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. 

LLNL researchers have developed a TDLAS-based, standalone, real-time gas analyzer in a small form-factor for continuous or single-point monitoring.  The system can analyze multiple gases with ultra-high sensitivity (ppm detection levels) in harsh conditions when utilizing wavelength-modulation spectroscopy (WMS). 

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.

The approach is to develop a solid-state X-ray imager based on the architecture of the Silicon Drift Detector (SDD) which uses a series of cathode strips on both sides of a silicon wafer to achieve bulk depletion and electron drift.  The invention leverages this SDD functionality to achieve signal stretching of liberated charge carriers from X-Ray photons that converts the time domain…

LLNL’s novel approach is to use a continuous moving camera with a scan speed of >1 mm/sec and a frame rate of 100 frames per second.  The key is to have a light source that flashes with a duration of one nanosecond, thus essentially freezing the image with no blur.  Clear images of high resolution can then be captured through a high-magnification objective lens (reflection mode)…

LLNL’s approach to the development of a wide-field, three-dimensional quantum (3DQ) microscope is to harness quantum entangled photons to form simultaneous 3D optical images, which could be a new paradigm for 3D volumetric imaging of biological specimens.  The 3DQ microscope is comprised of a novel optical system with highly sensitive detectors and an on-demand light source of entangled…

LLNL’s novel approach combines 2-color spectroscopy with CRDS, a combination not previously utilized.

The approach is to build a high voltage insulator consisting of two materials:  Poly-Ether-Ether-Ketone (“PEEK”) and Machinable Ceramic (“MACOR”).  PEEK has a high stress tolerance but cannot withstand high temperatures, while MACOR has high heat tolerance but is difficult to machine and can be brittle.  MACOR is used for the plasma-facing surface, while PEEK will handle the…

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's 3D X-ray imager combines two different hardware pieces. The first is an x-ray optic with a depth-of-field that is small compared to the object under investigation. Reflective Wolter type x-ray optics are one such design. These hollow optics have a relatively large collection efficiency and can be designed with a large field of view. The depth of focus, which is the distance over which a…

LLNL researchers have designed and tested performance characteristics for a multichannel pyrometer that works in the NIR from 1200 to 2000 nm. A single datapoint without averaging can be acquired in 14 microseconds (sampling rate of 70,000/s). In conjunction with a diamond anvil cell, the system still works down to about 830K.

LLNL's method of equivalent time sampling incorporates an embedded system that generates the pulses used to trigger the external circuit and the data acquisition (DAQ). This removes the external reference clock, allowing the overall system clock rate to change based on the ability of the embedded system. The time delays needed to create the time stepping for equivalent time sampling is done by…

LLNL's high fidelity hydrocode is capable of predicting blast loads and directly coupling those loads to structures to predict a mechanical response. By combining this code and our expertise in modeling blast-structure interaction and damage, along with our access to experimental data and testing facilities, we can contribute to the design of protective equipment that can better mitigate the…