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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LLNL researchers have developed an innovative and uniform single-pot polymer multi-material system, based on a combination of 3 different reactive chemistries. By combining the three different constituent monomers, fine control of mechanical attributes, such as elastic modulus, can be achieved by adjusting the dosage of UV light throughout the additive manufacturing process. This results in…
To overcome challenges that existing techniques for creating 3DGs face, LLNL researchers have developed a method that uses a light-based 3D printing process to rapidly create 3DG lattices of essentially any desired structure with graphene strut microstructure having pore sizes on the order of 10 nm. This flexible technique enables printing 3D micro-architected graphene objects with complex,…
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…
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…
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."