RTS Noise in Si MOSFETs and GaN/AlGaN HFETs

Transcription

1 RTS Noise in Si MOSFETs and GaN/AlGaN HFETs JAN PAVELKA *, JOSEF ŠIKULA *, MUNECAZU TACANO ** * FEEC, Brno University of Technology Technicka 8, Brno 66, CZECH REPUBLIC ** AMRC, Meisei University 2-- Hodokubo, Hino, Tokyo 9-856, JAPAN pavelka@feec.vutbr.cz Abstract: Low frequency noise of Si n-mosfet and GaN/AlGaN HFET devices was measured in µhz to khz range, given by /f noise and RTS noise components. RTS noise voltage signal was analysed by means of zero cross method in ms to s windows and noise spectral density of crossing events was found almost constant in the -5 to 3 Hz frequency range in all samples. This indicates that there is no /f fluctuation of crossing rate given by trap characteristics, although charge carrier transport mechanisms give rise to quite different /f noise levels in Si and GaN devices. Statistical analysis of carrier capture and emission events duration revealed departure from exponential distribution in some samples, but any correlation among successive pulses wasn t obvious. Key-Words: GaN, GaN/AlGaN, HFET, MOSFET, /f noise, RTS noise Introduction In small area devices such as submicron MOSFETs, a single defect may be present, which in time domain gives two level switching signals known as random telegraph signal (RTS) noise. An example of RTS noise voltage time dependence is given in Fig., measured on.35μm Si MOSFET and 2μm GaN/AlGaN HFET. Such two levels in drain current are attributed to trapping/detrapping events caused by individual defect in the oxide near the Si-SiO 2 interface t t [s] Fig.. Time dependence of RTS noise voltage on load resistance, Si MOSFET, GaN HFET The charge carrier transitions between the oxide trap and channel are governed by the Shockley- Read-Hall statistics, which defines an exponential distribution of capture τ C and emission times [], [2]. When measured over sufficiently long time interval with 5-2 million pulses recorded, in some cases we observed deviation from this statistics (Fig.2b), given as superposition of two exponential terms, as well as anomalous capture rate dependence on drain current, and suggested an enhanced twostep capture process model [3]. In the frequency domain, power noise spectral density S U of RTS is given by Lorentz function S U = S () U + 2 ( πfτ ) 2 = + (2) τ τ C where τ is time constant defined by capture τ C and emission parameters. According to the McWhorter model [4], /f noise is given by charge carrier number fluctuation due to trapping processes. The /f noise spectrum is then given by superposition of multiple Lorentzians with suitable time constants. In Fig.3. frequency dependence of noise spectral density measured on three MOSFET devices is given, showing almost perfect Lorentz spectrum when RTS noise is dominant (N3), superposition of two Lorentzians in sample with two active traps (N) and device M2 with very small capture rate, resulting in RTS peak almost buried in ISSN: Issue 9, Volume 4, September 27

2 background /f noise. We analysed such different noise sources to find more about RTS kinetics. Further investigation is needed in case of multipletrap signal (see Fig.4.). n n τ e =2.7ms τ c =2.3ms N3a t τ e =.27ms τ c =.85ms N3c t Fig.2. Histogram of carrier capture and emission events duration in Si MOSFET, sample N3. T=234K, U G =.68V, U DS =.26V, I DS =.83μA T=257K, U G =.7V, U DS =.27V, I DS =2.6μA t Fig.4. Time dependence of noise voltage of multiple trap capture/emission events signal in Si MOSFET 2 Zero Cross Analysis In this paper we discuss new approach to RTS noise evaluation based on zero cross analysis. This method allows for finding any possible fluctuation in electron capture and emission characteristics. We divided time sequence of measured RTS voltage into series of intervals of constant width w in the range of ms to s and examined number of pulses corresponding to arbitrary level up or down CD crossing events in each window. This quantity has discrete Poisson distribution, which for higher number of pulses tends in limit to Gaussian distribution with mean value of pulses per window µ and dispersion σ, as is shown in Fig.5. p.6.4 w=s N3a -9 - N3 N S U = S U +(2πfτ) 2.2 w=s w=s 5 6 μ 7 8 S U [db] -3-5 M2 [s - ] Fig.5. Normalised distribution of crossing up events in windows width w = s, s and s. Measured on Si MOSFET N3, U G =.68V, T=234K /f -7.. f [Hz] Fig.3. Noise spectral density frequency dependence, measured on Si MOSFETs: sample N3, T=22K, U G =.7V, sample N, T=235K, U G =.695V and sample M2, T=3K, U G =.75V For Poisson processes, the lowest value of dispersion (standard deviation) is given as a root mean square of number of occurrences, in this case number of pulses in every single window. It is interesting to note, that next to this intrinsic Poisson (shot) noise, we found no other noise contribution expressing themselves by increased value of σ over this limit μ, as is shown in Fig.6a. It means that the ISSN: Issue 9, Volume 4, September 27

3 fluctuation of the crossing rate is about the same in all samples, although the other noise sources next to the RTS noise give quite different background noise intensity according to the temperature or type of Si or GaN device, as can be seen in Fig.. and Fig.3. The shape of distribution given by the ratio of σ to μ is obviously different in every sample for particular window width because of the various RTS time constant values in the range over 5 decades, as is summarised in Fig.6b. The capture and emission time constants change with temperature and gate voltage (see Fig.7.). From the Arrhenius plot in Fig.7a the activation energy of about.5ev can be estimated. τ τ C. ΔE E =.52eV /T [K - ] τ=τ exp(δe/kt) ΔE C =.37eV M2 N3a N3b N3c N GaN τ τ C σ σ / μ μ.5 μ.. M2 N3a N3b N3c N GaN ~w w [s] Fig.6. Dispersion of crossing rate Gaussian distribution σ as a function of mean value μ or window width w. Measured on Si MOSFET samples M2, N3 and N and GaN HFET. Parameters: M2: T=3K, U G =.75V, N3a: T=234K, U G =.68V, N3b: T=22K, U G =.7V, N3c: T=257K, U G =.7V, N: T=235K, U G =.695V, GaN: T=3K, U G =V [V] Fig.7. Dependence of capture τ C and emission time constants on a) temperature, sample N3, U G =.7V b) gate voltage, sample N5, T=259K One of the basic properties of Poisson processes is their memorylessness, which means statistical independence of number of events in disjoint (nonoverlapping) intervals. However, since we experimentally found non-standard distribution of pulse lengths (see Fig.2b), we checked this characteristic by correlation analysis of pulse length in doublets and triplets of successive pulses. We divided all recorded pulses according to their duration into about groups, covering logarithmically whole time span. Then we evaluated slope of every exponential sub-distribution and thus determined time constant corresponding to every group and plotted as a function of preceding pulse length. Results are given in Fig.8. and Fig.9. In these histograms, we tried to found, whether the probability of charge carrier capture by a trap is somehow influenced either by the duration of the previous capture process or by the amount of time, when trap was unoccupied. U G ISSN: Issue 9, Volume 4, September 27

4 It turned out, that in standard case of perfect exponential distribution of pulse length duration there is absolutely no dependence among successive events (Fig.8.). 2.5 However, in case of distorted characteristic with double emission curve (Fig.2b), there is a slight tendency of increasing probability of longer pulses (Fig.9.) (c) (c) (d) 2... Fig.8. Correlation of the successive pulse lengths, Si MOSFET sample N3, T=234K, U G =.68V. lower level duration after upper level, upper level after lower level, (c) upper level pulse length and next upper level, (d) lower level and following lower level.84 (d) Fig.9. Correlation of the successive pulse lengths, Si MOSFET sample N3, T=257K, U G =.68V. lower level duration after upper level, upper level after lower level, (c) upper level pulse length and next upper level, (d) lower level and following lower level ISSN: Issue 9, Volume 4, September 27

5 MOS M2 T=3K τ U =.8ms τ D =.86s MOS N3 T=234K τ U =2.7ms τ D =2.3ms SU [a.u.] -8 - MOS N3 T=257K τ U =.27ms τ D =.85ms -2-4 MOS N T=235K τ U =.2ms τ D =.2ms -6-8 GaN T=3K τ U =.2s τ D =.9s Fig.. Noise spectral density of the signal given as a series of number of crossing up events or time spent on the upper level within successive windows of width w. Measured on Si MOSFETs M2, N3 and N and GaN HFET. M2 T=3K, U G =.75V, w=s and s. N3 T=234K, U G =.68V, w=s and ms. N3 T=257K, U G =.7V, w=s and ms. N T=235K, U G =.695V, w=ms and ms. GaN T=3K U G =V, w=s. f [Hz] Finally we evaluated spectral characteristics of signal constituted by the sequences of crossing up events or total time spent on the upper level within the series of windows of the duration w. Resulting noise spectral density is almost constant in whole experimental range from khz down to μhz (Fig.) in all devices. 3 Conclusion Zero cross analysis was applied on the time trace of RTS voltage measured on Si n-mosfet and GaN/AlGaN HFET devices in order to obtain new statistical characteristics of RTS noise. Noise spectral density of signal made by counting number of pulses recorded in windows ranging from ms to s reveals no additional fluctuation of trap characteristics next to Poisson shot noise in frequency range -5 to 3 Hz, although charge carrier transport mechanisms give rise to quite different /f noise levels in various Si and GaN devices. Acknowledgment This research was supported by grants GACR No. 2/5/295, GACR No. 2/8/26 and project MSM MOSFET samples were kindly provided by Asahi Kasei Microsystems. One of the authors (J.P.) gratefully acknowledges the JSPS fellowship. References: [] M.J. Kirton and M.J. Uren, Noise in solid-state microstructures: A new perspective on individual defects, interface states and lowfrequency (/f) noise, Advances in Physics, Vol. 38, 989, pp [2] Z. Celik-Butler and N.V. Amarasinghe, Random Telegraph Signals in Deep Submicron Metal Oxide Semiconductor Field Effect Transistors, Noise and Fluctuations Control in Electronic Devices, ed. A. Balandin, American Scientific Publishers, 22, pp [3] J. Šikula, J. Pavelka, V. Sedláková, M. Tacano, S. Hashiguchi and M. Toita, RTS in submicron MOSFETs and quantum dots, Proc. of 2 nd SPIE Symposium Fluctuation and Noise, Maspalomas, Spain, 24, pp [4] A.L. McWhorter, /f Noise and germanium surface properties in Semiconductor Surface Physics, ed. R.H. Kingston, University of Pennsylvania Press, 957, pp ISSN: Issue 9, Volume 4, September 27