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The aging phenomenon is commonly observed in quantum-dot light emitting diodes (QLEDs), involving complex chemical or physical processes. Resolving the underlying mechanism of these aging issues is crucial to deliver reliable electroluminescent devices in future display applications. Here, we report a reversible positive aging phenomenon that the device brightness and efficiency significantly improve after device operation, but recover to initial states after long-time storage or mild heat treatment, which can be termed as warming-up effects. Steady and transient equivalent circuit analysis suggest that the radiative recombination current dramatically increases but electron leakage from the quantum dots (QDs) to hole transport layer becomes more accessible during the warming-up process. Further analysis discloses that the notable enhancement of device efficiency can be ascribed to the filling of shell traps in gradient alloyed QDs. This work reveals a distinct positive aging phenomenon featured with reversibility, and further guidelines would be provided to achieve stable QLED devices in real display applications. [ABSTRACT FROM AUTHOR]

Rapid advancements in electric vehicle (EV) technology have highlighted the importance of lithium-ion (Li) batteries. These batteries are essential for safety and reliability. Battery data show non-stationarity and complex dynamics, presenting challenges for current monitoring and prediction methods. These methods often fail to manage the variability seen in real-world environments. To address these challenges, we propose a Transformer model with a wavelet transform dynamic attention mechanism (WADT). The dynamic attention mechanism uses wavelet transform. It focuses adaptively on the most informative parts of the battery data to enhance the anomaly detection accuracy. We also developed a deep learning model with an improved Transformer architecture. This architecture is tailored for the complex dynamics of battery data time series. The model accounts for temporal dependencies and adapts to non-stationary behavior. Experiments on public battery datasets show our approach's effectiveness. Our model significantly outperforms existing technologies with an accuracy of 0.89 and an AUC score of 0.88. These results validate our method's innovation and effectiveness. [ABSTRACT FROM AUTHOR]

In this work, we report the quantitative determination of charge accumulation and recombination in an operated QLED using time-resolved electroluminescence (TREL) spectroscopy. As a supplement technique, time-resolved current (TRC) measurement was introduced and simulated using equivalent circuit model with a series resistance, a parallel resistance, and a capacitance. By modeling the key processes in a typical TREL spectra, the stages of delay, rising, and decay can be correlated to the charge accumulations, charge injection and recombination, and charge release and recombination, respectively. In particular, the rising stage can be described using a modified Langevin recombination model. The electroluminescence recombination rate can be derived by fitting the rising stage curves in the TREL spectra, providing an intrinsic parameter of the emissive materials. In all, this work provides a methodology to quantitatively determine the charge accumulation and recombination of an operational QLED device.