The competition between epitaxial vs. equiaxed solidification has been investigated in CMSX-4 single crystal superalloy during laser melting as practiced in additive manufacturing. Single-track laser scans were performed on a powder-free surface of directionally solidified CMSX-4 alloy with several combinations of laser power and scanning velocity. Electron backscattered diffraction (EBSD) mapping facilitated identification of new orientations, i.e., stray grains that nucleated within the fusion zone along with their area fraction and spatial distribution. Using high-fidelity computational fluid dynamics simulations, both the temperature and fluid velocity fields within the melt pool were estimated. This information was combined with a nucleation model to determine locations where nucleation has the highest probability to occur in melt pools. In conformance with general experience in metals additive manufacturing, the as-solidified microstructure of the laser-melted tracks is dominated by epitaxial grain growth; nevertheless, stray grains were evident in elongated melt pools. It was found that, though a higher laser scanning velocity and lower power are generally helpful in the reduction of stray grains, the combination of a stable keyhole and minimal fluid velocity further mitigates stray grains in laser single tracks.

This work utilized computer vision and machine learning techniques to predict both qualitative characteristics and quantitative values, from SEM images of Ti—6Al—4V fracture surfaces from compact tension specimen fatigue crack growth tests. This work found that Convolutional Neural Networks (CNNs) focused on different features in images based on the length scale of the image. This study determined a lower limit field of view related to the number of grains imaged, and confirmed that transfer learning of a pre-trained CNN can distinguish between two forging direction and two different load ratios, and predict crack length, a, and repurposed for ΔK, and dadN.

Porosity defects are currently a major factor that hinders the widespread adoption of laser-based metal additive manufacturing technologies. One common porosity occurs when an unstable vapor depression zone (keyhole) forms because of excess laser energy input. With simultaneous high-speed synchrotron x-ray imaging and thermal imaging, coupled with multiphysics simulations, we discovered two types of keyhole oscillation in laser powder bed fusion of Ti-6Al-4V. Amplifying this understanding with machine learning, we developed an approach for detecting the stochastic keyhole porosity generation events with submillisecond temporal resolution and near-perfect prediction rate. The highly accurate data labeling enabled by operando x-ray imaging allowed us to demonstrate a facile and practical way to adopt our approach in commercial systems. Laser fusion techniques build metal parts through a high-energy melting process that too often creates structural defects in the form of pores. Ren et al. used x-rays to track the formation of these pores while also making observations with a thermal imaging system. This setup allowed the authors to develop a high-accuracy method for detecting pore formation from that thermal signature with the help of a machine learning method. Implementing this sort of tracking of pore formation would help avoid building parts with high porosity that are more likely to fail. ?BG Thermal imaging can detect pore formation during laser powder bed fusion, helping to ensure quality control.

Hot cracking as the major concern in the manufacturing process of metal alloys is detrimental to part performance and can lead to catastrophic failure. However, current research in this field is restricted to the scarcity of the relevant hot cracking susceptibility data. Here, using the DXR technique provided at 32-ID-B beamline of Advanced Photon Source (APS) at Argonne National Laboratory, we characterized the hot cracking formation in Laser Powder Bed Fusion (L-PBF) process for ten commercial alloys (Al7075, Al6061, Al2024, Al5052, Haynes 230, Haynes 160, Haynes X, Haynes 120, Haynes 214, and Haynes 718). The extracted DXR images captured the post-solidification hot cracking distribution and allow the quantification of the hot cracking susceptibility of those alloys. We further exploited this in our recent effort on hot cracking susceptibility prediction $[$1$]$ and established a hot cracking susceptibility dataset posted on Mendeley Data for the purpose of facilitating the relevant research in this field.

The metal additive manufacturing industry is actively developing instruments and strategies to enable higher productivity, optimal build quality, and controllable as-built microstructure. A beam controlling technique, laser oscillation has shown potential in all these aspects in laser welding; however, few attempts have been made to understand the underlying physics of the oscillating keyholes/melt pools which are the prerequisites for these strategies to become a useful tool for laser-based additive manufacturing processes. Here, to address this gap, we utilized a synchrotron-based X-ray operando technique to image the dynamic keyhole oscillation in Ti-6Al-4V using a miniature powder bed fusion setup. We found good agreement between the experimental observations and simulations performed with a validated Lattice Boltzmann multiphysics model. The study revealed the continuous and periodic fluctuations in the characteristic keyhole parameters that are unique to the oscillating laser beam processing and responsible for the chevron pattern formation at solidification. In particular, despite the intrinsic longer-range fluctuation, the oscillating technique displayed potential for reducing keyhole instability, mitigating porosity formation, and altering surface topology. These insights on the oscillating keyhole dynamics can be useful for the future development and application of this technique.

The aim of this manuscript is to give a compact overview of the results that illustrate the applicability of processing-structure-property relationships in the increasingly important context of 3D printing of metals. A process qualification approach based on the physics-based understanding of defect formation in laser powder bed fusion (L-PBF) additive manufacturing (AM) is investigated for an aerospace-grade titanium alloy (Ti-6Al-4V). A physically interpretable qualification approach is critical for enabling L-PBF part certification for structure-critical applications. This approach relies on systematic experimentation, characterization, testing, and data analysis tasks including design of experiments varying power and velocity to generate varying defect populations, process window development based on defect structure, high throughput fatigue testing, and fractography, 2D porosity characterization, and use of extreme value statistics to develop a porosity metric that, in turn, could have predictive power for the variation in fatigue performance. Results from four-point bend fatigue tests demonstrate that a process window can be defined based on this key mechanical property. This relatively high throughput approach can, in turn, support a reduced set of round bar fatigue tests typically used for qualification. Overall, the proposed ecosystem for process qualification of L-PBF AM shows promise and is expected to apply to other materials and powder bed fusion AM technologies.

The structural design and additive manufacturing (AM) of cross-flow heat exchangers (HXs) are studied. A unit-based design framework is proposed to optimize the channel configuration in order to improve the heat exchange performance (HXP) and meanwhile control the pressure drop (PD) between the fluid inlet and outlet. A gradient-based optimization methodology is employed to drive the design process. Both shape and topology changes are observed during the channel configuration evolution. Moreover, AM printability evaluation is considered and some re-design work is proposed to improve the printability of the designs with respect to the metal laser powder bed fusion (LPBF) process. For an optimized structure from the unit-based design, corner rounding operation is adopted first, specifically to avoid sharp features. Then the building process of the entire HX containing top, bottom caps, side walls, and the optimized thin-walled channels is simulated, and residual deformation is predicted through sequential layer-by-layer analysis. Based on the residual deformation profile, geometrical compensation is implemented to reduce geometrical inaccuracy of the printed HX. In addition, build orientation selection is also studied to avoid overhang issues in some specific unit-based design results. Finally, a mature design scheme for the cross-flow HX can be achieved as the solution that leads to largely improved HXP (e.g., nearly 200\% increase), well controlled PD, and enhanced printability with respect to the LPBF AM process.

The aim of this manuscript is to give a compact overview of the results that illustrate the applicability of processing-structure-property relationships in the increasingly important context of 3D printing of metals. A process qualification approach based on the physics-based understanding of defect formation in laser powder bed fusion (L-PBF) additive manufacturing (AM) is investigated for an aerospace-grade titanium alloy (Ti-6Al-4V). A physically interpretable qualification approach is critical for enabling L-PBF part certification for structure-critical applications. This approach relies on systematic experimentation, characterization, testing, and data analysis tasks including design of experiments varying power and velocity to generate varying defect populations, process window development based on defect structure, high throughput fatigue testing, and fractography, 2D porosity characterization, and use of extreme value statistics to develop a porosity metric that, in turn, could have predictive power for the variation in fatigue performance. Results from four-point bend fatigue tests demonstrate that a process window can be defined based on this key mechanical property. This relatively high throughput approach can, in turn, support a reduced set of round bar fatigue tests typically used for qualification. Overall, the proposed ecosystem for process qualification of L-PBF AM shows promise and is expected to apply to other materials and powder bed fusion AM technologies.

The current study revealed that the development of γ-fibre texture in IF-steel through static recrystallisation alters the distribution of grain boundary misorientations and plane orientations. In the initial transformed condition, the grain boundary plane distribution has a maximum at the (110) orientation. However, as the intensity of the γ-fibre texture increased, the maximum shifted to (111) and intensified. Furthermore, the presence of γ-fibre texture gradually increased the low angle boundary population at the expense of high angle boundaries, leading to a nearly uniform misorientation angle distribution. A calculation of the disorientation distribution assuming random orientations along the γ-fibre showed a flat distribution in the domain from 0 to 60$\,^\circ$, consistent with the observations. The presence of γ-fibre texture changed the intensity, but not the shape of the grain boundary distribution at ∑3 = 60$\,^\circ$/[111], which displayed maxima at low energy 112 symmetric tilt boundaries.

Advances in manufacturing technologies and materials are crucial to the commercial deployment of energy technologies. We present the case of concentrating solar power (CSP) with molten salt (MS) thermal storage, where low-cost, high-efficiency heat exchangers (HXs) are needed to achieve cost competitiveness. The materials required to tolerate the extreme operating conditions in CSP systems make it difficult or infeasible to produce them using conventional manufacturing processes. Although it is technically possible to produce HXs with adequate performance using additive manufacturing, specifically laser powder bed fusion (LPBF), here we assess whether doing so is cost-effective. We describe a process-based cost model (PBCM) to estimate the cost of fabricating a MS-to-supercritical carbon dioxide HX using LPBF. The PBCM is designed to identify modifications to designs, process choices, and manufacturing innovations that have the greatest effect on manufacturing cost. Our PBCM identified HX design and LPBF process modifications that reduced projected HX cost from \$750 per kilo-Watt thermal (kW-th) (\$8/cm3) to \$350/kW-th (\$6/cm3) using currently available LPBF technology, and down to \$220/kW-th (\$4/cm3) with improvements in LPBF technology that are likely to be achieved in the near term. The PBCM also informed a redesign of the HX design that reduced projected costs to \$140?160/kW-th (\$3/cm3).