This novel detector for characterizing IFE implosions is an alternative to the current RTNADs to measure neutron fluxes > 3x1011 neutrons/cm2 at high shot rates. The detector consists of a stack of small square metal wafers separated by thin insulating spacers. Every other wafer is held at high voltage while the remaining wafers are grounded. The stack acts as an…
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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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LLNL researchers have designed and tested performance characteristics for a multichannel pyrometer that works in the NIR from 1200 to 2000 nm. A single datapoint without averaging can be acquired in 14 microseconds (sampling rate of 70,000/s). In conjunction with a diamond anvil cell, the system still works down to about 830K.
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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…