A multi-scale multi-physics modeling framework has been developed to predict solidification cracking susceptibility (SCS) during welding. The framework integrates a thermo-mechanical finite element model to simulate temperature and strain rate profiles during welding, a cellular automata model to simulate the solidified microstructure in the weld pool, and a granular model to calculate the pressure drop in the mushy zone. Verification was achieved by comparing the model’s predictions with welding experiments on two steels, demonstrating its capability to accurately capture the effects of process parameters, grain refinement, and alloy composition on SCS. Results indicate that increasing welding velocity, while maintaining a constant power-to-velocity ratio, extends the size of the mushy zone and increases the maximum pressure drop in the mushy zone, leading to higher SCS. Grain refinement decreases separation velocities and the permeability of liquid channels, which increases SCS, but it also raises the coalescence temperature, resulting in an overall reduction in SCS. Alloy composition impacts SCS through thermal diffusivity and segregation. Lower thermal diffusivity or stronger segregation tends to elongate the mushy zone, resulting in an increase in SCS. This framework provides a robust tool for understanding the mechanisms of solidification cracking, optimizing welding parameters to prevent its occurrence, and comparing SCS of different compositions during alloy design.@en

Wire arc additive manufacturing (WAAM) is a significant area of interest within the field of additive manufacturing (AM). In the present research, WAAM technology was employed to deposit a Ni-based alloy on a ductile cast iron substrate to fabricate a bimetallic structure of Ni-45 %Fe alloy and ductile cast iron. Scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), electron back scattered diffraction (EBSD) and X-ray diffraction (XRD) were used to study phase transformations, microstructure and crystallographic texture development in interfacial regions as well as deposited material. The mechanical properties were also studied using micro-hardness and profilometry-based indentation plastometry (PIP) measurements. The results showed that a wide variety of phases are generated within the heat-affected zone (HAZ) and partially melted zone (PMZ). These phases form complex microstructures with single and double shell morphology. The deposited alloy has a face-centred cubic (FCC) structure, with some carbides and graphite that are formed during the solidification of the first deposited layer. The compositional changes were also observed across the interface. The texture of the deposited alloy showed around 30° deviation from 〈100〉 II building direction due to the shape and overlap of the melt pools. The present results provide a better understanding of interface development mechanisms during WAAM of bimetallic structures. The peak of the hardness across the interface was observed in PMZ because of the formation of a martensitic matrix. The PIP measurements showed that the σ_y and the UTS of deposited alloy are lower than the cast iron base metal.

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Superelastic metamaterials have attracted significant attention recently, but achieving such functionality remains challenging due to partial superelasticity and premature fracture in additively manufactured components. To address these issues, this study investigates the premature fracture in Ni-rich NiTi metamaterials fabricated by laser powder bed fusion. A comparative analysis of two structures (Gyroid network and Diamond shell) reveals that the structural stability of bending- and stretching-dominated structures is reversed compared to typical elastic-plastic response, due to the tension-compression asymmetry of base NiTi. The premature fracture and partial superelasticity of these as-fabricated samples are attributed to low deformation ability for accommodating tensile stress. Based on these findings, a heat treatment introducing Ni₄Ti₃ precipitates was employed, successfully achieving macroscopic superelasticity in the NiTi metamaterials, with consistency between model prediction and experiments.

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Microstructure features including grain morphology and texture are key factors in determining the properties of laser additively manufactured metallic components. Beyond the traditional trial-and-error approach, which is costly and time-consuming, microstructure control increasingly relies on predictions from mechanistic models. However, existing mechanistic models to predict microstructure and texture are computationally expensive. Here, we present a cellular automata solidification model, which is up to two orders-of-magnitude faster than traditional models. By analytically calculating growth length and utilizing a multi-level capture algorithm, a large time step can be employed without compromising simulation accuracy. The model is validated through simulations of 316L steel and three NiTi cases, showing good agreement with experimental results. Our findings reveal that preferential orientations are selected by the vertical and the inclined temperature gradients from multi-pass temperature profiles, leading to different microstructures and textures. Three-dimensional additive manufacturing simulations demonstrate that orientation-dependent growth patterns govern grain growth, leading to columnar, planar and spiral shaped grains. This approach offers a significant reduction in computational cost while maintaining accuracy, contributing to the practical application of microstructure control in additive manufacturing. The insights gained on grain and texture evolution pave the way for customized microstructure design through additive manufacturing.@en

In this study, three-dimensional functionally graded NiTi bulk materials were fabricated using laser powder bed fusion (LPBF) by in-situ adding Ni powder into equiatomic NiTi powder. The gradient zone exhibited a Ni composition ranging from approximately 49.6 to 52.4 at.% over a distance of about 2.75 mm. The functionalities along the compositional gradient were examined through differential scanning calorimetry analysis and spherical indentation. This unique gradient resulted in location-specific functionalities, including superelasticity characterized by wide and narrow hysteresis loops, shape memory effect, and various phase transformation temperatures. The rapid cooling rate during fabrication led to the presence of excess Ni in the solid-solute state within NiTi. This unique solid-solute compositional gradient in NiTi resulted in varying lattice parameters, influencing the compatibility between martensite and austenite and allowing for tailored hysteresis. This discovery presents new avenues for designing multifunctional materials through in-situ additive manufacturing.

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Boron doped MoSi₂ particles have been envisioned as sacrificial particles for self-healing thermal barrier coatings (TBCs) but their oxidation behaviour is yet not well understood. In this work, oxidation of MoSi₂ based particle is studied in the temperature range of 1050–1200 °C. The oxidation proceeds from a transient to a steady-state oxidation stage. The kinetics during steady-state oxidation is captured with a thermal diffusion-based model. As compared to the oxidation of pure MoSi₂ particles, the addition of boron strongly enhances the silica formation. Also, a finer dispersion of MoB_x in the MoSi₂ matrix accelerates the formation of silica. The oxide growth rate constant increases proportional with the boron content of the MoSi₂ particles. This enhanced oxidation is related to the microstructure of the oxide scale. Upon oxidation, boron yields B₂O₃, which promptly merge with SiO₂ to form amorphous borosilicate, hindering the formation of crystalline SiO₂. Consequently, the migration of oxygen in the borosilicate oxide scale is faster than in the silica oxide scale on pure MoSi₂ particles.

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The binary Fe–Ni system offers alloys with notably low linear coefficients of thermal expansion (CTE), contingent upon their Ni content. In this respect twin-wire arc additive manufacturing (T-WAAM) presents the opportunity of in-situ alloying through the simultaneous feeding of two metal wires into a weld pool to obtain desired alloy compositions. This study aims to deposit a graded wall with Ni contents targeted at 42, 46, and 52 wt% in the building direction of the wall, along with a block comprising of 46 wt% Ni, employing the T-WAAM approach. The results show effective incorporation of additional Ni into the weld pool and geometrically stable weld beads in the continuous metal transfer mode during the T-WAAM process. This mode led to the defect-free and chemically stable deposition of the graded wall and the block with average Ni contents of 42.3 ± 1.1, 45.8 ± 1.4, 52.6 ± 0.8 wt%, and 46.4 ± 0.9 wt%, respectively. The measured Curie temperatures of the as-deposited alloys and the mean CTE values of alloy 46 were found to be comparable to the commercial alloys. In summary, this study validates the feasibility of in-situ deposition of low thermal expansion alloy compositions, thereby enabling the possibility of on-demand thermal expansion properties.

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Additively manufactured Nitinol (NiTi) architectured materials, designed with unit cell architectures, hold promise for customisable applications. However, the common assumption of homogeneity in modeling and additive manufacturing of these architectured materials needs further investigation because geometric-dependent melt pool behaviour results in inhomogeneous microstructure and thermomechanical properties. This study shows that property inhomogeneity at the mesoscale is one reason for pseudo-linear response and partial superelasticity of the fabricated NiTi body-centered cubic (BCC) architectured materials. We modeled using a phenomenological constitutive relation and additively manufactured NiTi architectured materials with varying relative densities. These fabricated samples showed distinct microstructural textures and compositions that affected their local recoverability. The edge effects and laser turn regions were identified as the causes underlying the observed microstructural inhomogeneity. The dimensionless Fourier number is used to describe the transition of printing modes. This study provides valuable information on rigorous experimental/computational consistency in future work.

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This study examines the interface layer between a high-strength low-alloy steel and an overlaying austenitic stainless steel as deposited through wire arc additive manufacturing in a bi-metal block. By utilizing optical and electron microscopy techniques, and accompanied by phenomenological and thermodynamic modeling, the work elucidates on the nature of the distinct microstructural features at a new level of detail. Results showcase martensite in the form of a band along the fusion line of the first dissimilar layer, as well as in segregated islands. Within the same bead, yet away from the fusion line, an austenite matrix is identified alongside a large phase fraction of primary ferrite and sparse bainite. These findings enhance our understanding of the nature of the heterogeneous microstructure at the interface of a bi-metal build and establish empirical evidence for future modeling of microstructural development. Supplementary characterization reveals the impact of these microstructural heterogeneities on bulk mechanical performance. Hardness indents exhibit varied results along the interface, peaking at martensite islands with values up to 370HV_0.2, surpassing the neighboring matrix by 50%. Under quasi-static tensile loading, bi-metallic specimens display strain partitioning along the fusion boundary, as confirmed by Digital Image Correlation. When compared to the adjoining stainless steel, the diluted interface layer exhibits superior strength (σ_y: 411 MPa) and comparable ductility (24%), leading to necking and failure away from this region. These results help predict the structural performance of bi-metal parts, and build a base for further research in more intricate loading scenarios, such as crack propagation processes.

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Invar alloys exhibit low thermal expansion and are useful in applications requiring dimensional stability when subject to temperature changes. Conventional production of Invar faces certain challenges that can be offset by exploiting additive manufacturing processes. This study employed pulsed gas tungsten arc welding (GTAW) to deposit Invar 36 alloy blocks at five heat inputs (HI) ranging from 200 to 550 J mm⁻¹. The results show that the microstructure comprised of columnar grains and remained in the austenitic phase regardless of the HI. Ductility dip cracking was found to prevail in all the blocks except the block deposited at the lowest HI. The decreased susceptibility to cracking with a reduction in the HI was due to the preservation of the grain boundary area, consequently leading to an improved partitioning of strain among the grain boundaries. On lowering the HI from 550 to 200 J mm⁻¹ the average yield strength, tensile strength and elongation improved by 16%, 23% and 38%, respectively. The HI had a negligible effect on the mean linear coefficient of thermal expansion (CTE) in different temperature ranges as the CTE values were nearly identical between the blocks deposited at 200 and 550 J mm⁻¹. In general, the CTE in the building direction was slightly higher than the travel direction, with a maximum difference between the CTE of the two directions being 15%. In summary, this work demonstrates the application of the cold wire GTAW process as an alternative to conventional/laser based methods for realizing the functional properties of Invar.

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Additive manufacturing of NiTi shape memory alloys has attracted attention in recent years, due to design flexibility and feasibility to achieve four-dimensional (4D) function response. To obtain customized 4D functional responses in NiTi structures, tailorable phase transformation temperatures and stress windows as well as one-way or two-way shape memory properties are required. To achieve this goal, various heat treatments, including direct aging, annealing and annealing followed by aging, were optimized for the Ti-rich NiTi (Ni49.6Ti (at. %)) fabricated by laser powder bed fusion (L-PBF). Microstructural evolution, phase transformation, precipitation and shape memory behaviour were systematically investigated by multiscale correlative microstructural, differential scanning calorimetry analysis and thermomechanical analysis. Based on optimized heat treatments, ∼25 K phase transformation temperature windows and ∼90 MPa stress windows were achieved for the one-way shape memory effect. Solutionized annealing was found to be the most effective way to improve one-way shape memory degradation resistance, due to the reduction of defects and solid solution strengthening. One of the main findings of this study is that the heterogonous microstructures between hard intergranular Ti₂NiO_x and soft NiTi matrix, induced by solutionized annealing with subsequent aging, result in strain partitioning and enclosing the internal stress state, which was found to promote a pronounced two-way shape memory effect response. The results of this work provide in-depth knowledge on tailoring and designing functional shape memory characteristics via heat treatments, which contributes to expanding L-PBF NiTi application fields, such as biomedical implants, aerospace components, and other advanced engineering applications.

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Wire and Arc Additive Manufacturing (WAAM) emerged as a manufacturing process for large scale structures with extensive form and design freedom. WAAM can be fully exploited once the relation between the transient thermal history and its relation to microstructure development and resultant mechanical properties is established. This relation can be further used for computational design tools such as Topology Optimization. This paper presents a model to predict the relation between the thermal history and solid-state phase transformations in a widely applicable High Strength Low Alloy steel ER110S-G. The transient thermal history of parts manufactured by WAAM is modelled using finite element analysis. The modelled thermal history is validated with thermocouple measurements. Our results show that a critical cooling cycle is responsible for the solid-state phase transformation in an AM part. The cooling rate of this particular cooling cycle is superimposed onto an experimentally constructed Continuous Cooling Transformation (CCT) diagram to determine the local solid-state phase fractions. The predicted phase fractions in three wall samples with different design and processing conditions of AM parts are used to predict the hardness. The predicted hardness is 10% higher than the measured hardness of AM samples. The effect of tempering is also considered in the model through JMAK equation. The results show that the tempering is caused in regions with high martensite content and it lowers the hardness by 8 − 10%. The micrographs of the AM parts show that the microstructural features are same for the AM parts with similar critical cooling rates.

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Superelastic metallic materials possessing large recoverable strains are widely used in automotive, aerospace and energy conversion industries. Superelastic materials working at high temperatures and with a wide temperature range are increasingly required for demanding applications. Until recently, high-temperature superelasticity has only been achievable with multicomponent alloys fabricated by complex processes. In this study, a novel framework of multi-scale models enabling texture and microstructure design is proposed for high-performance NiTi fabrication via laser powder bed fusion. Based on the developed framework, a Ni-lean Ni(49.4 at.%)-Ti alloy is, for the first time, endowed with a 4% high-temperature compressive superelasticity. A 001 texture, unfavorable for plastic slip, is created to realize enhanced functionality. The unprecedented superelasticity can be maintained up to 453 K, which is comparable with but has a wider superelastic temperature range (∼110 K) than rare earth alloyed NiTi alloys, previously only realizable with grain refinement, and other complicated post-processing operations. At the same time, its shape memory stability is also improved due to existing textured 100 martensite and intergranular precipitation of Ti₂NiOx. This discovery reframes the way that we design superior performance NiTi based alloys through directly tailoring crystallographic orientations during additive manufacturing.

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The pursuit of enhancing NiTi superelasticity through laser powder bed fusion (L-PBF) and [001] texture creation poses a challenge due to increased susceptibility to hot cracking in the resulting microstructure with columnar grains. This limitation restricts NiTi's application and contributes to material waste. To overcome this, we introduce a pioneering approach: utilising spark plasma sintering (SPS) to heal directional cracks in [001] textured L-PBF NiTi shape memory alloy. Diffusion bonding and oxygen utilisation for Ti₂NiO_x formation was found to successfully heal the cracks. SPS enhances mechanical properties, superelasticity at higher temperatures, and two-way shape memory strain during thermomechanical cycling. This work provides an alternative solution for healing cracks in L-PBF parts, enabling the sustainable reuse of cracked materials. By implementing SPS, this approach effectively addresses hot cracking limitations, expanding the application potential of L-PBF NiTi parts while improving their functional and mechanical properties.

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A cellular automata (CA) model has been developed for solidification simulation considering the kinetic undercooling at the interface. The state-of-the-art model incorporates a decentered growth algorithm to suppress the grid anisotropy and a generalized height function method to calculate the curvature accurately. To develop a CA model which is independent of the mesh size, a new diffusion term is proposed to handle the diffusion between the interface cells and liquid cells. The developed CA model is employed to simulate the single-dendritic solidification of an Al–3Cu (wt pct) alloy. The simulated tip velocities agree with the prediction of the Kurz–Giovanola–Trivedi (KGT) model. Further studies show that the developed CA model converges to an equilibrium model with increasing kinetic mobility values. Moreover, it is found that the virtual liquid cell assumption which is commonly used in existing CA models may lead to a deviation in the mass balance. The mass balance error has been resolved by redistributing solutes from neighboring liquid cells in each time step. The developed CA model could be potentially used in solidification simulations with a high undercooling, which is common in welding and additive manufacturing.

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Localised laser treatments enable the creation of sophisticated austenite/martensite mesostructures in Fe–Ni–C steel with the potential of achieving enhanced mechanical performance. The control of phase topology is essential to modify the properties of these structures on demand and requires a profound understanding of the effect of the processing parameters on the development of the different phases upon the application of laser treatment. In this work, the microstructure evolution under exceptional gradients in temperature and heating rates is thoroughly investigated. The extent of the laser-affected zone and the heat input were tailored by varying laser parameters and specimen thickness, based on a model that considers transient material properties and the coupling between temperature and microstructure. The predicted temperature fields resulted in a complex interplay between martensite to austenite phase transformation and martensite tempering. Considering the high heating rates of up to 25000 K/s and the observed microstructures, it is suggested that austenite was formed by a pseudo-displacive mechanism and subsequently fully recrystallised in the zones most directly affected by the laser heat source. A smooth strength transition from austenite to martensite, affected by the laser parameters, could be exploited for more effective deformation mechanisms and improved material mechanical properties.

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Mo(Al_xSi_1-x)₂ alloy with x in the range of 0.35–0.65 were prepared by a one-step spark plasma sintering. To study the exclusive formation of an α-Al₂O₃ scale, oxidation experiments were conducted in low and high oxygen partial pressure ambient at 1373 K; viz.: 10⁻¹⁴ and 0.21 atm. The oxidation kinetics follows a parabolic rate law after a transient period. A counter-diffusion process of O and Al along grain boundaries of Al₂O₃ scale is responsible for the equiaxed and columnar grain growth based on a two-layered microstructure. The formation of a dense equiaxed α-Al₂O₃ layer contributes to excellent oxidation resistance.

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Laser beam shaping offers remarkable possibilities to control and optimise process stability and tailor material properties and structure in laser-based welding and additive manufacturing. However, little is known about the influence of laser beam shaping on the complex melt-pool behaviour, solidified melt-track bead profile and microstructural grain morphology in laser material processing. A simulation-based approach is utilised in the present work to study the effects of laser beam intensity profile and angle of incidence on the melt-pool behaviour in conduction-mode laser melting of stainless steel 316L plates. The present high-fidelity physics-based computational model accounts for crucial physical phenomena in laser material processing such as complex laser–matter interaction, solidification and melting, heat and fluid flow dynamics, and free-surface oscillations. Experiments were carried out using different laser beam shapes and the validity of the numerical predictions is demonstrated. The results indicate that for identical processing parameters, reshaping the laser beam leads to notable changes in the thermal and fluid flow fields in the melt pool, affecting the melt-track bead profile and solidification microstructure. The columnar-to-equiaxed transition is discussed for different laser-intensity profiles.

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To prevent premature triggering of the healing reaction in Mo-Si containing self-healing thermal barrier coating system, an oxygen impenetrable shell (α-Al₂O₃) around the sacrificial healing particles (MoSi₂) is desired. Here an encapsulation method is presented through selective oxidation of Al in Mo(Al_xSi_1-x)₂ particles. Healing particles of Mo(Al_xSi_1-x)₂ is designed in terms of alumina shell thickness, particle size and fraction Al dissolved. By replacing Si by Al in MoSi₂ up to the maximum solubility (x = 0.65) a strong crack healing ability is maintained (relative volume expansion ≥ 40 %). The formed exclusive α-Al₂O₃, featuring a two-layered structure, results from a counter-diffusion process along the grain boundaries, and its oxidation kinetics fits well with the 3D diffusion-Jander model. After 16 h exposure in gaseous ambient with a pO₂ of 5 × 10^-10 atm. at 1100 °C, a closed and dense shell of α-Al₂O₃ is formed with a thickness of about 1.3 µm. The oxide shell produced under this condition provided healing particles with significantly improved stability upon exposure to high pO₂ of 0.2 atm. at 1100 °C for 50 h. The particles after exposure feature an inner core of MoSi₂ with Al completely consumed and an oxide shell of α-Al₂O₃.

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The current research work investigates the possibility of using machine learning models to deduce the relationship between WAAM (wire arc additive manufacturing) sensor responses and defect presence in the printed part. The work specifically focuses on three materials from the nickel alloy family (Inconel 718, Invar 36 and Inconel 625) and uses three sensor responses for data analysis, which are welding voltage, welding current and welding audio. Two different machine learning models are used—artificial neural networks (ANNs) and random forests (RF). The results for each of the materials, separately, indicate that the accuracies range from 60% to 90% and the correlation coefficient is less than 0.5 (indicating weak positive correlation), depending on the model and material. In addition to separate material analysis, a cross-material data analysis was formed to test the models’ general prediction capabilities. This led to predictions that are significantly worse, with accuracies ranging from 20% to 27% and very weak correlation coefficients (less than 0.1), indicating that the choice of material is still important as a boundary condition. Analysis of the results indicates that the relative importance of audio sensor response depends on the nature of defect formation. Random forests are found to perform the best for single material analysis, with the comparatively inferior performance of ANNs possibly being due to lack of sufficient datapoints.@en