To address these challenges and explore the scale-up science of MXene, LLNL researchers have developed a scalable solution-phase synthesis method to generate MXene with over 70% production yield via top-down exfoliation approaches with non-aqueous solvents and salts.  The novel method is a dramatic improvement compared to conventional approaches (10-20%). Furthermore, the shielding…

LLNL researchers have developed a novel photocurable silicone useful for producing three-dimensional objects via additive manufacturing. The resin formulations consist of a mult-component siloxane polymers with different functionalities, a platinum catalyst, a photoinitiator, and other organic peroxides.  The LLNL invention involves controlling the spatial and temporal aspects of the…

LLNL has developed a novel Production of Readily compressible dies for Enhanced Sintering of Solids (PRESS) method for ceramic parts manufacturing that uses compressible, non-sintering powder materials as a mold which can match the compaction of the ceramic powder starting materials during pressure-assisted sintering. PRESS enables uniform deformation of the part under a constant linear travel…

As an important step toward overcoming the technical and environmental limitations of current REE processing methods, the LLNL team has patented and demonstrated a biobased, all-aqueous REE extraction and separation scheme using the REE-selective lanmodulin protein. Lanmodulin can be fixed onto porous support materials using thiol-maleimide chemistry, which can enable tandem REE purification…

The essence of this invention is a method that couples network architecture using neural implicit representations coupled with a novel parametric motion field to perform limited angle 4D-CT reconstruction of deforming scenes.

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…

LLNL researchers have developed a method to incorporate gas phase synthesized graphene (GSG) as a unique additive in a UV-crosslinkable polymer formulation. The GSG is added by using a planetary mixer to obtain a homogenous suspension of GSG in polymer. The resulting formulation is highly stable and doesn't show signs of phase separation or solid sedimentation. The polymer formulation is then…

LLNL researchers developed a novel method to nucleate the alpha phase of Tantalum on a polymer surface at room temperature, allowing for the controllable formation of a variety of 3D structures, such as airbridges. Using this method with a subsequent Piranha etch results in the complete removal of the residues of the polymer 'scaffolding' or template while allowing the deposited tantalum…

LLNL researchers have developed a Li-Sn-Zn ternary alloy and its method of production.  Instead of traditional alloying techniques, the alloy was synthesized using mechanical alloying (high energy ball milling).  With high purity elemental powders of lithium, tin and zinc, LLNL researchers were able to prepare Li60Sn20Zn20 as well as Li70Sn20Zn10 nanopowders.

LLNL inventors have created innovative steps in the synthesis, carbonation and activation steps of aerogel manufacturing that allows for large scale production. These steps are:

1. Synthesis: a novel pre-cure step with subsequent gelation (RF precursor solution is heated with stirring to achieve a mixed liquid intermediate temperature, the precursor solution is then allowed to cool,…

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 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,…

The novel technology developed at LLNL is a new, effective means of separating and concentrating Sc from lanthanides and non-REEs in unconventional, waste-derived feedstocks, thereby transforming an essentially valueless solution into valuable Sc concentrates.  The results represent an important advance in the development of an environmentally sustainable alternative to organic solvent-…

LLNL researchers along with collaborators at Pennsylvania State University have found that a newly discovered natural protein named Lanmodulin (LanM) could be a potential candidate for extracting REEs from ore or other sources such as coal ash as well as purifying the REE material.  Through joint research, the scientists found that LanM undergoes a large conformational change in response…

LLNL researchers have developed a custom formulated extreme low viscosity reactive silicone resin base modified with a temperature dependent thixotrope along with a modified catalyst package.  The uncatalyzed composition is capable of accepting loadings of polymer microspheres sufficient to produce a cured bulk rubber that has a density as low as 0.3 g/cc, thus compatible with high-…

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.

To solve these challenges using new and existing CT system designs, LLNL has developed an innovative software package for CT data processing and reconstruction. Livermore Tomography Tools (LTT) is a modern integrated software package that includes all aspects of CT modeling, simulation, reconstruction, and analysis algorithms based on the latest research in the field. LTT contains the most…

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…

The LLNL method is based on freeze‐casting of aerosolized and pressurized metal salt solutions and subsequent thermal processing. This method generates both porous particles with sizes down to one micron and macroscopic monoliths with nanometer scale ligaments/struts. The material's density can be controlled during the freeze‐dried stage. Compared to conventional approaches, this method…

LLNL has developed a liquid-free method that increases the overall mechanical resistance of self-supported, carbon nanotube assemblies through nanoscale reinforcement by gas-phase deposition of a thermally cross-linkable polymer. Polymer-reinforcement increases the strength of CNT yarns after crosslinking. For example, a minimal amount (<200 nm) of poly-glycidyl metacrylate (PGMA) deposited…

LLNL researchers have developed a novel method of 3D printing regular microstructured architectures and subsequent complex macrostructures from additively manufactured bio-based composite thermoset shape memory polymer composite materials. This technology for 3D additively manufactured parts utilizes up to a 4 axis control DIW system for fabricating bio­ based thermally cured epoxy based SMP…

LLNL researchers have developed the hardware and chemistry to allow additive manufacturing of short carbon fibers in a thermoset polymer matrix which have a high degree of structural alignment over conventional cast or pressed short/chopped carbon fiber polymer composites.

The invention is based on the shear dispersal, alignment and concentration of fiber fraction within a resin…

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…

Redox ion-exchange polymers ("redox-ionites") and membranes possessing cation- and anion- exchange, amphoteric, complex-forming and oxidation-reduction abilities have been developed on the basis of the biocompatible synthetic and chemically modified natural polymers. In addition, developments have been made towards methods of obtaining of water-soluble and spatially cross-linked ionites of…