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Stock image of 3d render of network made of wind turbines, solar panels, battery and house

LLNL researchers have designed and produced, both conductive and non-conductive porous electrode components manufactured for improved metal deposition, discharging, and fluid dynamics in hybrid flow batteries.  This is achieved through Direct Ink Writing (DIW) additive manufacturing.  The engineered 3D electrodes enable uniform current distribution and even metal deposition during charging…

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Small-angle X-ray scattering (SAXS) data of crosslinked polyelectrolyte membrane films formed under different equilibrium humidity conditions

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.

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Picture of SLA printed structures using 3D printable nitrile-containing photopolymer resins

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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Examples of different UV exposure patterns printed from the same multi-material resin.  Darker yellow regions have higher UV exposure times leading to tougher regions.

LLNL researchers have developed an innovative and uniform single-pot polymer multi-material system, based on a combination of 3 different reactive chemistries.  By combining the three different constituent monomers, fine control of mechanical attributes, such as elastic modulus, can be achieved by adjusting the dosage of UV light throughout the additive manufacturing process.  This results in…

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Electrodeposition of Zn onto 3D printed copper nanowire (CuNW)

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…

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Livermore researchers support efforts to limit the need for rare-earth elements in U.S. clean-energy technologies.

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…

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A sample of micro-architectured graphene aerogel, made from one of the lightest materials on Earth, sits atop a flower.

To overcome challenges that existing techniques for creating 3DGs face, LLNL researchers have developed a method that uses a light-based 3D printing process to rapidly create 3DG lattices of essentially any desired structure with graphene strut microstructure having pore sizes on the order of 10 nm. This flexible technique enables printing 3D micro-architected graphene objects with complex,…

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One embodiment of a solid-state lithium-air battery based on gyroid foams.

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…

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AI Innovation Incubator

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.

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Catalyst HPC cluster

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…

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medical_x-rays_x-ray_tech

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…

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MimicGAN data set example

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…

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nanocomposite_aerogel

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-…

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Nanoporus gold

By combining 3D printing and dealloying., researchers at LLNL have developed a method for fabricating metal foams with engineered hierarchical architectures consisting of pores at least 3 distinct length scales. LLNL’s method uses direct ink writing (DIW), a 3D printing technique for additive manufacturing to fabricate hierarchical nanoporous metal foams with deterministically controlled 3D…

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medical_x-rays_x-ray_tech

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…

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Batteryless Sensor

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…

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3D printed electrodes

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)…

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3D printed electrodes

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…