The approach is to build a high voltage insulator consisting of two materials: Poly-Ether-Ether-Ketone (“PEEK”) and Machinable Ceramic (“MACOR”). PEEK has a high stress tolerance but cannot withstand high temperatures, while MACOR has high heat tolerance but is difficult to machine and can be brittle. MACOR is used for the plasma-facing surface, while PEEK will handle the stresses and high…
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LLNL’s approach is to use their patented Photoconductive Charge Trapping Apparatus (U.S. Patent No. 11,366,401) as the active switch needed to discharge voltage across a vacuum gap in a particle accelerator, like the one described in their other patent (U.S. Patent No.
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Livermore researchers have developed a method for implementing closed-loop control in extrusion printing processes by means of novel sensing, machine learning, and optimal control algorithms for the optimization of printing parameters and controllability. The system includes a suite of sensors, including cameras, voltage and current meters, scales, etc., that provide in-situ process monitoring…
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The LLNL method for optimizing as built optical designs uses insights from perturbed optical system theory and reformulates perturbation of optical performance in terms of double Zernikes, which can be calculated analytically rather than by tracing thousands of rays. A new theory of compensation is enabled by the use of double Zernikes which allows the performance degradation of a perturbed…
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LLNL researchers have developed a system that relies on machine learning to monitor microfluidic devices. The system includes (at least) a microfluidic device, sensor(s), and a local network computer. The system could also include a camera that takes real-time images of channel(s) within an operating microfluidic device. A subset of these images can be used to train/teach a machine learning…