Laser micro-machining and damage testing of rounded shadow cone blockers on silica glass for arresting laser damage growth by redirection of light.

Structured conical blockers manufactured on optical input surfaces are being used to shadow, and thereby, arrest growth of exit surface damage on large optics for applications in high-energy laser systems to extend their lifetime usage. However, as the size of the Shadow Cone Blocker (SCB) is increased, the deflected light must be carefully managed to prevent consequential damage from downstream intensification. Here, we design and fabricate a distinct input SCB geometry to alleviate this problem, enabling larger damage site mitigation. The demonstrated ∼1 mm diameter SCB was manufactured with a convergent approach using a CO2 pulsed laser ablative scanning sequence on a fused silica window. The SCB design was refined to maximize resistance to both input and exit surface damage initiations on 1 cm thick fused silica windows when exposed to 351 nm irradiation and validated with laser damage testing. The design showed to prevent damage onset to the exit surface for incident fluences on the SCB of 10.7 ± 1.3  J·cm-2 and is resistant to damage on the input surface exceeding 30 J·cm-2 input fluence.

Fused silica optics damage from downstream intensification on laser-induced damage precursors.

Management and control of damage initiation and growth on high-value National Ignition Facility (NIF) optics are critical to its operation. Cone-shaped features are currently being used on the input surfaces to arrest growth of exit surface damage by creating "shadows." Light refracted from the walls of the cones interferes with the incident beam at the exit surface to create an intensified annulus. Significant exit surface damage was observed at the locations of these annuli. Analysis showed that this damage is consistent with a recently reported new mechanism that degrades damage resistance by dispersing damage precursors over the surface upon exposure to UV laser radiation. This has significant implications for the design and operation of high-energy and power laser systems such as the NIF.

Enhancement of laser material drilling using high-impulse multi-laser melt ejection.

Laser drilling and cutting of materials is well established commercially, although its throughput and efficiency limit applications. This work describes a novel approach to improve laser drilling rates and reduce laser system energy demands by using a gated continuous wave (CW) laser to create a shallow melt pool and a UV ps-pulsed laser to impulsively expel the melt efficiency and effectively. Here, we provide a broad parametric study of this approach applied to common metals, describing the role of fluence, power, spot size, pulse-length, sample thickness, and material properties. One to two order-of-magnitude increases in the average removal rate and efficiency over the CW laser or pulsed-laser alone are demonstrated for samples of Al and stainless steel for samples as thick as 3 mm and for holes with aspect ratios greater than 10:1. Similar enhancements were also seen with carbon fiber composites. The efficiency of this approach exceeds published values for the drilling of these materials in terms of energy to remove a given volume of material. Multi-laser material removal rates, high-speed imaging of ejecta, and multi-physics hydrodynamic simulations of the melt ejection process are used to help clarify the physics of melt ejection leading to these enhancements. Our study suggests that these high-impulse multi-laser enhancements are due to both laser-induced surface wave instabilities and cavitation of the melt for shallow holes and melt cavitation and ejection for deeper channels.

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.

"Metallic burn paper" used for in situ characterization of laser beam properties.

In situ ablation of thin metal films on fused silica substrates by picosecond class lasers was investigated as a method of characterizing the beam at the sample plane. The technique involved plotting the areas enclosed by constant fluence contours identified in optical microscope images of the ablation sites versus the logs of the pulse energies. Inconel films on commercially available neutral density filters as well as magnetron sputtered gold films were used. It was also shown that this technique could be used to calibrate real-time beam profile diagnostics against the beam at the sample plane. The contours were shown to correspond to the boundary where part or all of the film was ablated.

Picosecond laser damage performance assessment of multilayer dielectric gratings in vacuum.

Precise assessment of the high fluence performance of pulse compressor gratings is necessary to determine the safe operational limits of short-pulse high energy lasers. We have measured the picosecond laser damage behavior of multilayer dielectric (MLD) diffraction gratings used in the compression of chirped pulses on the Advanced Radiographic Capability (ARC) kilojoule petawatt laser system at the Lawrence Livermore National Laboratory (LLNL). We present optical damage density measurements of MLD gratings using the raster scan method in order to estimate operational performance. We also report results of R-on-1 tests performed with varying pulse duration (1-30 ps) in air, and clean vacuum. Measurements were also performed in vacuum with controlled exposure to organic contamination to simulate the grating use environment. Results show sparse defects with lower damage resistance which were not detected by small-area damage test methods.

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.

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.

Controlling interdependent meso-nanosecond dynamics and defect generation in metal 3D printing.

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.

Subsurface Cooling Rates and Microstructural Response during Laser Based Metal Additive Manufacturing.

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 ß-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 ß-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 ß-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.

Resonance excitation of surface capillary waves to enhance material removal for laser material processing.

The results of detailed experiments and high fidelity modeling of melt pool dynamics, droplet ejections and hole drilling produced by periodic modulation of laser intensity are presented. Ultra-high speed imaging revealed that melt pool oscillations can drive large removal of material when excited at the natural oscillation frequency. The physics of capillary surface wave excitation is discussed and simulation is provided to elucidate the experimental results. The removal rates and drill through times as a function of driving frequency is investigated. The resonant removal mechanism is driven by both recoil momentum and thermocapillary force but the key observation is the latter effect does not require evaporation of material, which can significantly enhance the efficiency for laser drilling process. We compared the drilling of holes through a 2 mm-thick Al plate at modulation frequencies up to 20 kHz. At the optimal frequency of 8 kHz, near the resonant response of the melt pool, the drilling efficiency is greater than 10x with aspect ratio of 12:1, and without the collateral damage that is observed in unmodulated CW drilling.

Dynamics of pore formation during laser powder bed fusion additive manufacturing.

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.

In situ monitoring of surface postprocessing in large-aperture fused silica optics with optical coherence tomography.

Optical coherence tomography (OCT) is explored as a method to image laser-damage sites located on the surface of large aperture fused silica optics during postprocessing via CO2 laser ablation. The signal analysis for image acquisition was adapted to meet the sensitivity requirements for this application. A long-working-distance geometry was employed to allow imaging through the opposite surface of the 5 cm thick optic. The experimental results demonstrate the potential of OCT for remote monitoring of transparent material processing applications.

Metal vapor micro-jet controls material redistribution in laser powder bed fusion additive manufacturing.

The results of detailed experiments and finite element modeling of metal micro-droplet motion associated with metal additive manufacturing (AM) processes are presented. Ultra high speed imaging of melt pool dynamics reveals that the dominant mechanism leading to micro-droplet ejection in a laser powder bed fusion AM is not from laser induced recoil pressure as is widely believed and found in laser welding processes, but rather from vapor driven entrainment of micro-particles by an ambient gas flow. The physics of droplet ejection under strong evaporative flow is described using simulations of the laser powder bed interactions to elucidate the experimental results. Hydrodynamic drag analysis is used to augment the single phase flow model and explain the entrainment phenomenon for 316 L stainless steel and Ti-6Al-4V powder layers. The relevance of vapor driven entrainment of metal micro-particles to similar fluid dynamic studies in other fields of science will be discussed.