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您的检索式：作者名="Longquan Quan"
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| 1 | Efficient InGaN-based yellow-light-emitting diodes显示文摘Realization of efficient yellow-light-emitting diodes(LEDs) has always been a challenge in solid-state lighting.Great effort has been made, but only slight advancements have occurred in the past few decades. After comprehensive work on InGaN-based yellow LEDs on Si substrate, we successfully made a breakthrough and pushed the wall-plug efficiency of 565-nm-yellow LEDs to 24.3% at 20 A∕cm^2 and 33.7% at 3 A∕cm^2. The success of yellow LEDs can be credited to the improved material quality and reduced compressive strain of InGaN quantum wells by a prestrained layer and substrate, as well as enhanced hole injection by a 3 D pn junction with V-pits. | FENGYI JIANG JIANLI ZHANG LONGQUAN XU JIE DING GUANGXU WANG XIAOMING WU XIAOLAN WANG CHUNLAN MO ZHIJUE QUAN XING GUO CHANGDA ZHENG SHUAN PAN JUNLIN LIU | 2019 | Photonics Research2019，7，2： | 13 |
| 2 | Efficient emission of InGaN-based light-emitting diodes:toward orange and red显示文摘Indium gallium nitride(InGaN)-based light-emitting diodes(LEDs)are considered a promising candidate for red-green-blue(RGB)micro displays.Currently,the blue and green LEDs are efficient,while the red ones are inefficient for such applications.This paper reports our work of creating efficient InGaN-based orange and red LEDs on silicon(111)substrates at low current density.Based on the structure of InGaN yellow LEDs,by simply reducing the growth temperature of all the yellow quantum wells(QWs),we obtained 599 nm orange LEDs with peak wall-plug efficiency(WPE)of 18.1%at 2 A/cm^2.An optimized QW structure was proposed that changed two of the nine yellow QWs to orange ones.Compared with the sample containing nine orange QWs,the sample with two orange QWs and seven yellow QWs showed similar emission spectra but a much higher peak WPE up to 24.0%at 0.8 A/cm^2 with a wavelength of 608 nm.The improvement of peak WPE can be attributed to the improved QW quality and the reduced active recombination volume.Subsequently,a series of efficient InGaN-based orange and red LEDs was demonstrated.With further development,the InGaN-based red LEDs are believed to be attainable and can be used in micro LED displays. | Shengnan Zhang Jianli Zhang Jiangdong Gao Xiaolan Wang Changda Zheng Meng Zhang Xiaoming Wu Longquan Xu Jie Ding Zhijue Quan Fengyi Jiang | 2020 | Photonics Research2020，8，11： | 10 |
| 3 | Double knock-in pig models with elements of binary Tet-On and phiC31 integrase systems for controllable and switchable gene expression显示文摘Inducible expression systems are indispensable for precise regulation and in-depth analysis of biological process.Binary Tet-On system has been widely employed to regulate transgenic expression by doxycycline.Previous pig models with tetracycline regulatory elements were generated through random integration.This process often resulted in uncertain expression and unpredictable phenotypes,thus hindering their applications.Here,by precise knock-in of binary Tet-On 3G elements into Rosa26 and Hipp11 locus,respectively,a double knock-in reporter pig model was generated.We characterized excellent properties of this system for controllable transgenic expression both in vitro and in vivo.Two att P sites were arranged to flank the td Tomato to switch reporter gene.Single or multiple gene replacement was efficiently and faithfully achieved in fetal fibroblasts and nuclear transfer embryos.To display the flexible application of this system,we generated a pig strain with Dox-inducing h KRASexpression through phiC31 integrase-mediated cassette exchange.After eight months of Dox administration,squamous cell carcinoma developed in the nose,mouth,and scrotum,which indicated this pig strain could serve as an ideal large animal model to study tumorigenesis.Overall,the established pig models with controllable and switchable transgene expression system will provide a facilitating platform for transgenic and biomedical research. | Qin Jin Xiaoyu Yang Shixue Gou Xiaoyi Liu Zhenpeng Zhuang Yanhui Liang Hui Shi Jiayuan Huang Han Wu Yu Zhao Zhen Ouyang Quanjun Zhang Zhaoming Liu Fangbing Chen Weikai Ge Jingke Xie Nan Li Chengdan Lai Xiaozhu Zhao Jiaowei Wang Meng Lian Lei Li Longquan Quan Yinghua Ye Liangxue Lai Kepin Wang | 2022 | Science China(Life Sciences)2022，65，11： | 1 |
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