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.

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 constructed. The…

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 electrode…

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 extruded…

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…

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:

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 interfacial…

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…

Livermore researchers have developed two novel TiCl4 based non-alkoxide sol-gel approaches for the synthesis of SiO2/TiO2 nanocomposite aerogels. Composite SiO2-TiO2 aerogels were obtained by epoxide-assisted gelation (EAG route) of TiCl4/DMF solution in the presence SiO2 aerogel particles. Additionally, the same TiCl4/DMF solution was employed to prepare SiO2@TiO2 aerogels by a facile one-…

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…

Chemical and biological sensors based on nanowire or nanotube technologies exhibit observable ultrasensitive detection limits due to their unusually large surface-to-volume architecture. This suggests that nanosensors can provide a distinct advantage over conventional designs. This advantage is further enhanced when the nanosensor can harvest its meager power requirements from the surrounding…

The design calculations that have been performed in exploring the potentialities of LLNL's new approaches to flywheel energy storage have been built on existing and past LLNL flywheel programs, including a program aimed at flywheel systems for the bulk storage of electricity at utility scale. To achieve the requirements of such systems, as mentioned above, LLNL has developed some key new…

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)…

LLNL has developed novel nanoporous carbon materials for the surface-stress-induced actuator technology. The morphology of these materials has been designed to combine high surface area and mechanical strength. The process allows for the fabrication of large monolithic pieces with low densities and high structural integrity. One actuation technology relies on electrochemically- induced changes…