This invention proposes to engineer the current density along the length of a laser diode to overcome the penalty associated with non-uniformity resulting from asymmetry in the gain, photon or carrier density despite having uniform contact. Optimizing the current density profile enables diode lasers to operate with greater power conversion efficiency or operate with equivalent power conversion…

This invention proposes to engineer the temperature dependence of the emission wavelength of LEDs and laser diodes. The approach is to use a strain-inducing coating to counteract the intrinsic temperature coefficient of the emission wavelength of the LED or laser diode device thereby rendering it athermal. This invention avoids additional complexity, size, weight and power dissipation of…

This invention proposes a method to overcome the key limitation of electrically pumped lasers based on AlN, AlGaN, or AlInGaN, namely the lack of suitable shallow donor and acceptor dopants. As the band gap of these materials increases (and the emission wavelength decreases), both electrons and holes require greater thermal energies in order to ionize.

Laser diode lensing effect can be substantially reduced by creating a pattern interface such that the substrate is only attached at the diode mesa. This is achieved by either creating a pattern solder joint and/or pattern substrate.

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.

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…

Recent advancements in additive manufacturing, also called 3D printing, allow precise placement of materials in three dimensions. LLNL researchers have invented mechanical logic gates based on flexures that can be integrated into the microstructure of a micro-architected material through 3D printing. The logic gates can be combined into circuits allowing complex logic operations to be…

The LLNL method for optimizing as built optical designs uses insights from perturbed optical system theory and reformulates perturbation of optical performance in terms of double Zernikes, which can be calculated analytically rather than by tracing thousands of rays. A new theory of compensation is enabled by the use of double Zernikes which allows the performance degradation of a perturbed…

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…