Oak Ridge National Laboratory

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Oak Ridge, Tennessee, United States

Oak Ridge National Laboratory is the world’s premier research institution, empowering leaders and teams to pursue breakthroughs in an environment marked by operational excellence and engagement with the communities where we live and work. As the US Department of Energy’s largest multi-disciplinary laboratory, we deliver scientific discoveries and technical breakthroughs to realize solutions for complex challenges including the transition to clean energy, mitigation of climate change, improvements to human health, and innovation that strengthens economic competitiveness. We play a pivotal role in building a clean, efficient, flexible, and secure energy future. Our scientists work with many of America’s best innovators and businesses to research, develop, and deploy cutting-edge technologies and to break down market barriers in sustainable transportation, smart power systems, and energy efficiency for homes, buildings, and manufacturing.

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Scalable in situ non-destructive evaluation of additively manufactured components using process monitoring, sensor fusion, and machine learning

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✍️ Authors: Zackary Snow, Luke Scime, Amirkoushyar Ziabari, Brian Fisher, Vincent Paquit

🔖 Topics: Additive Manufacturing, Quality Assurance, Nondestructive Test

🏢 Organizations: Oak Ridge National Laboratory, Raytheon


Laser Powder Bed Fusion (L-PBF) Additive Manufacturing (AM) is among the metal 3D printing technologies most broadly adopted by the manufacturing industry. However, the current industry qualification paradigm for critical-application L-PBF parts relies heavily on expensive non-destructive inspection techniques, which significantly limits the use-cases of L-PBF. In situ monitoring of the process promises a less expensive alternative to ex situ testing, but existing sensor technologies and data analysis techniques struggle to detect sub-surface flaws (e.g., porosity and cracking) on production-scale L-PBF printers. In this work, an in situ NDE (INDE) system was engineered to detect subsurface flaws detected in X-Ray Computed Tomography (XCT) directly from process monitoring data. A multilayer, multimodal data input allowed the INDE system to detect numerous subsurface flaws in the size range of 200–1000 µm using a novel human-in-the-loop annotation procedure. Furthermore, a framework was established for generating probability-of-detection (POD) and probability-of-false-alarm (PFA) curves compliant with NDE standards by systematically comparing instances of detected subsurface flaws to post-build XCT data. We also introduce for the first time in the AM in situ sensing literature the flaw size corresponding to a 90% detection rate on the lower 95% confidence interval of the POD curve. The INDE system successfully demonstrated POD capabilities commensurate with traditional NDE methods. Traditional ML performance metrics were also shown to be inadequate for assessing the ability of the INDE system’s flaw detection performance. It is the belief of the authors that future studies should adopt the POD and PFA approach outlined here to provide better insight into the utility of process monitoring for AM.

Read more at Additive Manufacturing

Material Manufacturing: New Weld Wire Reduces Failures from Hydrogen Damage

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✍️ Author: Seth Clark

🔖 Topics: Welding

🏢 Organizations: Oak Ridge National Laboratory


Oak Ridge National Laboratories, along with several other federal agencies, has developed a new alloy for welding applications in hopes of improving weld strength. While there are few details on the specifics of the new alloy, the welding wires created aim to reduce the effectiveness of hydrogen attack along welds.

The mechanisms of hydrogen damage are not well understood, but there are two common pathways in which hydrogen can lead to or further cracking in alloys. The localized cracking leads to a weak spot in the component, which will eventually lead to failure of the component, often below expected stress values.

Read more at Control Automation

The role of temperature on defect diffusion and nanoscale patterning in graphene

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✍️ Authors: Ondrej Dyck, Sinchul Yeom, Sarah Dillender, Andrew R. Lupini, Mina Yoon, Stephen Jesse

🔖 Topics: Materials Science

🏢 Organizations: Oak Ridge National Laboratory, Princeton University


Jesse said, “It heals locally, like the (fictitious) liquid-metal T-1000 in Terminator 2: Judgment Day.”

Graphene is of great scientific interest due to a variety of unique properties such as ballistic transport, spin selectivity, the quantum hall effect, and other quantum properties. Nanopatterning and atomic scale modifications of graphene are expected to enable further control over its intrinsic properties, providing ways to tune the electronic properties through geometric and strain effects, introduce edge states and other local or extended topological defects, and sculpt circuit paths. The focused beam of a scanning transmission electron microscope (STEM) can be used to remove atoms, enabling milling, doping, and deposition. Utilization of a STEM as an atomic scale fabrication platform is increasing; however, a detailed understanding of beam-induced processes and the subsequent cascade of aftereffects is lacking. Here, we examine the electron beam effects on atomically clean graphene at a variety of temperatures ranging from 400 to 1000 °C. We find that temperature plays a significant role in the milling rate and moderates competing processes of carbon adatom coalescence, graphene healing, and the diffusion (and recombination) of defects. The results of this work can be applied to a wider range of 2D materials and introduce better understanding of defect evolution in graphite and other bulk layered materials.

Read more at Science Direct