LLNL’s researchers use physical vapor deposition (sputter deposition or electron beam deposition) to coat an inert gasket material (i.e. PTFE) with a conductive metal (i.e. copper). The gas diffusion electrode overlaps onto the copper coated gasket to allow for electrical conductivity between the catalyst surface and the flow field/current collector of a CO2 electrolyzer. The coated gasket…

Using their computational design optimization, LLNL researchers have developed copper-based dilute alloy catalysts (contains <10 at.% of the minority metal alloy component) and demonstrated these novel catalysts have improved energy efficiency and selectivity of the methane conversion reaction.  By alloying copper with a small amount of the electropositive minority metal element, the…

LLNL’s innovation offers an alternate synthetic route to graphite at lower cost using a molten salt mixture of CaCl2-CaCO3-CaO.  The synthetic production of graphite and other high-value carbon materials is accomplished in molten salt media via electrochemical reduction and transformation of the carbon from the carbonate ion. The broad electrochemical window of molten salts enables the…

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…

The novel LLNL approach is to use projection microstereolithography (LAPµSL), starting with a photocurable methacrylate resin formulation consisting of a combination of a photoinitiator, photoabsorber, inhibitor, solvents, and other additives.  Prior to use, the resin is pretreated to control viscosity for easier handling.  The resin is fed to a LAPµSL printer which employs a near UV light…

The inventors have developed a 3% Yttria partially-stabilized Zirconia (3YZ) ceramic ink that produces parts with both nano and microporosity and is compatible with two AM techniques: DIW and projection microstereolithography (PμSL). The 3YZ nano-porous ceramic printed parts had engineered macro cavities measuring several millimeters in length, wall thicknesses ranging from 200 to 540 μm, and…

This invention describes a multiple nozzle microfluidic unit that allows simultaneous generation streams of multiple layered coaxial liquid jets. Liquids are pumped into the device at a combined flow rate from 100 mL/hr to 10 L/hr. Droplets are created with diameters in the range of 1 µm to 5 mm and can be created with 1-2 shell layers encapsulating fluid. Droplets created from the system can…

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 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'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…