LLNL’s Distributed Implicit Neural Representation (DINR) is a novel approach to 4D time-space reconstruction of dynamic objects. DINR is the first technology to enable 4D imaging of dynamic objects at sufficiently high spatial and temporal resolutions that are necessary for real world medical and industrial applications.
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LLNL researchers have developed a method to enhance the performance of polyelectrolyte membranes by using a humidity-controlled crosslinking process which can be applied to precisely adjust the water channels of the membrane.
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.
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 a patented process to produce colloidal silica directly from geothermal fluids. Livermore’s process uses membranes to produce a mono-dispense slurry of colloidal silica particles for which there are several applications. LLNL has demonstrated that colloidal silica solutions that result from extraction of silica from geothermal fluids undergo a transition to a solid gel over a range of…