Laser Heating Research Articles

Effect of Humidity on Head Smear Generation in Head-Assisted Magnetic Recording

The causes of head smears deposited on the magnetic head surface due to laser heating in heat-assisted magnetic recording should be investigated to achieve high recording densities of hard disk drives. These factors, such as outgassing from components and humidity, also affect smear formation in hard disk drives. In this study, we focused on the effect of relative humidity on smears generated via laser heating. Three types of lubricant film (dipped, ultraviolet-treated, and rinsed) were prepared, and the amount of smear generated on a glass pin surface was evaluated using a pin-on-disk tester with a laser heating system. It was confirmed that the amount of smear increased as the humidity increased, and lubricant films with higher chemical bonding fractions showed less smear generation and lower dependence on humidity. In addition, time-of-flight secondary ion mass spectroscopy confirmed that the migration of cobalt from the magnetic layer was accelerated by laser heating and humidity.

THE EFFECT OF ACCELERATED ABSORPTION OF LIQUID IN A TUBE DURING LASER CAVITATION ON A LASER HEATING ELEMENT

The expansion and collapse of a cavitation bubble during laser heating and subcooled boiling of water in the vicinity of the tip of an optical fiber (laser heating element) installed in a water-filled glass tube with two open ends is studied experimentally and numerically. Cavitation, initiated by continuous laser radiation, is accompanied by the pushing and pulling movement of the heated liquid in the tube and outside it. For the first time, it has been shown that in a tube with an installed laser heating element in a liquid flow moving behind the walls of the bubble, when it collapses at the pole of the bubble surface remote from the end, a liquid jet appears, directed through the bubble to the end of the optical fiber. The jet speeds up the process of sucking liquid into the tube.

Specific Features of Stresses Relaxation and Recrystallization of Steel under Laser Heating

Specific Features of Stresses Relaxation and Recrystallization of Steel under Laser Heating

Analysis of Thermal Processes in Steels during Laser Heating

Analysis of Thermal Processes in Steels during Laser Heating

Design and characterization of an optical-fiber-coupled laser-induced desorption source for gas-phase dynamics experiments.

Preparation of neutral non-volatile molecules intact in the gas phase for mass spectrometry or chemical dynamics experiments remains a challenge for many classes of molecules. Here, we report the design and characterization of a fiber-coupled laser-based thermal desorption source capable of preparing intact neutral molecules at high molecular densities in the gas phase for use in velocity-map imaging experiments. Within this source, the sample is deposited onto a thin tantalum foil. Irradiation of the foil from the reverse side by a focused laser beam leads to highly localized heating of the sample, resulting in desorption of a plume of molecules into the gas phase. The fiber-coupled design simplifies the alignment of the desorption laser beam, and the ability to rotate the foil relative to the fixed laser beam allows the sample to be continually refreshed under vacuum. We use 118nm photoionization of three test molecules-uracil, adenine, and phenylalanine-to characterize the source and to demonstrate various aspects of its performance. These include the dependence of the velocity-map imaging performance on the size of the interaction region and the dependence of the laser-induced desorption source emission on desorption laser power and heating time. Signal levels recorded in these measurements are comparable to those we typically obtain in similar experiments using a pulsed supersonic molecular beam, and we, therefore, believe that the source has considerable potential for use in a wide range of chemical dynamics and other experiments.

Finite element analysis of laser welding of 304L butt joint

Grade 304L is an Austenitic stainless steel, which is popular for different high temperature application like Nuclear power plants, thermal power plants and oil & Gas industries etc. In this paper, FEM based investigation was carried out for 1.2 mm thick 304L stainless steel welded using Laser welding process. Thermal cycle was measured at 10 mm distance from welding centerline using K type thermocouple compared with predicted values. FEM based thermal analysis was carried out using SYSWELD. Two different heat source models were selected for laser heat source distribution modeling, conical and double ellipsoidal model are selected. Predicted model has been validated experimental weld profile, results showed a good accuracy of conical model.

The Effect of Accelerated Absorption of Liquid in a Tube during Laser Cavitation on a Laser Heating Element

The Effect of Accelerated Absorption of Liquid in a Tube during Laser Cavitation on a Laser Heating Element

Automated crack detection on metallic materials with flying-spot thermography using deep learning and progressive training

ABSTRACT In non-destructive testing for metallic materials, ‘Flying-spot’ thermography allows the detection of cracks thanks to the scanning of samples by a local laser heat source observed in the infrared spectrum. However, distinguishing a crack from other surface structures such as air ducts or non-planar shapes on the material surface can be challenging in an automation perspective. To address this, we propose to use deep learning techniques, which can exploit contextual information but require a significant amount of labelled data. This study presents a training method based on curriculum learning and recent denoising diffusion models to generate synthetic images. The protocol progressively increases the complexity of training images, using successively simulated data from a multi-physics finite-element software, synthetically generated data with diffusion process, and finally real data. Several detection scores are measured for various machine learning and deep learning architectures, demonstrating the benefits of the proposed approach for regular application cases and degraded experimental conditions, consisting of limited thermal enlightenment recordings.

The Research on Ultrasonic Vibration Amplitudes in Ti6Al4V DED Additive Manufacturing

Ultrasonic-assisted Ti6Al4V Directed Energy Deposition (DED) additive manufacturing technology can improve the problem of uneven microstructure caused by laser heating and sudden cooling of the molten pool. In this paper, the numerical analysis and experimental verification methods were adopted. The influencing factors, such as the cavitations’ effect, sound flow enhancement effect, and sound flow thermal effect related to the ultrasonic assistance in the molten pool, were analyzed. After equating the energy of the ultrasound, the model of additive manufacturing was introduced in the form of a heat source. The temperature gradient changes during the solidification process of the molten pool with the addition of ultrasound assistance and the effect of ultrasonic vibration during the manufacturing process on its deposited state and microstructure of solution-aged formed parts were studied. The results showed that when the wire feeding rate is 5 mm/s and the laser scanning speed is 5 mm/s, the optimal laser power is 1000 W~1100 W, corresponding to the optimal ultrasonic amplitude of 120 μm. Then, by comparing the temperature field with the same amplitude of 0 μm (i.e., no ultrasonic vibration) and the microstructure of the formed parts, it was verified that ultrasonic vibration facilitates fluid flow in the molten pool, which could lead to a more uniform temperature distribution. This optimized approach not only enhances the understanding of the process but also contributes significantly to the advancement of related research endeavors.

Physics-Guided Long Short-Term Memory Networks for Emission Prediction in Laser Powder Bed Fusion

Abstract Powder bed fusion (PBF) is an additive manufacturing process in which laser heat liquefies blown powder particles on top of a powder bed, and cooling solidifies the melted powder particles. During this process, the laser beam heat interacts with the powder causing thermal emission and affecting the melt pool. This paper aims to predict heat emission in PBF by harnessing the strengths of recurrent neural networks. Long short-term memory (LSTM) networks are developed to learn from sequential data (emission readings), while the learning is guided by process physics including laser power, laser speed, layer number, and scanning patterns. To reduce the computational efforts on model training, the LSTM models are integrated with a new approach for down-sampling the pyrometry raw data and extracting useful statistical features from raw data. The structure and hyperparameters of the LSTM model reflect several iterations of tuning based on the training on the pyrometer readings data. Results reveal useful knowledge on how raw pyrometer data should be processed to work the best with LSTM, how physics features are informative in predicting overheating, and the effectiveness of physics-guided LSTM in emission prediction.

Fabrication of thin-walled hat-shaped beams from ultrahigh strength steel by laser-assisted robotic roller forming

Laser-assisted robotic roller forming (LRRF) can be applied to forming ultrahigh strength sheets to products with high geometrical accuracy. In this study, the geometrical profiles and three-point bending performance of thin-walled hat-shaped beams formed by LRRF and robotic roller forming (RRF, i.e., without laser heating) were experimentally investigated. It is found that the geometrical distortion resulted from the accumulation of longitudinal tension during multi-pass roller forming is significantly alleviated by LRRF. In addition, the bending performance of LRRF beam assembly is ameliorated at the initial deformation stage of three-point bending. The improvement is ascribed to a smaller bending radius and the alter of mechanical properties at the laser heat-affected zone. The lower geometrical precision of beams formed without laser heating results in early failure of spot welds of the beam assembly during three-point bending. LRRF beam assembly exhibits larger displacements at failure, and the failure mode is cracking at the edge of the laser-irradiated region. The pronounced microstructure differences on both sides of the crack suggest that the obvious laser-induced mechanical property gradients are responsible for the failure of LRRF beam assembly during three-point bending.

Numerical analysis of the effect of an oscillating metal vapor plume on the keyhole and molten pool behavior during deep penetration laser beam welding

The effect of the oscillating metal vapor plume on the keyhole and molten pool behavior during the laser beam welding of AlMg3 aluminum alloys is investigated by experimental and numerical methods. The real-time height of the metal vapor plume is measured by high-speed camera observation. The obtained experimental results are used to evaluate the additional heating source and laser beam attenuation caused by the scattering and absorption based on the Beer–Lambert theory. Furthermore, the dynamic behavior of the metal vapor plume is incorporated into a 3D transient heat transfer and fluid flow model, coupled with the ray tracing method, for the laser beam welding of the AlMg3 alloy. It is found that additional heating resulting from the scattered and absorbed laser beam energy by the metal vapor plume significantly expands the shape of the molten pool on the top region. Moreover, the oscillating metal vapor plume caused the fluctuation of the high-temperature region in the molten pool. The probability of keyhole collapse at the bottom increases 17% due to the oscillating laser power induced by the laser beam attenuation. The internal interplay between the metal vapor plume, molten pool shape, and keyhole collapse is obtained. The developed model has been validated by experiments, which shows a good agreement.

GiftBTE: an efficient deterministic solver for non-gray phonon Boltzmann transport equation

Advances in nanotechnology have facilitated the exploration of submicron thermal transport. At this scale, Fourier’s law is no longer applicable, and the governing equation for thermal transport is the phonon Boltzmann transport equation (BTE). However, the availability of open-source solvers for the phonon BTE is limited, impeding progress in this field. This study introduces an open-source package, GiftBTE, for numerically solving the non-gray phonon BTE. GiftBTE employs deterministic solutions and provides both steady-state and transient solvers. For the steady-state solver, GiftBTE employs the implicit discrete ordinates method (DOM) with second-order spatial accuracy and the synthetic iterative scheme. For the transient solver, GiftBTE employs the explicit DOM with second-order spatial accuracy. This package demonstrates excellent computational efficiency, enabling realistic three-dimensional simulations of devices and materials. By interfacing with first-principles calculations, this solver enables parameter-free computation of submicron thermal transport. The application of GiftBTE includes, but is not limited to, computing the thermal conductivity of nanostructures, predicting temperature rises in transistors, and simulating laser heating processes.

Light-driven nucleation, growth, and patterning of biorelevant crystals using resonant near-infrared laser heating

Spatiotemporal control over crystal nucleation and growth is of fundamental interest for understanding how organisms assemble high-performance biominerals, and holds relevance for manufacturing of functional materials. Many methods have been developed towards static or global control, however gaining simultaneously dynamic and local control over crystallization remains challenging. Here, we show spatiotemporal control over crystallization of retrograde (inverse) soluble compounds induced by locally heating water using near-infrared (NIR) laser light. We modulate the NIR light intensity to start, steer, and stop crystallization of calcium carbonate and laser-write with micrometer precision. Tailoring the crystallization conditions overcomes the inherently stochastic crystallization behavior and enables positioning single crystals of vaterite, calcite, and aragonite. We demonstrate straightforward extension of these principles toward other biorelevant compounds by patterning barium-, strontium-, and calcium carbonate, as well as strontium sulfate and calcium phosphate. Since many important compounds exhibit retrograde solubility behavior, NIR-induced heating may enable light-controlled crystallization with precise spatiotemporal control.

Parametric study of local laser heat treatment technology on multi forming of advanced-high strength steel (AHSS) part with complex shape

The effectiveness of local laser heat treatment technology to enhance the in situ formability of steels and aluminum alloys has already been widely acknowledged for the one-step forming of components with simple shape geometries. The present study demonstrates that this technology is also able to significantly improve the formability of a complex shaped multi-forming industrial part. An industrial grade advanced-high strength Dual-Phase DP1000 steel is used to analyze the multi-forming of a complex part to determine the most appropriate local laser heat treatment parameters and optimize in situ softening by correlating yield strength, ultimate tensile strength, elongation at fracture, strain hardening exponent and instantaneous strain hardening with local temperature dynamics during the laser treatment. Additionally, numerical simulation analysis using Autoform software is carried out to validate the selected heat affected zone and the in situ softening, ensuring that they are appropriate for improving the formability of the industrial part. These findings are then expanded to study the experimental forming of five in situ laser heat treated models, followed by comparative analysis with a benchmark. This study provides an insight and fundamental guidelines to perform in situ laser heat treatment on complex industrial parts leading to the production of the industrial multi-formed component with optimized formability.

Influences of laser heating parameters on thermophoretic enrichment of nanoparticles

Thermophoretic enrichment of particles has been recognised as an efficient way to concentrate nanovesicles in biomedical studies. Although some experimental and analytical studies have been undertaken to examine the thermophoretic accumulation mechanisms, few studies have been conducted to optimise the device design. This paper presents a detailed parametric study of a thermophoretic enrichment system, which sandwiches a microchamber containing particle/fluid mixture by a glass top, from where an infrared laser heat source is introduced, and a sapphire bottom, which has a high heat conductivity to prevent overheating. The influences of the laser spot radius, laser attenuation rate, nanoparticle size and laser power are investigated. The radius of the nanoparticle accumulation zone is found to be approximately 1.25 times the laser spot radius. A reduction in the laser attenuation length leads to a reduction of the time taken by the nanoparticles to reach the steady state, but an enlarged zone over which nanoparticles are concentrated. There exists an optimum range of the attenuation length, depending on the required size of the target area. We have also determined the threshold particle size, which decides whether the particle motion is convection-dominated or thermophoresis-dominated. Furthermore, an increase in the laser power reduces the accumulation time. These findings provide guidelines for the design of enrichment systems.

Three-dimensional measurement of laser-induced thermal mirror dynamics using photothermal vortex interferometer with azimuthal phase spectra analysis

Measurement of the thermal mirror caused by laser heating provides direct access to the optical, thermophysical, and mechanical properties of solid materials. However, the nanoscale time-dependent three-dimensional (3D) thermal mirror hinders the existing photothermal techniques to obtain the thermal mirror dynamics without sacrificing the spatial profile of the thermal mirror. To fill the gap of 3D measurement of laser-induced thermal mirror dynamics, a photothermal vortex interferometer (PTVI) is proposed. The PTVI produces a multi-ring petal-like interferogram by the coaxial coherent superposition of the high-order conjugated Laguerre-Gaussian beams. The nanoscale 3D thermal mirror with a rotationally symmetric surface profile can be encoded into different azimuthal phase shifts at the different radii of the interferogram. An azimuthal phase spectra analysis is proposed to extract the azimuthal phase shifts from the continuously captured interferograms, enabling reconstruction of the 3D thermal mirror dynamics. The experimental results verified that the PTVI can measure the surface deformation due to the thermal mirror at an accuracy of picometer scale, and the optical and thermophysical properties of an optical glass sample can be determined with the assistance of the thermophysical model of the 3D thermal mirror dynamics. The approach can be an effective tool for characterization of solid materials.

Deep-learning model for predicting hardness and phase distributions from two cross-sectional temperature distribution images in laser heat treatment of AH36 steel

Laser heat treatment of carbon steel is generally performed to increase the hardness of the specimen. However, when the heating temperature is high, softening of the specimen can occur along with melting. It is important to predict both hardening and softening processes, but such research has been limited so far. In this study, a deep learning model was developed that predicts both hardening and softening during laser heat treatment of AH36 steel using two cross-sectional temperature distributions obtained at 0.5-s intervals as inputs. Two temperature distributions were used as inputs to provide accurate information about cooling rate to the model. The input temperature distribution of the cross-section was calculated by solving the heat conduction equation using finite element method, and the hardness and phase distributions used as ground truth were obtained through a 2 kW multi-mode fiber laser experiment. The model was constructed based on a generative adversarial network with a residual network. It was found that when two temperature distributions were used, both softened and hardened areas were predicted accurately. However, when only one temperature distribution was used, only hardening could be predicted. On the other hand, both models could predict phase distributions, but much more accurate results were obtained when two temperature distributions were used as inputs.

Laser assisted diamond turning of silicon freeform surface

Freeform optics find wide applications in the field of illumination, imaging, and bio-medical devices. It is difficult to achieve high-quality, high-precision, and high-efficiency freeform machining on hard and brittle material substrate due to its brittle nature and severe diamond tool wear. Laser assisted diamond turning (LADT) method can effectively promote diamond tool life and machining quality. However, it is a difficult for LADT to ensure the stability of the thermal field and the accuracy of freeform surfaces. To overcome the defects, the PID laser power controller is utilized to accurately maintain the laser heating temperature in the ideal range, which is determined by the high-temperature nanoindentation tests. The LADT thermal expansion is also pre-compensated in the tool path according to the finite element thermal analysis results. The experimental results indicate that silicon freeform optics without thermal defects can be achieved with adaptive laser power in-process heating assistance. The effective improvement of form accuracy confirms the feasibility of the proposed tool path thermal pre-compensation method. Challenges and prospects are discussed to guide future studies.

Innovative technologies for strengthening of internal surfaces of suspension parts of heavy-loaded machines by laser and high-frequency induction methods

In the article innovative methods of surface hardening of internal surfaces of machine parts by laser and highfrequency induction heating are presented. The relevance of applying the methods of laser and induction hardening for the internal surfaces of heavily loaded parts of quarry equipment is proved. The results of modeling and calculation of thermal and electromagnetic fields under the influence of an external electromagnetic field and laser radiation beams are presented. The original design of a complex of equipment for processing the internal surfaces of suspension parts by external electromagnetic field is described. The optimal designs of inductors with magnetic circuits made of various materials are shown. The study of the structure and properties obtained on the internal surfaces of heavily loaded suspension parts of cars, line of the BelAZ company, treated according to the optimal modes of surface induction exposure is given. The developed original technology and equipment of laser surface hardening, which makes it possible to increase the wear resistance of heavily loaded parts, is described. Data on the implementation of research results at JSC “BELAZ” – the Management Company of the Holding “BELAZ-HOLDING” for processing a wide range of heavily loaded suspension parts are given.