scholarly journals Rate-equation model for multi-mode semiconductor lasers with spatial hole burning

2014 ◽  
Vol 22 (7) ◽  
pp. 8143 ◽  
Author(s):  
Daan Lenstra ◽  
Mirvais Yousefi
Keyword(s):  
Semiconductor Lasers ◽  
Rate Equation ◽  
Equation Model ◽  
Hole Burning ◽  
Rate Equation Model ◽  
Spatial Hole Burning ◽  
Multi Mode

scholarly journals Efficiency Droop and Effective Active Volume in GaN-Based Light-Emitting Diodes Grown on Sapphire and Silicon Substrates

2019 ◽  
Vol 9 (19) ◽  
pp. 4160 ◽  
Author(s):  
Ryu ◽  
Ryu ◽  
Onwukaeme
Keyword(s):  
Quantum Well ◽  
Rate Equation ◽  
Equation Model ◽  
Efficiency Droop ◽  
Internal Electric Field ◽  
Active Volume ◽  
Light Emitting ◽  
Rate Equation Model ◽  
Sapphire Substrates ◽  
The Difference

We compared the efficiency droop of InGaN multiple-quantum-well (MQW) blue light-emitting diode (LED) structures grown on silicon(111) and c-plane sapphire substrates and analyzed the efficiency droop characteristics using the rate equation model with reduced effective active volume. The efficiency droop of the LED sample on silicon was observed to be reduced considerably compared with that of the identical LED sample on sapphire substrates. When the measured external quantum efficiency was fitted with the rate equation model, the effective active volume of the MQW on silicon was found to be ~1.45 times larger than that of the MQW on sapphire. The lower efficiency droop in the LED on silicon could be attributed to its larger effective active volume compared with the LED on sapphire. The simulation results showed that the effective active volume decreased as the internal electric fields increased, as a result of the reduced overlap of the electron and hole distribution inside the quantum well and the inhomogeneous carrier distribution in the MQWs. The difference in the internal electric field of the MQW between the LED on silicon and sapphire could be a major reason for the difference in the effective active volume, and consequently, the efficiency droop.

A rate equation model for the energy transfer mechanism of a novel multi-color-emissive phosphor, Ca1.624Sr0.376Si5O3N6:Eu2+

2019 ◽  
Vol 6 (12) ◽  
pp. 3493-3500
Author(s):  
Jin Hee Lee ◽  
Satendra Pal Singh ◽  
Minseuk Kim ◽  
Myoungho Pyo ◽  
Woon Bae Park ◽  
...  
Keyword(s):  
Energy Transfer ◽  
Rate Equation ◽  
Equation Model ◽  
Transfer Mechanism ◽  
Energy Transfer Mechanism ◽  
Rate Equation Model ◽  
Broadband Emission

A novel multi-color-emissive phosphor (Ca1.624Sr0.376Si5O3N6:Eu2+) and a rate equation model to elucidate the mechanism of energy-transfer leading to broadband emission.

Application of a diffusion–desorption rate equation model in astrochemistry

2014 ◽  
Vol 168 ◽  
pp. 517-532 ◽  
Author(s):  
Jiao He ◽  
Gianfranco Vidali
Keyword(s):  
Rate Equation ◽  
Equation Model ◽  
Experimental Investigations ◽  
Desorption Rate ◽  
Desorption Energy ◽  
Energy Distributions ◽  
Rate Equation Model ◽  
Adsorption Sites ◽  
Adsorption Desorption ◽  
And Diffusion

Desorption and diffusion are two of the most important processes on interstellar grain surfaces; knowledge of them is critical for the understanding of chemical reaction networks in the interstellar medium (ISM). However, a lack of information on desorption and diffusion is preventing further progress in astrochemistry. To obtain desorption energy distributions of molecules from the surfaces of ISM-related materials, one usually carries out adsorption–desorption temperature programmed desorption (TPD) experiments, and uses rate equation models to extract desorption energy distributions. However, the often-used rate equation models fail to adequately take into account diffusion processes and thus are only valid in situations where adsorption is strongly localized. As adsorption–desorption experiments show that adsorbate molecules tend to occupy deep adsorption sites before occupying shallow ones, a diffusion process must be involved. Thus, it is necessary to include a diffusion term in the model that takes into account the morphology of the surface as obtained from analyses of TPD experiments. We take the experimental data of CO desorption from the MgO(100) surface and of D2 desorption from amorphous solid water ice as examples to show how a diffusion–desorption rate equation model explains the redistribution of adsorbate molecules among different adsorption sites. We extract distributions of desorption energies and diffusion energy barriers from TPD profiles. These examples are contrasted with a system where adsorption is strongly localized – HD from an amorphous silicate surface. Suggestions for experimental investigations are provided.

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