This LLNL invention is comprised of (1) a volumetric subtractive manufacturing system which can tomographically manufacture 3D structures with negative features (materials in negative space is degraded with light exposure), and (2) a hybrid volumetric additive/subtractive manufacturing system in which a gelled/solid structure is printed by resin material polymerization using one light, and…

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…

LLNL has developed a system and method that accomplishes volumetric fabrication by applying computed tomography (CT) techniques in reverse, fabricating structures by exposing a photopolymer resin volume from multiple angles, updating the light field at each angle. The necessary light fields are spatially and/or temporally multiplexed, such that their summed energy dose in a target resin volume…

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…