Suppr超能文献

溶液法制备的Ga掺杂ZnO纳米棒阵列作为有机太阳能电池中的电子受体。

Solution-processed Ga-doped ZnO nanorod arrays as electron acceptors in organic solar cells.

作者信息

Ginting Riski Titian, Yap Chi Chin, Yahaya Muhammad, Salleh Muhammad Mat

机构信息

School of Applied Physics, Faculty of Science and Technology, Universiti Kebangsaan Malaysia , 43600 UKM Bangi, Selangor, Malaysia.

出版信息

ACS Appl Mater Interfaces. 2014 Apr 9;6(7):5308-18. doi: 10.1021/am5007832. Epub 2014 Mar 25.

Abstract

This paper reports the utilization of ZnO nanorod arrays (NRAs) doped with various concentrations of Ga (0, 0.5, 1, 2, and 3 at %) as electron acceptors in organic solar cells. The donor, poly(3-hexylthiophene) (P3HT), was spin coated onto Ga-doped ZnO NRAs that were grown on fluorine-doped tin oxide (FTO) substrates, followed by the deposition of a Ag electrode by a magnetron sputtering method. Adjusting the Ga precursor concentration allowed for the control of the structural and optical properties of ZnO NRAs. The short circuit current density increased with increasing Ga concentration from 0 to 1 at %, mainly because of improved exciton dissociation and increased charge extraction. Meanwhile, the reduced charge recombination and lower hole leakage current led to an increase in the open circuit voltage with Ga concentrations up to 1 at %. The device with the optimum Ga concentration of 1 at % exhibited power conversion efficiency nearly three times higher compared to the device without Ga doping. This finding suggests that the incorporation of Ga can be a simple and effective approach to improve the photovoltaic performance of organic solar cells.

摘要

本文报道了将不同浓度(0、0.5、1、2和3原子百分比)的Ga掺杂的ZnO纳米棒阵列(NRA)用作有机太阳能电池中的电子受体。施主聚(3-己基噻吩)(P3HT)旋涂在生长于氟掺杂氧化锡(FTO)衬底上的Ga掺杂ZnO NRA上,随后通过磁控溅射法沉积Ag电极。调节Ga前驱体浓度可控制ZnO NRA的结构和光学性质。短路电流密度随着Ga浓度从0增加到1原子百分比而增大,这主要是由于激子解离得到改善且电荷提取增加。同时,电荷复合减少以及空穴漏电流降低导致开路电压随着Ga浓度增加到1原子百分比而升高。Ga浓度为1原子百分比的最佳器件的功率转换效率比未掺杂Ga的器件高出近三倍。这一发现表明,掺入Ga可以是提高有机太阳能电池光伏性能的一种简单有效的方法。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验