3.7 Time-Dependent Defect Spectroscopy (TDDS)

The TDDS framework has been introduced recently with the main purpose to characterize single oxide defects in MOSFETs [40]. In general, both, the setup for the cv extraction shown in Figure 3.13 and the setup for the cc extraction shown in Figure 3.15 can be used as experimental setups. However, in the following, the focus is on the cv setup since this method is in the focus of this thesis. The measurement procedure corresponds basically to a sequencing of the stress and recovery phase of the eMSM technique after the initial characterization of the device (Figure 3.14) including several postprocessing steps:

• 1. Characterization of the unstressed device by taking an initial -.

• 2. Subjecting the device to a stress bias for .

• 3. Monitoring for providing its recovery behavior over many decades in time.

• 4. Repetition of the second and third phase, for example times.

• 5. Mapping to as explained in Figure 3.12.

• 6. Postprocessing of the data by extractin step heights and step times.

As already discussed in the introduction, the capture and emission events of defects affect device characteristics like . As long as the energy level of the defect is located in a certain area in the band gap, it can be shifted above the Fermi level by applying a stress gate bias typically above nominal operating conditions and shifted below the Fermi level by applying a recovery gate bias typically around the threshold voltage. Depending on the detailed defect configuration the defect can capture and emit a charge carrier at stochastic times. Such charge exchange events between the oxide and the channel can be measured as stepwise shifts of . While the step heights cannot be resolved in large-area devices due to the small impact of one charge exchange event, they can be experimentally assessed in nano-scale devices containing only a handful of defects [17, 18].

Due to the fact that the capture and emission events are stochastic, TDDS requires a number, e.g., , of stress/recovery experiments to capture statistics for a reliable characterization. The top panel of Figure 2.7 shows typical recovery measurements containing the steps of five defects enumerated with 1, 2, 3, 4 and 12. These defects have each captured a charge carrier during the previous stress phase and emit this charge carrier during the recovery phase, which causes a step in the recovery trace. In a postprocessing step, and are extracted for each step and can be binned into a two-dimensional histogram shown in the bottom panel Figure 2.7 bottom. As a result, a cluster for each defect forms in the spectral map, which is an unambiguous fingerprint of the defect. By assignment of each cluster to a certain defect, the mean values for and can be calculated.

In contrast to , is measured indirectly. Two reasons can be mentioned in this regard. In BTI measurements no is applied and thus is nearly zero. Therefore, the charge exchange events cannot be measured in . In mixed NBTI/HC stress measurements the charge exchange events cannot be measured, especially for high . In addition, considering the number of charge carriers in the channel at stress conditions and the measurement range defined by the feedback resistor of the transimpedance amplifier the single steps cannot be resolved at stress. As a result, has to be extracted from the occupancy with respect to , which is shown in Figure 3.24.

In Figure 3.24 of a defect named D1 is extracted. This is done by exploiting the stress time dependence of the occupancy. From this, the occupancy can be calculated as the ratio of the number of emission events () to the number of recovery traces (). The occupancy / in respect to follows an exponential function according to Equation 2.18:

with

	occupancy, experimentally characterized as the ratio
	between and
	gate stress voltage
	drain stress voltage
	stress time
	corresponds to in Equaton 2.18
	capture time.

By fitting the measurement points with this exponential function, can finally be extracted. The spectral maps illustrate that with increasing the intensity of the cluster assigned to the defect named D1 increases as well.

One challenge of the TDDS, which has to be mentioned at this point is that defects with similar and cannot be distinguished in the spectral map because they cause clusters at similar positions. Often, this challenges the full characterization of a defect because the defect characteristics have to be recorded for a wide range of stress and recovery bias conditions. Each change of the stress bias results in a shift of , and/or . In devices with more than four experimentally feasible defect clusters in the spectral map it is quite likely that two defects cross their paths in the spectral map and thus cannot be distinguished. This limits the voltage range in which defects can be characterized fully. In most of the measurements, this leads to a pre-selection of defects.

However, the TDDS is one of the most reliable techniques in the context of single oxide defect characterization which has led to numerous conclusions as already discussed in Chapter 2. Although it has been developed for BTI measurements, it has been experienced that it is also reliable in mixed NBTI/HC measurements, presented in Chapter 5.