Laser powder bed fusion additive manufacturing is an emerging 3D printing technique for the fabrication of advanced metal components. Widespread adoption of it and similar additive technologies is ...hampered by poor understanding of laser-metal interactions under such extreme thermal regimes. Here, we elucidate the mechanism of pore formation and liquid-solid interface dynamics during typical laser powder bed fusion conditions using in situ X-ray imaging and multi-physics simulations. Pores are revealed to form during changes in laser scan velocity due to the rapid formation then collapse of deep keyhole depressions in the surface which traps inert shielding gas in the solidifying metal. We develop a universal mitigation strategy which eliminates this pore formation process and improves the geometric quality of melt tracks. Our results provide insight into the physics of laser-metal interaction and demonstrate the potential for science-based approaches to improve confidence in components produced by laser powder bed fusion.
Many traditional approaches for strengthening steels typically come at the expense of useful ductility, a dilemma known as strength-ductility trade-off. New metallurgical processing might offer the ...possibility of overcoming this. Here we report that austenitic 316L stainless steels additively manufactured via a laser powder-bed-fusion technique exhibit a combination of yield strength and tensile ductility that surpasses that of conventional 316L steels. High strength is attributed to solidification-enabled cellular structures, low-angle grain boundaries, and dislocations formed during manufacturing, while high uniform elongation correlates to a steady and progressive work-hardening mechanism regulated by a hierarchically heterogeneous microstructure, with length scales spanning nearly six orders of magnitude. In addition, solute segregation along cellular walls and low-angle grain boundaries can enhance dislocation pinning and promote twinning. This work demonstrates the potential of additive manufacturing to create alloys with unique microstructures and high performance for structural applications.
State-of-the-art metal 3D printers promise to revolutionize manufacturing, yet they have not reached optimal operational reliability. The challenge is to control complex laser-powder-melt pool ...interdependency (dependent upon each other) dynamics. We used high-fidelity simulations, coupled with synchrotron experiments, to capture fast multitransient dynamics at the meso-nanosecond scale and discovered new spatter-induced defect formation mechanisms that depend on the scan strategy and a competition between laser shadowing and expulsion. We derived criteria to stabilize the melt pool dynamics and minimize defects. This will help improve build reliability.
With the growing interest in metal additive manufacturing using laser powder bed fusion (LPBF), there is a need for advanced in-situ nondestructive evaluation (NDE) methods that can dynamically ...monitor manufacturing process-related variations, that can be used as a feedback mechanism to further improve the manufacturing process, leading to parts with improved microstructural properties and mechanical properties. Current NDE techniques either lack sensitivity beyond build layer, are costly or time-consuming, or are not compatible for in-situ integration. In this research, we develop an electrical resistance diagnostic for in-situ monitoring of powder fused regions during laser powder bed fusion printing. The technique relies on injecting current into the build plate and detecting voltage differences from conductive variations during printing using a simple, cheap four-point electrode array directly connected to the build plate. A computational model will be utilized to determine sensitivities of the approach, and preliminary experiments will be performed during the printing process to test the overall approach.
Thermoelectric (TE) materials convert heat energy directly into electricity, and introducing new materials with high conversion efficiency is a great challenge because of the rare combination of ...interdependent electrical and thermal transport properties required to be present in a single material. The TE efficiency is defined by the figure of merit ZT=(S2σ) T/κ, where S is the Seebeck coefficient, σ is the electrical conductivity, κ is the total thermal conductivity, and T is the absolute temperature. A new p‐type thermoelectric material, CsAg5Te3, is presented that exhibits ultralow lattice thermal conductivity (ca. 0.18 Wm−1 K−1) and a high figure of merit of about 1.5 at 727 K. The lattice thermal conductivity is the lowest among state‐of‐the‐art thermoelectrics; it is attributed to a previously unrecognized phonon scattering mechanism that involves the concerted rattling of a group of Ag ions that strongly raises the Grüneisen parameters of the material.
A p‐type thermoelectric material, CsAg5Te3, is presented. It exhibits ultralow thermal conductivity (ϰtol≈0.18 Wm−1 K−1) and a high figure of merit (ZT≈1.5 at 727 K). The low thermal conductivity is attributed to a previously unrecognized phonon scattering mechanism that involves the rattling of Ag ions, strongly raising the Grüneisen parameters of the material.
Structures formed by advanced manufacturing methods increasingly require nondestructive characterization to enable efficient fabrication and to ensure performance targets are met. This is especially ...important for aerospace, military, and high precision applications. Surface acoustic waves (SAW) generated by laser-based ultrasound can detect surface and sub-surface defects relevant for a broad range of advanced manufacturing processes, including laser powder bed fusion (LPBF). In particular, an all-optical SAW generation and detection configuration can effectively interrogate laser melt lines. Here we report on scattered acoustic energy from melt lines, voids, and surface features. Sub-surface voids are also characterized using X-ray Computed Tomography (CT). High resolution CT results are presented and compared with SAW measurements. Finite difference simulations inform experimental measurements and analysis.
•A machine learning autoencoder has shown utility in denoising electron backscatter diffraction patterns.•Usage of the denoised patterns results in gains to pattern indexing confidence, fit accuracy, ...and image quality.•Implementing denoising prior to Hough-transform enables a more robust EBSD indexing procedure.•Enables the use of noisier datasets and faster data collection rates, wider area, higher resolution EBSD.•Improved degree of fit accuracy results in more reliable strain cross-correlation data.
The rapid collection and indexing of electron diffraction patterns as produced via electron backscatter diffraction (EBSD) has enabled crystallographic orientation and structural determination, as well as additional property-determining strain and dislocation density information with increasing speed, resolution, and efficiency. Pattern indexing quality is reliant on the noise of the collected electron diffraction patterns, which is often convoluted by sample preparation and data collection parameters. EBSD acquisition is sensitive to many factors and thus can result in low confidence index (CI), poor image quality (IQ), and improper minimization of fit, which can result in noisy datasets and misrepresent the microstructure. In an attempt to enable both higher speed EBSD data collection and enable greater orientation fit accuracy with noisy datasets, an image denoising autoencoder was implemented to improve pattern quality. We show that EBSD data processed through the autoencoder results in a higher CI, IQ, and a more accurate degree of fit. In addition, using denoised datasets in HR-EBSD cross correlative strain analysis can result in reduced phantom strain from erroneous calculations due to the increased indexing accuracy and improved correspondence between collected and simulated patterns.
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Laser powder bed fusion (LPBF) is a method of additive manufacturing characterized by the rapid scanning of a high powered laser over a thin bed of metallic powder to create a single layer, which may ...then be built upon to form larger structures. Much of the melting, resolidification, and subsequent cooling take place at much higher rates and with much higher thermal gradients than in traditional metallurgical processes, with much of this occurring below the surface. We have used in situ high speed X-ray diffraction to extract subsurface cooling rates following resolidification from the melt and above the β-transus in titanium alloy Ti-6Al-4V. We observe an inverse relationship with laser power and bulk cooling rates. The measured cooling rates are seen to correlate to the level of residual strain borne by the minority β-Ti phase with increased strain at slower cooling rates. The α-Ti phase shows a lattice contraction which is invariant with cooling rate. We also observe a broadening of the diffraction peaks which is greater for the β-Ti phase at slower cooling rates and a change in the relative phase fraction following LPBF. These results provide a direct measure of the subsurface thermal history and demonstrate its importance to the ultimate quality of additively manufactured materials.
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