Christoph Zechner

Monte Carlo simulation and measurement of nanoscale n-MOSFETs

The output characteristics of state-of-the-art n-MOSFETs with effective channel lengths of 40 and 60 nm have been measured and compared with full-band Monte Carlo simulations. The device structures are obtained by process simulation based on comprehensive secondary ion mass spectroscopy and capacitance-voltage measurements. Good agreement between the measured output characteristics and the full-band Monte Carlo simulations is found without any fitting of parameters and the on-currents are reproduced within 4%. The analysis of the velocity profiles along the channel confirms that the on-current is determined by the drift velocity in the source side of the channel. Analytic-band Monte Carlo simulations are found to involve an overestimation of the drain current in the nonlinear regime which becomes larger for increasing drain voltage and decreasing gate length. The discrepancy originates from a higher nonlinear drift velocity and a higher overshoot peak in bulk silicon which is due to differences in the band structures above 100 meV. The comparison between analytic-band and full-band Monte Carlo simulation therefore shows that the source-side velocity in the on-state is influenced by nonlinear and quasiballistic transport.

Efficient TCAD Model for the Evolution of Interstitial Clusters, {311} Defects, and Dislocation Loops in Silicon

The simulation of deep-submicron silicon-device manufacturing processes relies on predictive models for extended defect clusters. For submicroscopic interstitial clusters and {311} defects, an efficient and highly accurate model for process simulation has been developed and calibrated recently [1]. This model combines equations for three small interstitial clusters and two moments for {311} defects. In this work, we extend this model to include dislocation loops and to reproduce a greatly increased range of experimental data, including thermal annealing of end-of-range defects after amorphizing implants.

Maximum Active Concentration of Ion-Implanted Phosphorus During Solid-Phase Epitaxial Recrystallization

In this paper, we showed that the maximum active P concentration of approximately 2 times10²⁰ cm^-3 exists during solid-phase epitaxial recrystallization (SPER). This maximum active concentration is close to the reported values for other active impurity concentrations during SPER. We introduced the concept of an isolated impurity that has no neighbor impurities with a certain lattice range. Assuming that impurities interact with three or four neighbor impurities, we can explain the activation phenomenon during SPER. According to our model, the isolated P concentration <i>N</i> _iso has a maximum value of approximately 2 times10²⁰ cm^-3 at a total impurity concentration of approximately 10²¹ cm^-3, and it decreases with a further increase in total impurity concentration. Deactivation occurs after the completion of SPER with increasing annealing time, and the active impurity concentration decreases with time but is always higher than the maximum diffusion concentration <i>N</i> _Diff _max. We also observed that <i>N</i> _Diff _max is independent of the annealing time despite nonthermal activation in the high-concentration region. We evaluated the dependence of <i>N</i> _Diff _max on annealing temperatures. We think that this <i>N</i> _Diff _max can be regarded as the electrical solid solubility <i>N</i> _Esol that the active impurity concentration reaches in thermal equilibrium. We observed the transient enhanced diffusion (TED) after the completion of SPER, and that, the deactivation process continues during and after TED, and the corresponding diffusion coefficient is still much higher than that in thermal equilibrium even after TED has finished, which suggests that the deactivation process releases point defects.

On a computationally efficient approach to boron-interstitial clustering

The physical concepts developed to describe the transient activation of boron during post-implantation annealing are based on the concurrent formation of complexes comprising boron atoms and self-interstitials. A complete implementation into TCAD software leads to a high number of equations to be solved which is often inadmissible for multi-dimensional simulations. In this work, a minimum number of such complexes is taken into considerations. We show that such a model is nevertheless able to reproduce a large variety of implant and annealing conditions.

Self-consistent single-particle simulation

Self-consistent single-particle Monte Carlo device simulations are presented. Self-consistency is achieved by an iterative coupling-scheme of single-particle frozen-field Monte Carlo simulations with solutions of the nonlinear Poisson equation. As an example a realistic 0.1 /spl mu/m n-MOSFET obtained from process simulation with maximum doping levels of about 2.5 /spl times/ 10/sup 20/ cm/sup -3/ is simulated. It is found that the resulting drain current is independent of the length of the time interval per iteration (provided that it is not too small) and independent of the density in the regions not visited by the particles taken either from a drift-diffusion or a hydrodynamic simulation. Therefore the self-consistent single-particle Monte Carlo simulation is an accurate and robust simulation tool for the quasi-ballistic regime in sub 0.1 /spl mu/m MOSFETs.

Physics-based diffusion simulations for preamorphized ultrashallow junctions

In recent years there have been major advances in our understanding of the energetics, Ostwald ripening and transformations between various types of extended self-interstitial defect in Si and Ge ion-implanted silicon. As a result we can now predict the detailed time- and temperature-dependent supersaturation of interstitials during thermal evolution of these defects. This opens the way to predictive simulation of transient enhanced diffusion and dose loss in preamorphized ultrashallow junctions, where dopant movement is driven by free interstitials emitted by self-interstitial “end-of-range” defects. We present recent progress on this topic, emphasizing novel effects in highly doped ultrashallow junctions. Two key influences – the chemical pump effect due to the high concentration of dopants in ultrashallow junctions, and the ‘long hop’ behaviour of the dopant – are discussed in detail. The paper concludes by presenting simulation results that explain the recent observation of ‘uphill diffusion’ of B ultrashallow junction profiles.

Fluorine clustering and diffusion in silicon: Ab initio calculations and kinetic Monte Carlo model

The authors performed systematic ab initio calculations of fluorine clustering in silicon. The calculated formation energies were used to implement a new kinetic Monte Carlo (KMC) model. They present the ab initio results, discuss the new KMC model, and compare the resulting simulated profiles to experimental profiles. The calculated formation energies show clear trends with the number of missing silicon atoms and the number of fluorine atoms. The deduced KMC model based on the ab initio energetics is able to reproduce the reduction in boron transient enhanced diffusion in the presence of fluorine.

Simulation of doping profile formation: Historical evolution, and present strengths and weaknesses

Dopant profile simulation for silicon-based process technology is focused on ion implantation and thermal annealing. In this work, the evolution of present strengths and weaknesses of corresponding process simulation models is presented, together with an overview on current modeling improvements, driven by the progress in process technology and the increase of computational resources.

Process modeling of chemical and stress effects in SiGe

Strained and relaxed SiGe, strained-silicon layers, and process-induced stress are widely used in state-of-the-art silicon process technology. Based on a literature review, we developed and calibrated continuum and kinetic Monte Carlo (kMC) process models for chemical and stress effects in SiGe. The models take into account the effects on band gap, amorphization and recrystallization, point defect generation and diffusion, extended defect evolution, dopant diffusion and clustering, and dopant segregation. The influence of Ge concentration and strain profile on Si self-interstitials and vacancies properties are deducted from experimental data as well as from ab initio studies. The {311} interstitial clusters are less stable in the presence of Ge or of compressive hydrostatic pressure, and the transformation of {311} defects into dislocation loops is faster. The corresponding parameter adjustments have been calibrated based on experimental data generated within the ATOMICS research project. The effects of G...

New implantation tables for B, BF 2 , P, As, In and Sb

After implantation, the distribution of ions can be described by analytical functions with parameters depending on implantation conditions. In this work, a calibrated Monte Carlo simulator was used to calculate tables for the implantation of B, BF2, P, As, In and Sb. Starting from systematic Monte Carlo data we extracted the parameters of two Pearson functions for dopant profiles in crystalline silicon and single Pearson functions for profiles in SiO2, Si3N4 and poly-silicon. The new tables cover more dopant species and implantation conditions than existing implantation tables and provide excellent agreement with 90 SIMS profiles. In a 2D nMOS test case, the implantation simulation with the new tables provides the same accuracy as Monte Carlo simulations.