Pulse Compression Photoconductive Switching Using Negative Differential Mobility
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42 ENGINEERING↗
SEARCH · Engineering Papers
Results for “Engineering, Lasers”
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.
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Performance of Public Film Cooling Geometries Produced Through Additive Manufacturing
Abstract Film cooling is an essential cooling technology to allow modern gas turbines to operate at high temperatures. For years, researchers in this community have worked to improve the effectiveness of film cooling configurations by maximizing the coolant coverage and minimizing the heat flux from the hot gas into the part. Working toward this goal has generated many promising film cooling concepts with unique shapes and configurations. However, until recently, many of these designs were challenging to manufacture in actual turbine hardware due to limitations with legacy manufacturing methods. Now, with the advances in additive manufacturing, it is possible to create turbine parts using high-temperature nickel alloys that feature detailed and unique geometry features. Armed with this new manufacturing power, this study aims to build and test the promising designs from the public literature that were previously difficult or impossible to implement. In this study, different cooling hole designs were manufactured in test coupons using a laser powder bed fusion process. Each nickel alloy coupon featured a single row of engine scale cooling holes, fed by a microchannel. To evaluate performance, the overall cooling effectiveness of each coupon was measured using a matched Biot test at engine relevant conditions. The results showed that certain hole shapes are better suited for additive manufacturing than others and that the manufacturing process can cause significant deviations from the performance reported in the literature.
Engineering↗
Development of Cadmium Magnesium Telluride for Picosecond Response X-Ray Optical Laser Photodetector
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36 MATERIALS SCIENCE↗
A Discrete Dendrite Dynamics Model for Epitaxial Columnar Grain Growth in Metal Additive Manufacturing with Application to Inconel
Epitaxial columnar grain growth is a prevalent microstructural feature in the additive manufacturing (AM) of metal components such as Inconel, with cubic unit cell crystal lattice structure (face centered cubic (FCC) or body centered cubic (BCC)). These columnar grains evolve from the partly molten grains in the substrate or the solidified metal. This work proposes an efficient model to simulate the competitive growth of epitaxial columnar dendritic grains. The proposed model tracks the dynamic changes in the dendrites emanating from discrete points along the solid/liquid interface of a quasi-steady melt pool (MP). These dynamic changes include convergence and divergence of growing dendrites. The model is extended to predict the microstructure of large 3D parts and experimentally validated by comparing the simulation results for laser powder bed fusion (L-PBF) and wire-arc additive manufacturing (WAAM) processes. The microstructure and pole figures are predicted for Inconel 718 samples produced by L-PBF and Inconel 740H samples produced by WAAM processes. Finally, the model predictions compare well with the observed microstructure and pole figures results for both the L-PBF and WAAM processes.
20 FOSSIL-FUELED POWER PLANTS↗
Influence of spattering on in-process layer surface roughness during laser powder bed fusion
Not provided.
Engineering↗
Designing the Next Generation of Uranium Atomic Vapor Laser Isotope Separation
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Nuclear science and engineering - Nuclear fuel cyc↗
ECE 4396 (Final Report)
In the summer of 2025, I was fortunate enough intern at Sandia National Laboratories in Albuquerque, New Mexico. I was hired into the Southwest Analysis Laboratories for Semiconductor Advancement (SALSA) intern program. In this internship, I applied my knowledge and skills in electrical engineering to conduct hardware failure analysis. I utilized various failure analyze techniques involving the use of Infrared Thermography (IRT) and Laser Scanning Microscopy (LSM) to test different Application-Specific Integrated Circuits (ASIC) chips that are available in the public market.
42 ENGINEERING↗
Floquet Engineering of Interactions and Entanglement in Periodically Driven Rydberg Chains
Neutral atom arrays driven into Rydberg states constitute a promising approach for realizing programmable quantum systems. Enabled by strong interactions associated with Rydberg blockade, they allow for simulation of complex spin models and quantum dynamics. We introduce a new Floquet engineering technique for systems in the blockade regime that provides control over novel forms of interactions and entanglement dynamics in such systems. Our approach is based on time-dependent control of Rydberg laser detuning and leverages perturbations around periodic many-body trajectories as resources for operator spreading. These time-evolved operators are utilized as a basis for engineering interactions in the effective Hamiltonian describing the stroboscopic evolution. As an example, we show how our method can be used to engineer strong spin exchange, consistent with the blockade, in a one-dimensional chain, enabling the exploration of gapless Luttinger liquid phases. In addition, we demonstrate that combining gapless excitations with Rydberg blockade can lead to dynamic generation of large-scale multipartite entanglement. Experimental feasibility and possible generalizations are discussed.
Floquet systems↗
LPBF Processability of NiTiHf Alloys: Systematic Modeling and Single-Track Studies
Research into the processability of NiTiHf high-temperature shape memory alloys (HTSMAs) via laser powder bed fusion (LPBF) is limited; nevertheless, these alloys show promise for applications in extreme environments. This study aims to address this limitation by investigating the printability of four NiTiHf alloys with varying Hf content (1, 2, 15, and 20 at. %) to assess their suitability for LPBF applications. Solidification cracking is one of the main limiting factors in LPBF processes, which occurs during the final stage of solidification. To investigate the effect of alloy composition on printability, this study focuses on this defect via a combination of computational modeling and experimental validation. To this end, solidification cracking susceptibility is calculated as Kou’s index and Scheil–Gulliver model, implemented in Thermo-Calc/2022a software. An innovative powder-free experimental method through laser remelting was conducted on bare NiTiHf ingots to validate the parameter impacts of the LPBF process. The result is the processability window with no cracking likelihood under diverse LPBF conditions, including laser power and scan speed. This comprehensive investigation enhances our understanding of the processability challenges and opportunities for NiTiHf HTSMAs in advanced engineering applications.
36 MATERIALS SCIENCE↗
Sequential order dependent dark-exciton modulation in bi-layered TMD heterostructure
We report the emergence of dark-excitons in transition-metal-dichalcogenide (TMD) heterostructures that strongly rely on the stacking sequence, i.e., momentum-dark K-Q exciton located exclusively at the top layer of the heterostructure. The feature stems from band renormalization and is distinct from those of typical neutral excitons or trions, regardless of materials, substrates, and even homogeneous bilayers, which is further confirmed by scanning tunneling spectroscopy. To understand the unusual stacking sequence, we introduce the excitonic Elliot formula by imposing strain exclusively on the top layer that could be a consequence of the stacking process. We further find that the intensity ratio of Q- to K-excitons in the same layer is inversely proportional to laser power, unlike for conventional K-K excitons. This can be a metric for engineering the intensity of dark K-Q excitons in TMD heterostructures, which could be useful for optical power switches in solar panels.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
ENG 572 Interim Report
Sandia National Laboratories is a Federally Funded Research and Development Center (FFRDC) founded in 1949 with the mission of developing and testing the non-nuclear components of nuclear weapons. Sandia has since been involved with numerous projects to support the Department of Defense’s (DOE) National Nuclear Security Administration (NNSA). One such set of projects has been implementing over-the-road transportation security enhancements. Under this program, Sandia National Laboratories (SNL) has worked to develop interface compatibility modifications for existing shipping configurations. This summer I will be working with a line of trailers that have been used to transport high asset cargo. These vehicles have successfully traveled millions of miles without any accidents over the course of 15 years. The primary motivation for the work that I will complete this summer is to provide support for existing electronic communication technologies implemented at SNL. As part of an ongoing project to implement modifications to a trailer system, I will focus primarily on the characterization and testing of thermal electric coolers (TEC). Within the scope of the trailer project, these devices provide temperature control for lasers used on optical communication boards (OCB).
42 ENGINEERING↗
In Situ Laser Induced Florescence Measurements of Fuel Dilution from Low Load to Stochastic Pre Ignition Prone Conditions
This work employs a novel laser induced fluorescence (LIF) diagnostic to measure fuel dilution in a running single cylinder research engine operated at stochastic pre ignition (SPI) and non-SPI prone conditions. Measurements of LIF based fuel dilution are quantified over a range of engine loads and fuel injection timings for two fuels. The in situ LIF measurements of fuel/lubricant interactions illustrate regions of increased fuel dilution from fuel-wall interactions and is believed to be a fundamental underpinning to generating top ring zone liquid conditions conducive to SPI. Furthermore, a novel level of dye doped in the fuel, between 50 to 500 ppm was used as the fluorescence source, at engine operating speed of 2000r/min from 5 to 18 bar of IMEPg injection timings was swept for two fuels of varying volatility. The direct real time LIF measurements highlight that there are non-linear trends in fuel dilution beyond simple dependencies of fuel volatility, injection duration or injection timing, suggesting that further understanding of spray interaction with engine surfaces and the turbulent field are needed to quantify fuel dilution effects that are conducive to SPI. Moreover, results show the potential of this diagnostic technique as an additional tool for quantifying spray and fuel mixing in fundamental studies deployable across a variety of engine loads from law to full load.
47 OTHER INSTRUMENTATION↗
A dynamic volumetric heat source model for laser additive manufacturing
Melt pool scale models of laser powder bed fusion (LPBF) offer insights into the process-structure-property relationships in additive manufacturing (AM). These models often neglect physical phenomena such as vapor cavity formation and fluid mechanics to reduce computational demands. Instead, volumetric heat source models are used to represent the effects that these phenomena have on the predicted melt pool dimensions. Generally, the dimensions and effective absorption of the volumetric heat source are calibrated to reproduce melt pool dimensions observed in metallographic cross sections taken from single-track experiments on bare plate. However, the transient nature of LPBF often deviates the melt pool dimensions from the assumed steady-state conditions of single-track experiments, motivating the need for a volumetric heat source model that more generally considers the dynamic relationship between melt pool shape and laser-material interactions. Here, we introduce a two-parameter volumetric heat source model that integrates several existing models into a generalized mathematical expression, providing independent control over the radial heat distribution via the parameter k and the volumetric shape of the heat source via the parameter m. This parameterization enables the calibration of melt pool shape predictions through simultaneous adjustment of these parameters, while keeping the radial heat source dimensions consistent with the experimental spot size (D4σ) and constraining the heat source depth and absorption to physically derived expressions for cavities. Consequently, the proposed volumetric heat source model adapts to changes in the local melt pool conditions due to scanning strategy and part geometry by dynamically adjusting the heat source depth and absorption. We demonstrate the capabilities of the proposed model through comparisons with a collection of experiments from the Additive Manufacturing Benchmark (AMBench).
36 MATERIALS SCIENCE↗
Toward memory-efficient melt pool monitoring: a classification framework using event-based imaging and sparse sensing technique
Vision sensors like CMOS and CCD cameras are often used for in-process monitoring of melt pools in laser-based additive and welding processes, but they require transferring large amounts of data and computational processing resources. Event-based neuromorphic imagery, on the other hand, detects only the change in pixel intensity, thus potentially reducing the data amount and latency. With an event imager, this study develops a framework for melt pool condition classification, including image construction, time scale selection, optimal pixel selection, and sparse classification, to achieve a highly memory-efficient scheme. These are based on sparse sensing techniques with singular value decomposition (SVD) and QR pivoting, the two fundamental matrix transformations for linear dimensionality reduction. The framework is then validated by classifying a controlled experiment by exciting various mode shapes of liquid gallium pools of varying depths (3, 6, and 8 mm). At 200 pixels, the classifier can reach overall accuracy of 75%, while at 2000 pixels (0.013% of the total possible pixels), the accuracy is nearly 90% (89.86%). At the same number of pixels, random selection can only achieve 46% and 67%, respectively. The memory savings of the sparsely sampled event data compared to a conventional imager is about 500 times. In addition to performance, implementation and limitations of the framework are also discussed.
42 ENGINEERING↗
Deep learning based x-ray spectrometer for high repetition rate characterization of betatron radiation
Betatron radiation produced from a laser-wakefield accelerator is a broadband, hard x-ray (>1 keV) source that has been used in a variety of applications in medicine, engineering, and fundamental science. Further development and optimization of stable, high repetition rate (HRR) (>1 Hz) betatron sources will provide a means to extend their application base to include single-shot dynamical measurements of ultrafast processes or dense materials. Recent advances in laser technology used in such experiments have enabled increases in shot-rate and system stability, providing improved statistical analysis and detailed parameter scans. However, unique challenges exist at high repetition rate, where data throughput and source optimization are now limited by diagnostic acquisition rates and analysis. Here, we present the development of a machine-learning algorithm for the real-time analysis of betatron radiation. We report on the fielding of this deep learning algorithm for online source characterization at the Institut National de la Recherche Scientifique's Advanced Laser Light Source. By fine-tuning an algorithm originally trained on a fully synthetic dataset using a subset of experimental data, the algorithm can predict the betatron critical energy with a percent error of 7.2 % with a reconstruction time of 1.5 ms, providing a valuable tool for real-time, multi-objective optimization at HRR.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗