A Stand-Alone, Physics-Based, Measurement-Driven Model and Simulation Tool for Random Telegraph Signals Originating From Experimentally Identified MOS Gate-Oxide Defects

• Published in: IEEE transactions on electron devices Vol. 63; no. 4; pp. 1428 - 1436
• Main Authors: Nour, Mohamed, Celik-Butler, Zeynep, Sonnet, Arif, Fan-Chi Hou, Shaoping Tang, Mathur, Guru
• Format: Journal Article
• Language: English
• Published: New York IEEE 01-04-2016; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Complex random telegraph signals (RTS); Electron traps; gate-oxide traps; Logic gates; Mathematical model; MOS devices; RTS; RTS simulation; Scattering; Silicon; Simulation; SiO₂ oxygen vacancies; RTS; gate-oxide traps; Complex random telegraph signals (RTS); SiO2 oxygen vacancies; RTS simulation
• ISSN: 0018-9383; 1557-9646
• DOI: 10.1109/TED.2016.2528218

Investigating random telegraph signals (RTS) observed in MOS devices is important for studying the gate-oxide defect characteristics and developing simulation and modeling tools in highly scaled devices. In this paper, we are presenting a comprehensive, variable-temperature, single-to-multitrap scalable RTS model and a simulation tool (RTSSIM) based on the first principles, and supported by experimental data. The physical and electrical characteristics of the actual oxide defects are considered, such as trapping barrier energy, capture cross section, trap-binding enthalpy, entropy change with emission, Coulombic scattering effect, and the trap location. Experimentally obtained time-domain switching data and RTS traces reconstructed by the developed simulation tool are compared for assessing the accuracy of the modeling. In this paper, we identified the trap species responsible for the RTS as an unrelaxed neutral oxygen deficiency center (V 0 ODC II) with measured and theoretically verified relaxation energy of 1.11, 1.25, and 0.60 eV. RTSSIM is a tool used to mimic or reproduce a given noise measurement on a particular device. The simulation tool shows over 92% accuracy in replicating the RTS and trap characteristics. The model also represents the first realistic simulation of multilevel RTS.