Laser Scanning Path Research Articles

Fabrication of microchannels on silica glass by femtosecond laser multi-scan: From surface generation mechanism to morphology control

Femtosecond laser processing has become a critical technique for the microfabrication of hard and brittle materials, particularly in microfluidic device applications. This study focuses on the fabrication of microchannels with controllable cross-sectional profiles in silica glass, a material known for its excellent physical and chemical properties. Through a combination of experimental research and theoretical analysis, the surface generation mechanisms governing microchannel morphology are investigated, alongside the influence of various processing parameters on the surface roughness at the microchannel bottom. A comprehensive optimization method is developed to control sidewall taper and surface roughness by adjusting laser scanning paths and modes. Utilizing a composite scanning approach, the study achieves near-rectangular microchannels with average sidewall taper angles below 5° and surface roughness (Sa) of 2.53 μm. These results provide a new strategy for precise control of microchannel morphology in silica glass, offering significant potential to enhance the efficiency and precision of microfluidic device fabrication, with broad applications in both industrial and research settings.

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.

Nanosecond laser cleaning method for high-capacity fast storage and data multiplexing in ARM architecture

As the application of laser cleaning technology continues to expand, various fields have put forward higher requirements for the performance and quality of the operation, and at present, laser cleaning has problems such as low efficiency in handling repetitive tasks, and the system deployment and maintenance costs are high. This paper proposes a nanosecond laser cleaning method based on ARM architecture with high-capacity fast storage and data reuse, integrating high-capacity fast storage technique and data reuse strategy to optimize the laser cleaning process. In this paper, SDRAM is used to store and record the laser scanning path, Cache is integrated to weaken the data calling delay and improve the system response speed, and the scanning cycle is finely adjusted by combining positional modulation laser frequency technology to avoid the edge erosion caused by the motor deceleration and to ensure the homogeneity and accuracy of laser cleaning. The results indicate that, under the same output point conditions, the dynamic phase difference spiral algorithm in this paper outperforms the linear filling algorithm in terms of speed and data filling efficiency, reducing the burden of repetitive task calculations. While maintaining surface erosion uniformity during cleaning, excessive erosion is prevented, leading to a comprehensive enhancement in the overall efficiency and performance of laser cleaning operations.

Reproducing wrought grain structure in additive IN718 through nanosecond laser induced cavitation

Pulsed laser assisted additive manufacturing has been demonstrated as a promising technology for controlling grain structure in 3D-printing processes. The integration of a nanosecond laser onto a wire arc additive manufacturing tool has enabled the localized printing of Inconel 718 with grain sizes meeting ASTM 9 standards (average measured grain size of 13.7μm) for wrought material within a single bead under solidification conditions that would otherwise produce 340μm columnar grains. The observed grain refinement holds promise, provided scale up is possible, for overcoming the highly anisotropic mechanical properties and microcracking associated with large columnar grains of Inconel 718 that have long stood in the way of leveraging the advantages of direct energy deposition printing techniques of difficult to machine alloys. Experiments on large bead sizes allowed for decoupling surface versus bulk nanosecond laser/liquid metal interaction mechanisms to determine that the source of the observed grain refinement is the collapse of cavitation bubbles originating from acoustic waves generated by momentum transfer into the melt of an ablation plasma. Additionally, experiments that increased the cavitation bubble density within the mushy zone during solidification by tuning the nanosecond laser scan path went beyond the 25 times reduction in grain size to a 70 times factor of refinement with a minimum average grain diameter approaching 4μm.

Additive manufacturing of heterogeneous combinatorial functional surface by plasmonic hierarchical sintering of silicon particles for active manipulation of rheological liquid motion

We present a sustainable and efficient additive manufacturing method of silicon-based heterogeneous combinatorial functional surfaces designed to actively manipulate liquid droplet motion dynamics to address advanced rheological engineering challenges and applications. This additive manufacturing enables the instantaneous formation and control of hierarchical multiscale structures with tunable wettability through instantaneous plasmonic thermophysical sintering between laser and Si particles, eliminating the need for additional masks and subsequent processing steps. Furthermore, this fabrication approach can selectively implement heterogeneous combinatorial functional surfaces in a single domain by reversibly switching extreme wettability modes (e.g., from superhydrophobic to superhydrophilic) upon laser irradiation. Continuous superhydrophilic channels in a superhydrophobic background created by selective laser re-irradiation provide sufficient local attraction to manipulate droplet motion along the channel due to van der Waals forces and Laplace pressure fields generated by the difference in wettability. Active manipulation of droplet dynamic motion, such as trajectory tracking and antigravity self-propulsion, can be realized by simply designing a laser scanning path that determines the geometry of the local channel. The manipulation platform for liquid motion dynamics can be applied to active microfluidic channels with no cavity, without the need for an external power source. This advancement has important implications for broad fluid and rheological engineering applications.

Finite element simulation and experimental validation of thermal damage to isolated porcine skin tissue by femtosecond laser welding.

The welding effect of the laser on skin tissue is reduced by thermal damage to skin tissue, and greater thermal damage to skin tissue caused by the laser is prevented by predicting thermal damage. In this paper, a finite element model is established for the temperature field of skin tissue scanned by a femtosecond laser to obtain the influence of laser process parameters and scanning path on the thermal damage parameters of skin tissue and the thermal damage area, and verified experimentally. The results show that the established finite element model is accurate and can accurately reflect the temperature distribution during the process of femtosecond laser welding of porcine skin tissues; used to predict the thermal damage parameters of the skin tissues and the thermal damage area; and provide guidance for the study of the femtosecond laser welding of the skin tissues process to obtain the optimal process parameters.

A highly efficient computational approach for fast scan-resolved microstructure predictions in metal additive manufacturing on the scale of real parts

In metal additive manufacturing (AM), fast and efficient simulation approaches are essential to explore the full potential of these promising processes, particularly in generating components with tailored microstructures via laser powder bed fusion (LPBF). Due to the inherent multiscale nature of LPBF, existing approaches often need to resort to strong simplifications, such as layer-wise heating models, to make part-scale simulations feasible. In contrast, the present article proposes a scan-resolved approach, which consistently resolves the laser scan path in a coupled thermo-microstructural model of LPBF. Building on a high-performance computing model for the thermal problem, we propose a highly efficient implementation of a recently developed microstructure model for Ti-6Al-4V with three main constituents: stable αs-phase, martensitic αm-phase and β-phase. The implementation is tailored to modern hardware features using vectorization and fast approximations of transcendental functions. A performance model and selected numerical examples of LPBF manufacturing of parts on the centimeter scale are studied to verify the high degree of optimization. Depending on the specific example, results were obtained with moderate computational resources in a few hours to days. We demonstrate how the proposed scan-resolved model allows us to predict the correlation between scan strategy and resulting microstructure composition, an aspect that layer-wise heating models cannot capture. The numerical examples include scan-resolved thermo-microstructure simulations of the full NIST AM Benchmark cantilever specimen. It is shown that varying the build plate temperature by only 100K can significantly change the microstructure composition from αm- to αs-dominated.

Laser-induced oxidation of Cf/SiC composites: Oxidation behavior analysis and parameter optimization

Cf/SiC composite is widely utilized in aerospace and defense sectors owing to their outstanding high-temperature and mechanical performance. However, this material is a typical hard-to-machining material. Building upon prior research on the novel laser-induced oxidation-assisted milling technology, this paper conducted an in-depth study of the oxidation of Cf/SiC composite under laser induction. The study combined thermodynamic analysis with the detection of oxidation products to ascertain the oxidation reaction types of Cf/SiC composite. The oxidation process under the induction of lasers with different energy densities was investigated by combining the oxide layer morphology, element distribution, and high-speed photography results. And the oxidation mechanism was elucidated. A second-order response surface model for the oxide layer thickness with respect to the laser energy density, scanning speed, and scanning path spacing was established, and parameter optimization was performed based on this model. Experimental validation demonstrated the reliability of the model predictions.

Data-driven prediction of inter-layer process condition variations in laser powder bed fusion

The pressing problem of laser powder bed fusion of metals (PBF-LB/M) is the inability to predict and mitigate undesired process conditions in a build. This study aims to develop an efficient and geometric-agnostic prediction tool for the variations of the average meltpool temperature of each layer given a laser scanning path. The approach is a data-driven model based on defined physics-based features and measurement data from a two-color coaxial photodiode system. Although the coaxial photodiode system cannot measure absolute meltpool temperature, it can measure relative changes in the meltpool temperature if the process is performed in the shallow or no-keyhole regimes, the focus of this study. Once trained, the model can predict meltpool temperature variations before the start of the build process for a part geometry which had not yet been printed. The results show that variations in the layer average meltpool temperature can be predicted with the average coefficient of determination (r2) score of 0.65. Furthermore, the method shows the significance of considering the effect of surrounding parts on the average meltpool temperature profile of an observed part. For part geometries investigated in this study, the model shows the information from at least 40 previous layers is needed to enable sufficient and stabilized prediction performance.

Femtosecond laser precision machining of carbon film based on aramid paper substrate

Carbon film has many applications in flexible electronic devices (FED) due to its low cost and high conductivity. However, it is difficult to remove carbon film from the substrate without damaging it. This research explores the use of femtosecond laser, which has minimal thermal effect and non-contact processing, for carbon film ablation. The main objectives are to determine the ablation threshold of carbon film and aramid paper, to optimize the laser ablation parameters and scanning path, and to analyze the ablation mechanism and quality. The results show that the optimal laser fluence is between 0.22 J/cm2 and 1.45 J/cm2, and the optimal scanning method is grid scanning method. The laser ablation achieves a removal depth of 9.4 μm and a minimum Sa of 3.0 μm. Raman spectroscopy confirms the complete removal of carbon film and the transformation of graphite to amorphous carbon. The ablation process is mainly governed by combustion and evaporation. A resistance strain gauge is fabricated using laser ablation to demonstrate its potential in carbon film FED manufacturing.

MeltpoolGAN: Melt pool prediction from path-level thermal history

In metal laser powder bed fusion, a laser beam rapidly scans through a thin layer of powder. The laser heats up and liquefies the powder forming a melt pool. The melt pool characteristics affect the material property and physical performance of the part. Physical simulations of melt pool dynamics are computationally expensive and are often limited to a short laser scan. Alternatively, Finite Element (FE) simulations for part-scale thermal history are less computationally intensive but do not capture the detailed melt pool temperature profile and geometry in general. Accurate modeling of the high spatial and temporal thermal gradients inside and near the melt pool is essential to many applications of the thermal history including design and optimization of the laser scan path, material microstructure characterization, and deformation prediction.In this work, we developed MeltpoolGAN, the first conditional Generative Adversarial Network (cGAN) to predict the melt pool image based on the simulated thermal history along the laser scan path. The integration of generative deep learning and thermal history simulation achieves melt pool-level accuracy while significantly reducing the physical and computational complexity. The data pair of thermal history and melt pool images for neural network training and validation are obtained through Contact-Aware Path Level (CAPL) thermal simulation and a co-axial melt pool monitoring system developed by NIST, respectively. The predicted melt pool morphology is validated against experimentally acquired melt pool images through geometric characteristics, including the length and width, of the melt pool.

Adaptive Ant Colony Optimization with Sub-Population and Fuzzy Logic for 3D Laser Scanning Path Planning.

For the precise measurement of complex surfaces, determining the position, direction, and path of a laser sensor probe is crucial before obtaining exact measurements. Accurate surface measurement hinges on modifying the overtures of a laser sensor and planning the scan path of the point laser displacement sensor probe to optimize the alignment of its measurement velocity and accuracy. This manuscript proposes a 3D surface laser scanning path planning technique that utilizes adaptive ant colony optimization with sub-population and fuzzy logic (SFACO), which involves the consideration of the measurement point layout, probe attitude, and path planning. Firstly, this study is based on a four-coordinate measuring machine paired with a point laser displacement sensor probe. The laser scanning four-coordinate measuring instrument is used to establish a coordinate system, and the relationship between them is transformed. The readings of each axis of the object being measured under the normal measuring attitude are then reversed through the coordinate system transformation, thus resulting in the optimal measuring attitude. The nominal distance matrix, which demonstrates the significance of the optimal measuring attitude, is then created based on the readings of all the points to be measured. Subsequently, a fuzzy ACO algorithm that integrates multiple swarm adaptive and dynamic domain structures is suggested to enhance the algorithm's performance by refining and utilizing multiple swarm adaptive and fuzzy operators. The efficacy of the algorithm is verified through experiments with 13 popular TSP benchmark datasets, thereby demonstrating the complexity of the SFACO approach. Ultimately, the path planning problem of surface 3D laser scanning measurement is addressed by employing the proposed SFACO algorithm in conjunction with a nominal distance matrix.

Laser Rescanning for Enhancing Mechanical Properties of Laser-Directed Energy-Deposited High-Manganese Steels.

This study investigates the effects of laser deposition and laser rescanning (LR) on the microstructure and mechanical properties of high-manganese steel (HMnS) deposited by laser-directed energy deposition (L-DED) comprising 24 wt.% Mn. Four types of laser deposition and LR strategies were investigated: unidirectional L-DED scanning without laser rescanning, L-DED scanning with 90° alterations in the laser scanning path on each layer without laser rescanning, unidirectional L-DED with laser rescanning in the same direction, and L-DED with laser rescanning with 90° alterations in the laser scanning path. The L-DED-processed HMnS had only a few small pores and exhibited a microstructure without any serious defects such as cracks. Additionally, a strong fibrous texture along the <101>/building direction of the fully austenite phase was found. The mechanical properties (microhardness and tensile strength) of HMnS were improved by the LR with a grain refinement effect and fine solidification cell size due to the significantly faster solidification rate in LR than that in L-DED.

Localized fabrication of flexible graphene-copper composites via a combined ultrafast laser irradiation and electrodeposition technique

Graphene-metal composites (GMC) possess superior properties, such as high specific strength, and high thermal and electrical conductivity, and have been widely used in many fields. However, the fabrication of GMC still remains to be explored, as existing methods via powder metallurgy and chemical synthesis are difficult to achieve uniform dispersion of graphene, not to mention achieving selective and localized preparation of GMC with complex patterns. In this paper, a simple method for the fabrication of graphene-copper composites (GCC) is firstly proposed by combining flexible laser irradiation and efficient electrodeposition. It not only effectively solves the problems of graphene agglomeration and inhomogeneous dispersion in GCC, but also enables the selective and precise preparation of GCC with spatial micro-patterns. Specifically, an ultrafast picosecond (ps) laser is firstly used to irradiate the polyimide (PI) film to selectively and precisely produce the desired laser-induced graphene (LIG) region. The localized deposition of copper atoms is subsequently made via the electrodeposition step, forming the flexible GCC with a laser-determined spatial pattern. The experimental study of LIG process on PI film has been carried out, and high-quality LIG region is obtained by optimizing the laser scanning path and parameters. On this basis, the regional flexible GCC of 45 μm in thickness with a compact and uniform copper layer of 20 μm has been efficiently fabricated, followed by the detailed characterizations of surface morphology and chemical composition. Furthermore, a significant enhancement of the electrical conductivity has been confirmed, as the measured value is up to 32.8 S/cm at the LIG region and further to about 60.9 S/cm at the GCC area. The mechanical properties of the obtained conductive GCC have been tested and good flexibility is confirmed by nanoindentation and bending tests, verifying its potential for a wide range of applications in flexible electronics, medical and many other fields.

Effects of Nanosecond Laser Scanning Paths on Weld Formation, Microstructure and Mechanical Properties of Dissimilar Ultra-Thin Al/Cu Foil Nanosecond Laser Welded Joints

Effects of Nanosecond Laser Scanning Paths on Weld Formation, Microstructure and Mechanical Properties of Dissimilar Ultra-Thin Al/Cu Foil Nanosecond Laser Welded Joints

Experimental study on the effect of scanning path on skin tissue properties of femtosecond laser welding.

To study the influence pattern of femtosecond laser scanning path on the welding effect of skin tissue, this experiment analyzed the influence of scanning path on the surface morphology, degree of thermal damage, tensile strength, and microstructure of skin samples after skin attachment by designing nine scanning paths to weld skin tissue. The results showed that the skin samples connected by interrupted parallel mattress eversion sewing method with d = 0.2 mm showed no obvious color changes in morphology, the skin samples were connected on both front and back sides, the tensile strength was the highest, reaching 12.80 N/cm2 , the thermal damage parameter was low at 1.08 × 10-2 , the microstructure had obvious directionality, and the texture was clear and uniformly distributed.

Oxidation mechanism of high-volume fraction SiCp/Al composite under laser irradiation and subsequent machining

Conventional mechanical machining of a composite material comprising an aluminum matrix reinforced with a high volume fraction of SiC particles (hereinafter referred to as an SiCp/Al composite) faces problems such as rapid tool wear, high specific cutting force, and poor surface integrity. Instead, a promising method for solving these problems is laser-induced oxidation-assisted milling (LOAM): under laser irradiation, the local workpiece material reacts with oxygen, thus forming loose and porous oxides that are easily removed. In the present work, the oxidation mechanism of SiCp/Al irradiated by a nanosecond pulsed laser is studied to better understand the laser-induced oxidation behavior and control the characteristics of the oxides, with laser irradiation experiments performed on a 65% SiCp/Al composite with various laser parameters and auxiliary gases (oxygen, nitrogen, and argon). With increasing laser pulse energy density, both the ablated groove depth and the width of the heat-affected zone increase. When oxygen is used as the auxiliary gas, an oxide layer composed of SiO2 and Al2O3 forms, and CO2 is produced and escapes from the material, thereby forming pores in the oxides. However, when nitrogen or argon is used as the auxiliary gas, a recast layer is produced that is relatively difficult to remove. Under laser irradiation, the sputtered material reacts with oxygen to form oxides on both sides of the ablated groove, and as the laser scanning path advances, the produced oxides accumulate to form an oxide layer. LOAM and conventional milling are compared using the same milling parameters, and LOAM is found to be better for reduced milling force and tool wear and improved machined surface quality.

Effect of solution heat treatment on the microstructure and crystallographic texture of IN939 fabricated by powder bed fusion-laser beam

The effect of various solution heat treatment temperatures (i.e., 1120, 1160, 1200 and 1240 °C) on the microstructure, grain morphology and crystallographic texture of IN939 fabricated by powder bed fusion-laser beam (PBF-LB) was investigated. Microstructural analyses showed that the high-temperature gradient and rapid solidification of the PBF-LB processing caused different resulting microstructures compared to conventionally produced counterparts. The melt pool morphologies and laser scanning paths were examined in the as-fabricated samples in the XZ- and XY-planes, respectively. After the application of solution heat treatment at 1120 °C, the as-fabricated PBF-LB initial microstructure was still apparent. For solution heat treatments of 1200 °C and above, the melt pool and scanning path morphologies disappeared and converted into a mixture of columnar grains in the XZ-plane and equiaxed grains in the XY-plane. On the other hand, large equiaxed grains were observed when the samples were solutionized at 1240 °C. Additionally, γ′ phase precipitated within the matrix after all solution heat treatment conditions, which led to increase in the microhardness values. According to electron backscatter diffraction (EBSD) analyses, both as-fabricated and solution heat-treated samples had intense texture with {001} plane normal parallel to the building direction. The first recrystallized grains began to appear when the samples were subjected to the solution heat treatment at 1160 °C and the fraction of the recrystallized grains increased with increasing temperature, as supported by kernel average misorientation (KAM) and grain spread orientation (GOS) analyses.

Enhanced cutting performance of electrosurgical units by oil-infused laser-textured surfaces

To enhance the cutting performance of electrosurgical units, urgent demands have been put forward for their work terminal, including an antiadhesion property and less thermal damage. Herein, an oil-infused surface (OIS) was fabricated by nanosecond laser texturing and spin-coating of medical olive oil and then applied to a work terminal (a scalpel). The effects of four laser scanning paths on the morphology of microdimples used for oil storage were investigated. Then, an array of 0° microdimples with vertical wall and symmetry features was selected to create OISs. The fabricated microdimples contained a nanoscale sponge-like morphology, which improved the oil storage capacity. From the point of view of experimental and theoretical analysis, we verified the autonomous sliding behaviour of plasma droplets on the inclined OIS, and the analysis of the viscosities of the oil film and a plasma droplet showed that the sliding velocity of the droplet decreased with increasing microdimple spacing. Cutting experiments proved that the OIS scalpel has excellent antiadhesion properties for multiple biological tissues. In particular, the OIS scalpel can reduce the cutting force by 19.0% and the tissue thermal damage by 30.8% when cutting pork tenderloin compared to the pristine scalpel. During the cutting process, the introduction of an oil film shifts the interfacial separation from within the tissue to the oil film itself, and the film acts as a thermal barrier to reduce tissue damage, thus greatly improving the cutting performance. The present study highlights the practical application of the OIS as an effective tool in the field of electrosurgical units.

Iterative closest point-based data fusion of non-synchronized in-situ and ex-situ data in laser powder bed fusion

With the development of additive manufacturing (AM) processes, a variety of methods and technologies for process monitoring and post-process inspection have become available. These, together with modern computerized machines, generate large amounts of data about the process. Hence, efficient analysis methods for extracting useful information and knowledge from these datasets are needed. This paper presents a method for automated data fusion of machine input toolpath commands, on-axis intensity monitoring, and Computed Tomography (CT) scan measurement data in laser metal powder-bed fusion AM. The iterative closest point (ICP) point-clouds registration method is used for fine spatial alignments of (1) on-axis intensity measurements with machine input toolpath commands and (2) machine input toolpath and CT scan. The input-toolpath point cloud is selected as the reference point cloud. We further propose a post-processing method that can correct part of the wrong connections between measurements and toolpath points as results of ICP registration. The proposed method is suitable for merging data where there is no temporal synchronization between the machine commands and the monitoring system, and where the actual laser scan path may deviate from the machine input toolpath commands, e.g., due to dynamics constraints of scanning galvo mirror system. The method is designed to handle dynamic changes in input process parameters such as dynamic changes in laser power and scan speed, which lays a solid foundation for advanced AM process control, qualification and certification. A practical solution for organizing and storing the fused data, which allows for efficient analysis, is also presented. The results show that the method can spatially align all three different types of data and find the corresponding input toolpath command for each measurement point. The alignment of on-axis measurements and machine input toolpath commands has been improved by using a clustering algorithm. The main limitation is that, for estimating the improvement and error of spatial alignment, the average difference between the closest points of two point clouds is used, but this metric does not give an exact value of an actual registration error. The estimation of connectivity error is based on a visual comparison of registration results.