Nanocrystalline silicon films as multifunctional material for optoelectronic and photovoltaic applications

Nanocrystalline silicon (nc-Si) already attracted a considerable attention as a promising material for photovoltaic applications, while its full opto-electronic potentiality is still under investigation, due to the relatively poor knowledge of the correlations between growth conditions, microstructure and physical properties. This paper aims at the illustration of the preliminary results of a 3 years project, addressed at the demonstration of the multifunctionality of nanocrystalline silicon, via the understanding of the quantitative correlations between growth process parameters and the structural, optical, electrical and physico-chemical properties of nc-silicon. The main topics foreseen and actively pursued were: The development of a gas phase kinetic model to be used for the simulations of the plasma enhanced chemical deposition (PECVD) process, the development of a kinetic model relative to the interaction of radicals present in the plasma phase at the substrate interface, and last but not least, the development of models relative to the subsequent nc-Si growth. The growth of undoped and doped nc-Si layers on convenient substrates by the low energy plasma enhanced chemical deposition (LEPECVD) process using silane, phosphine, diborane and hydrogen mixtures. The quantitative experimental determination of the correlation among the crystallinity fraction, the film microstructure, the grain size/shape/orientation, the hydrogen content, the density of the recombination centres, the optical absorption coefficient the strain/stress state and the carrier mobility and diffusion length in undoped and n-type and p-type films, in view of the optimization of the minority carrier generation and carrier collection. The preliminary results already demonstrate that a proper modelling of the growth process is of great help in the selection of optimised growth procedures for nc-Si films and that a full range experimental characterisation is needed to get the proper inputs to the modelling activity. (c) 2006 Elsevier B.V. All rights reserved.