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’s high throughput method involves proteome-wide screening for linear B-cell epitopes using native proteomes isolated from a pathogen of interest and convalescent sera from immunized animals. LLNL researchers have applied their newly developed generalizable screening method to the identification of pathogenic bacteria by screening linear B-cell epitopes in the proteome of Francisella…

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…

LLNL has developed a novel process of production, isolation, characterization, and functional re-constitution of membrane-associated proteins in a single step. In addition, LLNL has developed a colorimetric assay that indicates production, correct folding, and incorporation of bR into soluble nanolipoprotein particles (NLPs).

LLNL has developed an approach, for formation of NLP/…

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…