This LLNL invention allows for the fabrication of complex waveplate features and topologies from fused silica, a highly desirable and durable waveplate material.  It also is a unique technique for density multiplication and high-fidelity bidirectional deposition, which can create optical components that are generally for entirely new classes of optical materials.

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This LLNL invention concerns a method for patterning the index of refraction by fabricating a spatially invariant metasurface, and then apply spatially varied mechanical loading to compress the metasurface features vertically and spread them radially. In doing so, the index of refraction can be re-written on the metasurface, thus enabling index patterning. This process allows rapid 'rewriting…

This novel invention specifically enables the fabrication of arbitrarily tailored birefringence characteristics in nano-structured meta-surfaces on non-birefringent substrates (e.g. fused silica). The birefringent nano-structured meta-surface is produced by angled directional reactive ion beam etching through a nano-particle mask. This method enables the simultaneous tailoring of refractive…

This invention (US Patent No. 11,294,103) is an extension of another LLNL invention, US Patent No. 10,612,145, which utilizes a thin sacrificial metal mask layer deposited on a dielectric substrate (e.g. fused silica) and subsequently nanostructured through a laser generated selective thermal de-wetting process.

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-…

LLNL researchers have developed a fabrication process for creating 3D random interdigitated architectures of anodes and cathodes, eliminating the need for a membrane to separate them.  This approach is similar to the repeating interdigitated multi-electrode architectures that also were developed at LLNL. 

This invention consists of a method of forming nanoscale metal lines to produce a grating-like mask with wide area coverage over the surface of a durable optical material such as fused silica. Subsequent etching processes transfer the metal mask to the underlying substrate forming a birefringent metasurface. This method enables the production of ultrathin waveplates for high power laser…

Heat sensitive materials such as piezoelectric and MEMS devices and assemblies, magnetic sensors, nonlinear optical crystals, laser glass or solid-state laser materials, etc. cannot be exposed to excess temperatures which in the context of this invention, means materials that cannot be exposed to temperatures greater than 50°C (122°F). LLNL’s invention describes a low-temperature method of…

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…

Improving the active material of the Zn anode is critical to improving the practicality of Zn-MnO2 battery technology. LLNL researchers have developed a new category of 3D structured Zn anode using a direct-ink writing (DIW) printing process to create innovative hierarchical architectures.  The DIW ink, which is a gel-based mixture composed of zinc metal powder and organic binders, is…

To get the best of both worlds – the sensitivity of LC-MS with the speed of PS-MS – and a functional substrate that can maintain sample integrity, LLNL researchers looked to 3D printing.  They have patented a novel approach to create lattice spray substrates for direct ionization mass spectroscopy using 3D-printing processes.

LLNL researchers, through careful control over the chemistry, network formation, and crosslink density of the ink formulations as well as introduction of selected additives, have been successful in preparing 3D printable silicone inks with tunable material properties.  For DIW (direct in writing) applications, LLNL has a growing IP portfolio around 3D printable silicone feedstocks for…

This novel method of producing waveplates from isotropic optical materials (e.g. fused silica) consists of forming a void-dash metasurface using the following process steps:

LLNL’s method of 3D printing fiber-reinforced composites has two enabling features:

Lawrence Livermore National Laboratory (LLNL) is offering the opportunity to collaborate in accelerating artificial intelligence (AI) for applied science, including research in key areas such as advanced material design, 3D printing, predictive biology, energy systems, “self-driving” lasers and fusion energy research.

Clinical images have a wealth of data that are currently untapped by physicians and machine learning (ML) methods alike. Most ML methods require more data than is available to sufficiently train them. In order to obtain all data contained in a clinical image, it is imperative to be able to utilize multimodal, or various types of, data such as tags or identifications, especially where spatial…

Some COVID-19 diagnoses are utilizing computed tomography (CT)-scans for triage. CT-scans produce immediate results with high sensitivity. The digital images produced by a CT-scan require physicians to identify objects within the image to determine the presence of disease. Object identification can be done using machine learning (ML) techniques such as deep learning (DL) to improve speed and…

MimicGAN represents a new generation of methods that can “self-correct” for unseen corruptions in the data out in the field. This is particularly useful for systems that need to be deployed autonomously without needing constant intervention such as Automated Driver Assistance Systems. MimicGAN achieves this by treating every test sample as “corrupt” by default. The goal is to determine (a) the…

LLNL has developed a new system, called the Segmentation Ensembles System, that provides a simple and general way to fuse high-level and low-level information and leads to a substantial increase in overall performance of digital image analysis. LLNL researchers have demonstrated the effectiveness of the approach on applications ranging from automatic threat detection for airport security, to…