A thyristor will stay conducting until the current through the device is zero (“current zero”) or perhaps slightly negative.  LLNL’s approach is to use the opticondistor (“OTV”) to force this current zero in order to force the device into an “off” state.  By combining a light-activated thyristor with an OTV, a noise-immune, high efficiency, high-power switching device can be…

The approach is to leverage the fact that a momentary “load” equal to the power transmission line impedance, (Z0), during the transient can suppress its propagation.  Z(0) is typically a fixed impedance of several hundred ohms based on the geometry of most single wire transmission lines.

So, an isolated self-powered opticondistor (OTV) system may provide an ultrafast method of…

LLNL’s novel approach to enable MVDC power systems to operate safely is to develop a wideband gap bulk optical semiconductor switch (WBG BOSS) circuit breaker.  For higher power, efficiency and temperature operation, vanadium-doped silicon carbide (V-doped SiC) appears to be the most promising basis for WBG BOSS circuit breaker (other dopants like aluminum, boron and nitrogen may further…

LLNL researchers has developed an approach to mitigate HER on the ‘plating’ electrode, which uses a sub-device as a rebalancing cell to restore electrolyte properties, including pH, conductivity, and capacity across the main device of the flow battery.  This sub-device, which may need to be powered externally, has three major physical components: (1) a cathode electrode, (2) an anode…

LLNL has developed a novel methodology for using commercially available automated sensors and actuators which can be deployed at scale in large appliances and plug-in EVs to provide as needed electric grid stabilization capabilities. The approach comprises of a population of voltage relays with a range of setpoints that would gradually reduce load as voltage falls. More severe voltage…

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 address many of the aforementioned challenges of manufacturing LIBs and SSBs, LLNL researchers have developed a number of inventions that offer proposed solutions for their components:

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…

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…