Deep ultraviolet LEDs have broad applications in areas such as disinfection, sterilization, printing, and communications. The introduction of the international Minamata Convention has made the comprehensive application of deep ultraviolet LEDs increasingly urgent. However, the commercial deep ultraviolet LEDs' external quantum efficiency of less than 10% severely restricts their practical use. 
          AlN material quality is one of the key factors in deep-ultraviolet LEDs. AlN thin films are primarily grown by metal-organic chemical vapor deposition (MOCVD) on heteroepitaxial substrates such as c-sapphire, 6H-SiC, and Si(111). Due to significant lattice and thermal mismatches between AlN and the substrate, substantial stress and high dislocation density exist within the epitaxial layer, severely degrading device performance. 
          Meanwhile, the AlN precursor has a high migration barrier and poor wettability on such substrates, tending to grow in three-dimensional island-like structures, requiring a certain thickness before coalescence can occur, thereby increasing the time cost. 
          Recently, the Lighting Research Center of the Institute of Semiconductors, Chinese Academy of Sciences, in collaboration with the Nanoscale Chemistry Research Center of Peking University and the Liu Zhongfan team at the Beijing Graphene Research Institute, developed a novel graphene/sapphire epitaxial substrate and proposed a new strategy involving plasma pre-treatment to modify graphene, thereby promoting AlN film growth for deep-ultraviolet LEDs. 
          DFT calculations revealed that pyrrolic nitrogen introduced into graphene by plasma pre-treatment effectively promotes the nucleation and growth of AlN thin films. High-quality AlN films with low stress and low dislocation density can be obtained in a relatively short time, enabling deep-ultraviolet LED devices to exhibit excellent performance. 
          The study, titled "Improved Epitaxy of AlN Film for Deep-Ultraviolet Light-Emitting Diodes Enabled by Graphene," was published in Advanced Materials (Adv. Mater., DOI: 10.1002/adma.201807345). Researchers Jinmin Li and Tongbo Wei from the Institute of Semiconductors, along with Zhongfan Liu and Peng Gao from Peking University, served as co-corresponding authors, while Zhaolong Chen and Zhiqiang Liu were co-first authors. 
          Meanwhile, Wei Tongbo collaborated with Liu Zhongfan's team to propose a growth model for epitaxial AlN on graphene/NPSS nano-patterned substrates. Theoretical calculations and experimental results confirmed the enhanced migration of metal atoms on graphene surfaces. Graphene reduced the coalescence time of AlN on NPSS by two-thirds and significantly improved the power output of deep-ultraviolet LEDs, making deep-ultraviolet light sources a promising breakthrough for graphene industrialization. 
          The related work, published in Appl. Phys. Lett. 114, 091107 (2019), was selected as a Featured Article and specifically highlighted by AIP Scilight under the title "New AlN film growth conditions enhance emission of deep ultraviolet LEDs." It was also extensively covered in the March 2019 issue of Compound Semiconductor magazine and in Semiconductor Today. 
          Moreover, addressing the international technical challenge of p-type doping in deep-ultraviolet light-emitting devices, Liu Zhiqiang proposed a novel defect resonance state mechanism for p-type doping. This method, based on band structure engineering, achieves a high acceptor ionization rate while maintaining high hole mobility, resulting in a p-type gallium nitride conductivity of 0.16 Ω·cm, laying the foundation for future applications of graphene as transparent electrodes in deep-ultraviolet devices. 
          The related work was published in Semicond. Sci. Technol. 33, 114004 (2018), and received the Young Scientist Best Paper Award from the journal in 2018. The achievement has also been positively evaluated by Amano, a Nobel Prize laureate in Physics in 2014. 
The above series of research projects were supported by the National Key R&D Program, the National Natural Science Foundation of China, and the Beijing Natural Science Foundation.