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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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.
Rapid monolith development at scale is achieved through use of a functionally equivalent optic simulant made from a low-cost material to substitute the functional optic. Monolith optical performance is affected not only by thermal expansion but also by temperature inhomogeneity due to the temperature dependence of refractive index.
Aeroptics are a proposed new class of monolithic optical system in aerogel fabricated by molding around a master mandrel. This approach combines the intrinsic stability of proven monolithic telescopes, with the ultralow density of silica aerogels. In Aeroptics, the monolith is hollow with an aerogel substrate providing a supporting structure. Theoretically, Aeroptics could enable 1-m aperture…
This invention achieves both a wider field of view and faster f-number within a monolithic substrate by incorporating an aspheric convex refractive first surface and a planar aspheric field corrector surface on the final refractive surface. These two refractive surfaces work in conjunction with a concave aspheric primary and convex aspheric secondary mirror (e.g. Cassegrain type) to improve…
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-…
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 extruded…
CSP-POST provides the capability to inspect all incoming and outgoing emails while providing after-the-fact forensic capabilities. Using commercially available lightweight and serverless technologies, CSP-POST easily collects all email and parses it into easily searchable metadata, enriched and ready for analysis. The web-based application is deployed in a repeatable, testable, and auditable…
LLNL has invented a new system that uses public key cryptography to differentiate between human-generated text and AI-generated text. This invention can be used to validate that text is likely to be human generated for the purposes of sorting or gatekeeping on the internet, can detect cheating on essay assignments, and can be used as an automatic captcha that does away with the hassle of…
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 diverse…
To address shortcomings of current liposome drug delivery systems, the patented innovation uses drug-loaded liposomes containing carbon nanotube porins (CNTPs) inserted into the liposomal membranes for the delivery of the encapsulated drugs. Short CNTPs (10 nm in length) with narrow diameter (0.8 nm) has been demonstrated to facilitate efficient fusion of lipid bilayers resulting in the…
A new approach of developing synthetic antibacterial mineral assemblages can be used as an alternative treatment when traditional antibiotics fail in clinical and agricultural settings. Mineral mixtures can be synthesized with tunable metal release and reactive oxygen species generation that are capable of killing human pathogens and promoting wound healing. One of the key components in the…
The method described in a pending patent application uses a novel thiacrown (dibenzohexathia-18-crown-6) for efficient extraction of 197m,gHg and 197gHg from irradiated Pt target foils. The separation of 197m,gHg and 197gHg from Pt foils using this novel thiacrown was found to be highly specific. No detectable amount of the Pt foil was seen in the…
Combining the principles of nanotechnology, cell-free protein synthesis and microfluidics, LLNL researchers have developed a reusable, portable programmable system that can create purified, concentrated protein product in vitro in a microfluidic device containing nucleic acids.
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 scientists developed novel hydrogels, which are biodegradable soft materials synthesized by a water-soluble polymer. Incorporating silver imparts antimicrobial activity to the material at low concentration compared to currently used silver nanoparticles. Our hydrogels are composed of silver ions instead of silver nanoparticles, which eliminates the toxicity concerns of modern silver…
Monolithic Telescopes are a novel implementation of a solid catadioptric design form, instantiated in a monolithic block of fused silica.
LLNL has developed a new method for securely processing protected data on HPC systems with minimal impact on the existing HPC operations and execution environment. It can be used with no alterations to traditional HPC operations and can be managed locally. It is fully compatible with traditional (unencrypted) processing and can run other jobs, unencrypted or not, on the cluster simultaneously…
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…
LLNL is developing the Space-based Telescopes for Actionable Refinement of Ephemeris (STARE). STARE is a constellation of low cost nano-satellites (less than 5Kg) in low-earth orbit dedicated to the observation of space debris in conjunction with a ground-based infrastructure for maintenance, coordination and data processing. Each nano-satellite in the constellation is capable of recording an…
LLNL's NeMS system enables network mapping operations by using two LLNL-developed software systems: LLNL's NeMS tool and the Everest visualization system. Each software system can be also used separately for their specific applications. When the two systems are used together as an iterative analysis platform, LLNL's NeMS system provides network security managers and information technology…