBF) method. Various machine learning (ML) techniques are implemented to estimate the form deviation and process capability with the highest accuracy in 3D-printed cylindrical parts as a case study. Design/methodology/approach The workflow started by simulating the LPBF AM process using a finite element modeling approach. Then, different ML algorithms like artificial neural networks are used to predict the form deviation. The process capability value is forecasted using some classification ML models and process capability indices (PCIs) for cylindrical parts. Finally, concentricity tolerance classification is performed for cylindrical parts, which can ensure quality control issues in the production stage. Findings Results present an accuracy of about 93% for predicting form deviations and 95% accuracy for predicting PCI C_pm in PCI classification based on random forest model as an ML algorithm. Originality/value The noteworthy point of the research is accessing the form deviation due to AM and process capability evaluation in the AM process before the production stage, which has not been studied before based on the author’s knowledge. So that the product quality is evaluated based on the shape deviation and its tolerances in the AM process digital chain.

Density prediction for selective laser melting fabricated of CuCrZr alloy using hybrid Gaussian boosted regression

Selective laser melting (SLM), an emerging technology, constructs components through layer-by-layer material deposition and has gained popularity in the industry due to its advantages such as shorter lead time, higher flexibility, lower material wastage, and the capability to fabricate complex geometries. However, the development of process databases for new materials is often time-consuming and laborious because SLM involves multiple physical fields and multiple process steps with numerous process parameters. Recently, machine learning is renowned for its excellent capabilities in tasks such as classification, regression, and clustering. In this study, hybrid Gaussian boosted regression that combines Gaussian process regression with gradient boosting machine was used to obtain a process database for CuCrZr alloy, optimizing for density with laser power and scanning speed as characteristic parameters, under limited samples. A machine learning model was developed using fivefold cross-training on 36 datasets. With a determination coefficient (R2) of 0.96587, the model demonstrated a high level of fit. Next, by extending the prediction range, we achieved process parameters for the highest five densities of samples. Finally, the model’s precision was confirmed with experiments on the five predicted maximum densities, with all predictions falling within a ±0.09% error margin from the experimental values. This research precisely predicted the densities of SLM-formed CuCrZr parts, created a comprehensive process parameter database, and substantiated both theoretical and practical backing for the 3D printing of CuCrZr parts.

Optimization of laser process parameters and improved corrosion behaviour of LZ/YSZ thermal barrier coating

Abstract Laser processing the surfaces of plasma-sprayed thermal barrier coatings is one of the methods used to improve the corrosion resistance of the coatings. However, laser glazing alone is not sufficient to fully protect coatings from corrosion. In this study, optimum laser surface modification parameters were determined for plasma-sprayed LZ/YSZ double-layer thermal barrier coatings. The coating surface, whose entire surface was scanned with optimum parameters, was modified with nano YSZ using the electrophoretic deposition technique. Thus, the network cracks formed during laser glazing were filled with nano YSZ. The coating modified by laser and electrophoretic deposition processes was subjected to corrosion tests. As a result of the characterizations, it was determined that the optimum laser surface modification parameters for LZ/YSZ thermal barrier coatings were 200 mm laser distance, 120 scan speed, and 28w laser power. With these parameters, discontinuities on the as-sprayed coating surface were eliminated. A dense layer was successfully created on the LZ layer. As a result of the corrosion tests, it was determined that modifying the laser-glazed surface with nano YSZ reduced the penetration depth of corrosive contaminants. Thus, the glassy melt and hot corrosion resistance of LZ/YSZ thermal barrier coatings was increased.

Research on the optimal laser preparation process parameters of groove-shaped micro-texture on the mill roll surface

Laser micro-texture preparation technology significantly excels in micro-texture processing, yet there has been scant reported research on utilizing this technology for micro-texture processing and texture morphology control on the surface of wheat mill rolls. The aim was to ascertain the ideal laser preparation process parameters for the creation of groove-shaped micro-textures on the surface of the chilled alloy cast iron, serving as the surface layer material of the wheat mill roll. An experiment was conducted using a nanosecond pulsed fiber laser to explore the impact of laser power, scanning times, scanning velocity, and pulse frequency on the morphology and dimensions of the groove-shaped micro-textures. It was found that with laser power set at 7 W, 15 scanning times, a pulse frequency of 35 kHz, and a scanning speed of 500 mm/s, the desired microgroove can be successfully fabricated on the surface of the mill roll. The findings of this study offer insights for the surface modification of critical components in grain and oil machinery and equipment through the application of laser micro-texturing technology.