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’s novel approach is to use diamond substrates with the desired donor (nitrogen) and acceptor (boron) impurities. In order to optically activate these deep impurities, the invention requires at least one externally or internally integrated light source. The initial exposure to light can set up the desired conduction current, after which the light source could be turned off. Even with…
The LiDO code combines finite element analysis, design sensitivity analysis and nonlinear programming in a High-Performance Computing (HPC) environment that enables the solution of large-scale structural optimization problems in a computationally efficient manner. Currently, the code uses topology optimization strategies in which a given material is optimally distributed throughout the domain…
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…
Simrev is a python library imported into a user-generated program. As the program grows in capability and complexity, the engineered product matures. The "software twin" handles all changes to product configuration and is the portal to running supercomputing analysis and managing workflow for engineering simulation codes. Assemblies become program modules; parts, materials, boundary conditions…