Fig. 6.9 Complementary cumulative distribution function of RTN amplitude distribution in FinFET SONOS cells with a fin width=10nm. A Poisson-like shape is obtained.
Chapter 7 Conclusions
In short, this dissertation has involved major reliability issues in high-k (HfSiON)/metal gate(TiN) pMOSFET, among them, NBTI and RTN are studied.
Single charge phenomena are characterized statistically to get insight of threshold voltage shift distributions in small-area devices. The RTN in non-volatile flash memory cells and its structural dependence are also studied. Contributions of each subject in this work are summarized as follows.
First, we characterize NBTI trap creation in a large number of high-k dielectric pMOSFETs. The broad distribution of trap creation times is attributed to an activation energy distribution in the RD model. An activation energy distribution including a local electric field effect has been extracted from measured trap characteristic times.
We develop a statistical model to simulate an NBTI induced Vt distribution in small-area devices. Our model can reproduce the measurement results of an NBTI
Vt distribution and its stress time evolutions well.
Next, continued from the preceding paragraph, since Vt recovers partly after a NBTI stress, we use a similar statistical approach as in Chapter 2 to exploring NBTI recovery mechanisms and trapped charge characteristics. Thermally-assisted trapped charge tunnel emission has been confirmed to be a major mechanism in NBTI recovery, which is proposed in our earlier papers [3.4]. We extract a trapped charge activation energy distribution in the ThAT model for the first time. We find that the emission time distribution of trapped charges broadens as a sequence number increases. This feature is successfully explained by the ThAT model and verified by
measurement. A Monte Carlo based statistical model for a post-NBTI Vt distribution is developed for small area devices. Our model can predict a Vt distribution and its temporal evolution in relaxation very well. In chapter 2 and 3, NBTI induced Vt
distributions are successfully characterized and predicted.
Then, single trapped charge induced vt distributions in RTN and NBTI are characterized and simulated in pMOSFETs. Our simulation method takes into account a trap creation probability in NBTI stress. Our study shows that a NBTI stress created charge has a larger vt distribution tail than RTN due to current path percolation effect.
This large NBTI induced distribution tail poses to be a serious CMOS reliability concern and should be carefully considered in a precise NBTI lifetime model.
Furthermore, with respect to non-volatile flash memories, RTN induced vt in FG and SONOS cells and its structural dependence are investigated. In a FG flash, RTN amplitudes are mainly determined by random dopant induced percolation effect and identical in erase and program states. However, in a planar MLC SONOS, we find that RTN amplitudes have a wide spread after program. The program-state RTN distribution is affected by both random program charges and substrate dopants. In addition, the RTN amplitude varies from P/E cycle to P/E cycle due to program induced percolation effect. Therefore the program charge effect has to be considered in RTN modeling in MLC SONOS. According to our experiments and simulations, the program charge induced percolation effect can be significantly reduced in a surrounding gate structure, such as a FinFET SONOS.
Finally, we discussed that RTN amplitude fluctuations in a MOSFET with a nanowire-like channel can no longer be explained by a current-path modulation effect.
We perform a 1D channel Monte Carlo RTN simulation to investigate RTN behavior without the presence of such current-path modulation. Based on the simulation results
in a large number of devices, we conclude that RTN amplitudes in a 1D channel device are dependent on the number of dopants nearby an RTN trap. According to the findings, we develop an analytical RTN amplitude distribution model for MOSFETs having a one-dimension-like channel. Our model can fit the Monte Carlo RTN simulation results quite well for different doping concentrations and gate lengths. This model can also apply to SONOS flash memory cells since nitride program charges and substrate dopants have some similar features about channel current path percolation effect, as investigated in Chapter 5.
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