In this study, we investigated the microstructural variation of Ti-6Al-4 V in inverted pyramid parts built using Laser Powder Bed Fusion (LPBF). Two parts were fabricated with and without ghost parts to study the effects of interlayer delay time on thermal history and microstructure. Finite Element Method (FEM) based process simulation was used to predict the thermal history and cooling rates during the LPBF process to understand the location-specific microstructure and mechanical properties variation. The thermal analysis findings revealed that the variations in the cooling rates and pre-deposition temperature were notably significant. Within the same part, the cooling rates exhibited significant variations, differing by up to three orders of magnitude in two scenarios: (1) within the same layer, influenced by the proximity to the edges, and (2) at different heights, attributable to the strongly varying cross-section. Comparing the two parts, the cooling rates of the part with ghost parts were approximately two orders of magnitude higher than in the part without the ghost parts. This significant difference can be attributed to the extended interlayer cooling time and lower pre-deposition temperature resulting from the presence of two ghost parts which introduced an effective delay time between laser scans. Experimental validation against microstructure images and hardness measurements showed similar trends with the predicted results. These findings provide valuable insights into controlling microstructure at specific locations during LPBF fabrication, which is essential for building complex geometries with controlled material properties.

The three-dimensional grain-averaged response of solid bar samples under non-proportional (NP) elastoplastic axial-torsional loading was investigated using in situ high energy diffraction microscopy (HEDM) and companion crystal plasticity finite element (CPFE) modeling. Important stress metrics including applied shear ( sigma theta Z ) and axial ( sigma ZZ ) stress tensor components, stress and stress deviator tensor invariants (I 1 , J 2 , and J 3 ), von Mises equivalent stress ( sigma grain VM ), maximum resolved shear stress (mRSS), stress triaxiality ( eta), and lode angle parameter ( theta) values were tracked for300 grains under two different loading conditions: (1) Torsion-dominated loading (low NP) and (2) Tension-torsion loading (high NP) in equiatomic NiCoCr, a representative multicomponent face-centered cubic (FCC) superalloy. Overall, significant stress localizations existed within both samples as evidenced by the radial dependence of grain-resolved sigma theta Z , sigma grain VM , and J 2 ; by comparison, I 1 , J 3 , eta, and theta metrics did not show discernible trends within the volume. These stress localizations reveal a complex interplay between axial and shear stress components (e.g., stress coupling) resulting in grain yielding near the sample surface largely driven by shear stress, whereas internal grain yielding was largely accommodated by axial stress. Grain-resolved stress localization trends were described well by the CPFE model, although some discrepancies in magnitude occurred, particularly for volumetric stress metrics (I 1 and eta) due to initial type II residual stress distributions. The superposition of initial residual stress states onto CPFE grain-resolved data significantly improved model accuracy for eta. This suggests that residual stresses more strongly influence the simulation of volumetric rather than deviatoric (yield) stress metrics.

Powder bed fusion-laser beam (PBF-LB) parts experience a significant decline in fatigue performance when process-induced defects are present. In this work, a decline in 4-point bend fatigue life was observed in PBFLB Ti-6Al-4V coupons fabricated at constant power with increasing scanning velocity and which underwent subsequent stress relief and surface machining. Specifically, the presence of pores that resemble lack-of-fusion (LoF) and a decline in fatigue life were observed at scanning velocities lower than that expected from prior published work. It was hypothesized that this unexpected presence of LoF pores resulted from melt pool geometry variability that was not considered in prior work when the LoF criterion was implemented. Further, these pores can be small in size and infrequent in their occurrence when the melt pool geometry variability is not severe. Such sparse pores are challenging to characterize using conventional 2D characterization methods. This work leverages tall and narrow coupon geometry and high-resolution X-ray micro computed tomography (X-mu CT) to capture LoF porosity. The results show that a modified melt pool overlap-based LoF criterion considering melt pool geometry variability captures the unexpected occurrence of LoF pores observed in X mu CT. In addition, the LoF percent metric displays a strongly negative correlation with fatigue performance. The insights from this work provide guidance on characterizing melt pool geometry variability across scan lines to systematically evaluate processing parameters that generate LoF pores, which, in turn, could lower fatigue performance.

Laser hot wire directed energy deposition (LHW-DED) is a layer-by-layer additive manufacturing technique that permits the fabrication of large-scale Ti-6Al-4V (Ti64) components with a high deposition rate and has gained traction in the aerospace sector in recent years. However, one of the major challenges in LHW-DED Ti64 is heat accumulation, which affects the part quality, microstructure, and properties of as-built specimens. These issues require a comprehensive understanding of the layerwise heat-accumulation-driven process-structure-property relationship in as-deposited samples. In this study, a systematic investigation was performed by fabricating three Ti-6Al-4V single-wall specimens with distinct interlayer delays, i.e., 0, 120, and 300 s. The real-time acquisition of high-fidelity thermal data and high-resolution melt pool images were utilized to demonstrate a direct correlation between layerwise heat accumulation and melt pool dimensions. The results revealed that the maximum heat buildup temperature of the topmost layer decreased from 660 degrees C to 263 degrees C with an increase to a 300 s interlayer delay, allowing for better control of the melt pool dimensions, which then resulted in improved part accuracy. Furthermore, the investigation of the location-specific composition, microstructure, and mechanical properties demonstrated that heat buildup resulted in the coarsening of microstructures and, consequently, the reduction of micro-hardness with increasing height. Extending the delay by 120 s resulted in a 5\% improvement in the mechanical properties, including an increase in the yield strength from 817 MPa to 859 MPa and the ultimate tensile strength from 914 MPa to 959 MPa. Cooling rates estimated at 900 degrees C using a one-dimensional thermal model based on a numerical method allowed us to establish the process-structure-property relationship for the wall specimens. The study provides deeper insight into the effect of heat buildup in LHW-DED and serves as a guide for tailoring the properties of as-deposited specimens by regulating interlayer delay.

We report on the implementation of a high frequency beam oscillation (wobbling) strategy for improving process control during laser powder bed fusion of single weld tracks on Inconel 625. Oscillation frequencies ranging from ~ 600 Hz to 7000 Hz, and different oscillation trajectories (circular, parallel or perpendicular to the direction of scanning) were explored. Highspeed imaging was used to elucidate the dynamics of the melt pool induced by the wobble beams, along with in situ absorptivity measurements to substantiate our hypothesis that the dynamic nature of wobble beams reduces absorptive losses due to laser-vapor interactions and results in improved coupling at the melt pool. Operando X-ray radiography was carried out to visualize sub-surface melt flow dynamics, correlate to spatter mechanisms and optimize the window for improving process stability. Our observations indicate that wobble beams increase the aspect ratio of the melt pool by up to 4×, depending on the oscillation frequency and energy input. Highspeed imaging and X-ray radiography reveal an optimized process parameter window for reducing spatter, improving absorptivity and creating a stable melt pool at high (several kHz) oscillation frequencies.

Processing defects remain the primary cause for fatigue failure of laser beam powder bed fusion (PBF-LB) produced components. Accordingly, process mapping methodologies have been extensively developed to identify optimal processing parameters to avoid defects. For structure-critical applications, it is necessary to validate the defect-based process map through fatigue testing. We quantify the defect structure (porosity) process map for PBF-LB Ti-6Al-4V based on defect populations and fatigue properties. The defect populations were measured in samples fabricated at constant power and small increments in scanning velocity using X-ray micro-computed tomography and 2D metallography and analyzed using a number density approach. Furthermore, 4-point bend fatigue testing was used to establish stress-cycles to failure properties. Our results reveal distinct defect populations in both keyhole and lack-of-fusion defect regimes, with continuous variation in defect density. The number density-based defect size quantity strongly correlates with process parameters, peak stress, and initiating defect size, offering a quantitative approach to establish process-defect-fatigue relationships. We conclude that the process window exists just as clearly for fatigue as it does for defects, although more sensitive to variability in defects. Consequently, within this fatigue-based process window, one can expect to consistently produce dense components with superior fatigue properties.

A Fast Fourier Transform (FFT)-based viscoplasticity simulation is performed to study the microstructure-property relationship of the unit cell metal-metal composites. Three-dimensional digital unit cell composites, composed of single-crystalline hard BCC particles at regular positions and a single-crystalline soft FCC matrix, are used as instantiations to calculate the stress and strain-rate fields under uniaxial tension. Such regular unit cell composites are generated by growing particles from either simple cubic, body centered cubic or face centered cubic grid points, having particle volume fractions from 0.1 to 0.9. Topologically, each type of regular unit cell is found to be unique. Moreover, its topological measures change drastically once particles initiate simultaneous contacts. While the macroscopic mechanical behavior as a function of the particle volume fraction is insensitive to the type of the unit cell, the local micromechanical response of each phase shows a strong dependence both on the morphological evolution as a function of the particle volume fraction as well as on the type of the unit cell. However, such morphological effects on the local mechanical response weaken when the matrix has a hard crystallographic orientation with respect to the tension direction. No single determining microstructural feature could by itself explain the complex variation in the micromechanical response of the unit cell composite.

Laser powder bed fusion is a mainstream additive manufacturing technology widely used to manufacture complex parts in prominent sectors, including aerospace, biomedical, and automotive industries. However, during the printing process, the presence of an unstable vapor depression can lead to a type of defect called keyhole porosity, which is detrimental to the part quality. In this study, we developed an effective approach to locally detect the generation of keyhole pores during the printing process by leveraging machine learning and a suite of optical and acoustic sensors. Simultaneous synchrotron x-ray imaging allows the direct visualization of pore generation events inside the sample, offering high-fidelity ground truth. A neural network model adopting SqueezeNet architecture using single-sensor data was developed to evaluate the fidelity of each sensor for capturing keyhole pore generation events. Our comparative study shows that the near infrared images gave the highest prediction accuracy, followed by 100 kHz and 20 kHz microphones, and the photodiode sensitive to processing laser wavelength had the lowest accuracy. Using a single sensor, over 90\% prediction accuracy can be achieved with a temporal resolution as short as 0.1 ms. A data fusion scheme was also developed with features extracted using SqueezeNet neural network architecture and classification using different machine learning algorithms. Our work demonstrates the correlation between the characteristic optical and acoustic emissions and the keyhole oscillation behavior, and thereby provides strong physics support for the machine learning approach.

To investigate the difference between ionic and electronic conductors as infiltrates in solid oxide fuel cells (SOFCs), high -throughput and high-performance finite element simulations were carried out on 51 different cathode microstructures. Five cathode backbones, reconstructed from a commercial SOFC, were infiltrated computationally with varying number densities of nanoscale electronically or ionically conducting particles. Local electrochemical quantities were computed within the volumetric meshes that represent the complex 3D microstructural morphologies that include the infiltrated particles. As infiltrates, ionic conductors improve the performance more than electronic conductors. By differentiating transport and reaction pathways originating from backbone phases and infiltrates, we show that new ionic transport pathways opened by the ionically conducting infiltrates are the origin of this difference. These new transport paths redistribute current throughout the cathode, thereby increasing (decreasing) the available local activation (Ohmic) overpotential at triple phase boundaries and rendering them more active than for the case of electronic conductors as infiltrates. These results give us insight to engineering improved electrodes for SOFCs via infiltration with surface active nano -particles.

Composed of individual unit cells strategically arranged to achieve a desired function, lattices are a promising solution for laser powder bed fusion support structure design in additive manufacturing. Despite their many advantages (e.g., multifunctionality and reduced material cost), prior work in lattice support structure design primarily focuses on horizontal support domains that are not translatable to support domains for complex geometries, thereby limiting their application. This work introduces a multi-sized unit cell design optimization (MSO) method to create lattice support structures (LSS) for parts with complex geometries. The proposed method utilizes voxelization to generate LSS using box-like unit cells of different sizes. It also allows for efficient, high-dimensional design optimization for the types and locations of user-specified unit cells through a modified simulated annealing-based optimization algorithm. The effectiveness and efficiency of the MSO method are demonstrated through the case study of an adapter pipe for a high-temperature heat exchanger. For this demonstration, LSS using multi-sized unit cells is designed to increase heat transfer rate while satisfying structural integrity and material cost constraints. The case study results indicate that the design of the LSS derived from the MSO method fulfills all constraints, including the design constraint of 50\% material cost reduction, compared to the solid support structure. In contrast, the lattice support structure designs derived from equal-sized unit cell methods either cannot satisfy all design constraints or have a lower heat transfer rate than the design of the MSO method.