Nikolas Zographos

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.

Experimental and Theoretical Analysis of Dopant Diffusion and C Evolution in High-C Si:C Epi Layers: Optimization of Si:C Source and Drain Formed by Post-Epi Implant and Activation Anneal

A comprehensive physics based calibrated model was developed to explain the observed n-type dopant diffusion and substitutional carbon (Csub) evolution in high C (>1%) Si:C epitaxial films. Both experimentally and theoretically, we demonstrated a viable doping scheme with near 100% Csub retention using undoped Si:C epi with post-epi implant and optimized anneal.

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.

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...

Atomistic Modeling of Carbon Co-Implants and Rapid Thermal Anneals in Silicon

Carbon co-implantation after pre-amorphization implantation is a promising candidate for ultra shallow junction formation for advanced CMOS technologies due to its ability to suppress transient enhanced diffusion of dopants in silicon. Modeling the interaction of carbon with point defects is important for the development of these techniques. In this paper, we demonstrate a comprehensive atomistic model for carbon implantation, diffusion, clustering, and interaction with End-Of-Range (EOR) defects.

Continuum modeling of implantation and thermal processes for advanced devices formation

Technology Computer-Aided Design is widely used for the development and optimization of advanced device formation. Ion implantation and thermal annealing are the main focus of dopant profile simulation for process technologies. In this paper, we review the current continuum modeling capabilities and calibration for ion implantation and thermal processes, including Monte Carlo ion implantation, co-implantation, amorphization, recrystallization, damage evolution, and dopant diffusion and activation. In addition, modeling of alternative doping techniques such as thermal implantation, plasma doping, and melt laser annealing will be addressed. Continuum front-end process simulation of Si-based devices including advanced CMOS, memory, power, and optoelectronic devices is considered to be mature. With the introduction of new channel materials, the models and calibration of alternative materials such as SiGe, Ge, and III-V are also required and their current status is discussed.

Phosphorus diffusion and activation in silicon: Process simulation based on ab initio calculations

We present the results of extensive ab initio simulations for phosphorus clustering and diffusion in silicon and the application of these results in a state-of-the-art process simulator. The specific defects and the parameters that are investigated are selected according to the needs of diffusion and activation models, taking into account the availability of experimental data, the capabilities of current ab initio methods and the requirements for advanced technology development. The calculated formation energies, binding energies and migration barriers are used to determine a good starting point for the calibration of a new charged cluster model implemented in the process simulator. The defect species V, I, P, PV, PI, PI 2 , P 2 , P 2 V, P 2 I, P 3 , P 3 V, P 3 I and P 4 V are considered in all relevant charge states. The ab initio results are discussed as well as the transfer of this information into the process simulation model and the impact on model quality.

Modeling Evolution of Temperature, Stress, Defects, and Dopant Diffusion in Silicon During Spike and Millisecond Annealing

The bulk CMOS devices continue to be the dominant player for the next few technology nodes. This drives the increasingly contradicting requirements for the channel, source/drain extension, and heavily doped source/drain doping profiles. To analyze and optimize the transistors, it has become necessary to simultaneously analyze effects that have been previously decoupled. The temperature gradients, combined with stress engineering techniques such as embedded SiGe and Si:C source/drain and stress memorization techniques, create non-uniform stress distributions which are determined by the layout patterns. The interaction of implantinduced damage with dopants, stress, and defect traps defines the dopant activation, retention of useful stress, and junction leakage. This work reviews recent trends in modeling these effects using continuum and kinetic Monte Carlo methods.

From point defects to dislocation loops: A comprehensive TCAD model for self-interstitial defects in silicon

An atomistic model for self-interstitial extended defects is presented in this work. Using a limited set of assumptions about the shape and emission frequency of extended defects, and taking as parameters the interstitial binding energies of extended defects versus their size, this model is able to predict a wide variety of experimental results. The model accounts for the whole extended defect evolution, from the initial small irregular clusters to the {311} defects and to the more stable dislocation loops. The model predicts the extended defect dissolution, supersaturation and defect size evolution with time, and it takes into account the thermally activated transformation of {311} defects into dislocation. The model is also used to explore a two-phase exponential decay observed in the dissolution of {311} defects.