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CT Scanner Adobe Stock Image

The essence of this invention is a method that couples network architecture using neural implicit representations coupled with a novel parametric motion field to perform limited angle 4D-CT reconstruction of deforming scenes.

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SEM image of a prototype for a neural implant shuttle etched into a non-SOI wafer. The 7:1 (Si:Photoresist) etch selectivity used here allowed for a maximum structure height of 32 μm, with up to 75 steps of 0.4 μm height each. Scale bar 100 μm.

For this method, a Silicon on Insulator (SOI) wafer is used to tailor etch rates and thickness in initial steps of the process.  The simple three step process approach is comprised of grayscale lithography, deep reactive-ion etch (DRIE) and liftoff of the SOI wafer.  The liftoff process is used to dissolve the insulating layer, thus separating sections of the wafer as individual silicon…

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Livermore Tomography Tools  LTT

To solve these challenges using new and existing CT system designs, LLNL has developed an innovative software package for CT data processing and reconstruction. Livermore Tomography Tools (LTT) is a modern integrated software package that includes all aspects of CT modeling, simulation, reconstruction, and analysis algorithms based on the latest research in the field. LTT contains the most…

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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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Machine Learning for Monitoring microfluidic microcapsules
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…
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microcantilever3

LLNL has developed a compact and low-power cantilever-based sensor array, which has been used to detect various vapor-phase analytes. For further information on the latest developments, see the article "Sniffing the Air with an Electronic Nose."