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During the oxidation of SiGe regions, Si is preferably incorporated into the oxide, while Ge atoms accumulate at the SiGe side of the interface. Moreover, during oxidation of fin structures of Si/SiGe superlattices, Ge atoms diffuse from SiGe regions to Si regions along the oxide/SiGe interface, as recently reported. This surface diffusion can be used for the formation of Si nanowires surrounded by SiGe, and possibly for the fabrication of gate all‐around transistors. Herein, a new process simulation model is presented which describes SiGe oxidation and the diffusion of Ge atoms along the interface. During oxidation, Ge atoms can be trapped at the oxide/SiGe interface, diffuse along the interface, and be re‐emitted into the SiGe bulk. The model reproduces measured oxidation rates, the pileup of Ge atoms at the SiGe side of planar oxide/SiGe interfaces, the injection of self‐interstitials and the reduction of vacancies at oxidizing SiGe surfaces, and the recently reported diffusion of Ge atoms along the surface of fin structures made of Si/SiGe superlattices. [ABSTRACT FROM AUTHOR]

A comprehensive process model for 4H‐SiC oxidation is created and calibrated against a very large collection of experimental data. The model reproduces measured oxide thickness for Si‐face, C‐face, and a‐face SiC wafers, in the temperature range 950–1500 °C, in the pressure range 0.25–4.0 atm, in the thickness range 3–1600 nm, and for SiC doping ranging between 1019 cm−3 n‐type and 1019 cm−3 p‐type. The model is based on the Massoud model: Oxidation is driven by oxidants (O2, H2O) which are present in the gas phase, diffuse through the oxide, and form SiO2 at the oxide–SiC interface. For thin oxides, the interface reaction rate includes empirical correction terms which add to the oxidation rate, and which asymptotically approach zero with increasing oxide thickness. For dry oxidation, a remarkable dependence on the O2 partial pressure is discovered: For thick oxides, the oxidation rate scales linearly with the pressure, but the correction term for thin oxides scales with the square root of the pressure. This suggests that the atomistic processes responsible for the fast initial growth of oxides involve the splitting of O2 molecules into two O atoms. [ABSTRACT FROM AUTHOR]

The development of advanced semiconductor devices relies heavily on technology computer-aided design. Front-end process simulators model the fabrication of devices including different process steps and effects such as ion implantation, dopant and defect diffusion and interaction, epitaxial growth, and stress effects. Continuum process simulators continue to be the main tool; however, kinetic Monte Carlo simulators with and without lattice have become important as well. With the need to explore new materials other than silicon, such as SiGe, germanium, and III–V, more fundamental modeling is required to compensate for missing experimental information. Ab initio methods based on density functional theory and molecular dynamics can help address open questions of material characteristics that cannot be extracted explicitly by experiments. In this paper, we give an overview of a multiscale approach for advanced process modeling and discuss the latest progress. [ABSTRACT FROM AUTHOR]

In TCAD process simulation, the Poisson equation for electrostatic potential is usually solved in silicon and polysilicon regions, assuming a zero normal component of electric field (ZEF) boundary conditions (BCs) at material interfaces. This is correct for a free (or covered only with dielectric) flat surface of silicon, which is typical for 1D SIMS profile simulations. However, it is inaccurate in other important cases, in particular, under the gate of submicron MOS transistors, where more general BCs preserving the continuity of the flux of electric displacement should be applied. In a simulation, the choice of BCs changes the electrostatic potential near material interfaces and, thereby, impacts simulated dopant distributions and transistor characteristics. We introduced such general BCs in Sentaurus Process and applied them to the 2D simulation of CMOS transistors with polysilicon or metal gate. A noticeable (but moderate) increase of simulated threshold voltage in comparison to the ZEF BCs is demonstrated. In addition, the effect of carrier concentration reduction at silicon/dielectric interfaces due to quantum-mechanical repulsion was introduced into a continuum process simulation using the modified local-density approximation. This changes the dopant distributions in a nanometre thin layer in semiconductors at both sides of the gate oxide, resulting in a reduced concentration of the main dopant near the interface, which is most pronounced at high dopant concentrations. (© 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim) [ABSTRACT FROM AUTHOR]

Abstract: In recent years, physics-based models have been developed for the time evolution of defects formed by Si self-interstitials in ion-implanted Si. The accuracy of these models is crucial for a predictive process simulation of deep sub micron devices. However, the most complete models are usually not considered in applied process simulation, because they use too many equations. In this work, a new model is presented in which the essential physics behind the formation and dissolution of small interstitial clusters and {311} defects is described by a minimum set of five reaction equations. Three equations describe the kinetics of small interstitial clusters which governs the initial phase of implantation damage annealing. Two equations describe the formation and Ostwald ripening of {311} defects. The model is capable to reproduce experimental data over a wide range of implantation energies, doses and anneal temperatures. It allows predictive simulations of interstitial cluster kinetics at a minimum computational cost. [Copyright &y& Elsevier]

Computationally efficient ion implantation modeling has long been essential for the effective and accurate design of semiconductor devices. Three-dimensional (3D) analytic models are an attractive alternative to physics-based Monte Carlo simulations, since the latter can be prohibitively expensive in terms of computational time in the case of very large simulation domains. Here we present a new computationally efficient 3D analytic ion implantation model based on Legendre polynomials implemented in the Technology Computer-Aided Design (TCAD) Sentaurus™ Process simulator. Legendre polynomials are used as basic functions due to their orthogonality and good interpolation. Unlike other distributions such as Pearson or dual-Pearson functions, Legendre polynomials can be used to describe virtually any profile shape. We also describe a new simple yet accurate method to extract the depth-dependent lateral standard deviation. It uses calibrated Monte Carlo simulations as a reference and is applicable to arbitrary primary distribution functions. The analytic implantation model has been evaluated within a complete 3D process and device simulation flows of a complementary metal–oxide–semiconductor (CMOS) image sensor (CIS) and a silicon carbide (SiC) superjunction power metal-oxide-semiconductor field-effect transistor (MOSFET). In comparison to reference simulations in which a Monte Carlo model is used for ion implantation, excellent agreement is demonstrated for the as-implanted dopant profiles, the crystal damage profiles, and the electrical device characteristics, while the computational time needed for ion implantation is reduced by a factor of 25. [ABSTRACT FROM AUTHOR]