R. Pinacho

Carbon in silicon: Modeling of diffusion and clustering mechanisms

Carbon often appears in Si in concentrations above its solubility. In this article, we propose a comprehensive model that, taking diffusion and clustering into account, is able to reproduce a variety of experimental results. Simulations have been performed by implementing this model in a Monte-Carlo atomistic simulator. The initial path for clustering included in the model is consistent with experimental observations regarding the formation and dissolution of substitutional C–interstitial C pairs (Cs–Ci). In addition, carbon diffusion profiles at 850 and 900 °C in carbon-doping superlattice structures are well reproduced. Finally, under conditions of thermal generation of intrinsic point defects, the weak temperature dependence of the Si interstitial undersaturation and the vacancy supersaturation in carbon-rich regions also agree with experimental measurements.

Experimental observation of conductance transients in Al/SiNx:H/Si metal-insulator-semiconductor structures

Room temperature conductance transients in the SiNx:H/Si interface are reported. Silicon nitride thin films were directly deposited on silicon by the low temperature electron-cyclotron-resonance plasma method. The shape of the conductance transients varies with the frequency at which they are obtained. This behavior is explained in terms of a disorder-induced gap-state continuum model for the interfacial defects. A perfect agreement between experiment and theory is obtained proving the validity of the model.

Modeling arsenic deactivation through arsenic-vacancy clusters using an atomistic kinetic Monte Carlo approach

A comprehensive atomistic model for arsenic in silicon which includes charge effects and is consistent with first-principles calculations for arsenic-vacancy cluster energies has been developed. Emphasis has been put in reproducing the electrical deactivation and the annealed profiles in preamorphized silicon. The simulations performed with an atomistic kinetic Monte Carlo simulator suggest a predominant role of the mobile interstitial arsenic in deactivation experiments and provide a good understanding of the arsenic behavior in preamorphized silicon during annealing.

Physical modeling and implementation scheme of native defect diffusion and interdiffusion in SiGe heterostructures for atomistic process simulation

In order to simulate the diffusion kinetics during thermal treatments in SiGe heterostructures, a physically-based atomistic model including chemical and strain effects has been developed and implemented into a nonlattice atomistic kinetic monte carlo (KMC) framework. This model is based on the description of transport capacities of native point defects (interstitials and vacancies) with different charge states in SiGe alloys in the whole composition range. Lattice atom diffusivities have been formulated in terms of point defect transport, taking into account the different probability to move Si and Ge atoms. Strain effects have been assessed for biaxial geometries including strain-induced anisotropic diffusion, as well as charge effects due to strain-induced modifications of the electronic properties. Si-Ge interdiffusion in heterostructures has been analyzed from an atomistic perspective. A limited set of physical parameters have been defined, being consistent with previously reported ab initio calculations and experiments. The model has been implemented into a nonlattice KMC simulator and the relevant implementation details and algorithms are described. In particular, an efficient point defect mediated Si-Ge exchange algorithm for interdiffusion is reported. A representative set of simulated interdiffusion profiles are shown, exhibiting good agreement with experiments.In order to simulate the diffusion kinetics during thermal treatments in SiGe heterostructures, a physically-based atomistic model including chemical and strain effects has been developed and implemented into a nonlattice atomistic kinetic monte carlo (KMC) framework. This model is based on the description of transport capacities of native point defects (interstitials and vacancies) with different charge states in SiGe alloys in the whole composition range. Lattice atom diffusivities have been formulated in terms of point defect transport, taking into account the different probability to move Si and Ge atoms. Strain effects have been assessed for biaxial geometries including strain-induced anisotropic diffusion, as well as charge effects due to strain-induced modifications of the electronic properties. Si-Ge interdiffusion in heterostructures has been analyzed from an atomistic perspective. A limited set of physical parameters have been defined, being consistent with previously reported ab initio calculat...

Ion-beam amorphization of semiconductors: A physical model based on the amorphous pocket population

We introduce a model for damage accumulation up to amorphization, based on the ion-implant damage structures commonly known as amorphous pockets. The model is able to reproduce the silicon amorphous-crystalline transition temperature for C, Si, and Ge ion implants. Its use as an analysis tool reveals an unexpected bimodal distribution of the defect population around a characteristic size, which is larger for heavier ions. The defect population is split in both size and composition, with small, pure interstitial and vacancy clusters below the characteristic size, and amorphous pockets with a balanced mixture of interstitials and vacancies beyond that size.

Comprehensive model of damage accumulation in silicon

Ion implantation induced damage accumulation is crucial to the simulation of silicon processing. We present a physically based damage accumulation model, implemented in a nonlattice atomistic kinetic Monte Carlo simulator, that can simulate a diverse range of interesting experimental observations. The model is able to reproduce the ion-mass dependent silicon amorphous-crystalline transition temperature of a range of ions from C to Xe, the amorphous layer thickness for a range of amorphizing implants, the superlinear increase in damage accumulation with dose, and the two-layered damage distribution observed along the path of a high-energy ion. In addition, this model is able to distinguish between dynamic annealing and post-cryogenic implantation annealing, whereby dynamic annealing is more effective in removing damage than post-cryogenic implantation annealing at the same temperature.

Fermi-level effects in semiconductor processing: A modeling scheme for atomistic kinetic Monte Carlo simulators

Atomistic process simulation is expected to play an important role for the development of next generations of integrated circuits. This work describes an approach for modeling electric charge effects in a three-dimensional atomistic kinetic Monte Carlo process simulator. The proposed model has been applied to the diffusion of electrically active boron and arsenic atoms in silicon. Several key aspects of the underlying physical mechanisms are discussed: (i) the use of the local Debye length to smooth out the atomistic point-charge distribution, (ii) algorithms to correctly update the charge state in a physically accurate and computationally efficient way, and (iii) an efficient implementation of the drift of charged particles in an electric field. High-concentration effects such as band-gap narrowing and degenerate statistics are also taken into account. The efficiency, accuracy, and relevance of the model are discussed.

Atomistic Front-End Process Modelling: A Powerful Tool for Deep-Submicron Device Fabrication

The complexity attained by current microelectronics process technology can hardly be handled with simulators based on the continuum approach. Over the last few years, atomistic Kinetic Monte Carlo has proven to be a new way to tackle the problems that arise as device dimension shrink into the deep submicron regime. We present some encouraging results of exploring the capabilities of this new process modelling approach.

Ion implant simulations: Kinetic Monte Carlo annealing assessment of the dominant features

The atomistic physically based kinetic Monte Carlo method has been used in conjunction with the binary collision approximation (BCA) to elucidate the implant mechanisms most relevant for modeling transient-enhanced diffusion (TED). For the cases studied, we find that: (i) The spatial correlation of the interstitial, vacancy (I,V) Frenkel pairs is not critical, (ii) the interstitial supersaturation in simulations which include full I, V profiles or only the net I–V is the same, (iii) quick and noisy BCA implant I, V distributions can be directly used (or after smoothing them out) as they can still yield accurate annealing simulations, and (iv) when there is an impurity concentration comparable to the net I–V excess, the full I and V profiles have to be used in order to correctly reproduce the impurity clustering/deactivation. Finally, some practical implications for TED simulations are drawn.

Modeling and Simulation of the Influence of SOI Structure on Damage Evolution and Ultra-shallow Junction Formed by Ge Preamorphization Implants and Solid Phase Epitaxial Regrowth

Preamorphization implant (PAI) prior to dopant implantation, followed by solid phase epitaxial regrowth (SPER) is of great interest due to its ability to form highly-activated ultrashallow junctions. Coupled with growing interest in the use of silicon-on-insulator (SOI) wafers, modeling and simulating the influence of SOI structure on damage evolution and ultra-shallow junction formation is required. In this work, we use a kinetic Monte Carlo (kMC) simulator to model the different mechanisms involved in the process of ultra-shallow junction formation, including amorphization, recrystallization, defect interaction and evolution, as well as dopantdefect interaction in both bulk silicon and SOI. Simulation results of dopant concentration profiles and dopant activation are in good agreement with experimental data and can provide important insight for optimizing the process in bulk silicon and SOI.