Reliability of semiconducting oxides: the last roadblock for memory applications

Thin film transistors based on amorphous oxide semiconductors (AOS) are promising candidates to enable further DRAM scaling [1] and more complex architectures inherent to the CMOS 2.0 revolution [2]. Although meeting the performance requirement for embedded and stand-alone DRAM applications, the reliability of such technology needs to be further understood and improved to meet the stringent requirements for product deployment. More specifically, it was shown that the Bias-Temperature Instability (BTI) is currently the mechanism limiting the device lifetime [3,4].

The aim of this PhD research is hence to study and improve the BTI of IGZO TFTs, targeting memory applications. To this end, this novel device must be comprehensively characterized and modelled, from which fundamental understanding and insights on the reliability limiting mechanisms can be extracted, allowing for further process optimization and eventually the deployment of these devices in real products. The PhD student will play a key role in understanding device degradation by combining electrical characterization and modelling. Electrical characterization will take place within imec labs, in which the student will be responsible for developing ad-hoc measurements routines and analyzing the subsequent measured data. The experimental activity will be followed by a fundamental modelling study. The student will model the defect generation and simulate the degraded devices using state-of-the-art device simulators and in-house developed software. All the degradation mechanisms will be integrated within a comprehensive physics-based simulation framework which will be calibrated over a wide range of stress conditions. This approach is expected to shed light on physical mechanisms behind degradation of IGZO transistors and provide unprecedented accuracy for reliability modelling. The student will therefore be able to develop a solid measurement/characterization expertise, but also a deep understanding of the device degradation at the atomistic level. The obtained insights will be fed back into the device fabrication flow, to demonstrate improved device reliability.

The student will closely work with device process engineers, with the ab-initio modelling team to model the degradation in semiconducting oxides at the microscopic scale and with the reliability team to develop and apply electrical characterization routines and subsequent data analysis and modelling.

The applicant should have in-depth knowledge in the field of semiconductor/semiconductor device/solid-states physics, good programming skills (Python, Matlab, Perl and/or C/C++), eagerness to obtain exciting scientific results and continuous learning. Within this multiscale cross-disciplinary project, the PhD student will be part of a large imec group working in collaboration with industrial partners; hence, a strong team player spirit is essential.

[1] A. Belmonte, S. Kundu, S. Subhechha, A. Chasin, N. Rassoul, et al. “Lowest IOFF < 3 × 10^{− 21}A/mm in capacitorless DRAM achieved by Reactive Ion Etch of IGZO-TFT”. In: 2023 IEEE Symposium on VLSI Technology and Circuits (VLSI Technology and Circuits). 2023, pp. 1–2. DOI: 10.23919/VLSITechnologyandCir57934.2023.10185398.

[2] J. Ryckaert, S. B. Samavedam. “The CMOS 2.0 revolution”. Nature Reviews Electrical Engineering, 1(3), 139-140, 2024. Doi: 10.1038/s44287-023-00016-3

[3] A. Chasin, J. Franco, K. Triantopoulos, H. Dekkers, N. Rassoul, et al. “Understanding and modelling the PBTI reliability of thin-film IGZO transistors”. In: 2021 IEEE International Electron Devices Meeting (IEDM). 2021, pp. 31.1.1–31.1.4. DOI: 10 . 1109 / IEDM19574. 2021 .9720666

[4] A. Chasin, J. Franco, S. Van Beek, H. Dekkers, A. Kruv, et al. “Unraveling BTI in IGZO Devices: Impact of Device Architecture, Channel Film Deposition Method and Stoichiometry/Phase, and Device Operating Conditions”. In: 2024 IEEE International Electron Devices Meeting (IEDM). 2024, pp. 1–4. DOI: 10 . 1109 / IEDM50854 . 2024 . 10873388.