Background

For the last decades, the technology of silicon-based CMOS devices suffered significant fabrication challenges and sizeable characteristic variability [1–5]. Characteristics could be affected by various traps in high-κ/metal gate (HKMG) devices [6]. For emerging ultra-scaled transistors, the characteristic degradation induced by interface traps at the interface of SiO x /Si is severe for giga-scale circuit designs [7]. Furthermore, random interface traps (RITs) appearing at the interface of SiO x /Si depend on different fabrication processes of HKMG [8–13]. Except planar MOSFETs, fin-type field effect transistors (FinFETs) with HKMG play a key role in sub-22-nm technology nodes to boost electrical performance [14–16] and suppress various fluctuations. Recent studies reported the density of interface traps (Dit) resulting from the orientations of the vertical fin channel of FinFETs [6, 17]. The effects of RITs on sub-22-nm FinFETs have also been reported and compared between different device structures [18, 19]. Unfortunately, the impact of RITs on 16-nm-gate HKMG bulk FinFET devices has not been clearly discussed yet.

In this work, we study the DC characteristic fluctuation induced by RITs at the SiO x /Si interface of 16-nm TiN/HfSiON gate stack bulk FinFET devices by using experimentally calibrated three-dimensional (3D) device simulation. Under the same threshold voltage, more than 50% suppressions on the standard deviation of threshold voltage and subthreshold swing (SS) are achieved, benefiting from the nature of the vertical channel, compared with the planar MOSFET devices. By considering different levels of Dit, the effects of RIT position and number on the degradation of electrical characteristics are also examined. This paper is organized as follows: In the ‘Methods’ section, we illustrate the RIT simulation flow. In the ‘Results and discussion’ section, we report the results and discuss the characteristic fluctuation resulting from RITs on 16-nm-gate bulk FinFET devices. Finally, the conclusions are drawn.

Methods

RIT simulation method for FinFET devices

We study Si-based 16-nm-gate HKMG bulk FinFETs and planar MOSFET with amorphous-based titanium nitride/hafnium oxide/silicon oxide (TiN/HfO2/SiO x ) stacks of gate dielectric and an effective oxide thickness (EOT) of around 0.95 nm (EOT = To + Th × ϵSiO2/ϵHfO2 = 0.6 + 2 × 3.9/22 = 0.95 nm), where To is the thickness of SiO x , Th is the thickness of HfO2, and the dielectric constant of HfO2 is assumed to be 22. An aspect ratio of 4 (i.e., Hf/Wf = 32 nm/8 nm = 4), a 30-nm-long source/drain (S/D), and an 8-nm-long S/D extension for the explored FinFET are considered, as shown in Figure 1 (a). The doping applied to the channel (Nch), source/drain (NS/D), substrate (NB), and source/drain extension regions is 4 × 1018 cm−3, 5 × 1020 cm−3, 1015 cm−3, and 6 × 1018 cm−3 for the n-type 16-nm-gate HKMG bulk FinFET devices, respectively. First, we calibrate the nominal DC characteristic of the studied devices according to the International Technology Roadmap for Semiconductor (ITRS) roadmap for low-power applications, which was experimentally quantified in our recent study, and fix the threshold voltage at 300 mV. To estimate device characteristics, a set of 3D drift-diffusion equations coupled with the density gradient equation for quantum correction is performed [20–23]. The mobility model used in the 3D device simulation involves fin channel surface roughness, high-field saturation, and impurity scattering. The mobility model was quantified with our device measurements for the best accuracy, and the characteristic fluctuation was validated with the experimentally measured DC baseband data from 15/20-nm CMOS and FinFET devices in our earlier work [24].

Figure 1
figure 1

The RIT simulation technique for the bulk FinFET devices. (a) and (a’) are the device structures. (b)-(b”’) are the distribution of ITs. (c) and (c’) illustrate the IT planes. (d) shows the individual trap’s density versus the trap’s energy.

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To perform 3D device simulation with two-dimensional (2D) interface trap fluctuation (ITF) for each randomly generated device sample, we assume that the size of each RIT (SRIT) is equal to 2 nm × 2 nm at the interface of SiO x /Si. Notably, the value of SRIT is numerically set for the simulation of ITF [2, 25]. To generate RITs for the statistical device simulation of ITF, we first generate 3,389 acceptor-like traps marked as pink color in the three large 2D planes for the n-type FinFET device, as shown in Figure 1, and the corresponding concentration of RITs is around 1.5 × 1012 cm−2[26, 27]. The total number of generated acceptor-like traps follows the Poisson distribution, as shown in Figure 1 (b)-(b”). Then, we partition the large planes into many subplanes and map them to form a surface of RITs, as shown in Figure 1(c), where the number of traps in the subplanes varies from 0 to 6 at the top side and from 0 to 14 at the lateral sides, and the average number of interface traps is 3, 8, and 8, respectively. The concentration of each RIT (Nit) on a subplane is randomly assigned according to the RIT’s energy following the relationship, as shown in Figure 1 (d). Then, the level of Dit is the total product of (Nit × SRIT) divided by the total area of the SiO x /Si interface. Ultimately, we repeat this process until all subplanes are assigned. Notably, each subplane with RITs is numerically solved with the quantum mechanically corrected device model, where the RITs appear at the right-hand side of the Poisson equation.

Notably, the Dit varies with respect to the different process treatments on the TiN/HfSiON gate stacks [9, 11, 13], so we also consider the impact of three different Dit levels on device performance degradation. The ranges of high, typical, and low Dit vary from 5 × 1012 to 5 × 1013 eV−1 cm−2, 1 × 1012 to 1 × 1013 eV−1 cm−2, and 5 × 1011 to 5 × 1012 eV−1 cm−2, respectively. For the p-type devices, we have a similar simulation setting with modification of the acceptor-like traps to donor-like traps. For the planar MOSFET ITF simulation, it follows our recent work, as shown in Figure 1 (a’), (b”’), and (c’), and the details could be found in [7, 28].

Results and discussion

The nominal Vth for the fresh device (i.e., device with ultra-low Dit) is calibrated to 300 mV using a constant-current method. To meet the ITRS roadmap for low-power applications, the voltages applied for the 16-nm-gate HKMG bulk FinFET and planar MOSFET devices were 0.6 and 0.8 V, respectively. As shown in Figure 2, we firstly simulate the RIT-fluctuated ID-VG curves for the n-/p-type bulk FinFET (Figure 2a,b) and n-/p-type planar MOSFET (Figure 2c,d) devices with different levels of Dit, respectively. For all devices, the magnitude of ITF becomes smaller as the level of Dit decreases. The inset tables list the estimated fluctuation of Ion (σIon), Ioff (σIoff), and Vth (σVth) for devices with different levels of Dit. As shown in Figure 3, we compare the ITs-fluctuated Vth under different levels of Dit, where the normalized standard deviation (σ/μ) of Vth is calculated, and σ and μ are the standard deviation and average of the fluctuated cases, respectively. The Vth shifts and its normalized standard deviation becomes larger when the level of Dit is increased. Both the n- and p-type FinFET devices, as shown in Figure 3a,c, have comparable magnitudes of σ/μ which are smaller than that of the planar MOSFET devices (about 50% reduction), as shown in Figure 3b,d. Nevertheless, the ITs-fluctuated Vth is strongly governed by high Dit varying from 5 × 1012 to 5 × 1013 eV−1 cm−2. In Figure 4, we show the Ion versus Ioff for all devices with different levels of Dit. The results of the normalized standard deviation of Ion and Ioff imply that the advantage of the vertical channel in the suppression of ITF will be weakened when the level of Dit is increased; for example, the ellipsoid-shape distribution of Ion and Ioff is broadened as the Dit increases. For the cases of low Dit, as shown in Figure 4a,c, the FinFET σ/μ of Ion and Ioff is about three times smaller than that of the planar device, owing to their significant structural dominance. However, such strength is destroyed with the increasing level of Dit; as listed in the inset tables, the normalized standard deviations are considerable and comparable between the two devices for the cases of high Dit, in particular, the σ/μ of Ioff.

Figure 2
figure 2

I D - V G curves of the studied devices with different D it levels. The line indicates the ID-VG of a fresh sample. (a, b) n-/p-type bulk FinFET and (c, d) n-/p-type planar MOSFET devices.

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Figure 3
figure 3

Fluctuated V th for the studied devices with different D it levels. The line indicates the threshold voltage of a fresh sample. (a, c) n-/p-type bulk FinFET and (b, d) n-/p-type planar MOSFET devices.

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Figure 4
figure 4

I off versus I on for the studied devices with different D it levels. The black dot is the result of a free device. (a, c) n-/p-type bulk FinFET and (b, d) n-/p-type planar MOSFET devices.

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The degradation of SS becomes more critical when the level of Dit increases. Owing to large gate capacitance (Cg) coupling in FinFETs, the dependence relationship of ITs-fluctuated SS versus drain-induced barrier lowering (DIBL) is reduced, as shown in Figure 5a,c; however, the distribution of SS versus DIBL exhibits a negative dependency in the planar MOSFETs, as shown in Figure 5b,d. The significant dependence relationship of ITs-fluctuated SS versus DIBL indicates that the characteristic degradation was caused by an even stronger short-channel effect [29]. To maximize VDD scaling for logical application, the fluctuations of transconductance (gm) and subthreshold swing must be minimized. As shown in Figure 6, the ITs-fluctuated transconductances are calculated for the studied devices with different levels of Dit. The flatter normalized standard deviations (within 2%) of the maximum transconductance (gm,max) listed in the inset tables are found for the FinFET devices with high Dit, as shown in Figure 6a,c.

Figure 5
figure 5

SS versus DIBL for the studied devices with different D it levels. (a, c) n-/p-type bulk FinFET and (b, d) n-/p-type planar MOSFET devices.

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Figure 6
figure 6

ITs-fluctuated g m, max for the studied devices with different D it levels. (a, c) n-/p-type bulk FinFET and (b, d) n-/p-type planar MOSFET devices.

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To go deep into the physics of the results reported above, as shown in Figure 7, we now examine the advantage of the vertical structure and the effect of random distribution (i.e., the random position) and the random number of ITs on the surface potential profiles of the ITs-fluctuated devices. As shown in the inset of Figure 7a, along the channel direction (Z-direction) from the source (S) to the drain (D) at the interface of SiO x /Si on the top gate, the two profiles of conduction band are extracted and compared for the fresh FinFET device and the FinFET device with high Dit under off-state condition, where the barrier difference induced by a single interface trap is about 0.1365 eV. Similarly, as shown in Figure 7b, for the planar MOSFET device, the barrier difference is about 0.2732 eV. Comparison between Figure 7a and 7b indicates the significant structural effect; the planar MOSFET device severely suffers from the impact of RIT compared to the FinFET one. The coupling of gate electrodes from both the lateral sides to the top gate enhances the Cg, and thus, it effectively reduces the impact of RITs on the energy band. The findings of this comparison confirm the superiority of a 3D channel structure and the aforementioned results. The random position effect of RITs is further examined for the FinFET device. For similar Ion and different Ioff, the two illustration cases (case A and case B) shown in Figure 7c have the same number of ITs (15 ITs) but different Vth owing to the different positions of RITs. For similar Ioff and different Ion, the numbers of ITs for the two illustration cases (case A and case C) shown Figure 7c are 15 and 17. Therefore, according to the random number effect, they have different Vth because the effective Dit of case C is higher than that of case A. Thus, the device has similar Ioff and different Ion.

Figure 7
figure 7

Barrier height fluctuation induced by RITs for the studied devices with high D it. n-type HKMG (a) bulk FinFET and (b) planar MOSFET devices. The devices are under off-state condition, where VG = Vs = VB = 0 V and VD = 0.6 V for the FinFET and VG = Vs = VB = 0 V and VD = 0.8 V for the planar MOSFET. (c) The Ioff-Ion plot used to explain the position and number effects of RITs.

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Conclusions

In this work, we have investigated the impact of RITs on n-/p-type 16-nm-gate HKMG bulk FinFETs using an experimentally validated device simulation technique. We examined the ITs-fluctuated short-channel effect (SCE) parameters for the bulk FinFET and planar MOSFET devices. Benefiting from the improved gate controllability and stronger gate coupling capability, the estimated normalized standard deviation indicates that the 16-nm-gate HKMG bulk FinFET devices can effectively suppress the DC characteristic and SCE parameter fluctuations induced by RITs with respect to different levels of Dit. The insets of Figures 3, 4, 5, 6 listed the fluctuation magnitudes of Ioff and DIBL which are severely governed by RITs with high Dit level ranging from 5 × 1012 to 5 × 1013 eV−1 cm−2. Due to the strong screening effect for devices under high gate bias, the fluctuation magnitudes of SS and gm induced by different levels of RITs are minimized. To effectively control the magnitude of normalized fluctuation within 5% for the Vth, Ioff, Ion, SS, and DIBL, the Dit should be lower than 1 × 1012 eV−1 cm−2. We are currently designing a proper experiment to measure the characteristic fluctuation induced by RITs and study the random bulk traps’ influence together with RITs on device characteristic variability.