• Title/Summary/Keyword: FCA coefficient

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Deep Learning-based Extraction of Auger and FCA Coefficients in 850 nm GaAs/AlGaAs Laser Diodes

  • Jung-Tack Yang;Hyewon Han;Woo-Young Choi
    • Current Optics and Photonics
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    • v.8 no.1
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    • pp.80-85
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    • 2024
  • Numerical values of the Auger coefficient and the free carrier absorption (FCA) coefficient are extracted by applying deep neural networks (DNNs) to the L-I characteristics of 850 nm GaAs/AlGaAs laser diodes. Two elemental DNNs are used to extract each coefficient sequentially. The fidelity of the extracted values is established through meticulous correlation of L-I characteristics bridging the realms of simulations and measurements. The methodology presented in this paper offers a way to accurately extract the Auger and FCA coefficients, which were traditionally treated as fitting parameters. It is anticipated that this approach will be applicable to other types of opto-electronic devices as well.