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…
Keywords
- Show all (86)
- Instrumentation (38)
- Diagnostics (13)
- Data Science (5)
- Therapeutics (5)
- Brain Computer Interface (BCI) (4)
- Cybersecurity (4)
- Analysis (2)
- Computing (2)
- Simulation (2)
- Vaccines (2)
- Polymer Electrodes (1)
- Quantum Science (1)
- Synthesis and Processing (1)
- (-) Imaging Systems (3)
- (-) Rare Earth Elements (REEs) (2)
- (-) Information Technology (1)
LLNL’s Distributed Implicit Neural Representation (DINR) is a novel approach to 4D time-space reconstruction of dynamic objects. DINR is the first technology to enable 4D imaging of dynamic objects at sufficiently high spatial and temporal resolutions that are necessary for real world medical and industrial applications.
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 discovered that some inexpensive and commercially available molecules used for other applications, could render certain lanthanide and actinide elements highly fluorescent. These molecules are not sold for applications involving the detection of REEs and actinides via fluorescence. They are instead used as additives in cosmetic products and/or in the pharmaceutical…
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…
LLNL has developed a new active memory data reorganization engine. In the simplest case, data can be reorganized within the memory system to present a new view of the data. The new view may be a subset or a rearrangement of the original data. As an example, an array of structures might be more efficiently accessed by a CPU as a structure of arrays. Active memory can assemble an alternative…