Skip to main content
Image
Photograph of glass sample unplated on one side (left) and plated with nickel phosphorous on the other (right)

LLNL researchers have continued to develop their pioneering DIW 3D-printed glass optics technology that allows for the 3D printing of single- and multi-material optical glass compositions in complex shapes. This LLNL invention further proposes incorporating dopants (including, but not limited to TiO2 and Pd) into slurries and inks for 3D printing of glass components that can then be directly…

Image
Flash Stock Image

This invention proposes achieving the same effect of a single, high intensity pulse through the use of a closely spaced burst of short duration pulses. By keeping the intensity of the individual pulses below the damage threshold the risk of catastrophic damage is greatly mitigated. Additionally, the pulses are directed to strike the target at locations temporally and spatially sufficiently…

Image
Left to right: Drew Willard, Brendan Reagan, and Issa Tamer work on the Tm:YLF laser system. Photos by Jason Laurea

This invention proposes the use of a nonlinear spectral broadening subsystem as a post-CPA pulse compression add-on for high energy laser systems. The proposed solution utilizes the beam profile of a high peak power laser as a reference to shape a highly transmissive nonlinear plastic (e.g., CR39) itself to ensure a spatially homogeneous nonlinear spectral broadening.

Image
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.

Image
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…

Image
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…

Image
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…

Image
gradient_composition_glass

LLNL researchers have developed a custom resin formulation which uses a dispersing solvent and only a multifunctional monomer as the binding agent. The dispersing solvent system typically used has multiple components meant to achieve excellent dispersal of silica in order to create a flowable resin (rather than a paste). The dispersing agent has low vapor pressure, which allows the 3D printed…

Image
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…