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-…
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![Picture of SLA printed structures using 3D printable nitrile-containing photopolymer resins](/sites/default/files/styles/scale_exact_400x400_/public/2024-04/SLA%20printed%20structures%20using%203D%20printable%20nitrile-containing%20photopolymer%20resins.jpg?itok=cVxxoNNY)
![CT Scanner Adobe Stock Image](/sites/default/files/styles/scale_exact_400x400_/public/2024-03/CT%20Scanner.jpeg?itok=tHCxNWpA)
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.
![Printed TPMS membrane structures using nanoporous photoresist](/sites/default/files/styles/scale_exact_400x400_/public/2023-12/Printed%20TPMS%20membrane%20structures.png?itok=siH1EwC9)
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-…
![Potential reactor configurations with printed TPMS scaffolds](/sites/default/files/styles/scale_exact_400x400_/public/2023-12/Reactor_Config_with_TPMS_scaffolds.png?itok=stDW7Z7n)
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:
![Filled (8,8) (left) and (15,15) (right) CNTs with [EMIM+][BF4- ] using SGTI with the proposed spliced soft-core potential (SSCP) approach](/sites/default/files/styles/scale_exact_400x400_/public/2023-10/Filled%20CNTs%20using%20SGTI.png?itok=Dy0ObN7i)
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…
![Livermore Tomography Tools LTT](/sites/default/files/styles/scale_exact_400x400_/public/2022-06/LTT.jpg?itok=cQE9Kpef)
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…
![Nanoporus gold](/sites/default/files/styles/scale_exact_400x400_/public/2022-06/nanoporus%20gold%20875x500.jpg?itok=A0gFmVPT)
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…
![energy_absorbing_material.jpg energy_absorbing_material](/sites/default/files/styles/scale_exact_400x400_/public/2019-08/energy_absorbing_material.jpg?itok=UxNZ6nWH)
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…