“Background Fluctuation due to random discrete dopant (RDD


“Background Fluctuation due to random discrete dopant (RDD) distribution is becoming a major concern for continuously scaled down metal-oxide semiconductor field-effect transistors (MOSFETs) [1–4]. For ultra-small MOSFETs, not only random location MDV3100 manufacturer of individual dopant atoms but also fluctuation of the number of active impurities is expected to have significant impacts on

the device performance. Effects of the RDD distribution are usually analyzed with a randomly generated RDD distribution. The actual RDD distribution, however, should be correlated with the process condition and can be different from a mathematically generated one. In the present study, we investigate the effects of random discrete distribution of implanted and annealed arsenic (As) atoms in source and drain (S/D) extensions on the characteristics of n-type gate-all-around (GAA) silicon nanowire (Si NW) transistors. We investigate a GAA Si NW transistor since it is considered as a promising structure for ultimately scaled

CMOS because of its excellent gate control [2, 5–7]. Kinetic Monte Carlo (KMC) simulation is used for generating realistic random distribution of active As atoms in Si NWs. The current–voltage characteristics are then calculated using the non-equilibrium Green’s function (NEGF) method. Our results demonstrate that the on-current fluctuation mainly originated from the randomness of the dopant location and hence is inherent in ultra-small NW transistors. Methods Random discrete As distribution in a Si NW is PP2 clinical trial calculated using Sentaurus KMC simulator (Synopsys, Inc., Mountain View, CA, USA) [8–10]. Figure 1 shows an example of the calculated discrete As distribution in a Si NW (3 nm wide, 3 nm high, and 10 nm long) with 1-nm-thick oxide. The Si NW is implanted with As (0.5 keV, 1 × 1015 cm−2) and annealed at 1,000°C with a hold time of 0 s. Statistical variations are investigated using 200 different random seeds. The active As distributions obtained through the KMC simulation are then introduced into the S/D extensions of n-type Si NW MOSFETs, whose device structure is given in Figure 2. In the present study, we consider

only an intrinsic channel, and impacts of IACS-010759 possible Vasopressin Receptor penetration of dopant atoms into the channel region are not examined. To mimic metal electrodes, the S/D regions are heavily doped with N d = 5 × 1020 cm−3 (continuously doping). We simulate 100 samples using 200 different random seeds (each sample needs two random seeds for S/D extensions). The drain current-gate voltage (I d V g) characteristics are calculated using the NEGF method with an effective mass approximation [11, 12]. The discrete impurities are treated with a cloud-in-cell charge assignment scheme [13]. Phonon scattering is not taken into account in the present calculation. Figure 1 Discrete As distribution in a Si NW. Cross-sectional view (left) and entire view (right). Red dots show active As atoms in Si.

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