Precipitation of (3-Mg2Si in recycled aluminum alloys is strongly influenced by impurity-driven second-phase particles such as Fe- and Mn-bearing compounds, and by grain and subgrain boundaries. Quantitatively understanding such precipitate-particle and precipitate-boundary interactions is mandatory to improve the recyclability of aluminum alloys. Here, we present CEMIA (Coupled Electron Microscopy and Image Analysis), an open-source Python program that combines high-resolution Backscattered Electron (BSE) imaging with Electron BackScatter Diffraction (EBSD) orientation mapping using projective and Thin Plate Spline (TPS) registration. CEMIA achieves sub-pixel registration accuracy and enables quantitative analysis of the size, distribution, and spatial correlations of the precipitates to identify their homogeneous or heterogeneous nucleation sites. Applied to the precipitation of (3-Mg2Si precipitates in an Al-Mg-Si alloy containing Al-(Fe,Mn)-Si second-phase particles (intermetallics and dispersoids), CEMIA reveals that isothermal hot compression increased (3-Mg2Si number density, reduced mean particle size, and promoted heterogeneous nucleation along grain and subgrain boundaries. Intermetallics exhibit high nucleation potency but low overall impact due to their scarcity, while dispersoids-with lower potency but higher abundance-dominate the heterogeneous nucleation fraction. Fine (3-Mg2Si precipitates exert the strongest Zener pinning boundary-stabilizing effect, particularly along subgrain boundaries after isothermal deformation. CEMIA provides a generalizable and extensible program for microstructure quantification, alloy design, and process optimization.

The formation of β-Mg2Si precipitates influences the microstructural evolution and, consequently, the final mechanical properties of Al–Mg–Si alloys during thermomechanical processing. Here, the sensitivity of the nucleation rate to interfacial energy and temperature is quantified within the framework of classical nucleation theory (CNT), capturing coupled thermodynamic and kinetic contributions and accounting for homogeneous and heterogeneous nucleation conditions. The analysis reveals a transition from kinetically limited nucleation at low temperatures and interfacial energies to thermodynamically suppressed nucleation at high temperatures and interfacial energies, where the nucleation rate becomes most sensitive to parameter variations. Heterogeneous nucleation is significantly less sensitive than homogeneous nucleation due to the reduced nucleation barrier. These results clarify the origin of strong dependence of CNT predictions on interfacial energy and temperature, provide a physically interpretable basis for parameter selection, and improve the robustness of precipitation modeling for industrial Al–Mg–Si alloy design.

Additive manufacturing by Powder Bed Fusion using a Laser Beam on Metals (PBF-LB/M) enables unprecedented design freedom but remains limited by defect formation that stems from unstable melt pool dynamics. Current monitoring approaches often depend on machine learning, which can obscure the underlying physics and complicate industrial deployment. Here, a direct acoustic emission-based methodology is introduced that captures sound signatures of conduction-keyhole transitions and keyhole collapse. Using acoustic emission measurements validated by operando synchrotron X-ray imaging, a series of envelope-based indicators are established that robustly distinguish stable and unstable regimes in 316 L steel and Ti6Al4V under continuous and pulsed lasers. This physics-driven framework provides transparent, localized regime prediction, paving the way for more reliable and industrially scalable monitoring solutions in metal additive manufacturing.

Laser powder bed fusion (LPBF) as an additive manufacturing (AM) technology has emerged as a powerful platform for producing multi-material metallic structures. The main drawbacks of using metallic powders for multi-material printing are related to technical issues (i.e. powder contamination reducing the reusability of the powder) and interfacial defects. This paper attempts to demonstrate the advantages of using a combination of metallic powders and thin foils for printing light titanium-aluminum multi-material structures. An AlSi12 powder was printed using the conventional LPBF process and the behavior of the second material feedstock was investigated using both Ti6Al4V powders and foils. The printing process was simulated numerically using a finite element model (FEM), and characterized experimentally through operando X-Ray diffraction (XRD). For the powder-powder combination, cracking near the interface between the two alloys was considered as a combined effect of residual stresses and the presence of brittle intermetallic compounds (IMCs); both were investigated using nanoindentation. Replacing the Ti6Al4V powder by a foil resulted in a thinner layer of Ti-Al IMCs near the interface, and eliminated the large interfacial cracks. The results from FEM and CALPHAD thermodynamic simulations, supported by operando XRD, indicated that the increased thermal conductivity of the foil, compared to powders, led to heat transfer within the foil and to the underlying LPBF structure, prior to local melting. The new thermal regime produced a flawless interface between Ti6Al4V and AlSi12, due to reduced residual stresses in the plane normal to the building direction, and lower volumes of brittle IMCs. It is concluded that using foils instead of powders mitigates cracking and enhances microstructures near the interface, due to changes in thermal regime and alloys mixing patterns.

This study investigates various cracking mechanisms and their prevalence in fusion processing of steel-copper multi-materials using operando X-ray diffraction and imaging during laser powder-bed fusion (LPBF) of 316L-CuCrZr multi-material. During this investigation, three main types of cracking were identified: (i) solidification cracking, (ii) metal-induced embrittlement (MIE), and (iii) liquation cracking. All cracking types are closely related to phase formation during processing and stem from two underlying mechanisms. First, liquid-liquid phase separation (LLPS) and the monotectic reaction in the 316L-CuCrZr system cause two liquids with vastly different solidification ranges to form, leading to solidification cracking. Second, LLPS and the monotectic reaction uniformly distribute Cu-rich liquid between the Fe-rich dendrites, leading to MIE and/or liquation cracking. Conducted based on the insights gained from the operando characterisation, further experiments showed that cracking can be drastically reduced by avoiding phase separation. However, the complete elimination of cracking necessitates chemical alterations in the material feedstock, indicating that while process adjustments can mitigate cracking, they may fail to fully prevent it. These findings serve as a guideline for understanding the underlying causes of cracking in steel-copper multi-materials, how process optimisation can effectively mitigate cracking, and to what extent such adjustments in processing can achieve this outcome.

This work reports on the development of a downsized laser powder bed fusion device for operando neutron characterization. The design considerations, device configurations, and detailed setup are described. The device is optimized for installations at neutron diffraction and instruments for diverse studies of the structural and microstructural evolution and constitution of metallic components during printing. In conjunction with introducing the device, we provide examples of operando neutron diffraction for strain analysis and operando neutron imaging for defect characterization and temperature mapping at two different beamlines of the Swiss Spallation Neutron Source. By acquiring diffraction patterns of crack-susceptible materials and tracking the shift of a diffraction peak, the evolution of thermal contributions to elastic strains within a fixed volume can be determined, during processing. Bulk defect characterization is realized by continuously acquiring radiographs during manufacturing. The change in the neutron beam attenuation is correlated with the final microstructure and it confirms the capability of the technique to operando characterize defect formation within the probed bulk. We further demonstrate how using a Beryllium filter and, thus, the long wavelength part of a cold neutron spectrum, allows obtaining spatially and temporally resolved temperature maps during printing of bimetallic composites.

Laser powder bed fusion (LPBF) is a bottom-up manufacturing technique using a high-energy laser to selectively melt metallic alloys, enabling the creation of complex microstructures. While rapid cooling rates and process stochasticity can lead to unpredictable properties, LPBF's layer-wise powder deposition method unlocks unprecedented opportunities for in-situ alloying and microstructure engineering. This work introduces a novel blend of 316 L stainless steel with less than two percent of aluminium, demonstrating the potential for readily tunable microstructures leading to versatile mechanical properties - either as-built or following a post-process heat treatment. Compared to conventional fully austenitic LPBF 316 L, this new alloy solidifies into a combination of large BCC delta-ferrite grains and fine FCC gamma-austenite grains. Medium temperature furnace heat treatments significantly reinforce the BCC phase through the formation of NiAl B2 precipitates, leading to hardness values up to 708 HV. Furthermore, in situ selective laser heat treatments allow the transformation from columnar to equiaxed microstructure in a very short time. This unique alloy therefore appears well suited for tailoring local mechanical properties of phases through appropriate ex situ or in situ heat treatments, paving the way for designing composite-like materials within a single build.

Powder Bed Fusion - Laser Based/Metal (PBF-LB/M), respective Laser powderbed fusion (LPBF) has become a key additive manufacturing method, driving the need for robust monitoring techniques to ensure process stability and reproducibility. In -situ monitoring methods are broadly categorized into optical and acoustic approaches, each with distinct advantages. Acoustic methods, unlike optical ones, can capture emissions from within the substrate and are often more cost-effective. Most PBF-LB/M monitoring systems rely on either airborne or structure -borne sensors, rarely on both. This work demonstrates a dual-sensor system integrating airborne and structure -borne sensors to leverage their complementary strengths for predicting both the process state of a PBF-LB/M-machine and defects (e.g. cracks or delamination, visible via secondary process emissions) occuring during the build. Using a fine-tuned neural network, both sensor types individually, as well as their combination, achieved a classification accuracy of 99 % for predicting the process state based on acquired emissions. Additionally, the structure-borne sensor proved superior in detection of secondary process emissions and slightly more accurate in process state classification. The compact form factor of the structure-borne sensor further enhances system flexibility, making this dual -sensor approach a versatile solution for PBF-LB/M monitoring.

Watchmakers and jewellers are looking for novel 18 carat (ct) gold alloys (75 wt% Au) that combine superior hardness (>= 300 HV) and scratch resistance with the excellent ductility and machinability characteristic of traditional 18 ct Au-Cu-Ag alloys. The Au-Ti system has attracted attention due to the extremely high hardness of the intermetallic compound Ti3Au. We propose a processing route for the development of an 18 carat Au-Ti alloy based on casting with a grain refiner, followed by subsequent thermomechanical treatments. The resulting microstructures were analysed using scanning electron microscopy (SEM), transmission electron microscopy (TEM) and hardness measurements. After homogenisation, the TiAu matrix exhibited a grain size smaller than 100 mu m, medium hardness (similar to 225 HV) and good ductility. Subsequent age-hardening treatments increased the hardness up to similar to 415 HV, but at the expense of ductility, owing to the precipitation of Ti3Au. Cold deformation prior to ageing treatment resulted in a fine and complex microstructure and enhanced hardness to similar to 600 HV, doubling the hardness of conventional 18 ct Au-Cu-Ag alloys. Additionally, the TiAu phase exhibits a martensitic transition at a temperature that depends on the precipitation state. These results highlight the potential of the 18 ct Au-Ti alloy as a new hard 18 ct gold alloy for jewellery and watchmaking applications.

The versatility and flexibility in laser-based layer-wise additive manufacturing processes allow for the fabrication of metallic parts with tailorable mechanical properties. Interest in microstructure control during the process has led to varying applications of laser post-exposure strategies. In this study, in-situ laser heat treatment (LHT) through subsequent laser rescanning on specific layers was performed on 316L and Al-added 316L. In-situ neutron diffraction was carried out in between the LHT steps to qualitatively assess the dislocation density within the probed volume, revealing the influence of process-induced thermal history on the recovery and recrystallization capabilities of these materials. In-situ neutron diffraction during in-situ LHT was realized by using a custom designed laser powder bed fusion system installed on the beamline. Post-mortem measurements followed by microstructural and mechanical analyses shed light on the extensive effect of the in-situ LHT on the final microstructure, validating its ability to promote recovery and recrystallization and, thus, tune the mechanical properties. While microstructural analysis permits observations at the microscopic level, it is destructive, and its local nature may limit reliability. In-situ non-destructive bulk characterization with neutron diffraction enables following the evolutionary process on larger scales, confirming the microstructure evolution phenomena within representative materials volume with greater statistics.

The significant computational expenses associated with simulating the Laser Powder Bed Fusion (LPBF) process often restrict the insights gained from modeling endeavors to specific combinations of process parameters, hindering broader conclusions. In this study, we employ a classical Design of Experiments approach on results obtained by multiphase Finite Element simulations. Utilizing this framework, we derive quadratic metamodels for the dimensions of the melt pool, enabling predictions of melt pool width, depth, and length across a wide spectrum of processing conditions. Notably, our findings indicate that as few as 25 simulations can suffice to predict melt pool dimensions in conduction mode LPBF across varying laser power, velocity, initial temperature, and spot size parameters. Among other insights, the metamodels uncover and quantify the substantial influence of initial temperature (the local temperature of the volume preceding the laser interaction). Additionally, rare insights regarding the melt pool sensitivity towards the laser spot size are provided. Furthermore, our investigation delves into laser interactions with different phases (powder, liquid, solid) across diverse processing conditions to establish a net global absorption coefficient. These analyses underscore that, under conventional process conditions, most of the incident laser intensity falls onto the liquid phase during conduction mode LPBF simulations of 316L stainless steel and Ti-6Al-4V. However, the laser spot size significantly affects the laser intensity interacting with the liquid phase, warranting consideration of laser spot size dependent absorptivity values in part-scale models. Lastly, employing straightforward geometric simulations, we derive a full processing map predicting the occurrence of Lack of Fusion defects, based on calculated melt pool dimensions and the associated scanning strategy.

Powder bed fusion with laser beam (PBF-LB) is a promising additive manufacturing technique that enables the production of complex geometries with fine resolution and material efficiency, offering significant design freedom and material versatility. However, its broader adoption is limited by the need for extensive parameter tuning, which is often dependent on the specific machine, as well as the material and batch of powder used. In this paper, we introduce a novel algorithm that autonomously identifies melting regimes in an unsupervised manner using optical data acquired from photodiodes — specifically optical emission and reflection. This method eliminates the need for labeled data and achieves an F1-score of 89.2% across both materials tested: Ti-6Al-4V and 316L. Additionally, we propose an uncertainty-driven iterative strategy designed to efficiently generate processing maps by performing experiments based on uncertainty. This approach enables up to a 67% reduction in the number of required experiments, significantly lowering the associated costs of parameter exploration, while sustaining a maximum performance reduction of only 8.88% compared to traditional full factorial designs. Our results demonstrate the potential of this method to streamline PBF-LB optimization, making it more feasible for industrial applications and paving the way for its broader adoption.

Laser Powder Bed Fusion (LPBF) stations mostly use lasers with a Gaussian beam intensity distribution, as it has advantages like small divergence and high ability to be focused. This distribution creates significant thermal gradients leading to high cooling rates, which promote the formation of an α’‐martensitic structure in Ti‐6Al‐4V. While this microstructure offers high strength, it sacrifices ductility, necessitating post‐processing heat treatments to decompose the α’‐martensite into an α+β lamellar structure. However, these post‐treatments are time‐consuming, and notably transform the part microstructure in a uniform way. In this study, an advanced laser beam shaping module, based on a liquid crystals on silicon‐spatial light modulator (LCoS‐SLM) is employed, to customize the intensity distribution and reduce the cooling rate with appropriate processing parameters. Thermal camera monitoring, along with finite element modeling (FEM), confirmed a significant reduction in the cooling rate for the tailored beam, compared to the Gaussian profile. This technique is implemented in the LPBF process, resulting in specimens with a mixture of lamellar α+β and α’‐martensitic structures site specifically. Beam shaping is thereby shown to provide new degrees of freedom for fine‐tuning of microstructures at the melt pool scale, and for LPBF building of 3D architected microstructures.

The microstructure evolution associated with the cold forming sequence of an Fe-14Cr-1W-0.3Ti-0.3Y2O3 grade ferritic stainless steel strengthened by dispersion of nano oxides (ODS) was investigated. The material, initially hot extruded at 1100 °C and then shaped into cladding tube geometry via HPTR cold pilgering, shows a high microstructure stability that affects stress release heat treatment efficiency. Each step of the process was analyzed to better understand the microstructure stability of the material. Despite high levels of stored energy, heat treatments, up to 1350 °C, do not allow for recrystallization of the material. The Vickers hardness shows significant variations along the manufacturing steps. Thanks to a combination of EBSD and X-ray diffraction measurements, this study gives a new insight into the contribution of statistically stored dislocation (SSD) recovery on the hardness evolution during an ODS steel cold forming sequence. SSD density, close to 4.1015 m−2 after cold rolling, drops by only an order of magnitude during heat treatment, while geometrically necessary dislocation (GND) density, close to 1.1015 m−2, remains stable. Hardness decrease during heat treatments appears to be controlled only by the evolution of SSD.

This study focuses on investigating Acoustic Emission (AE) monitoring in the Laser Powder Bed Fusion (LPBF) process, using premixed Ti6Al4V-(x wt%) Fe, where x = 0, 3, and 6. By employing a structure-borne AE sensor, we analyze AE data statistically, uncovering notable discrepancies within the 50-750kHz frequency range. Leveraging Machine Learning (ML) methodologies, we accurately predict composition for particular processing conditions. These fluctuations in AE signals primarily arise from unique microstructural alterations linked to martensitic phase transformation, corroborated by operando synchrotron X-ray diffraction and post-mortem SEM and EBSD analysis. Moreover, cracks are evident at the periphery of the printed parts, stemming from local inadequate heat input during the blending of Ti6Al4V with added Fe powder. These cracks are discerned via AE signals subsequent to the cessation of the laser beam, correlating with the presence of brittle intermetallics at their junction. This study highlights for the first time the potential of AE monitoring in reliably detecting footprints of martensitic transformations during the LPBF process. Additionally, AE is shown to prove valuable for assessing crack formations, particularly in scenarios involving premixed powders and necessitating precise selection of processing parameters, notably at part edges.

Small quantities of crystalline domains created in an amorphous matrix are seen as an active driver for enhanced properties in bulk metallic glasses (BMGs). We investigated partial crystallization and phase transformations through a series of isotherms at 370 degrees C performed on amorphous Pd-based BMG samples with the nominal composition of Pd 43 Cu 27 Ni 10 P 20 (Pd-BMG) and a density of 9.425 g/cm3. X-ray based methods such as X-ray diffraction (XRD) and phase enhanced micro-computed tomography (mu-CT) have been pushed to their limits for studying atomic structure and morphology, while time available before crystallization has additionally been investigated via differential scanning calorimetry (DSC), and are combined with optical microscopy (OM), scanning electron microscopy (SEM), and hardness measurements for their mechanical properties. We reveal that Pd-based BMG samples isothermally treated at 370 degrees C start to crystallize after 20 min and still undergo phase transformations and recrystallization even after being fully crystalline after 60 min of the isothermal treatment. Interestingly, 3D phase enhanced micro-computed tomography shows a clear separation of two domains of slightly different densities. We highlight X-ray tomographic scans, allowing the 3D spatial visualization of extremely low-density contrast in different material domains, thus providing a multi-scale physical description of the Pd-BMG system. Interesting is the fact, that the re-crystallization is not homogenous and the crystalline domains can reach large size of (100-200 mu m) in an amorphous matrix.

Titanium-based Metal Matrix Composites (MMCs) manufactured by additive manufacturing offer tremendous lightweighting opportunities. However, processing the high reinforcement contents needed to substantially improve elastic modulus while conserving significant ductility remains a challenge. Ti-TiC MMCs fabricated in this study reported fracture strains in tension up to 1.7% for a Young’s modulus of 149 GPa. This fracture strain is 30% higher than the previously reported values for Ti-based MMCs produced by Laser Powder Bed Fusion (LPBF) displaying similar Young’s moduli. The heat treatment used after the LPBF process leads to the doubling of the fracture strain thanks to the conversion of TiCx dendrites into equiaxed TiCx grains. The as-built microstructure shows both un-dissolved TiC particles and sub-stoichiometric TiC dendrites resulting from the partial dissolution of TiC particles. The reduction of the C/Ti ratio in TiC during the process results in an increase in the reinforcement content, from a nominal 12 vol% to an effective 21.5 vol%. The variation of the TiC lattice constant with its stoichiometry is measured, and an empirical expression is proposed for its effect on TiC’s Young’s modulus. The lower TiC powder size distribution displayed higher mechanical properties thanks to a reduced number of intrinsic flaws.

Laser metal additive manufacturing has the potential to revolutionize the production of complex geometries with high precision across various industrial applications. To optimize the reliability of the process, a detailed understanding of the melt pool dynamics during the process is essential, particularly in the nearly pore-free regimes. In this study, the melt pool dynamics across conduction mode to keyhole mode in laser powder bed fusion processing of stainless steel 316L have been investigated by means of in-situ synchrotron X-ray imaging utilizing tungsten particles as tracers. The spatial distribution of the fluid flow in the melt pool has been quantified with a resolution of ~10 µm through automatic tracing all moving particles in the melt pool. The results identified the influence of the interplay between laser power and scanning speed on melt flow velocities. The measurements also revealed a pronounced impact of the inward Marangoni convection on the conduction-keyhole threshold, offering a new degree of freedom to broaden the pore-free process window of laser-based additive manufacturing. These findings contribute to a more comprehensive understanding of the melt pool dynamics during laser metal additive manufacturing and provide a valuable reference for calibrating high-fidelity computational fluid dynamics models.