Powder atomic layer deposition process is used to coat nanopowders of host materials (e.g. yttrium aluminum garnet) with optically active neodymium organometal precursor followed by O2/O3 RF plasma to convert to a single layer of Nd2O3. The process can be repeated to build arbitrarily thick layers with custom doping profiles and followed by post-…
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This invention works by imaging an ultrafast pulse diffracted from a large grating onto a spatial light modulator (SLM) thereby directly transcribing an arbitrary record on a pulse front tilted (PFT) ultrafast pulse. The grating generates PFT of the input pulse, and the SLM provides temporal control of the pulse through the space-to-time mapping of the tilted pulse. Coupling this patterned…
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This invention exploits the non-linearities of optical Mach-Zehnder (MZ) electrooptic modulators to enhance small signal dynamic range at higher bandwidths. A linear photodiode (PD) converts the amplified optical signal output from the MZ back to an electrical signal completing an Electrical-Optical-Electrical (EOE) conversion cycle. The dynamic range can be further enhanced by daisy chaining…
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This invention proposes using a pulse laser configured to generate laser pulses and a controller for controlling operation of the pulse laser. The controller is further configured to control the pulse laser to cause the pulse laser to generate at least one of the laser pulses with a spatiotemporally varying laser fluence over a duration of at least one of the laser pulses. The spatiotemporally…
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LLNL researchers in the NIF Directorate DoD Technologies RF Photonics Group explored phase modulation solutions to this signal processing challenge. Optical frequency combs offer phase noise characteristics that are orders of magnitude lower than available from commercial microwave references. The Photonics Group researchers recognized that by converting the intensity information into phase,…
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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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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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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 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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Livermore Lab researchers have developed two new methods for improving the efficiency of laser drilling. The first method is based on multi-pulse laser technology. Two synchronized free-running laser pulses from a tandem-head Nd:YAG laser and a gated CW laser are capable of drilling through 1/8-in-thick stainless-steel targets at a standoff distance of 1 m without gas-assist. The combination of a…
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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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The new LLNL technique works by transiently removing and trapping concrete or rock surface material, so that contaminants are confined in a manner that is easy to isolate and remove. Our studies suggest that 10 m2 of surface could be processed per hour. The technique easily scales to more surface/hr.