卤化物
光致发光
发光
材料科学
铜
光激发
光电子学
化学物理
化学
无机化学
激发态
物理
原子物理学
冶金
作者
Linyuan Lian,Tongjin Zhang,Hongyan Ding,P. Zhang,Xiuwen Zhang,Yong-Biao Zhao,Jianbo Gao,Daoli Zhang,Yong Sheng Zhao,Jianbing Zhang
出处
期刊:ACS materials letters
[American Chemical Society]
日期:2022-07-07
卷期号:4 (8): 1446-1452
被引量:19
标识
DOI:10.1021/acsmaterialslett.2c00233
摘要
Zero-dimensional (0D) copper-based metal halides have exhibited great potential as luminescent materials with structural tunability and impressive emission properties. Luminescence from highly ordered self-assembly of copper halides is typically characterized by high photoluminescence quantum efficiencies (PLQEs) and large Stokes shifts, which are the most attractive features for active optical waveguides. Here, we report a novel highly luminescent organic copper halide, (PTMA)3Cu3I6 (PTMA: phenyltrimethylammonium), in which individual face- and edge-sharing [Cu3I6]3– clusters are surrounded by PTMA+ organic molecules, forming a highly ordered 0D crystal structure at the molecular level. Upon photoexcitation, (PTMA)3Cu3I6 single crystals exhibit a broadband yellow emission with a high PLQE of up to 80.3%. Theoretical calculations revealed that the photogenerated electron–hole pairs in (PTMA)3Cu3I6 are spatially separated from each other, i.e., electrons are preferred to be localized in PTMA+ organic molecules, while holes are highly localized in the inorganic [Cu3I6]3– clusters; thus, the emission arises from the radiative recombination of ligand-to-metal charge transfer (LMCT). In addition, colloidal nanocrystals of (PTMA)3Cu3I6 were successfully prepared, which show similar luminescence properties with their single crystals. The high PLQE, negligible self-absorption as well as the highly ordered self-assembly of metal halide clusters make (PTMA)3Cu3I6 microplates promising materials for low-loss optical waveguides, exhibiting an optical loss coefficient of 0.0157 dB μm–1 and highly linear polarized luminescence with a polarization anisotropy of 1.78.
科研通智能强力驱动
Strongly Powered by AbleSci AI