Additively manufactured hierarchical stainless steels with high strength and ductility.

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.

Interference effects in laser-induced plasma emission from surface-bound metal micro-particles.

The light-matter interaction of an optical beam and metal micro-particulates at the vicinity of an optical substrate surface is critical to the many fields of applied optics. Examples of impacted fields are laser-induced damage in high power laser systems, sub-wavelength laser machining of transmissive materials, and laser-target interaction in directed energy applications. We present a full-wave-based model that predicts the laser-induced plasma pressure exerted on a substrate surface as a result of light absorption in surface-bound micron-scale metal particles. The model predictions agree with experimental observation of laser-induced shallow pits, formed by plasma emission and etching from surface-bound metal micro-particulates. It provides an explanation for the prototypical side lobes observed along the pit profile, as well as for the dependence of the pit shape on the incident laser and particle parameters. Furthermore, the model highlights the significance of the interference of the incident light in the open cavity geometry formed between the micro-particle and the substrate in the resulting pit shape.

Diode-based additive manufacturing of metals using an optically-addressable light valve.

Selective Laser Melting (SLM) of metal powder bed layers, whereby 3D metal objects can be printed from a digital file with unprecedented design flexibility, is spurring manufacturing innovations in medical, automotive, aerospace and textile industries. Because SLM is based on raster-scanning a laser beam over each layer, the process is relatively slow compared to most traditional manufacturing methods (hours to days), thus limiting wider spread use. Here we demonstrate the use of a large area, photolithographic method for 3D metal printing, using an optically-addressable light valve (OALV) as the photomask, to print entire layers of metal powder at once. An optical sheet of multiplexed ~5 kW, 20 ms laser diode and ~1 MW, 7 ns Q-switched laser pulses are used to selectively melt each layer. The patterning of near infrared light is accomplished by imaging 470 nm light onto the transmissive OALV, which consists of polarization-selective nematic liquid crystal sandwiched between a photoconductor and transparent conductor for switching.

Laser-induced Hertzian fractures in silica initiated by metal micro-particles on the exit surface.

Laser-induced Hertzian fractures on the exit surface of silica glass are found to result from metal surface-bound micro particles. Two types of metal micro-spheres are studied (stainless-steel and Al) using ultraviolet laser light. The fracture initiation probability curve as a function of fluence is obtained, resulting in an initiation threshold fluence of 11.1 ± 4.7 J/cm2 and 16.5 ± 4.5 J/cm2 for the SS and Al particles, accordingly. The modified damage density curve is calculated based on the fracture probability. The calculated momentum coupling coefficient linking incident laser fluence to the resulting plasma pressure is found to be similar for both particles: 32.6 ± 15.4 KN/J and 28.1 ± 10.4 KN/J for the SS and Al cases accordingly.

Utilizing dynamic laser speckle to probe nanoscale morphology evolution in nanoporous gold thin films.

This paper demonstrates the use of dynamic laser speckle autocorrelation spectroscopy in conjunction with the photothermal treatment of nanoporous gold (np-Au) thin films to probe nanoscale morphology changes during the photothermal treatment. Utilizing this spectroscopy method, backscattered speckle from the incident laser is tracked during photothermal treatment and both the characteristic feature size and annealing time of the film are determined. These results demonstrate that this method can successfully be used to monitor laser-based surface modification processes without the use of ex-situ characterization.

Mechanisms governing the interaction of metallic particles with nanosecond laser pulses.

The interaction of nanosecond laser pulses at 1064- and 355-nm with micro-scale, nominally spherical metallic particles is investigated in order to elucidate the governing interaction mechanisms as a function of material and laser parameters. The experimental model used involves the irradiation of metal particles located on the surface of transparent plates combined with time-resolved imaging capable of capturing the dynamics of particle ejection, plume formation and expansion along with the kinetics of the dispersed material from the liquefied layer of the particle. The mechanisms investigated in this work are informative and relevant across a multitude of materials and irradiation geometries suitable for the description of a wide range of specific applications. The experimental results were interpreted using physical models incorporating specific processes to assess their contribution to the overall observed behaviors. Analysis of the experimental results suggests that the induced kinetic properties of the particle can be adequately described using the concept of momentum coupling introduced to explain the interaction of plane metal targets to large-aperture laser beams. The results also suggest that laser energy deposition on the formed plasma affects the energy partitioning and the material modifications to the substrate.

Damage on fused silica optics caused by laser ablation of surface-bound microparticles.

High peak power laser systems are vulnerable to performance degradation due to particulate contamination on optical surfaces. In this work, we show using model contaminant particles that their optical properties decisively determine the nature of the optical damage. Borosilicate particles with low intrinsic optical absorption undergo ablation initiating in their sub-surface, leading to brittle fragmentation, distributed plasma formation, material dispersal and ultimately can lead to micro-fractures in the substrate optical surface. In contrast, energy coupling into metallic particles is highly localized near the particle-substrate interface leading to the formation of a confined plasma and subsequent etching of the substrate surface, accompanied by particle ejection driven by the recoil momentum of the ablation plume. While the tendency to create fractured surface pitting from borosilicate is stochastic, the smooth ablation pits created by metal particles is deterministic, with pit depths scaling linearly with laser fluence. A simple model is employed which predicts ~3x electric field intensity enhancement from surface-bound fragments. In addition, our results suggest that the amount of energy deposited in metal particles is at least twice that in transparent particles.

Light scattering from laser induced pit ensembles on high power laser optics.

Far-field light scattering characteristics from randomly arranged shallow Gaussian-like shaped laser induced pits, found on optics exposed to high energy laser pulses, is studied. Closed-form expressions for the far-field intensity distribution and scattered power are derived for individual pits and validated using numerical calculations of both Fourier optics and FDTD solutions to Maxwell's equations. It is found that the scattered power is proportional to the square of the pit width and approximately also to the square of the pit depth, with the proportionality factor scaling with pit depth. As a result, the power scattered from shallow pitted optics is expected to be substantially lower than assuming complete scattering from the total visible footprint of the pits.

Characterization of laser-induced plasmas associated with energetic laser cleaning of metal particles on fused silica surfaces.

Time-resolved plasma emission spectroscopy was used to characterize the energy coupling and temperature rise associated with single, 10-ns pulsed laser ablation of metallic particles bound to transparent substrates. Plasma associated with Fe(I) emission lines originating from steel microspheres was observed to cool from >24,000 to ~15,000 K over ~220 ns as τ(-0.28), consistent with radiative losses and adiabatic gas expansion of a relatively free plasma. Simultaneous emission lines from Si(II) associated with the plasma etching of the SiO(2) substrate were observed yielding higher plasma temperatures, ~35,000 K, relative to the Fe(I) plasma. The difference in species temperatures is consistent with plasma confinement at the microsphere-substrate interface as the particle is ejected, and is directly visualized using pump-probe shadowgraphy as a function of pulsed laser energy.

Directed dewetting of amorphous silicon film by a donut-shaped laser pulse.

Irradiation of a thin film with a beam-shaped laser is proposed to achieve site-selectively controlled dewetting of the film into nanoscale structures. As a proof of concept, the laser-directed dewetting of an amorphous silicon thin film on a glass substrate is demonstrated using a donut-shaped laser beam. Upon irradiation of a single laser pulse, the silicon film melts and dewets on the substrate surface. The irradiation with the donut beam induces an unconventional lateral temperature profile in the film, leading to thermocapillary-induced transport of the molten silicon to the center of the beam spot. Upon solidification, the ultrathin amorphous silicon film is transformed to a crystalline silicon nanodome of increased height. This morphological change enables further dimensional reduction of the nanodome as well as removal of the surrounding film material by isotropic silicon etching. These results suggest that laser-based dewetting of thin films can be an effective way for scalable manufacturing of patterned nanostructures.

Measurement of optical scattered power from laser-induced shallow pits on silica.

A model describing far-field scattered power and irradiance by a silica glass slab with a shallow-pitted exit surface is experimentally validated. The comparison to the model is performed using a precisely micromachined ensemble of ∼11 µm wide laser ablated shallow pits producing 1% of the incident beam scatter in a 10 mrad angle. A series of samples with damage initiations and laser-induced shallow pits resulting from 351 nm, 5 ns pulsed laser cleaning of metal microparticles at different fluences between 2 J/cm2 and 11 J/cm2 are characterized as well and found in good agreement with model predictions.

Growth model for laser-induced damage on the exit surface of fused silica under UV, ns laser irradiation.

We present a comprehensive statistical model which includes both the probability of growth and growth rate to describe the evolution of exit surface damage sites on fused silica optics over multiple laser shots spanning a wide range of fluences. We focus primarily on the parameterization of growth rate distributions versus site size and laser fluence using Weibull statistics and show how this model is consistent with established fracture mechanics concepts describing brittle materials. Key growth behaviors and prediction errors associated with the present model are also discussed.

Nanoscale surface tracking of laser material processing using phase shifting diffraction interferometry.

Phase shifting diffraction interferometry (PSDI) was adapted to provide real-time feedback control of a laser-based chemical vapor deposition (LCVD) process with nanometer scale sensitivity. PSDI measurements of laser heated BK7 and fused silica substrates were used to validate a finite element model that accounts for both refractive index changes and displacement contributions to the material response. Utilizing PSDI and accounting for the kinetics of the modeled thermomechanical response, increased control of the LCVD process was obtained. This approach to surface tracking is useful in applications where extreme environments on the working surface require back-side optical probing through the substrate.

Deep learning with mixup augmentation for improved pore detection during additive manufacturing.

In additive manufacturing (AM), process defects such as keyhole pores are difficult to anticipate, affecting the quality and integrity of the AM-produced materials. Hence, considerable efforts have aimed to predict these process defects by training machine learning (ML) models using passive measurements such as acoustic emissions. This work considered a dataset in which keyhole pores of a laser powder bed fusion (LPBF) experiment were identified using X-ray radiography and then registered both in space and time to acoustic measurements recorded during the LPBF experiment. Due to AM's intrinsic process controls, where a pore-forming event is relatively rare, the acoustic datasets collected during monitoring include more non-pores than pores. In other words, the dataset for ML model development is imbalanced. Moreover, this imbalanced and sparse data phenomenon remains ubiquitous across many AM monitoring schemes since training data is nontrivial to collect. Hence, we propose a machine learning approach to improve this dataset imbalance and enhance the prediction accuracy of pore-labeled data. Specifically, we investigate how data augmentation helps predict pores and non-pores better. This imbalance is improved using recent advances in data augmentation called Mixup, a weak-supervised learning method. Convolutional neural networks (CNNs) are trained on original and augmented datasets, and an appreciable increase in performance is reported when testing on five different experimental trials. When ML models are trained on original and augmented datasets, they achieve an accuracy of 95% and 99% on test datasets, respectively. We also provide information on how dataset size affects model performance. Lastly, we investigate the optimal Mixup parameters for augmentation in the context of CNN performance.

High absorptivity nanotextured powders for additive manufacturing.

The widespread application of metal additive manufacturing (AM) is limited by the ability to control the complex interactions between the energy source and the feedstock material. Here, we develop a generalizable process to introduce nanoscale grooves to the surface of metal powders which increases the powder absorptivity by up to 70% during laser powder bed fusion. Absorptivity enhancements in copper, copper-silver, and tungsten enable energy-efficient manufacturing, with printing of pure copper at relative densities up to 92% using laser energy densities as low as 83 joules per cubic millimeter. Simulations show that the enhanced powder absorptivity results from plasmon-enabled light concentration in nanoscale grooves combined with multiple scattering events. The approach taken here demonstrates a general method to enhance the absorptivity and printability of reflective and refractory metal powders by changing the surface morphology of the feedstock without altering its composition.

A Denoising Autoencoder for Improved Kikuchi Pattern Quality and Indexing in Electron Backscatter Diffraction.

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.

Evaporation kinetics of laser heated silica in reactive and inert gases based on near-equilibrium dynamics.

Evaporation kinetics of fused silica were measured up to ≈3000K using CO(2) laser heating, while solid-gas phase chemistry of silica was assessed with hydrogen, air, and nitrogen. Enhanced evaporation in hydrogen was attributed to an additional reduction pathway, while oxidizing conditions pushed the reaction backwards. The observed mass transport limitations supported use of a near-equilibrium analysis for interpreting kinetic data. A semi-empirical model of the evaporation kinetics is derived that accounts for heating, gas chemistry and transport properties. The approach described should have application to materials laser processing, and in applications requiring knowledge of thermal decomposition chemistry under extreme temperatures.

Characterization of ejected fused silica particles following surface breakdown with nanosecond pulses.

The light emission produced near the surface of fused silica following laser-induced breakdown on the exit surface was spatially and spectrally resolved. This signal is in part generated by ejected particles while traveling outside the hot ionized region. The thermal emission produced by the particles can be separated from the plasma emission near the surface and its spectral characteristics provide information on the temperature of the particles after ejection from the surface. Assuming the emission is thermal in origin, data suggest an initial average temperature on the order of at least 0.5 eV.

A laser powder bed fusion system for operando synchrotron x-ray imaging and correlative diagnostic experiments at the Stanford Synchrotron Radiation Lightsource.

Laser powder bed fusion (LPBF) is a highly dynamic multi-physics process used for the additive manufacturing (AM) of metal components. Improving process understanding and validating predictive computational models require high-fidelity diagnostics capable of capturing data in challenging environments. Synchrotron x-ray techniques play a vital role in the validation process as they are the only in situ diagnostic capable of imaging sub-surface melt pool dynamics and microstructure evolution during LPBF-AM. In this article, a laboratory scale system designed to mimic LPBF process conditions while operating at a synchrotron facility is described. The system is implemented with process accurate atmospheric conditions, including an air knife for active vapor plume removal. Significantly, the chamber also incorporates a diagnostic sensor suite that monitors emitted optical, acoustic, and electronic signals during laser processing with coincident x-ray imaging. The addition of the sensor suite enables validation of these industrially compatible single point sensors by detecting pore formation and spatter events and directly correlating the events with changes in the detected signal. Experiments in the Ti-6Al-4V alloy performed at the Stanford Synchrotron Radiation Lightsource using the system are detailed with sufficient sampling rates to probe melt pool dynamics. X-ray imaging captures melt pool dynamics at frame rates of 20 kHz with a 2 µm pixel resolution, and the coincident diagnostic sensor data are recorded at 470 kHz. This work shows that the current system enables the in situ detection of defects during the LPBF process and permits direct correlation of diagnostic signatures at the exact time of defect formation.

Nondiffractive beam shaping for enhanced optothermal control in metal additive manufacturing.

High thermal gradients and complex melt pool instabilities involved in powder bed fusion­based metal additive manufacturing using focused Gaussian-shaped beams often lead to high porosity, poor morphological quality, and degraded mechanical performance. We show here that Bessel beams offer unprecedented control over the spatiotemporal evolution of the melt pool in stainless steel (SS 316L) in comparison to Gaussian beams. Notably, the nondiffractive nature of Bessel beams enables greater tolerance for focal plane positioning during 3D printing. We also demonstrate that Bessel beams significantly reduce the propensity for keyhole formation across a broad scan parameter space. High-speed imaging of the melt pool evolution and solidification dynamics reveals a unique mechanism where Bessel beams stabilize the melt pool turbulence and increase the time for melt pool solidification, owing to reduced thermal gradients. Consequently, we observe a distinctively improved combination of high density, reduced surface roughness, and robust tensile properties in 3D-printed test structures.