A comprehensive model of PMOS NBTI degradation

TLDR: A comprehensive model for NBTI phenomena within the framework of the standard reaction–diffusion model is constructed and it is demonstrated how to solve the reaction-diffusion equations in a way that emphasizes the physical aspects of the degradation process and allows easy generalization of the existing work.

About: This article is published in Microelectronics Reliability.The article was published on 2005-01-01 and is currently open access. It has received 710 citations till now. The article focuses on the topics: Negative-bias temperature instability.

Figures

Fig. 5. Time evolution of (normalized) drain current shift for PMOS inversion and NMOS accumulation NBTI stress. Degradation at low VG for all time and high VG at shorter time is due to interface-trap generation, while long-time enhanced degradation at high VG is due to bulk-trap generation [15,16]. Under identical oxide field ðVGjinv ¼ VGjacc 1 V to account for difference in flatband voltage) PMOS inversion and NMOS accumulation (short time) stress show similar degradation, which characterizes the role of holes for NBTI.

Fig. 6. Voltage- and field-acceleration factors (cV and cE, respectively) plotted as a function of oxide thickness. The thickness independence of the field acceleration factor suggests lifetime of the form s expðcEEOXÞ. Since NIT sn, therefore NIT expðEOX=E0Þ with E0 ¼ 1=ncE is the form that describes the NBTI data well.

Fig. 7. Experimental and theoretical time evolution of threshold voltage shift data for a wide range of stress VG. The calculated bulk trap contributions are shown by dashed lines [15]. Theory matches well with experiment. Bulk trap generation at large oxide fields (high VG) affects overall threshold voltage shift and must be taken into account for properly estimating the forward reaction rate of the R–D model.

Fig. 1. (a) Schematic description of the reaction–diffusion model u Broken Si–H bonds at the Si–SiO2 interface create Si þ (interface trap bond dissociation (reaction), while the later rate depends on H remo diffuser, H removal is triggered by H2 diffusion (see Section 3). (b) Hy the hydrogen profile equals generated interface traps (see Section 2). limited (1,2) and diffusion-limited (3,4) regimes. Once the diffusion fro poly ensures that the concentration of H2 at the poly-oxide interface w in the hydrogen profile resulting in faster H removal from the Si/oxide

Fig. 8. (a) Universal scaling scheme for generated interface traps versus time data. Density axis reflects higher Si–H bond dissociation (reaction) while time axis denotes faster hydrogen diffusion. Assuming neutral diffusion species, the reaction and diffusion components can be independently scaled by voltage dependent (time independent) and time dependent (voltage independent) functions respectively. (b) Universality of scaled generated interface traps versus time data. Data taken under a wide bias and temperature range validates the scaling hypothesis.

Fig. 9. Temperature activation of 1=tBREAK and DH. The DH is calculated from the universal scaling of temperature dependent (fixed oxide field) generated interface trap data. Obtained activation energy supports neutral H2 diffusion [32].

Frequently asked questions

Q1. What contributions have the authors mentioned in the paper "A comprehensive model of pmos nbti degradation" ?

In this paper, the authors construct a comprehensive model for NBTI phenomena within the framework of the standard reaction–diffusion model. The authors demonstrate how to solve the reaction–diffusion equations in a way that emphasizes the physical aspects of the degradation process and allows easy generalization of the existing work. The authors also augment this basic reaction–diffusion model by including the temperature and field-dependence of the NBTI phenomena so that reliability projections can be made under arbitrary circuit operating conditions. 

Q2. What are the future works mentioned in the paper "A comprehensive model of pmos nbti degradation" ?

One of the key goal of their future work would be to clarify the role of such processing changes on NBTI performance.