2023
DOI: 10.1109/ted.2022.3226672
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Trap Behavior of the Optical Power Fluctuation in AlGaN-Based UV-C LEDs Degradation

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Cited by 3 publications
(6 citation statements)
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“…[139][140][141][142][143][144] The density of point defects acting as centers for trap-assisted radiative recombination outside the active region increased. Typically, the degradation is accelerated by the operation current and temperature 28,40,41,49,57,100,107,126,[142][143][144][145][146][147][148] Trivellin et al 127 summarized mechanisms for the degradation of output power deep UV LEDs during operation and suggested that there were a number of processes that could be present. These included: i.…”
Section: Literature Resultsmentioning
confidence: 99%
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“…[139][140][141][142][143][144] The density of point defects acting as centers for trap-assisted radiative recombination outside the active region increased. Typically, the degradation is accelerated by the operation current and temperature 28,40,41,49,57,100,107,126,[142][143][144][145][146][147][148] Trivellin et al 127 summarized mechanisms for the degradation of output power deep UV LEDs during operation and suggested that there were a number of processes that could be present. These included: i.…”
Section: Literature Resultsmentioning
confidence: 99%
“…120,121 Uedono et al 122 reported formation of vacancy-oxygen complexes in AlN epitaxial films and suggested these could be a source of grown-in defects in the layers used for the deep UV LEDs. Su et al 147 reported an increase in concentration of deep trap states at Ec-0.5 eV (E2), 0.68--0.79 eV (E3), and 0.95-1.2 eV (E4) after current stress.…”
Section: Literature Resultsmentioning
confidence: 99%
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“…[74] The energy consumption of simulated excitatory and inhibitory per spike is calculated to be ≈234 and 40 fJ respectively, close to the energy consumption of biological synapses (≈10 fJ), demonstrating the immense potential of 2D FeFETs in neural computing. [75] In addition, the thermal configuration of the device for neuromorphic computing is shown in Figure 7e. Thermal assistance can provide a larger dynamic range for network weight mapping, which can help improve computational accuracy.…”
Section: Spiking Neural Network and Artificial Neural Networkmentioning
confidence: 99%