Atomistic Simulation Techniques in Front-End Processing
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1070-E06-01
Atomistic Simulation Techniques in Front-End Processing Luis A. Marqués, Lourdes Pelaz, Iván Santos, Pedro López, and María Aboy Department of Electronics, University of Valladolid, ETSI Telecomunicación, Campus Miguel Delibes s/n, Valladolid, 47011, Spain ABSTRACT Atomistic process models are beginning to play an important role as direct simulation approaches for front-end processes and materials, and also as a pathway to improve continuum modeling. Detailed insight into the underlying physics using ab-initio methods and classical molecular dynamics simulations will be needed for understanding the kinetics of reduced thermal budget processes and the role of impurities. However, the limited sizes and time scales accessible for detailed atomistic techniques usually lead to the difficult task of relating the information obtained from simulations to experimental data. The solution consists of the use of a hierarchical simulation scheme: more fundamental techniques are employed to extract parameters and models that are then feed into less detailed simulators which allow direct comparison with experiments. This scheme will be illustrated with the atomistic modeling of the ion-beam induced amorphization and recrystallization of silicon. The model is based on the bond defect or IV pair, which is used as the building block of the amorphous phase. It is shown that the recombination of this defect depends on the surrounding bond defects, which accounts for the cooperative nature of the amorphization and recrystallization processes. The implementation of this model in a kinetic Monte Carlo code allows extracting data directly comparable with experiments. INTRODUCTION Silicon processing is facing an increasingly high level of complexity as CMOS technology is pushed closer to its limits. In particular, front-end processing is trying to extend the use of conventional and well established techniques, such as ion implantation and annealing, into the nanometer regime [1]. With further reduction of the devices size, new effects or effects that were neglected so far become relevant. Their experimental characterization is a complex task, firstly because the realization of test lots is extremely expensive, and secondly because usually these effects occur simultaneously which makes difficult the interpretation of measurements. In this situation the use of simulation tools can be very helpful [2]. Most process simulators used in industrial applications are based on continuum methods, where the physics of the system is formulated as a series of differential equations for each particle type considered to be relevant in the process. Typically they are continuity equations, where each particle gain or loss is formulated in terms of its generation and recombination rates and the diffusion flux [3,4]. In the equations there are a number of parameters such as binding energies, diffusivities, capture radii, etc., that have to be provided. The numerical solution of the set of partial differential equations requires spatial and tempora
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