On the Development of Smart Framework for Printability Maps in Additive Manufacturing of AISI 316L Stainless Steel.

In this work, we propose a methodology to develop printability maps for the laser powder bed fusion of AISI 316L stainless steel. Regions in the process space associated with different defect types, including lack of fusion, balling, and keyhole formation, have been considered as a melt pool geometry function, determined using a finite element method model containing temperature-dependent thermophysical properties. Experiments were performed to validate the printability maps, showing a reliable correlation between experiments and simulations. The validated simulation model was then applied to collect the data by varying laser scanning speed, laser power, powder layer thickness, and powder bed preheating temperature. Following this, the collected data were used to train and test the adaptive neuro-fuzzy interference system (ANFIS)-based machine learning model. The validated ANFIS model was used to develop printability maps by correlating the melt pool characteristics to the defect types. The smart printability maps produced by the proposed methodology can be used to identify the processing window to attain defects-free components, thus attaining dense parts.

A Robust Recurrent Neural Networks-Based Surrogate Model for Thermal History and Melt Pool Characteristics in Directed Energy Deposition.

In directed energy deposition (DED), accurately controlling and predicting melt pool characteristics is essential for ensuring desired material qualities and geometric accuracies. This paper introduces a robust surrogate model based on recurrent neural network (RNN) architectures-Long Short-Term Memory (LSTM), Bidirectional LSTM (Bi-LSTM), and Gated Recurrent Unit (GRU). Leveraging a time series dataset from multi-physics simulations and a three-factor, three-level experimental design, the model accurately predicts melt pool peak temperatures, lengths, widths, and depths under varying conditions. RNN algorithms, particularly Bi-LSTM, demonstrate high predictive accuracy, with an R-square of 0.983 for melt pool peak temperatures. For melt pool geometry, the GRU-based model excels, achieving R-square values above 0.88 and reducing computation time by at least 29%, showcasing its accuracy and efficiency. The RNN-based surrogate model built in this research enhances understanding of melt pool dynamics and supports precise DED system setups.

Effect of Pre-Heating on Residual Stresses and Deformation in Laser-Based Directed Energy Deposition Repair: A Comparative Analysis.

Laser-directed energy deposition (DED), a metal additive manufacturing method, is renowned for its role in repairing parts, particularly when replacement costs are prohibitive. Ensuring that repaired parts avoid residual stresses and deformation is crucial for maintaining functional integrity. This study conducts experimental and numerical analyses on trapezoidal shape repairs, validating both the thermal and mechanical models with experimental results. Additionally, the study presents a methodology for creating a toolpath applicable to both the DED process and Abaqus CAE software. The findings indicate that employing a pre-heating strategy can reduce residual stresses by over 70% compared to no pre-heating. However, pre-heating may not substantially reduce final distortion. Notably, final distortion can be significantly mitigated by pre-heating and subsequently cooling to higher temperatures, thereby reducing the cooling rate. These insights contribute to optimizing DED repair processes for enhanced part functionality and longevity.

Mathematical formalism of femtosecond laser-deoxyribonucleic acid interaction: thermal evolution.

A novel analytical formalism is proposed based upon Quantum heat transport equation in order to describe the femtoseconds/picoseconds laser pulses interaction with the Deoxyribonucleic acid (DNA). The formalism generates solutions based upon inputs as: voltage, laser beam intensity and laser - DNA interaction time. Thermal waves induced inside irradiated DNA are defined and accounted for. Analytical simulations show that the optimum regime of laser - DNA interaction was reached for a potential carrier generated at the interface equal to 3.5 × 10-3 eV. It has to be mentioned that the formalism breaks down if the potential carrier generated at the interface is inferior to 10-2 eV. Accordingly, for pulse duration inferior to 1 ps, the laser beam spatial-temporal distribution has an essential role in defining the shape and magnitude of the thermal distribution within the irradiated DNA strands.

Printability for additive manufacturing with machine learning: Hybrid intelligent Gaussian process surrogate-based neural network model for Co-Cr alloy.

AM has revolutionized the manufacturing industry, involving several operating parameters that may affect the properties of the final manufactured part. In AM, LPBF has proved its reliability in producing dense components; however, process development for every material necessitates extensive testing. Even the tiniest change can negate all the data for the same material. It is vital to have a P-P correlation that can train itself following a change in powder or machine to achieve defects-free parts and optimal properties. These goals cannot be met alone by multi-physics. One of the ways to address this issue is to apply ML, but it requires a huge data set for training and testing purposes. A framework has been developed for Co-Cr S-S curves to resolve this issue. Twenty-two experimental S-S curves have been generated to produce YS, TS, and EL data points. In combination with DNN, these data points have been applied to the validated and tested GPS-surrogate model to develop a smart processing window to achieve desired YS, TS, and EL. LP, LSS, HD, and PLT have been selected during the whole framework as inputs, while YS, TS, and EL have been classified as outputs. The output of the smart window was verified experimentally. It is found that the highest YS (1110.91 MPa) is attained using LP = 180 W, LSS = 600 mm/s and HD = 70 µm, while least YS (645.05 MPa) is identified using LP = 160 W, LSS = 900 mm/s and HD = 70 µm. For TS, the maximum (165.91 MPa) and minimum (689.73 MPa) values have been achieved using LP = 180 W, LSS = 900 mm/s and HD = 70 µm, and LP = 180 W, LSS = 1000 mm/s and HD = 70 µm, respectively. In the case of EL, LP = 180 W, LSS = 700 mm/s and HD = 70 µm, and LP = 180 W, LSS = 600 mm/s and HD = 70 µm, resulted 23.04% and 0.789% EL, respectively. Using CC, LP and HD did not significantly affect the TS, YS, and EL, while a negative relationship has been found for LSS with TS, YS, and EL. The smart processing window showed that the YS and TS could be achieved at low-high LP and low LSS at the cost of EL. This study provides a technique for framework development in the case of P-P relation based on the provided inputs and the corresponding outputs, leading toward process smartification.

One-Temperature Analytical Model for Femto-/Atto-Second Laser-Metals Drilling: A Novel Approach.

Recently, ultrafast lasers have been developed and potentially become a point of interest worldwide, as their interaction with matter is yet unknown and can be mediated by new physical mechanisms. Real-time experimentation requires enormous costs, and there is therefore a need to develop computational models for this domain. By keeping in view this idea, a non-Fourier heat equation has solved the case of ultrafast laser-material interaction. Initial and boundary conditions were considered, and a one-dimensional mathematical model was presented. The simulations were compared with the experimental results for ultrashort laser-metallic sample interaction, and a close correlation was proven. It was found that the coupling of electron-phonon becomes "zero" due to short laser-material interaction time. The propagation of thermal waves was identified due to non-Fourier heat implementation. When the pulse duration increases, the variation in the thermal distribution becomes trivial due to an inverse correlation between the pulse duration and total energy within the pulse. When the laser-material interaction time decreases from fs to as, the generation of thermal waves increases and the powerful laser intensity acts as a shock wave during laser-material interaction, which causes a higher intensity of the thermal wave.

Advances in Laser Additive Manufacturing of Cobalt-Chromium Alloy Multi-Layer Mesoscopic Analytical Modelling with Experimental Correlations: From Micro-Dendrite Grains to Bulk Objects.

This study presents two analytical models for the laser powder bed fusion (LPBF) process. To begin, the single layer's dimensions were measured using principal operating conditions, including laser power, laser scanning speed, powder layer thickness, and hatch distance. The single-layer printing dimensions were transformed into multi-layer printing using the hatch distance. The thermal history of the printed layers was used as an input to the Johnson-Mehl-Avrami-Kolmogorov model to estimate the average dendrite grain size. LPBF experiments were conducted for a Cobalt-chromium (Co-Cr) alloy to validate the developed model. The average dendrite grain size was estimated using a scanning electron microscope (SEM) combined with "Image J" software. The Vickers hardness test was performed to correlate the average dendrite grain size and operating conditions. A 10-15% mean absolute deviation was presented between experiments and simulation results. In all samples, a Co-based γ-FCC structure was identified. An inverse correlation was established between the laser power and smaller average dendrite grain, while a direct relationship has been determined between laser scanning speed and average dendrite grain size. A similar trend was identified between hatch distance and average dendrite grain size. A direct link has been determined between the average dendrite grain size and hardness value. Furthermore, a direct relationship has connected the laser volume energy density and hardness value. This study will help experimentalists to design operating conditions based on the required grain size and corresponding mechanical characteristics.

Laser Melting Deposition Additive Manufacturing of Ti6Al4V Biomedical Alloy: Mesoscopic In-Situ Flow Field Mapping via Computational Fluid Dynamics and Analytical Modelling with Empirical Testing.

Laser melting deposition (LMD) has recently gained attention from the industrial sectors due to producing near-net-shape parts and repairing worn-out components. However, LMD remained unexplored concerning the melt pool dynamics and fluid flow analysis. In this study, computational fluid dynamics (CFD) and analytical models have been developed. The concepts of the volume of fluid and discrete element modeling were used for computational fluid dynamics (CFD) simulations. Furthermore, a simplified mathematical model was devised for single-layer deposition with a laser beam attenuation ratio inherent to the LMD process. Both models were validated with the experimental results of Ti6Al4V alloy single track depositions on Ti6Al4V substrate. A close correlation has been found between experiments and modelling with a few deviations. In addition, a mechanism for tracking the melt flow and involved forces was devised. It was simulated that the LMD involves conduction-mode melt flow only due to the coaxial addition of powder particles. In front of the laser beam, the melt pool showed a clockwise vortex, while at the back of the laser spot location, it adopted an anti-clockwise vortex. During printing, a few partially melted particles tried to enter into the molten pool, causing splashing within the melt material. The melting regime, mushy area (solid + liquid mixture) and solidified region were determined after layer deposition. This research gives an in-depth insight into the melt flow dynamics in the context of LMD printing.

Non-Destructive X-ray Characterization of a Novel Joining Method Based on Laser-Melting Deposition for AISI 304 Stainless Steel.

In this study, an application of the laser-melting deposition additive manufacturing technique as a welding method has been studied for the laser welding (LW) of AISI 304 stainless steel, specifically 0.4 mm and 0.5 mm thick sheets. The welding was carried out without and with filler material. Inconel 718 powder particles were used as filler material in the second case. A series of experiments were designed by changing the process parameters to identify the effect of operating conditions on the weld width, depth, and height. The welds were examined through metallographic experiments performed at various cross-sections to identify the defects and pores. All the deposited welds were passed through a customized mini-focus X-ray system to analyze the weld uniformities. The optimal operating conditions were determined for 0.4 mm and 0.5 mm sheets for the LW with and without filler material. It was found that laser power, laser scanning speed, powder flow rate, and helium to argon gases mixture-control the weld bead dimensions and quality. X-ray analyses showed that the optimal operating conditions gave the least peak value of non-uniformity in the laser welds. This study opens a new window for laser welding via additive manufacturing with X-ray monitoring.

Keyhole Formation by Laser Drilling in Laser Powder Bed Fusion of Ti6Al4V Biomedical Alloy: Mesoscopic Computational Fluid Dynamics Simulation versus Mathematical Modelling Using Empirical Validation.

In the laser powder bed fusion (LPBF) process, the operating conditions are essential in determining laser-induced keyhole regimes based on the thermal distribution. These regimes, classified into shallow and deep keyholes, control the probability and defects formation intensity in the LPBF process. To study and control the keyhole in the LPBF process, mathematical and computational fluid dynamics (CFD) models are presented. For CFD, the volume of fluid method with the discrete element modeling technique was used, while a mathematical model was developed by including the laser beam absorption by the powder bed voids and surface. The dynamic melt pool behavior is explored in detail. Quantitative comparisons are made among experimental, CFD simulation and analytical computing results leading to a good correspondence. In LPBF, the temperature around the laser irradiation zone rises rapidly compared to the surroundings in the powder layer due to the high thermal resistance and the air between the powder particles, resulting in a slow travel of laser transverse heat waves. In LPBF, the keyhole can be classified into shallow and deep keyhole mode, controlled by the energy density. Increasing the energy density, the shallow keyhole mode transforms into the deep keyhole mode. The energy density in a deep keyhole is higher due to the multiple reflections and concentrations of secondary reflected beams within the keyhole, causing the material to vaporize quickly. Due to an elevated temperature distribution in deep keyhole mode, the probability of pores forming is much higher than in a shallow keyhole as the liquid material is close to the vaporization temperature. When the temperature increases rapidly, the material density drops quickly, thus, raising the fluid volume due to the specific heat and fusion latent heat. In return, this lowers the surface tension and affects the melt pool uniformity.

A State-of-the-Art Review on Integral Transform Technique in Laser-Material Interaction: Fourier and Non-Fourier Heat Equations.

Heat equations can estimate the thermal distribution and phase transformation in real-time based on the operating conditions and material properties. Such wonderful features have enabled heat equations in various fields, including laser and electron beam processing. The integral transform technique (ITT) is a powerful general-purpose semi-analytical/numerical method that transforms partial differential equations into a coupled system of ordinary differential equations. Under this category, Fourier and non-Fourier heat equations can be implemented on both equilibrium and non-equilibrium thermo-dynamical processes, including a wide range of processes such as the Two-Temperature Model, ultra-fast laser irradiation, and biological processes. This review article focuses on heat equation models, including Fourier and non-Fourier heat equations. A comparison between Fourier and non-Fourier heat equations and their generalized solutions have been discussed. Various components of heat equations and their implementation in multiple processes have been illustrated. Besides, literature has been collected based on ITT implementation in various materials. Furthermore, a future outlook has been provided for Fourier and non-Fourier heat equations. It was found that the Fourier heat equation is simple to use but involves infinite speed heat propagation in comparison to the non-Fourier heat equation and can be linked with the Two-Temperature Model in a natural way. On the other hand, the non-Fourier heat equation is complex and involves various unknowns compared to the Fourier heat equation. Fourier and Non-Fourier heat equations have proved their reliability in the case of laser-metallic materials, electron beam-biological and -inorganic materials, laser-semiconducting materials, and laser-graphene material interactions. It has been identified that the material properties, electron-phonon relaxation time, and Eigen Values play an essential role in defining the precise results of Fourier and non-Fourier heat equations. In the case of laser-graphene interaction, a restriction has been identified from ITT. When computations are carried out for attosecond pulse durations, the laser wavelength approaches the nucleus-first electron separation distance, resulting in meaningless results.

3D Printing at Micro-Level: Laser-Induced Forward Transfer and Two-Photon Polymerization.

Laser-induced forward transfer (LIFT) and two-photon polymerization (TPP) have proven their abilities to produce 3D complex microstructures at an extraordinary level of sophistication. Indeed, LIFT and TPP have supported the vision of providing a whole functional laboratory at a scale that can fit in the palm of a hand. This is only possible due to the developments in manufacturing at micro- and nano-scales. In a short time, LIFT and TPP have gained popularity, from being a microfabrication innovation utilized by laser experts to become a valuable instrument in the hands of researchers and technologists performing in various research and development areas, such as electronics, medicine, and micro-fluidics. In comparison with conventional micro-manufacturing methods, LIFT and TPP can produce exceptional 3D components. To gain benefits from LIFT and TPP, in-detail comprehension of the process and the manufactured parts' mechanical-chemical characteristics is required. This review article discusses the 3D printing perspectives by LIFT and TPP. In the case of the LIFT technique, the principle, classification of derivative methods, the importance of flyer velocity and shock wave formation, printed materials, and their properties, as well as various applications, have been discussed. For TPP, involved mechanisms, the difference between TPP and single-photon polymerization, proximity effect, printing resolution, printed material properties, and different applications have been analyzed. Besides this, future research directions for the 3D printing community are reviewed and summarized.

Thermal Nonlinear Klein-Gordon Equation for Nano-/Micro-Sized Metallic Particle-Attosecond Laser Pulse Interaction.

In this study, a rigorous analytical solution to the thermal nonlinear Klein-Gordon equation in the Kozlowski version is provided. The Klein-Gordon heat equation is solved via the Zhukovsky "state-of-the-art" mathematical techniques. Our study can be regarded as an initial approximation of attosecond laser-particle interaction when the prevalent phenomenon is photon-electron interaction. The electrons interact with the laser beam, which means that the nucleus does not play a significant role in temperature distribution. The particle is supposed to be homogenous with respect to thermophysical properties. This theoretical approach could prove useful for the study of metallic nano-/micro-particles interacting with attosecond laser pulses. Specific applications for Au "nano" particles with a 50 nm radius and "micro" particles with 110, 130, 150, and 1000 nm radii under 100 attosecond laser pulse irradiation are considered. First, the cross-section is supposed to be proportional to the area of the particle, which is assumed to be a perfect sphere of radius R or a rotation ellipsoid. Second, the absorption coefficient is calculated using a semiclassical approach, taking into account the number of atoms per unit volume, the classical electron radius, the laser wavelength, and the atomic scattering factor (10 in case of Au), which cover all the basic aspects for the interaction between the attosecond laser and a nanoparticle. The model is applicable within the 100-2000 nm range. The main conclusion of the model is that for a range inferior to 1000 nm, a competition between ballistic and thermal phenomena occurs. For values in excess of 1000 nm, our study suggests that the thermal phenomena are dominant. Contrastingly, during the irradiation with fs pulses, this value is of the order of 100 nm. This theoretical model's predictions could be soon confirmed with the new EU-ELI facilities in progress, which will generate pulses of 100 as at a 30 nm wavelength.

An Analytical Multiple-Temperature Model for Flash Laser Irradiation on Single-Layer Graphene.

A Multiple-Temperature Model is proposed to describe the flash laser irradiation of a single layer of graphene. Zhukovsky's mathematical approach is applied to solve the Fourier heat equations based upon quantum concepts, including heat operators. Easy solutions were inferred with respect to classical mathematics. Thus, simple equations were set for the electrons and phonon temperatures in the case of flash laser treatment of a single layer of graphene. Our method avoids the difficulties and extensive time-consuming nonequilibrium green function method or quantum field theories when applied in a condensed matter. Simple expressions were deduced that could prove useful for researchers.

Metal Matrix Composites Synthesized by Laser-Melting Deposition: A Review.

Metal matrix composites (MMCs) present extraordinary characteristics, including high wear resistance, excellent operational properties at elevated temperature, and better chemical inertness as compared to traditional alloys. These properties make them prospective candidates in the fields of aerospace, automotive, heavy goods vehicles, electrical, and biomedical industries. MMCs are challenging to process via traditional manufacturing techniques, requiring high cost and energy. The laser-melting deposition (LMD) has recently been used to manufacture MMCs via rapid prototyping, thus, solving these drawbacks. Besides the benefits mentioned above, the issues such as lower ultimate tensile strength, yield strength, weak bonding between matrix and reinforcements, and cracking are still prevalent in parts produced by LMD. In this article, a detailed analysis is made on the MMCs manufactured via LMD. An illustration is presented on the LMD working principle, its classification, and dependent and independent process parameters. Moreover, a brief comparison between the wire and powder-based LMDs has been summarized. Ex- and in-situ MMCs and their preparation techniques are discussed. Besides this, various matrices available for MMCs manufacturing, properties of MMCs after printing, possible complications and future research directions are reviewed and summarized.

Artificial Neural Network Algorithms for 3D Printing.

Additive manufacturing with an emphasis on 3D printing has recently become popular due to its exceptional advantages over conventional manufacturing processes. However, 3D printing process parameters are challenging to optimize, as they influence the properties and usage time of printed parts. Therefore, it is a complex task to develop a correlation between process parameters and printed parts' properties via traditional optimization methods. A machine-learning technique was recently validated to carry out intricate pattern identification and develop a deterministic relationship, eliminating the need to develop and solve physical models. In machine learning, artificial neural network (ANN) is the most widely utilized model, owing to its capability to solve large datasets and strong computational supremacy. This study compiles the advancement of ANN in several aspects of 3D printing. Challenges while applying ANN in 3D printing and their potential solutions are indicated. Finally, upcoming trends for the application of ANN in 3D printing are projected.

Early Results of the Modified Right Atrial Lesion Set for the Cox-CryoMaze Procedure.

OBJECTIVE: The standard right atrial lesion (RAL) set, as originally outlined in the Cox-Maze III procedure, can be technically challenging when using a cryoprobe to create the lesions. We report our initial experience with an alternative set of RALs for the surgical treatment of atrial fibrillation (AF). METHODS: Between September 2011 and January 2015, a total of 112 patients underwent a CryoMaze procedure with biatrial lesions using argon-based cryoablation (cryoprobe temperature, -160°C). Although the standard left atrial lesion set was used, the RAL pattern was modified in this cohort of patients. The intracaval superior vena cava-inferior vena cava lesion was performed as in the pattern described for the standard Cox-Maze III procedure. In addition, a horizontal atriotomy incision (the "T" lesion) in the mid free wall of the right atrium was based roughly in the midintercaval line and extended medially as a linear cryolesion to the lateral tricuspid annulus at the so-called 2-o'clock position as in the Cox-Maze III lesion pattern. Ordinarily, a linear cryolesion would be placed from the tip of the right atrial appendage (RAA) to the anterior tricuspid annulus at the so-called 10-o'clock position to prevent macro re-entry around the base of the RA appendage. Our modification consisted of, instead, a linear cryolesion directed perpendicularly from the mid portion of the atriotomy (T lesion) to the tip of the RA appendage, which simply interrupted RAA re-entry at another point. RESULTS: The mean ± standard deviation age was 72.7 ± 10.6 years, 56.3% were males, and 63.1% had long-standing persistent AF. There were three operative deaths (2.6% with an observed over expected of 0.58), all in the concomitant procedures with associated cardiac disease. Overall follow-up was 91.3%. Freedom from AF at discharge, 1-, 3-, 6-, 12-, 24-month, and last follow-up [16.1 ± 11.3 months (range, 0.4-43 months)], was 100%, 76.3%, 84.2%, 98.3%, 89.5%, 89.2%, and 90.5%, respectively. Similarly, freedom from antiarrhythmic drugs was 74% and 81%, whereas freedom from anticoagulants was 72% and 78% at 12 and 24 months, respectively. CONCLUSIONS: These results suggest the modified RAL set to be an effective alternative to the traditional RALs of Cox-Maze III. By substituting this lateral RAA lesion for the more technically difficult medial lesion, the procedure becomes easier to perform and favorably impacts operative time while achieving comparable results in reducing AF burden.