Emission Properties of Wide InGaN/GaN Quantum Wells-Evidence for "Dark Charge" from Time-Resolved Photo- and Electroluminescence
Abstract
InGaN/GaN quantum wells on polar substrates exhibit a pronounced quantum-confined Stark effect, which significantly limits their efficiency as light emitters. Surprisingly, this detrimental effect is significantly reduced when wider wells (above 10 nm) are used; their emission kinetics are the central focus of this work. A time range spanning nine orders of magnitude, from picoseconds to milliseconds, is explored through various experiments. This includes experiments on the optical visualization of slow decays of charge in the ground states (called "dark charge") in the millisecond range, experiments on radiative recombination of excited states in the nanosecond range, and experiments on the relaxation of hot carriers in the picosecond range. All data are explained within the framework of qualitative and semi-quantitative models. The highly diverse kinetics of ground and excited states are due to the fact that the ground states of electrons and holes have negligible overlap and screen the built-in field, are optically inactive, and recombine nonradiatively in milliseconds. Meanwhile, when the field is screened, the excited states recombine radiatively in the picosecond/nanosecond ranges. The pulses of photo- and electroluminescence depend strongly on the excitation period. The application of negative-voltage pulses allows us to deplete the well of charge and generate short pulses of light.
Read the paper
Related studies
- Chaos and quantum thermalization
- The Dalton quantum chemistry program system
- Quantum dots: synthesis, bioapplications, and toxicity
- Cord Blood Leptin and Adiponectin as Predictors of Adiposity in Children at 3 Years of Age: A Prospective Cohort Study
- A Guide to In Silico Drug Design
- Quantitative metabolomics by H-NMR and LC-MS/MS confirms altered metabolic pathways in diabetes
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.