Characterization of Low-Frequency Excess Noise in CH3NH3PbI3-Based Solar Cells Grown by Solution and Hybrid Chemical Vapor Deposition Techniques
Source abstract
Abstract
In this study, detailed investigations of low-frequency noise (LFN) characteristics of hybrid chemical vapor deposition (HCVD)- and solution-grown CH 3 NH 3 PbI 3 (MAPI) solar cells are reported. It has been shown that LFN is a ubiquitous phenomenon observed in all semiconductor devices. It is the smallest signal that can be measured from the device; hence, systematic characterization of the LFN properties can be utilized as a highly sensitive nondestructive tool for the characterization of material defects in the device. It has been demonstrated that the noise power spectral densities of the devices are critically dependent on the parameters of the fabrication process, including the growth ambient of the perovskite layer and the incorporation of the mesoscopic structures in the devices. Our experimental results indicated that the LFN arises from a thermally activated trapping and detrapping process, resulting in the corresponding fluctuations in the conductance of the device. The results show that the presence of oxygen in the growth ambient of the HCVD process and the inclusion of an mp-TiO 2 layer in the device structure are two important factors contributing to the substantial reduction in the density of the localized states in the MAPI devices. Furthermore, the lifetimes of the MAPI perovskite-based solar cells are strongly dependent on the material defect concentration. The degradation process is substantially more rapid for the devices with higher initial defect density compared to the devices prepared under optimized conditions and structure that exhibit substantially lower initial trap density.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Perovskite Materials and Applications · Chalcogenide Semiconductor Thin Films · Semiconductor Quantum Structures and Devices
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR
Department of Physics, The University of Hong Kong, Pokfulam, Hong Kong Island, Hong Kong SAR
Department of Physics and Materials Science, City University of Hong Kong, Kowloon, Hong Kong SAR
School of Engineering, Nazarbayev University, 53 Kabanbay Batyr Avenue, Astana 010000, Kazakhstan
Funding
Research Grants Council, University Grants Committee · Hong Kong Polytechnic University
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