| 1. |
- Ke, You, et al.
(författare)
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Defect Passivation for Red Perovskite Light-Emitting Diodes with Improved Brightness and Stability
- 2019
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Ingår i: The Journal of Physical Chemistry Letters. - : AMER CHEMICAL SOC. - 1948-7185. ; 10:3, s. 380-385
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Tidskriftsartikel (refereegranskat)abstract
- Efficient and stable red perovskite light-emitting diodes (PeLEDs) are important for realizing full-color display and lighting. Red PeLEDs can be achieved either by mixed-halide or low-dimensional perovskites. However, the device performance, especially the brightness, is still low owing to phase separation or poor charge transport issues. Here, we demonstrate red PeLEDs based on three-dimensional (3D) mixed-halide perovskites where the defects are passivated by using 5-aminovaleric acid. The red PeLEDs with an emission peak at 690 nm exhibit an external quantum efficiency of 8.7% and a luminance of 1408 cd m(-2). A maximum luminance of 8547 cd m(-2) can be further achieved as tuning the emission peak to 662 nm, representing the highest brightness of red PeLEDs. Moreover, those LEDs exhibit a half-life of up to 8 h under a high constant current density of 100 mA cm(-2), which is over 10 times improvement compared to literature results.
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| 2. |
- Lin, Jianpu, et al.
(författare)
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Image segmentation by improved minimum spanning tree with fractional differential and Canny detector
- 2019
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Ingår i: Journal of Algorithms and Computational Technology. - : SAGE PUBLICATIONS LTD. - 1748-3018 .- 1748-3026. ; 13
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Tidskriftsartikel (refereegranskat)abstract
- In this study, we propose an algorithm that uses an improved Minimum Spanning Tree algorithm and a modified Canny edge detector to segment images that contain a considerable amount of noises. First, we use our modified Canny operator to pre-process an image, and record the obtained object boundary information; then, we apply the improved Minimum Spanning Tree algorithm to associate the above information with boundary points in order to separate edges into two classes in the image, namely the inner and boundary regions. In particular, Minimum Spanning Tree algorithm is improved by using Fractional differential and combining the functions of the intra-regional and inter-regional differences with a function for edge weights. Based on the experimental results, compared with the other four exiting algorithms, the new algorithm has the higher accuracy and the better effect for noised image segmentation.
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| 3. |
- Zhang, Liang, et al.
(författare)
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Deep Learning for Additive Screening in Perovskite Light-Emitting Diodes
- 2022
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Ingår i: Angewandte Chemie International Edition. - : WILEY-V C H VERLAG GMBH. - 1433-7851 .- 1521-3773. ; 61:37
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Tidskriftsartikel (refereegranskat)abstract
- Additive engineering with organic molecules is of critical importance for achieving high-performance perovskite optoelectronic devices. However, experimentally finding suitable additives is costly and time consuming, while conventional machine learning (ML) is difficult to predict accurately due to the limited experimental data available in this relatively new field. Here, we demonstrate a deep learning method that can predict the effectiveness of additives in perovskite light-emitting diodes (PeLEDs) with a high accuracy up to 96 % by using a small dataset of 132 molecules. This model can maximize the information of the molecules and significantly mitigate the duplicated problem that usually happened with previous models in ML for molecular screening. Very high efficiency PeLEDs with a peak external quantum efficiency up to 22.7 % can be achieved by using the predicated additive. Our work opens a new avenue for further boosting the performance of perovskite optoelectronic devices.
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