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Adobe Stock image laser beam

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…

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Schematic showing mismatched coefficient of thermal expansion (CTE) coating

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…

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Photoconductive Semiconductor Laser Diodes and LEDs

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.

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Adobe Stock image laser beam

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.

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graphic_of_simulation
Livermore researchers have developed a method for implementing closed-loop control in extrusion printing processes by means of novel sensing, machine learning, and optimal control algorithms for the optimization of printing parameters and controllability. The system includes a suite of sensors, including cameras, voltage and current meters, scales, etc., that provide in-situ process monitoring…
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Machine Learning for Monitoring microfluidic microcapsules
LLNL researchers have developed a system that relies on machine learning to monitor microfluidic devices. The system includes (at least) a microfluidic device, sensor(s), and a local network computer. The system could also include a camera that takes real-time images of channel(s) within an operating microfluidic device. A subset of these images can be used to train/teach a machine learning…