Ions-induced Epitaxial Growth of Perovskite Nanocomposites for Highly Efficient Light-Emitting Diodes with EQE Exceeding 30%

Cesium lead bromide (CsPbBr3) is a widely used emitter for perovskite light-emitting diodes (PeLEDs), benefiting from its large carrier mobility, high color purity and good thermal stability. However, the three-dimensional CsPbBr3 films encounter challenges due to their massive intrinsic defects and weak exciton binding effect, which limited their electroluminescence efficiency. To address this issue, the prevailing approach is to confine carriers by reducing dimensionality or size. Nonetheless, this method results in an increase in surface trap states due to the larger surface-to-volume ratio and presents difficulties in carrier injection and transport after reducing lattice splitting to smaller sizes. Here, we successfully achieved proper control over film crystallization by introducing sodium ions, which facilitate the epitaxial growth of zero-dimensional Cs4PbBr6 on the surface of CsPbBr3, forming large grain matrixes where CsPbBr3 is encapsulated by Cs4PbBr6. Notably, the ions-induced epitaxial growth enables the CsPbBr3 emitter with significantly reduced trap states, and generates coarsened nanocomposites of CsPbBr3&Cs4PbBr6 with grain size that surpass the average thickness of the thin perovskite film, resulting in a wavy surface conducive to light out-coupling. Additionally, another additive of formamidinium chloride was incorporated to assist the growth of nanocomposites with larger size and lower defects as well as better carrier injection and transportation. As a result, our demonstrated PeLEDs based on the coarsened nanocomposites exhibit low nonradiative recombination, enhanced light extraction and well-balanced carrier transportation, leading to high-performance devices. The champion device achieved an external quantum efficiency of 31.0% at the emission peak of 521 nm with a narrow full width at half-maximum (FWHM) of 18 nm

An Inverse Node Graph-Based Method for the Urban Scene Segmentation of 3D Point Clouds

Urban object segmentation and classification tasks are critical data processing steps in scene understanding, intelligent vehicles and 3D high-precision maps. Semantic segmentation of 3D point clouds is the foundational step in object recognition. To identify the intersecting objects and improve the accuracy of classification, this paper proposes a segment-based classification method for 3D point clouds. This method firstly divides points into multi-scale supervoxels and groups them by proposed inverse node graph (IN-Graph) construction, which does not need to define prior information about the node, it divides supervoxels by judging the connection state of edges between them. This method reaches minimum global energy by graph cutting, obtains the structural segments as completely as possible, and retains boundaries at the same time. Then, the random forest classifier is utilized for supervised classification. To deal with the mislabeling of scattered fragments, higher-order CRF with small-label cluster optimization is proposed to refine the classification results. Experiments were carried out on mobile laser scan (MLS) point dataset and terrestrial laser scan (TLS) points dataset, and the results show that overall accuracies of 97.57% and 96.39% were obtained in the two datasets. The boundaries of objects were retained well, and the method achieved a good result in the classification of cars and motorcycles. More experimental analyses have verified the advantages of the proposed method and proved the practicability and versatility of the method

An Innovative Virtual Simulation Teaching Platform on Digital Mapping with Unmanned Aerial Vehicle for Remote Sensing Education

This work mainly discusses an innovative teaching platform on Unmanned Aerial Vehicle digital mapping for Remote Sensing (RS) education at Wuhan University, underlining the fast development of RS technology. Firstly, we introduce and discuss the future development of the Virtual Simulation Experiment Teaching Platform for Unmanned Aerial Vehicle (VSETP-UAV). It includes specific topics such as the Systems and function Design, teaching and learning strategies, and experimental methods. This study shows that VSETP-UAV expands the usual content and training methods related to RS education, and creates a good synergy between teaching and research. The results also show that the VSETP-UAV platform is of high teaching quality producing excellent engineers, with high international standards and innovative skills in the RS field. In particular, it develops students’ practical skills with technical manipulations of dedicated hardware and software equipment (e.g., UAV) in order to assimilate quickly this particular topic. Therefore, students report that this platform is more accessible from an educational point-of-view than theoretical programs, with a quick way of learning basic concepts of RS. Finally, the proposed VSETP-UAV platform achieves a high social influence, expanding the practical content and training methods of UAV based experiments, and providing a platform for producing high-quality national talents with internationally recognized topics related to emerging engineering education