The evolution of the field effect transistor technology has led to the reduction of the device dimensions to a few tenths of nanometers or even smaller. As the devices' dimensions are reduced, the occurrence of short-channel effects becomes unavoidable and degrades, to some extent, the electrical characteristics of the devices even when multiple gate or nanowire technologies are applied. This effect contributes to the variability of the devices, and, as a consequence, to its reliability.In ultimate devices such as nanowire FETs, reliability is inherently important since small variations in the electrical parameters, e.g. the drain current or the threshold voltage, can significantly affect the device performance in a circuit application. Several reliability issues such as Self-Heating Effect (SHE), Negative-Bias Temperature Instabilities (NBTI), Low-Frequency Noise (LFN), Random Telegraph Noise (RTN), and Time-Dependent Dielectric Breakdown (TDDB) are geometry-dependent and become more important for short-channel devices. Most of these parameters are strongly affected by the occurrence of defects or traps in the interface between the active region and gate dielectric. Thus, the analysis of the quality of the semiconductor-dielectric interface has become increasingly important and can be performed through different techniques. Each of them demands different facilities and can deliver different information from DUTs.Low-Frequency Noise Several is one of the most complete analyses that can be performed in terms of reliability in ultimate devices, as it enables access to several parameters with respect to traps’ characteristics. By the fundamental shape of the drain current noise spectral density (SId) as a function of the frequency (f), it is possible to verify the presence of trap centers, which overwhelm the overall noise, such that SId presents a plateau followed by a 1/f2 decay with frequency increase, the so-called G-R noise, instead of the standard 1/f shape, as shown in Fig. 1 for junctionless transistors. Also, through some mathematical manipulation in the case of 1/f shape, one can extract the active trap density (Nit), its dependence on bias conditions (Fig. 2(A)), and the trap depth inside the dielectric layer (Fig. 2(B)). If structures with different geometrical characteristics, such as different dielectric thicknesses need to be compared, it is useful to calculate the Gate Noise Parameter (GNP), which enables a fair comparison between different samples. This parameter can also be used to indicate the nature of the energy distribution of traps. For samples with 1/f2 aspect, where G-R noise is dominant, the activation energy of the dominant trap center can also be extracted through the measurement of LFN as a function of the temperature by plotting the Arrhenius curve. However, the low-frequency noise characterization requires a specific setup, including an LFN analyzer, Low-Noise Amplifiers (LNAs), and, frequently, strategies to compensate for the instrumentation background noise. Besides that, there are some situations in which the determination of Nit through LFN is difficult, as in the case of NBTI occurrence, where traps are generated along time.Therefore, other techniques can be applied either to extract parameters not easily obtained through LFN or to avoid the use of a specific setup. In this case, it could also be possible to extract trap density through capacitance curves, where a C-V meter is needed, or even through current curves (ID) as a function of time (t) or gate bias (VG). The ID-t and ID-VG characteristics can be an alternative to estimate active trap density and its profile along the bandgap, for example. Through a charge-pumping-like method, a pulsed signal can be applied in the gate of a transistor. Thus, the drain current will follow the gate bias, and the rise and fall times of ID can be associated with the occupation and release of traps, allowing for an estimation of Nit. It is worth mentioning that the accuracy of this estimation is better for devices with larger total trap density (N0) as stated in Fig. 3. Finally, there are methods that permit the extraction of active trap density and its profile along bandgap directly through ID-VG curves. In long devices, the active trap density can be estimated through the behavior of subthreshold swing, which is directly correlated to Nit and, in some ultimate devices, such as junctionless nanowire transistors, the variation of the substrate bias permits extraction of Nit profile along the bandgap (Fig. 4). This is only possible because, in these devices, the surface potential is not pinned at twice the Fermi potential in the conduction regime as it occurs in inversion mode transistors. Figure 1
7Drain breakdown voltage: A comparison between junctionless and inversion mode p-channel MOSFETs
Drain breakdown voltage: A comparison between junctionless and inversion mode p-channel MOSFETs
Discussion on the Figures of Merit of Identified Traps Located in the Si Film: Surface Versus Volume Trap Densities
In this work a discussion on the estimated volume trap densities (NT) compared to surface traps densities (Neff) related to identified traps in the Si fin of Si/SiGe superlattice I/O n-channel FinFETs using low frequency noise spectroscopy is made. The investigated devices present a fin width of 10 nm, a fin height of 10 nm and four fins in parallel, leading to an equivalent channel width of 120 nm. The equivalent oxide thickness (EOT) is 5.6 nm. More details on the device fabrication and experimental setup may be found in [1,2]. The noise spectra and the estimated surface traps densities are provided in [3]. In this work, focus is only on the identified T4 trap, for which using the linear dependence that should exist between A0i and t0i related to the same trap, without any other assumption, a surface trap density of 2.8∙1012cm-2 is obtained [3]. It should be noted that from the 1/f flat-band noise level an interface trap density value of about 1.9∙1018 eV-1cm-3 is obtained at 300 K.However, as the traps in the Si film are related to a volume phenomenon, two methodologies to estimate the volume trap densities are employed: one using the relationship between the surface trap density and volume trap densitiy [4], where B is a coefficient estimated to be 1/3 [4,5]; and a second one from the temperature (T) evolution at fixed frequency of the Lorentzian plateau level associated to the same trap (from equation 34 in [4]). Using the first method leads to a volume trap density of T4 of about 1.7∙1019 cm-3.The second method consists to use the maximum of the measured Svg_Lor(f 0,T) dependence with temperature. Indeed, the Svg_Lor(f 0,T) of Lorentzians associated to the same trap are proportional with ti(T)/{1 + [2pf 0ti(T)]2}. For a given frequency f 0, if 2pf 0ti(T) ≫ 1, SVg_Lor(f 0,T) ∝ ti(T)]-1, and SVg_Lor(f 0,T) increases with increasing temperature because ti decreases. If 2pf 0ti(T) ≪ 1, then SVg_Lor(f 0,T) ∝ ti(T) and SVg_Lor(f 0,T) decreases with increasing temperature, as explained in detail in [4]. The evolution of the Svg_Lor(f 0,T)∙f 0 in a temperature range where T4 traps are active is illustrated in Figure 1 and presents a bell-shaped behavior, as expected. Using this method, volume trap densities of about 1.25∙1018 cm-3 for f 0 = 10 kHz and of about 1.1∙1018 cm-3 for f 0 = 14 kHz are obtained. It may be observed that the estimated volume trap densities of the T4 defect are about one decade lower than when using the first method. This overestimation by the first method is related to the fact that the theoretical B coefficient was determined for conventional planar devices with one gate [4,5]. Moreover, it may be noticed that the second method is dependent on the fixed f 0 selected.The paper will present a discussion with more details, considering all identified traps in [1] and considering additional new low frequency noise spectroscopy results.References :[1] Hellings, H. Mertens, A. Subirats, E. Simoen, T. Schram, L.-A. Ragnarsson et al., “Si/SiGe superlattice I/O finFETs in a vertically-stacked Gate-All-Around horizontal Nanowire Technology”, in Tech. Dig. Symp. on VLSI Technology, The IEEE New York, 2018, p.p. 85-86, DOI: 10.1109/VLSIT.2018.8510654.[2] Boudier, B. Cretu, E. Simoen, R. Carin, A. Veloso, N. Collaert, and A. Thean, “Low frequency noise assessment in n- and p-channel sub-10 nm triple-gate FinFETs: Part I: Theory and methodology,” Solid State Electron., vol. 128, pp. 102-108, 2017, DOI: 10.1016/j.sse.2016.10.012.[3] Boudier, B. Cretu, E. Simoen, G. Hellings, T. Schram, H. Mertens and D. Linten, “Low frequency noise analysis on Si/SiGe superlattice I/O n-channel FinFETs”, In Proceedings of EUROSOI-ULIS’2019.[4] Lukyanchikova, “Noise and Fluctuations Control in Electronic Device”, edited by A. Balandin, American Scientific, Riverside, CA, 2002, pp. 201-233.[5] Yau and C-T. Sah, “Theory and experiments of low-frequency generation-recombination noise in MOS transistors”, IEEE Trans. Electron Dev., 1969, vol.16, pp. 170-177.Figure 1 : SVg_Lor(f 0,T)·f 0 versus temperature for the T4 trap identified in [3]; on the secondary Oy axis the characteristic frequency f 0i of the Lorentzians is displayed in function of temperature. Figure 1
Read more19Time-Dependent Random Threshold Voltage Variation Due to Random Telegraph Noise
With the downscaling of device dimensions, the variability of metal–oxide–semiconductor field-effect transistor (MOSFET) electrical behavior is produced by factors other than variations in physical dimensions and doping profiles, which are there since device fabrication and remain static over time. Besides these time-zero variability factors, factors that lead to performance variability from one instant in time to the other start playing a significant role. Random telegraph noise (RTN) is among these relevant time-dependent variability sources, causing the threshold voltage ( ${V}_{T}$ ) of a transistor to change from one instant in time to the other. In this work, we extend the knowledge of the time-dependent random variability induced by RTN, by providing a statistical model for RTN-induced threshold voltage variance over time. The area scaling of threshold voltage variance is detailed and discussed, supporting designers in transistor sizing toward a more reliable design. Not only the threshold voltage variance expected in a single transistor is modeled but also its variability among transistors that by design should behave the same way. It is shown that with device size downscaling, the variability of RTN among devices increases faster than its mean value. The relationship between the time domain (RTN) and frequency domain (low-frequency noise) is studied. The modeling provides equations to extract trap amplitude contribution and trap densities from the moments of a measured low-frequency noise distribution or from the moments of a measured ${V}_{T}$ variation distribution, without having to characterize individual step heights. Besides analytical modeling, Monte Carlo simulations are run, illustrating the RTN-induced time-dependent random ${V}_{T}$ variation and model applicability.
Read more3Statistical analysis of relationship between negative-bias temperature instability and random telegraph noise in small p-channel metal–oxide–semiconductor field-effect transistors
It is demonstrated from a statistical perspective that the generation of random telegraph noise (RTN) changes before and after the application of negative-bias temperature instability (NBTI) stress. The NBTI stress generates a large number of permanent interface traps and, at the same time, a large number of RTN traps causing temporary RTN and one-time RTN. The interface trap and the RTN trap show different features in the recovery process. That is, a re-passivation of interface states is the minor cause of the recovery after the NBTI stress, and in contrast, rapid disappearance of the temporary RTN and the one-time RTN is the main cause of the recovery. The RTN traps are less likely to become permanent. This two-type trap, namely, the interface trap and RTN trap, model simply explains NBTI degradation and recovery in scaled p-channel metal–oxide–semiconductor field-effect transistors.
Read moreHow to measure intrinsic low frequency noise in thin film samples?
The measurement of low frequency noise can be considered as an important part in optimization of sensor noise-signal ratio. But sometimes, the intrinsic low frequency noise is affected by contact noise, which can be generated by geometrical defect of thin film. Thus, the measured noise level could not reveal material properties. We report different low frequency noise measurement methods in a general geometry sample of thin film. A detailed analysis of noise measurement has been described by relative equations. Finally, a discussion has been investigated in systematic measurements of low frequency noise at room temperature in La <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0.7</sub> Sr <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0.3</sub> MnO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> (LSMO) thin films and noise measurements are presented by noise spectral densities as function of frequency.
Read more3Correlation Between the Electric Field and the Negative Temperature Bias Instabilities Degradation in Junctionless Nanowire Transistors
In this work, we have correlated the degradation by Negative Bias Temperature Instability (NBTI) in MOS Junctionless Nanowire Transistors (JNTs) to the electric field inside the devices. We have measured samples with doping concentrations of 1×10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">19</sup> cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-3</sup> , biased at two different drain voltages, with several channel lengths (L) and widths (W). To extend the analysis, aiming at the understanding the physical behavior of the devices, we performed simulations of NBTI considering devices with similar characteristics. As a result, a higher degradation by the NBTI effect was obtained for the JNTs with lower doping concentration and shorter channel. The behavior of the NBTI has been correlated to the electric field of the devices and it is shown that the electric field becomes important mainly in accumulation regime.
Read more12RTN assessment of traps in polysilicon cylindrical vertical FETs for NVM application
RTN assessment of traps in polysilicon cylindrical vertical FETs for NVM application
10Defect spectroscopy using 1/ fγ noise of gate leakage current in ultrathin oxide MOSFETs
Defect spectroscopy using 1/ fγ noise of gate leakage current in ultrathin oxide MOSFETs
11Analytical Model for Low-Frequency Noise in Junctionless Nanowire Transistors
This article aims at proposing a compact analytical model for the low-frequency noise (LFN) of junctionless nanowire transistors (JNTs), operating at different bias conditions and temperatures. The model is validated through tridimensional numerical simulations, accounting for different trap configurations, as well as devices with different channel lengths, nanowire widths, and doping concentrations. Experimental results of short-channel junctionless transistors have also been used to demonstrate the model's applicability and accuracy.
Read more3Effect of Annealing Process on Trap Properties in High-k/Metal Gate n-Channel Metal–Oxide–Semiconductor Field-Effect Transistors through Low-Frequency Noise and Random Telegraph Noise Characterization
In this research, trap properties in n-channel metal–oxide–semiconductor field-effect transistors (MOSFETs) with different annealing sequences have been studied on the basis of low-frequency (1/f) noise and random telegraph noise (RTN) analyses. The 1/f noise results indicate that the source of the drain current fluctuation is electron trapping. The higher trap density in the devices annealed before the TaN layer causes serious noise and lower trap energy in RTN results. The substitution mechanism explains that the increment of defects is due to the additional nitrogen atoms in HfO2. On the contrary, fewer defects in the devices annealed after the TaN layer are due to the effect of passivation in the TiN layer. The defect in HfO2 is the source of trapping/detrapping; thus, fewer defects cause the decrement of the fluctuation and the increment of the drain current. We believe that this process has a potential to remove defects in advanced MOSFETs.
Read more5Robust, versatile, direct low-frequency noise characterization method for material/process quality control using cross-shaped 4-terminal devices
Robust, versatile, direct low-frequency noise characterization method for material/process quality control using cross-shaped 4-terminal devices
Read moreA Novel Method for Reliability Estimation of Optoelectronic Coupled Devices Based on Low-frequency Noise Measurements
In this paper the theoretical analysis of Low-frequency (LF) noise sources in Optoelectronic Coupled Devices (OCDs) is given and the relation between typical defects and LF noise (1/f noise, generationrecombination (g-r) nosie and burst noise) is described. According to LF noise sources of OCDs and device reliability estimation methods, a novel measurement system based on virtual instrument for OCDs is introduced and nV-level measurement precision can be achieved with the typical LF noise measurement system, which can be used to screen potential devices with excess noise and assess device relibility classifications. In this experiment, the top and bottom limitative thresholds were used to estimate the components parameters of the Power Spectrum Density (PSD) for estimating the reliability of OCDs by the average noise PSD for the 200 OCDs and the classification criterions of electronic components. The experimental results demonstrated that high reliability requirements can be satisfied.
Read more4Correlation of Negative Bias Temperature Instability and Breakdown in HfO2/TiN Gate Stacks
Both negative bias temperature instability (NBTI) and time dependent dielectric breakdown (TDDB) are two major reliability issues for long term performance of high-k gate stacks. In this work, these two degradation mechanisms were extensively analyzed to explore any possible correlation in terms of defects formation. A variety of dielectric stacks were considered to perform NBTI and TDDB. It was observed that NBTI induced defects, generated at the interface and in the interfacial layer were somewhat identical to the defects that dominate the breakdown process.
Read more10Empirical relationship between low-frequency drain current noise and grain-boundary potential barrier height in high-temperature-processed polycrystalline silicon thin-film transistors
The relationship between low-frequency drain current noise spectral density SI and grain-boundary potential barrier height Vb is investigated in high-temperature-processed polycrystalline silicon thin-film transistors. It is demonstrated that a general empirical relationship exists between SI and Vb indicating that the noise sources are located at the grain boundaries. The implications of the obtained relationship between SI and Vb from the practical viewpoint are discussed.
Read more13Interface state densities, low frequency noise and electron mobility in surface channel In 0.53Ga 0.47As n-MOSFETs with a ZrO 2 gate dielectric
Interface state densities, low frequency noise and electron mobility in surface channel In 0.53Ga 0.47As n-MOSFETs with a ZrO 2 gate dielectric
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