Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Engineering, Materials science, Lasers, Physics”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Precision Polishing of Ablator Capsules via in situ Process Monitoring and Machine Learning–Based Optimization

In inertial confinement fusion (ICF) experiments seeking output gains of unity and beyond, the quality of the ablator capsule is paramount for minimizing the hydrodynamic mix that quenches the central hot spot. Defects in the form of foreign particles or missing mass on the surface and within the wall of the capsule are primary offenders. High-density carbon capsules made for ICF experiments at the National Ignition Facility are precision polished to achieve surface smoothness on the order of a few nanometers as well as to minimize isolated defects in the form of pits. Given the critical role of this process, we are developing smart manufacturing techniques with the goal of elevating the efficiency of this process. Our approach is to use MEMS (micro-electromechanical systems)–based sensors to capture the fine vibration signals generated during the polishing process and combine them with synchronized visual feedback as needed. Beyond using these sensors for process monitoring, we use specific deep learning methods to analyze the data and extract correlations with both the process parameters and the final performance of the polishing run. Here, in this work, we describe the multiple fronts we have explored in this regard and the results we have gotten so far. This approach promises to have the potential to ultimately provide real-time feedback that can be used to ensure the progress of the run as well as a means for faster optimization.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Peening Techniques for Surface Modification: Processes, Properties, and Applications

Surface modification methods have been applied to metals and alloys to change the surface integrity, obtain superior mechanical properties, and improve service life irrespective of the field of application. In this review paper, current state-of-the-art of peening techniques are demonstrated. More specifically, classical and advanced shot peening (SP), ultrasonic impact peening (UIP), and laser shock peening (LSP) have been discussed. The effect of these techniques on mechanical properties, such as hardness, wear resistance, fatigue life, surface roughness, and corrosion resistance of various metals and alloys, are discussed. This study also reports the comparisons, advantages, challenges, and potential applications of these processes.

microstructure↗
DOE OSTI2026

LDRD FY25 Program Overview

As Lawrence Livermore National Laboratory’s (LLNL’s) Laboratory Directed Research and Development (LDRD) program enters its fifth decade of leading-edge research and development, its impact and importance have never been stronger. The program continues to advance strategic investments in pioneering science, technology, and engineering, ensuring LLNL will be ready to deliver on our mission as it evolves over the coming decades. Investing in LDRD research, and the people who perform this critical work, gives LLNL the ability to sustain our role as a leader in the Department of Energy and National Nuclear Security Administration enterprise. The LDRD program enables high-risk, high-payoff research that anticipates emerging threats and future mission needs. By nurturing the ingenuity of the Lab’s greatest asset, its people, LDRD funding advances not only our research but also grows and nurtures our workforce: engaging future innovators with student mentoring, challenging postdoctoral researchers to apply their skills to support national security, and strengthening the leadership skills of early career staff. This annual report documents how LDRD investments advance LLNL’s science, technology, and engineering across our mission space. To assess LDRD’s impact we track both short and long-term metrics such as peer-reviewed publications, number of students, or professional fellows. In addition to reviewing these metrics, I encourage you to delve deeper into the breadth of science and technology that illustrate the strategic value of this research portfolio. For instance, a recent exploratory research project used advanced manufacturing to construct miniaturized three-dimensional ion traps for a quantum computer with reduced quantum error rates to enable applications that address national security missions and support basic science. Another project has delved into studying detonation by examining deflagration to enhance the safety and security of the nuclear weapons stockpile. LDRD researchers are also deploying AI agents on two of the world’s most powerful supercomputers to automate and accelerate inertial confinement fusion experiments. Other teams are delivering more accurate optical constants to enable improved validation for aluminum to advance atomic and molecular physics models. LDRD-driven discoveries of how metals deform under extreme conditions strengthen our ability to model and design materials for demanding national security environments. National security challenges are increasingly complex and continuously evolving. LDRD focuses our most innovative science and technology on these challenges, ensuring the Laboratory is developing creative, forward-leaning solutions for our nation and the world. The following pages feature highlights of published scientific advances, patents, and honors that stem from LDRD investments. As you read this report, I hope you will understand how these investments position the Laboratory, and our partners, to meet the demands of the decades ahead.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Transient Phase-Driven Cyclic Deformation in Additively Manufactured 15-5 PH Steel

The present work extends the examination of selective laser melting (SLM)-fabricated 15-5 PH steel with the 8%-transient-austenite-phase towards fully-reversed strain-controlled low-cycle fatigue (LCF) test. The cyclic-deformation response and microstructural evolution were investigated via in-situ neutron-diffraction measurements. The transient-austenite-phase rapidly transformed into the martensite phase in the initial cyclic-hardening stage, followed by an almost complete martensitic transformation in the cyclic-softening and steady stage. The compressive stress was much greater than the tensile stress at the same strain amplitude. The enhanced martensitic transformation associated with lower dislocation densities under compression predominantly governed such a striking tension-compression asymmetry in the SLM-built 15-5 PH.

15-5 PH stainless steel↗
DOE OSTI2025

Sample glue layer investigation and mitigation for laser induced prompt impulse experiments

Understanding longer timescale material reactions under dynamic stress loading is critical for applications in materials engineering, shock physics, and planetary science. Prompt impulse experiments generate lower pressures since the ablator—the material first removed by the laser—is thicker and farther from the diagnostic plane, capturing aggregate material responses from the initial shock wave, rarefaction waves, and later time effects. This complexity demands thorough material characterization and simulation support. Since traditional sample construction is specific to supported shock experiments, designing prompt impulse experiments requires reconsideration around target design and sample engineering. Here, we present sample preparation techniques, experimental investigations, and theoretical simulations to investigate glue layer impacts, aiming to standardize samples for consistent data at lower laser fluences. We find that glue layers <30 μm have a minimal impact on peak velocity and pulse shape. The peak velocity scales linearly with glue layer thickness until a glue layer of 75 μm. For glue layers >75 μm, the peak velocity no longer scales with thickness; however, the pulse shape continues to degrade as described by simulations.

Lasers↗
DOE OSTI2020

Nanoscale serration characteristics of additively manufactured superalloys

Structural elements made of nickel-based superalloys usually operate at high temperatures. Many surface failure mechanisms such as creep, fatigue, fretting fatigue, corrosion, and stress corrosion cracking start from the surface. Thus, studying the surface mechanical properties and deformation behavior of materials is vital in order to draw a correlation between the surface properties and failures. Herein, a nanoindentation technique was implemented to characterize surface properties of a widely used additively manufactured (AM) superalloy, i.e., Inconel 625. The specimens were tested in a range of temperatures in a vacuum chamber. Serrated plastic flow characterized by pop-in events during nanoindentation, known as Portevin-Le Chatelier (PLC) effect, was observed in all three tested elevated temperatures. This phenomenon depicts itself as bursts of plasticity in the loading section of the load-displacement curves. These bursts were studied comprehensively to explore incipient plasticity. Hertzian contact mechanics were implemented to extract the maximum shear stress beneath the indenter from the pop-in loads. The results show that the initial pop-in load increases as the temperature increases. The average initial pop-in load increases by almost four times from 300 °C to 650 °C. This was attributed to the formation of strengthening precipitates. The average size of the serrations and the magnitude of dislocation nucleation increase from 300 °C to 500 °C and decrease from 500 °C to 650 °C. Finally, the serrations are attributed to the dislocation generation and movement as well as their interaction with the solute atoms and precipitates.

36 MATERIALS SCIENCE↗
DOE OSTI2024

In Situ Prediction of Microstructure and Mechanical Properties in Laser-Remelted Al-Si Alloys: Towards Enhanced Additive Manufacturing

Laser surface remelting of aluminum alloys has emerged as a promising technique to enhance mechanical properties through refined microstructures. This process involves rapid cooling rates ranging from 10 3 to 10 8 °C/s, which increase solid solubility within aluminum alloys, shifting their eutectic composition to a larger value of silicon content. Consequently, the resulting microstructure combines a strengthened aluminum matrix with silicon fibers. This study focuses on the laser scanning of Al-Si aluminum alloy to reduce the size of aluminum matrix spacings and transform fibrous silicon particles from micrometer to nanometer dimensions. Analysis revealed that the eutectic structure contained 17.55% silicon by weight, surpassing the equilibrium eutectic composition of 12.6% silicon. Microstructure dimensions within the molten zones, termed ‘melt pools’, were extensively examined using Scanning Electron Microscopy (SEM) at intervals of approximately 20 μm from the surface. A notable increase in hardness, exceeding 50% compared to the base plate, was observed in the melt pool regions. Thus, it is exemplified that laser surface remelting introduces a novel strengthening mechanism in the alloy. Moreover, this study develops an in situ method for predicting melt pool properties and dimensions. A predictive model is proposed, correlating energy density and spectral signals emitted during laser remelting with mechanical properties and melt pool dimensions. This method significantly reduces characterization time from days to seconds, offering a streamlined approach for future studies in additive manufacturing.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Deep-Learning-Based Segmentation of Keyhole in In-Situ X-ray Imaging of Laser Powder Bed Fusion

In laser powder bed fusion processes, keyholes are the gaseous cavities formed where laser interacts with metal, and their morphologies play an important role in defect formation and the final product quality. The in-situ X-ray imaging technique can monitor the keyhole dynamics from the side and capture keyhole shapes in the X-ray image stream. Keyhole shapes in X-ray images are then often labeled by humans for analysis, which increasingly involves attempting to correlate keyhole shapes with defects using machine learning. However, such labeling is tedious, time-consuming, error-prone, and cannot be scaled to large data sets. To use keyhole shapes more readily as the input to machine learning methods, an automatic tool to identify keyhole regions is desirable. In this paper, a deep-learning-based computer vision tool that can automatically segment keyhole shapes out of X-ray images is presented. The pipeline contains a filtering method and an implementation of the BASNet deep learning model to semantically segment the keyhole morphologies out of X-ray images. The presented tool shows promising average accuracy of 91.24% for keyhole area, and 92.81% for boundary shape, for a range of test dataset conditions in Al6061 (and one AliSi10Mg) alloys, with 300 training images/labels and 100 testing images for each trial. Prospective users may apply the presently trained tool or a retrained version following the approach used here to automatically label keyhole shapes in large image sets.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Investigation of compression of indirect-drive targets under conditions of the NIF facility using one-dimensional modelling

The indirect compression dynamics of targets containing capsules with ablators of a plastic, high-density carbon and beryllium is simulated in the framework of a one-dimensional model based on the 1D RADIAN code. Experiments with such targets are performed on the NIF facility in the Livermore Laboratory (USA) in 2014 – 2018. The 1D simulation data are consistent with the results of experiments and calculations made at this Laboratory. The effect of the hard part of hohlraum radiation on capsule compression parameters is confirmed. We demonstrate the feasibility of eliminating this influence not only by selecting the hohlraum material but also by introducing admixtures into the capsule that absorb this radiation. It is shown how varying the amount of admixture in the capsule ablator varies the spectrum of the radiation that heats the DT fuel. (interaction of laser radiation with matter. laser plasma)

36 MATERIALS SCIENCE↗
DOE OSTI2024

Selective CW Laser Synthesis of MoS2 and Mixture of MoS2 and MoO2 from (NH4)2MoS4 Film

Very recently, the synthesis of 2D MoS2 and WS2 through pulsed laser-directed thermolysis can achieve wafer-scale and large-area structures, in ambient conditions. In this paper, we report the synthesis of MoS2 and MoS2 oxides from (NH4)2MoS4 film using a visible continuous-wave (CW) laser at 532 nm, instead of the infrared pulsed laser for the laser-directed thermolysis. The (NH4)2MoS4 film is prepared by dissolving its crystal powder in DI water, sonicating the solution, and dip-coating onto a glass slide. We observed a laser intensity threshold for the laser synthesis of MoS2, however, it occurred in a narrow laser intensity range. Above that range, a mixture of MoS2 and MoO2 is formed, which can be used for a memristor device, as demonstrated by other research groups. We did not observe a mixture of MoS2 and MoO3 in the laser thermolysis of (NH4)2MoS4. The laser synthesis of MoS2 in a line pattern is also achieved through laser scanning. Due to of the ease of CW beam steering and the fine control of laser intensities, this study can lead toward the CW laser-directed thermolysis of (NH4)2MoS4 film for the fast, non-vacuum, patternable, and wafer-scale synthesis of 2D MoS2.

(NH4)2MoS4↗
DOE OSTI2022

Monitoring and prediction of porosity in laser powder bed fusion using physics-informed meltpool signatures and machine learning

In this work we accomplished the monitoring and prediction of porosity in laser powder bed fusion (LPBF) additive manufacturing process. This objective was realized by extracting physics-informed meltpool signatures from an in-situ dual-wavelength imaging pyrometer, and subsequently, analyzing these signatures via computationally tractable machine learning approaches. Porosity in LPBF occurs despite extensive optimization of processing conditions due to stochastic causes. Hence, it is essential to continually monitor the process with in-situ sensors for detecting and mitigating incipient pore formation. In this work a tall cuboid-shaped part (10 mm × 10 mm × 137 mm, material ATI 718Plus) was built with controlled porosity by varying laser power and scanning speed. This test caused various types of porosity, such as lack-of-fusion and keyhole formation, with varying degrees of severity in the part. The meltpool was continuously monitored using a dual-wavelength imaging pyrometer installed in the machine. Physically intuitive process signatures, such as meltpool length, temperature distribution, and ejecta (spatter) characteristics, were extracted from the meltpool images. Subsequently, relatively simple machine learning models, e.g., K-Nearest Neighbors, were trained to predict both the severity and type of porosity as a function of these physics-informed meltpool signatures. These models resulted in a prediction accuracy exceeding 95% (statistical F1-score). The same analysis was carried out with a complex, black-box deep learning convolutional neural network which directly used the meltpool images instead of physics-informed features. The convolutional neural network produced a comparable F1-score in the range of 89–97%. Finally, these results demonstrate that using pragmatic, physics-informed meltpool signatures within a simple machine learning model is as effective for flaw prediction in LPBF as using a complex and computationally demanding black-box deep learning model.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Hybrid Organic Inorganic Perovskites: Physical Properties and Applications (in 4 Volumes)

This four-volume handbook gives a state-of-the-art overview of hybrid organic inorganic perovskites, both two dimensional (2D) and three dimensional (3D), from synthesis and characterization and simulation to optoelectronic devices (such as solar cells and light emitting diodes), spintronics devices and catalysis application. The editors, coming from academia and national laboratory, are known for their didactic skills as well as their technical expertise. Coordinating the efforts of 30 expert authors in 21 chapters, they construct the story of hybrid perovskite structural and optical properties, electronic and spintronic response, laser action, and catalysis from varied viewpoints: materials science, chemical engineering, and energy engineering. The four volumes are arranged according to the focus material properties. Volume 1 is focused on the material physical properties including structure, deposition characteristic and the structure of the electronic bands and excitons of these compounds. Volume 2 covers the hybrid perovskite optical properties including the ultrafast optical response, photoluminescence and laser action. Volume 3 contains the spin response of these compounds including application such as spin valves, photogalvanic effect, and magnetic response of light emitting diodes and solar cell devices. Finally, and highly relevant to tomorrow's energy challenges, volume 4 is focused on the physics and device properties of the most relevant applications of the hybrid perovskites, namely photovoltaic solar cells. The text contains many high-quality colorful illustrations and examples, as well as thousands of up-to-date references to peer-reviewed articles, reports and websites for further reading. This comprehensive and well-written handbook is a must-have reference for universities, research groups and companies working with the hybrid organic inorganic perovskites.

applications↗
DOE OSTI2021

Directed energy deposition additive manufacturing of functionally graded Al-W composites

Directed energy deposition using laser heat sources (DED-L) is a metal additive manufacturing method that can be used to fabricate functionally graded materials by feeding multiple powder streams directly into a laser-generated melt pool. Additionally, the composition can be spatially varied by independent control of the materials feed rates. DED-L additive manufacturing is used in this work to create continuously graded Al/W composites that span 0–55 vol% W in Al over length scales from 0.6 to 1.2 mm with individual layers on the order of 0.1 mm and powder particle sizes on the order of 10 µm. The obtained composition and thickness ranges are comparable to those typically achieved using conventional powder metallurgy approaches and enables fabrication of composites to be used as a high impedance graded density impactor (GDI) in dynamic ramp compression experiments to study matter under extreme conditions. DED-L additive manufacturing of a GDI presents an opportunity to reduce GDI fabrication time to less than a day compared to many weeks by conventional methods. It is also possible to scale the deposition by DED-L to essentially unlimited dimensions in the lateral directions, whereas conventional methods become limited.

36 MATERIALS SCIENCE↗
NASA NTRS1973

Research in the aerospace physical sciences

Research efforts are reported in various areas including dynamics of thin films, polymer chemistry, mechanical and chemical properties of materials, radar system engineering, stabilization of lasers, and radiation damage of organic crystals. Brief summaries of research accomplished and literature citations are included.

Whitehurst, R. N.↗