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 invention is a photopolymerizable polymer resin that consists of one or more nitrile-functional based polymers. The resin is formulated for SLA based 3D printing allowing for the production of nitrile-containing polymer components that can then be thermally processed into a conductive, highly graphitic materials. The novelty of the invention lies in (1) the photo-curable nitrile-…
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.
LLNL researchers have developed novel advanced manufactured biomimetic 3D-TPMS (triply periodic minimal surface) membrane architectures such as a 3D gyroid membrane. The membrane is printed using LLNL's nano-porous photoresist technology. LLNL’s 3D-TPMS membranes consist of two independent but interpenetrating macropore flow channel systems that are separated by a thin nano-porous wall. 3D-…
LLNL researchers have devised a set of design principles that facilitates the development of practical TPMS-based two fluid flow reactors.; included in the design are these new concepts:
LLNL researchers have developed a novel simulation methodology using slow growth thermodynamic integration (SGTI) utilizing spliced soft-core interaction potential (SSCP). The approach to filling the molecular enclosures is a nonphysical one. Rather than filling the pores from the open ends this method creates steps in the algorithm that allow molecules to pass through the pore wall and…
LLNL has developed a method of extending device lifetimes by imprinting into the device a shape that excludes specific vibrational modes, otherwise known as a phononic bandgap. Eliminating these modes prevents one of the primary energy loss pathways in these devices. LLNL’s new method enhances the coherence of superconducting circuits by introducing a phononic bandgap around the system’s…
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…
By combining 3D printing and dealloying., researchers at LLNL have developed a method for fabricating metal foams with engineered hierarchical architectures consisting of pores at least 3 distinct length scales. LLNL’s method uses direct ink writing (DIW), a 3D printing technique for additive manufacturing to fabricate hierarchical nanoporous metal foams with deterministically controlled 3D…
To overcome limitations with cellular silicone foams, LLNL innovators have developed a new 3D energy absorbing material with tailored/engineered bulk-scale properties. The energy absorbing material has 3D patterned architectures specially designed for specific energy absorbing properties. The combination of LLNL's capabilities in advanced modeling and simulation and the additive…