In‐Device Ballistic‐Electron‐Emission Spectroscopy for Accurately In Situ Mapping Energy Level Alignment at Metal–Organic Semiconductors Interface
Energy level alignment at metal/organic semiconductors (OSCs) interface governs electronic processes in organic electronics devices, making its precise determination essential for understanding carrier transport behaviors and optimizing device performance. However, it is proven that accurately characterizing the energy barrier at metal/OSC interface under operational conditions remains challenging due to the technical limitations of traditional methods. Herein, through integrating highly-improved device constructions with an ingenious derivative-assisted data processing method, this study demonstrates an in-device ballistic-electron-emission spectroscopy using hot-electron transistors to accurately characterize the energy barrier at metal/OSC interface under in-operando conditions. This technique is found that a remarkable improvement in measurement accuracy, reaching up to ±0.03 eV, can be achieved-surpassing previous techniques (±0.1-0.2 eV). The high accuracy allows us to monitor subtle changes in energy barriers at metal/OSC interface caused by variations in the aggregation state of OSCs, a phenomenon that is theoretically possible but failed to be directly demonstrated through conventional methods. Moreover, this study makes demonstration that this technology is universally applicable to various metal/OSC interfaces consisting of electron-transporting, hole-transporting, and ambipolar OSCs. These findings manifest the great potential of this method to advance both theoretical exploration and technical applications in organic electronics.
Authors
- Ankang Guo (ORCID: https://orcid.org/0000-0003-4826-7225)
- Yang Qin (ORCID: https://orcid.org/0009-0009-4996-4250)
- Lidan Guo (ORCID: https://orcid.org/0000-0002-7771-9932)
- Xiangnan Sun (ORCID: https://orcid.org/0000-0002-5461-9699)
- Xueli Yang (ORCID: https://orcid.org/0000-0001-6172-8669)
- Shunhua Hu
- Xianrong Gu
- Jianqi Zhang (ORCID: https://orcid.org/0000-0002-3549-1482)
- Meng Wu (ORCID: https://orcid.org/0000-0001-6362-9971)
- Rui Zhang (ORCID: https://orcid.org/0000-0003-1516-9653)
- Cheng Zhang (ORCID: https://orcid.org/0000-0003-2233-7141)
- Ke Meng (ORCID: https://orcid.org/0000-0002-6150-9228)
- Tingting Yang (ORCID: https://orcid.org/0000-0001-6773-8438)
- Ruiheng Zheng
- Min Li (ORCID: https://orcid.org/0000-0001-8786-5629)
Institutions
- China University of Petroleum, Beijing (CN)
- Beijing University of Technology (CN)
- National Center for Nanoscience and Technology (CN)
- University of Chinese Academy of Sciences (CN)
Publication Details
- Journal
- Advanced Materials
- Published
- 2024-11-10
- DOI
- https://doi.org/10.1002/adma.202412758
- Citations
- 1
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.21
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Beijing Municipality
- Beijing Nova Program