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 researchers have developed a method to enhance the performance of polyelectrolyte membranes by using a humidity-controlled crosslinking process which can be applied to precisely adjust the water channels of the membrane.
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 a Li-Sn-Zn ternary alloy and its method of production. Instead of traditional alloying techniques, the alloy was synthesized using mechanical alloying (high energy ball milling). With high purity elemental powders of lithium, tin and zinc, LLNL researchers were able to prepare Li60Sn20Zn20 as well as Li70Sn20Zn10 nanopowders.
CMI—a DOE Energy Innovation Hub—is a public/private partnership led by the Ames Laboratory that brings together the best and brightest research minds from universities, national laboratories (including LLNL), and the private sector to find innovative technology solutions to make better use of materials critical to the success of clean energy technologies as well as develop resilient and secure…
LLNL researchers have developed a new 3D printable lithium-air battery that uses a novel thin solid state ceramic electrolyte. LLNL’s invention overcomes the combined challenges of low power density and low cycle life in previously designed lithium-air batteries by using solid state electrolytes to achieve stability and multiscale structuring of the electrolyte to achieve low…
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…
Nanomaterials that are emerging out of cutting edge nanotechnology research are a key component for an energy revolution. Carbon-based nanomaterials are ushering in the "new carbon age" with carbon nanotubes, nanoporous carbons, and graphene nanosheets that will prove necessary to provide sustainable energy applications that lessen our dependence on fossil fuels.
Carbon aerogels (CAs)…