S. Coffa

Origin and perspectives of the 1.54 μm luminescence from ion-beam-synthesized β-FeSi2 precipitates in Si

The structural and optical properties of β-FeSi2 precipitates in Si have been analyzed. Float zone Si samples were implanted at 250 °C with 350 keV Fe ions to fluences in the range 1–5×1015/cm2 and annealed in vacuum at 800 °C for times up to 24 h. Detailed morphological analyses of these samples, using transmission electron microscopy, reveal the presence of (i) a band of small (with a diameter 100 nm diameter) fully relaxed β-FeSi2 precipitates centered at a depth of ∼320 nm, and (iii) residual extended defects. A sharp photoluminescence peak at 1.54 μm is measured at 17 K. This peak remains unchanged when the region containing the small precipitates is removed, using Ar sputtering. On the other hand, it is also fully suppressed when the large precipitates region is removed and a high concentration of extended defects remains in the samples. This allowed us to identify the large unstrained precipitates as...

Design, fabrication, and testing of an integrated Si-based light modulator

We have fabricated and characterized a novel Si-based light modulator working at the standard communication wavelength of 1.5 /spl mu/m. It consists of a three-terminal bipolar mode field effect transistor integrated with a silicon rib waveguide on epitaxial Si wafers. The modulator optical channel is embodied within its vertical electrical channel. Light modulation is achieved moving a plasma of carriers inside and outside the optical channel by properly biasing the control electrode. The carriers produce an increase of the Si absorption coefficient. The devices have been fabricated using clean-room processing. Detailed electrical characterization and device simulations confirm that strong conductivity modulation and plasma formation in the channel are achieved. The plasma distribution in the device under different bias conditions has been directly derived from emission microscopy analyses. The device performances in terms of modulation depth will be presented.

Accelerated Monte Carlo algorithms for defect diffusion and clustering

Abstract We present a hierarchy of accelerate Monte Carlo (MC) algorithms which can be used to investigate the kinetic evolution of systems consisting of interacting defects or impurities in a solid matrix. Local models are used to approximate the interactions among particles and a specific application of the algorithms to the study of vacancy agglomeration is presented. It is shown that an extension of the Ising model, including an effective second neighbour interaction, gives a vacancy clusters energetics in good agreement with some recent quantum mechanical calculations. The accelerate algorithms implemented allow to speed up the calculations avoiding the bottlenecks which occur when the standard Metropolis algorithm is applied. These bottlenecks are due to the huge amount of rejected transition attempts and to the rapid fluctuations between quasi-degenerate configurations. We demonstrate the equivalence between the results obtained using standard and accelerated algorithms. Moreover we discuss in detail the gain in terms of CPU time when the algorithms are applied to two different vacancy interaction models. In the case of a simple Ising model (SIM) an optimised code ∼105 times faster than the standard Metropolis can be implemented; on the other hand, when the extended interaction is considered, the gain reduces to ∼103. Therefore the gain in speed, achievable with accelerate codes, is strongly dependent on the kinetic features of the interaction models. Indeed a relevant consequence of the second neighbor interaction is the migration of the aggregates which boosts the agglomeration process. This faster agglomeration reduces the effects of bottlenecks during the ripening process thus reducing the difference in efficiency between accelerated and conventional codes.

Quantitative determination of the clustered silicon concentration in substoichiometric silicon oxide layer

We present an analytical methodology, based on electron energy loss spectroscopy (EELS) and energy-filtered transmission electron microscopy, which allows us to quantify the clustered silicon concentration in annealed substoichiometric silicon oxide layers, deposited by plasma-enhanced chemical vapor deposition. The clustered Si volume fraction was deduced from a fit to the experimental EELS spectrum using a theoretical description proposed to calculate the dielectric function of a system of spherical particles of equal radii, located at random in a host material. The methodology allowed us to demonstrate that the clustered Si concentration is only one half of the excess Si concentration dissolved in the layer.

Role of the internal strain on the incomplete Si∕SiO2 phase separation in substoichiometric silicon oxide films

Silicon nanoclusters were formed in plasma-enhanced chemical vapor deposited substoichiometric silicon oxide films by annealing at 1100°C for 1∕2h as a function of different deposition parameters. The samples were analyzed by energy filtered transmission electron microscopy and Rutherford backscattering. At any deposition condition, the clustered silicon concentration is significantly lower than the initial silicon excess concentration. This behavior is explained by taking into account the free energy difference between the metastable SiO and stable SiO2 phase and the strain energy associated with the different atomic densities of Si and SiO2.

Miniaturizable Si-based electro-optical modulator working at 1.5 μm

Optoelectronic devices are considered the innovative element for the next generation of microelectronic integrated circuits. For this purpose, both active and passive devices—extremely miniaturized—must be implemented. We fabricated and electro-optical Si-based light intensity modulator working at 1.5 μm using a bipolar mode field-effect transistor integrated within a Si rib waveguide. The principle of operation is the light absorption by a plasma of free carriers that can be opportunely moved inside or outside of the device optical channel by properly changing the control bias. The devices, only 100 μm long, were fabricated using epitaxial Si wafers and standard clean room processing. The optical characterization at 1.48 μm in static conditions shows a modulation of ∼90% while the dynamic electrical characterization provides a switching time of ≈10ns (foreseen modulation frequency of hundreds of MHz). A modulation depth above 25% is observed for modulation frequency up to 300 kHz.

Low-Temperature Annealing Combined with Laser Crystallization for Polycrystalline Silicon TFTs on Polymeric Substrate

The formation of polycrystalline Si layers on flexible plastic substrates, through plasma enhanced chemical vapor deposition and excimer laser annealing, is investigated. Combining low-temperature (300°C) annealing with laser dehydrogenation/crystallization produces good-quality polycrystalline silicon with a reduced shot density. By using optimal crystallization conditions it is possible to achieve a superlateral growth crystallization regime, with a grain size up to 1 μm, and void-free material, as confirmed by the presented structural analysis. The beneficial effect of the low-temperature thermal annealing has been related to the removal of nonbound hydrogen, as supported by the elastic recoil detection analysis and IR analysis of the samples. To validate the process, we fabricated non-self-aligned polysilicon thin-film transistors (TFTs) directly on spin-coated polyimide substrates, with a maximum processing temperature of 300°C and with a relatively low shot density ( 10 6 , a field-effect mobility up to 65 cm 2 /V s, and a threshold voltage of 7 V. These results confirmed that the developed crystallization process is suitable to fabricate polysilicon TFTs on polymeric substrates, allowing an increased process throughput.

Coupled Monte Carlo-Poisson method for the simulation of particle-particle effects in dielectrophoretic devices

Simulations can aid to bridge the gap between the proof-of-concept stage and the engineering of dielectrophoretic devices. We present a simulation method overcoming the limits of fluid-flow based approaches. In our Monte-Carlo-Poisson simulator, the colloidal system is described at the particle resolution. This characteristic allows for taking into account volume forces and particle-particle interactions usually neglected in the continuum approximation. In turn, large number of particles and large systems can be simulated to meet the device design needs. In an experimentally verifiable case study, we discuss the role of the multi-particle interaction in high and moderate density regimes.

A kinetic lattice Monte-Carlo approach to the evolution of boron in silicon

Abstract A kinetic 3D lattice Monte-Carlo (MC) model is introduced, which allows to describe the evolution of boron-rich silicon, especially the formation of boron-interstitial clusters of various structures and compositions. Using a refined bcc lattice with lattice constant abcc=aSi/4 a large variety of defect configurations can be mapped essentially without geometrical distortions. The energetics of defects can be specified by means of a set of energy parameters. Boron diffusion is implemented via an interstitial-assisted mechanism. First results of interstitial-mediated boron clustering are presented. The future capabilities to study the kinetics of BnIm cluster formation are outlined.

Particle-chain formation in a dc dielectrophoretic trap; a reaction-diffusion approach

Dielectrophoresis has proven to be an effective method for the separation of bioparticles such as cells. Nevertheless, the electric polarization induced by nonuniform electric fields leads to a dipole-dipole interaction between particles and therefore the formation of chains is likely to occur. In this paper, we will present an approach based on a drift-diffusion dynamics to quantitatively study formation and kinetics of particle-chains via the introduction of the particle stitching as chemical-like reactions. This approach will allow us to dynamically describe, in the framework of a numerical simulation, particle clustering, thus providing a suitable tool for reproducing data from dielectrophoretic experimental setup.