This study aims to improve the Additive Manufacturing (AM) design space for the popular multi-component Ni alloy Inconel 625 (IN625) thorough investigating the microstructural evolution, namely the solidification microstructure and the solid-state phase transformations during the Laser Powder Bed Fusion (LPBF) process. Highly non-equilibrium solidification and the complex reheating conditions during the LPBF process result in the formation of various types of solidification microstructures and grain morphologies which consequently lead to a wide range of mechanical properties. Understanding the melt’s thermal conditions, alloy chemistry, and thermodynamics during the rapid solidification and solid-state phase transformation in AM process will help to control material properties and even produce a material with specific microstructural features suited to a given application. This research helps to better understand the process-microstructure-property relationships of LPBF IN625. First, a set of simple but effective analytical solidification models were employed to evaluate their ability to predict the solidification microstructure in AM applications. As a case study, Solidification Microstructure Selection (SMS) maps were created to predict the solidification growth mode and grain morphology of a ternary Al-10Si-0.5Mg alloy manufactured by the LPBF process. The resulting SMS maps were validated against the experimentally obtained LPBF microstructure available in the literature for this alloy. The challenges, limitations, and potential of the SMS map method to predict the microstructural features in AM were comprehensively discussed. Second, The SMS map method was implemented to predict the solidification microstructure and grain morphology in an LPBF-built multi-component IN625 alloy. A single-track LPBF experiment was performed utilizing the EOSINT M280 machine to evaluate the SMS map predictions. The resulting microstructure was characterized both qualitatively and quantitatively in terms of the solidification microstructure, grain morphology, and Primary Dendrite Arm Spacing (PDAS). Comparing the experimentally obtained solidification microstructure to the SMS map prediction, it was found that the solidification mode and grain morphology were correctly predicted by the SMS maps. Although the formation of precipitates was predicted using the CALculation of PHAse Diagrams (CALPHAD) approach, it was not anticipated from the analytical solution results. Third, to further investigate the microsegregation and precipitation in IN625, Scanning Transmission Electron Microscopy (STEM) using Energy-Dispersive X-ray Spectroscopy (EDS), High-Angle Annular Dark-Field Scanning Transmission Electron Microscopy (HAADF-STEM), Scheil-Gulliver (with solute trapping) model, and DIffusion-Controlled TRAnsformations (DICTRA) method were employed. It was found that the microstructural morphology mainly consists of the Nickel-Chromium (gamma-FCC) dendrites and a small volume fraction of precipitates embedded into the interdendritic regions. The precipitates predicted with the computational method were compared with the precipitates identified via HAADF-STEM analysis inside the interdendritic region. The level of elemental microsegregation was overestimated in DICTRA simulations compared to the STEM-EDS results; however, a good agreement was observed between the Scheil and STEM-EDS microsegregation estimations. Finally, the spatial variations in mechanical properties and the underlying microstructural heterogeneity of a multi-layer as-built LPBF part were investigated to complete the process-structure-properties relationships loop of LPBF IN625. Towards this end, numerical thermal simulation, electron microscopy, nano hardness test, and a CALPHAD approach were utilized to investigate the mechanical and microstructural heterogeneity in terms of grain size and morphology, PDAS, microsegregation pattern, precipitation, and hardness along the build direction. It was found that the as-built microstructure contained mostly columnar (Nickel–Chromium) dendrites were growing epitaxially from the substrate along the build direction. The hardness was found to be minimum in the middle and maximum in the bottom layers of the build’s height. Smaller melt pools, grains, and PDAS and higher thermal gradients and cooling rates were observed in the bottom layers compared to the top layers. Microsegregation patterns in multiple layers were also simulated using DICTRA, and the results were compared with the STEM-EDS results. The mechanism of the formation of precipitates in different regions along the build direction and the precipitates’ corresponding effects on the mechanical properties were also discussed. / Thesis / Doctor of Philosophy (PhD)

No description available.

Laser powder bed fusion is an additive manufacturing technique that is capable of building metallic parts by spreading many layers of metal powder over a build surface and using a laser to melt specific sections of the surface. The part is built by melting consecutive layers on top of each other until the design is completed. However, during this process defects can occur. These defects have impacts on the part’s physical properties, and it is important to detect them for quality assurance. A single part takes several hundred or thousands of layers to build. While each layer is built, cameras and sensors are used to create images of each layer. These images are used for identification and classification of defects that could have a negative impact on a printed part’s physical properties, such as tensile strength. Classification of defects would reduce manual inspection of the printed part. Thus, the classification of defects in each layer must be automated, as it would be infeasible to manually classify each layer. Recently, machine learning have proven to be an effective method for automating defect classification in laser powder bed fusion. However, machine learning and especially deep-learning approaches generally require a large amount of labeled training data, which is typically not available for laser powder bed fusion printed parts. Labeling of images requires manual labor and domain knowledge. One of the greatest obstacles in defect classification, is how machine learning can be applied despite this absence of labeled data. A machine learning approach that show potential for being trained with less data, is the siamese neural network approach. In this thesis, a novel approach for automating defect classification is developed, using layer images from a laser powder bed fusion printing process. In order to cope with the limited access to labeled data, the classifiers are based on the siamese neural network structure. Two siamese neural network structures are developed, a one-shot classifier, which directly classifies the instance, and a hierarchical classifier with a hierarchical classification process according to the hierarchy of the defect classes. The classifiers are evaluated by inferring a test set of images collected from the laser powder bed fusion process. The one-shot classifier is able to classify the images with an accuracy of 70%and the hierarchical classifier with an accuracy of 86%. For the hierarchical classifier area of the ROC curves were calculated to be, 0.96 and 0.95 for the normal vs defect and overheating vs spattering stages respectively. Unlabeled images were added to the training set of a new instance of the hierarchical classifier, which could infer the test set without any major changes to test set accuracy.

Laser-material interaction of Nickel based superalloy Haynes 282 melt pools were studied for laser parameters similar to laser powder bed fusion (PBF-LB) without powder. The effect of power, speed, hatch distance and laser focus offset were analysed by characterizing different types of melt pool behaviour, including conduction, transition to keyhole, and keyhole mode. Focus offset parameter was found to modify the melting mode from keyhole to conduction type in experiments with and without powder. This change in melting mode is attributed to the variation in laser beam spot size for the same line energy. Such manipulation of type of melting with control of focus offset can be utilized as a method to optimize process parameters for novel materials in the PBF-LB process at high layer thickness. Based on the above study, cubes were built with refined process parameters utilizing powder layer thicknesses of 60- and 90-microns for improved productivity, using partial factorial design of experiment. The conduction mode of melting helped reducing defects, minimizing lack of fusion and keyhole porosity in specimens built with powder at 60- and 90-microns layer thickness. Effect of process parameters and indirect measure like area energy, on the melt pool overlap, defect level and dominant shape of the defects are presented. Optimizing the process parameters to identify the boundaries for building cubes with reduced porosity is also discussed. / Den Ni-baserade superlegeringen, Haynes 282, skannades med laserparametrar liknande de som används i laserpulverbäddfusion (PBF-LB), men utan pulver.Studien undersökte inverkan av effekt, hastighet, avstånd mellan två intilliggandeskanningspass och laserfokusförskjutning, vilket karakteriserades genom olikatyper av beteenden hos smältbadet, inklusive värmeledning, övergång frånvärmeledning till nyckelhål, och nyckelhål. Fokusförskjutningen visade sig ändrasmältbadets läge från nyckelhål till värmeledning. Denna förändring observeradesbåde i experiment utan pulver och i de med pulver. Förändringen beror påbreddningen av laserstrålens punktstorlek samtidigt som samma linjeenergibibehålls. Denna förändring i smältningstyp genom fokusförskjutning kananvändas som en metod för att optimera utforskningen av nya material i PBFLB-processen. Baserat på detta byggdes kuber med pulver med lagertjocklekar på 60 och 90mikrometer, användande olika processparametrar enligt en experimentell designbaserad på en central sammansatt design. Smältning genom värmeledning bidrogtill att minska defekter, minimera bindningsfel och nyckelhålsporositet i proversom byggts med pulver med lagertjocklekar på 60 och 90 mikrometer. Inverkanav processparametrarna och indirekta mått såsom areaenergi på smältbadetsöverlappning, defektnivå och den dominerande formen på defekter presenteras.Optimering av processparametrarna samt identifiering av parameterrymden föratt bygga kuber med minskad porositet undersöks också. / <p>Paper A is to be submitted, and paper C is acceptet and are not included in this licentiate thesis. We do  not have permission to publish paper B in the digital version.</p>

This work investigates the influence of microstructure and cooling and heating rates on the physical and chemical properties of fast crystallizing polymers. The primary objectives were to 1) utilize advanced methodologies to accurately determine the fundamental thermodynamic value of equilibrium melting temperature (Tmo) for the semi-crystalline polymer poly(ether ketone ketone) (PEKK), 2) increase understanding of the influence of microstructure (random versus blocky) of functionalized semi-crystalline polymers on physical and chemical properties, and 3) understand the influence of additive manufacturing process parameters on semi-crystalline polymer crystallization and final properties. All objectives utilized the advanced characterization technique of fast scanning calorimetry (FSC) using the Mettler Toledo Flash DSC 1. The first half of this work focuses on the high-performance semi-crystalline aromatic polymer poly(ether ketone ketone) (PEKK) with a copolymerization ratio of terephthalate to isophthalate moieties (i.e., T/I ratio) of 80/20. Due to the fast heating and cooling rates of the Flash DSC, PEKK underwent melt-reorganization upon heating at slow heating rates. This discovery resulted in utilizing a Hoffman-Weeks linear extrapolation of the zero-entropy production temperature to establish a new equilibrium melting temperature of 382 oC. Additionally, a new NMR solvent, dichloroacetic acid, was discovered for PEKK, allowing for comprehensive NMR analysis of PEKK for the first time. Diphenyl acetone (DPA) was discovered as a novel, benign gelation solvent for PEKK, enabling heterogeneous gel-state bromination and sulfonation to afford blocky microstructures. The gel state functionalization process resulted in a blocky microstructure with runs of pristine crystallizable PEKK retained within the crystalline domains, and amorphous domains containing the functionalized PEKK monomers. The preservation of the pristine crystalline domains resulted in enhanced physical and chemical properties compared to the randomly functionalized analogs. Additionally, heterogeneous gel state functionalization of PEKK gels prepared from different solvents and gelation temperatures resulted in differences in crystallization behavior between blocky microstructures of the same degree of functionalization. This result demonstrates that the blocky microstructure can be tuned through controlling the starting gel morphology. The second half of this work focuses on understanding the influence of cooling and heating rates on the melting, crystal morphology, and crystallization kinetics on isotactic polypropylene (iPP), iPP-polyethylene copolymers (iPP-PE), and iPP/iPP-PE blends and using this information to gain understanding of how these polymers crystallize during the additive manufacturing processes of powder bed fusion (PBF) and material extrusion (MatEx). The crystallization kinetics of iPP, iPP-PE copolymers, and iPP/iPP-PE blends exhibited bimodal parabolic-like behavior attributed to crystallization of the mesomorphic crystal polymorph at low temperatures and the α-form crystal at high temperatures. Incorporation of non-crystallizable polyethylene fractions both covalently and blended as a secondary component, resulted in decreasing crystallization rates, inhibition of crystallization, and decreased crystallizability. Additionally, the non-isothermal crystallization behavior of these systems shows that the non-crystallizable fractions influence the crystal nucleation density and temperature at which polymorphic crystallization occurs. Utilizing in-situ IR thermography in the PBF system, the heating and cooling rates observed for a single-layer PBF print were used to mimic the PBF process by FSC. Partial melting in the printing process leads to self-seeding and increased crystallization onset temperatures upon cooling, which influences the final part melting morphology. Nucleation from surrounding powder and partially melted crystals greatly influences the crystallization kinetics and crystal morphology of the final part. Utilizing rheological experiments and process-relevant cooling rates observed in the MatEx process, the miscibility of iPP/iPP-PE blends influenced the nucleation behavior and crystallization rates, subsequently leading to differences in printed part properties. / Doctor of Philosophy / The crystalline morphology of semi-crystalline polymers depends on their microstructure and thermal history. The resultant crystalline morphology greatly affects the physical and chemical properties. In the first part of this work, the effect of microstructure on material properties is explored. Block copolymer microstructures consist of two or more blocks of distinct polymer segments covalently bonded to one another. This leads to self-organization of the components into unique structural order that would not be attainable if the polymer segments were randomly bonded together. This structural order enhances material properties; thus, block copolymers are advantageous for many applications. However, synthesis of block copolymers can be tedious and expensive. Thus, additional methodologies for block copolymer synthesis are desired. In this work blocky (i.e., statistically non-random) copolymers are synthesized through a facile post-polymerization functionalization method. These blocky copolymers result in enhanced physical and chemical properties compared to the randomly synthesized analogs. This work shows blocky functionalization of a new polymer under new post-polymerization conditions and expands upon the synthesis methodology for block copolymers. In the second part of this work, the effect of heating and cooling rates on the formation of crystals during additive manufacturing is explored. Additive manufacturing modalities of powder bed fusion and material extrusion consist of rapid heating and cooling processes, which can affect how crystals form and ultimately affect the final printed part properties. Using a technique called fast scanning calorimetry, the different heating and cooling rates that the polymer witnesses during printing can be mimicked, and the formation of crystals under these different conditions can be replicated. This mimicking analysis can be related to the printing process and be used to help guide printing processes to enhance printed part properties.

<p>Powder bed fusion (PBF) process is a metal additive manufacturing process, which can build parts with any complexity from a wide range of metallic materials. Research in the PBF process predominantly focuses on the impact of a few parameters on the ultimate properties of the printed part. The lack of a systematic approach to optimizing the process parameters for a better performance of given material results in a sub-optimal process limiting the potentialof the application. This process needs a comprehensive study of all the influential parameters and their impact on the mechanical and microstructural properties of a fabricated part. Furthermore, there is a need to develop a quantitative system for mapping the material properties and process parameters with the ultimate quality of the fabricated part to achieve improvement in the manufacturing cycle as well as the quality of the final part produced by the PBF process. To address the aforementioned challenges, this research proposes a framework to optimize the process for 316L stainless steel material. This framework characterizes the influence of process parameters on the microstructure and mechanical properties of the fabricated part using a series of experiments. These experiments study the significance of process parameters and their variance as well as study the microstructure and mechanical properties of fabricated parts by conducting tensile, impact, hardness, surface roughness, and densification tests, and ultimately obtain the optimum range of parameters. This would result in a more complete understanding of the correlation between process parameters and part quality. Furthermore, the data acquired from the experimentsare employed to develop an intelligent parameter suggestion multi-layer feedforward (FF) backpropagation (BP) artificial neural network (ANN). This network estimates the fabrication time and suggests the parameter setting accordingly to the user/manufacturers desired characteristics of the end-product. Further, research is in progress to evaluate the framework for assemblies and complex part designs and incorporate the results in the network for achieving process repeatability and consistency.</p><br>

Additive manufacturing (AM) is the name given to the technology of building 3D parts by adding layer-by-layer of materials, including metals, plastics, concrete, etc. Of the different types of AM techniques, electron beam melting (EBM), as a powder bed fusion technology, has been used in this study. EBM is used to build parts by melting metallic powders by using a highly intense electron beam as the energy source. Compared to a conventional process, EBM offers enhanced efficiency for the production of customized and specific parts in aerospace, space, and medical fields. In addition, the EBM process is used to produce complex parts for which other technologies would be either expensive or difficult to apply. This thesis has been divided into three sections, starting from a wider window and proceeding to a smaller one. The first section reveals how the position-related parameters (distance between samples, height from build plate, and sample location on build plate) can affect the microstructural characteristics. It has been found that the gap between the samples and the height from the build plate can have significant effects on the defect content and niobium-rich phase fraction. In the second section, through a deeper investigation, the behavior of Alloy 718 during the EBM process as a function of different geometry-related parameters is examined by building single tracks adjacent to each other (track-by-track) andsingle-wall samples (single tracks on top of each other). In this section, the main focus is to understand the effect of successive thermal cycling on microstructural evolution. In the final section, the correlations between the main machine-related parameters (scanning speed, beam current, and focus offset) and the geometrical (melt pool width, track height, re-melted depth, and contact angle) and microstructural (grain structure, niobium-rich phase fraction, and primary dendrite arm spacing) characteristics of a single track of Alloy 718 have been investigated. It has been found that the most influential machine-related parameters are scanning speed and beam current, which have significant effects on the geometry and the microstructure of the single-melted tracks.

Au cours du procédé de fusion laser sur lit de poudre, la température atteinte dans une zone locale est susceptible de générer des gradients thermiques importants. Ces gradients conduisent à leur tour à l'apparition de contraintes résiduelles qui ont un effet sur les caractéristiques mécaniques de la pièce, provoquent des déformations, ainsi que des micro et macro fissures. Dans ce contexte, les trajectoires de lasage jouent un rôle fondamental sur le niveau et la distribution de la température au cours de la fabrication. Il est ainsi nécessaire de valider la génération des trajectoires au regard du comportement thermique induit par ce procédé.Cette thèse propose d'exploiter une méthode analytique pour développer un modèle qui permette d'analyser d'une manière rapide et efficace le comportement thermique dans la pièce lors de la fabrication. En effet, à partir d'une trajectoire de lasage donnée, d'un ensemble de paramètres liés au matériau de la pièce à fabriquer et de paramètres liés au procédé, l'outil développé effectue une simulation de la température en chaque point de la pièce, au cours de temps et de manière rapide, comparée aux autres logiciels de simulation thermique. En effet, afin de réduire le temps de calcul et l'espace mémoire utilisé pour une telle simulation, un ensemble de techniques d'optimisation a été mis en place.Le modèle proposé a été validé dans le cas de l'alliage Ti6Al4V par comparaison avec une simulation thermique par éléments finis obtenue par un logiciel industriel. Ensuite, les résultats de ce modèle sont confrontés aux résultats expérimentaux. Une fois le modèle validé, il a été mis en œuvre pour analyser des trajectoires couramment utilisées dans la littérature et dans l'industrie.Afin de réduire les gradients thermiques et améliorer la qualité des pièces, la solution proposée consiste à contrôler la température et la taille du bain de fusion. Pour se faire, le modèle thermique développé a été exploité pour moduler les paramètres du procédé au cours de la fabrication d'une part et pour développer une stratégie de lasage à pas adaptatif d'autre part. / During manufacturing by Laser Powder Bed Fusion (LPBF), the achieved temperatures in local areas could generate significant thermal gradients. These gradients lead to the apparition of residual stresses which affect the mechanical characteristics of the part and may cause deformation, as well as micro and macro cracks. In this context, scanning paths play a fundamental role on temperature level and distribution during manufacturing. For that reason, it is necessary to validate the generation of trajectories considering the thermal behaviour induced by this process.The purpose of this PhD thesis is to use an analytical method in order to develop a model that allows a fast and efficient analysis of thermal behaviour, during part manufacturing. Indeed, with a given scanning path, material properties and process parameters, the developed tool performs a temperature simulation at each point of the part, over time and in a fast way, compared to other thermal simulation software. In order to reduce computation time and memory storage used for such a simulation, a set of optimization techniques has been proposed.The developed model has been validated in the case of the Ti6Al4V alloy through a comparison with a finite element thermal simulation obtained by industrial software. Then, the results of this model were compared to experimental results. Once validated, it has been implemented to analyze trajectories commonly used in the literature and industry.In order to reduce thermal gradients and improve part quality, the proposed solution consists in controlling the temperature and size of melt pool. For this purpose, the developed thermal model has been used to modulate the process parameters during manufacturing on the one hand and to develop an adaptive scanning strategy on the other hand.

No description available.

<p>This dissertation presents research work related to laser micro sintering, laser micro machining and laser-induced plasma. Firstly, we present extensive experimental studies of double-pulse laser micro sintering (DP-LMS), which typically utilizes the high pressure generated by laser-induced plasma over the powder bed surface to promote molten flow and enhance densification. Chapter 2 shows a single-track experimental study of the DP-LMS process using cobalt powder. The related fundamental mechanisms and effects of different laser parameters on the sintering results are analyzed with the help of <em>in-situ</em> time-resolved temperature measurements. Chapter 3 shows a multi-track experimental study of the DP-LMS process using iron powder. The sintered materials are characterized via the top surface porosity, elemental composition, grain microstructure, nanohardness and metal phase. Three strategic guidelines for laser parameter selection are summarized in the end. Chapter 4 shows time-resolved imaging and OES measurements for plasma induced during DP-LMS. The plasma temperature and free electron number density are deduced by its optical emission spectra (OES). These three chapters have clearly demonstrated DP-LMS can produce much more continuous and densified materials than LMS only using the sintering or pressing laser pulses.</p> <p><br></p> <p>Then, we present laser micro grooving of silicon carbide (SiC) in Chapter 5 by ultrasound-assisted water-confined laser micromachining (UWLM), in comparison with laser machining in water without ultrasound and laser machining in air. UWLM applies <em>in-situ</em> ultrasound to the water-immersed workpiece surface to improve the machining quality and/or productivity. Time-resolved water pressure measurements are carried out to help analyze relevant mechanisms. It has been demonstrated UWLM can be a competitive approach to produce high-quality micro grooves on SiC. The crack problem appears to be effectively solved using a high pulse repetition rate.</p> <p><br></p> <p>Finally, we report a double-front phenomenon for plasma induced by high-intensity nanosecond laser ablation of aluminum in Chapter 6. An additional plasma front is observed via an intensified CCD (ICCD) camera, which propagates very fast at the beginning but stops propagating soon after the laser pulse mostly ends. Its formation could be caused by the inverse bremsstrahlung absorption of laser energy by the ionized ambient gas. Three possible mechanisms on how the ambient gas breakdown is initiated are proposed. </p>