In this Letter we investigate boron diffusion as a function of the Fermi-level position in crystalline silicon using ab initio calculations. Based on our results, a new mechanism for B diffusion mediated by Si self-interstitials is proposed. Rather than kick out of B into a mobile channel, we find a direct diffusion mechanism for the boron-interstitial pair for all Fermi-level positions. Our activation energy of 3.5 3.8 eV, migration barrier of 0.4 0.7 eV, and diffusion-length exponent of 20.6 to 20.2 eV are in excellent agreement with experiment.

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We present a theoretical treatment of the effect of stress on dopant and defect diffusion in Si. A prior treatment ͓P. H. Dederichs and K. Schroeder, Phys. Rev. B 17, 2524 ͑1978͔͒ of vacancy diffusion in strained fcc metals is extended to include more general defects and crystallinity. The new method is applied to two examples in Si: ͑1͒ a vacancy, including Jahn-Teller distortions, and ͑2͒ a B-I pair. Both are predicted to show isotropic diffusion for ͑100͒ grown uniaxially strained film, but strong anisotropic diffusion for ͑111͒ films.

A vacancy-mediated diffusion mechanism has been assumed in traditional models of P diffusion in Si. However, recent experiments have suggested that for intrinsic P diffusion in Si, the interstitial-assisted diffusion mechanism dominates. Here, we describe first-principles calculations of P diffusion in Si performed to study interstitial- and vacancy-mediated diffusion mechanisms. Special care is taken with regard to structural minimization, charge state effects and corrections. We calculated the defect formation energies and migration barriers for the various competing P–interstitial diffusion mechanisms, as well as P–vacancy diffusion energetics in different charge states. For P–interstitial diffusion, we find overall diffusion activation energies of 3.1–3.5 eV for neutral and +1 charge states, in close agreement with experiments at intrinsic conditions. For P–vacancy diffusion, our calculation is in agreement with previous calculations in the neutral case, but suggests that only P+V= plays a role in the heavily doped n region while the interstitial mechanisms may dominate in near-intrinsic regions.

The process of implementing a damage detection strategy for aerospace, civil and mechanical engineering infrastructure is referred to as structural health monitoring (SHM). The authors' approach is to address the SHM problem in the context of a statistical pattern recognition paradigm. In this paradigm, the process can be broken down into four parts: (1) Operational Evaluation, (2) Data Acquisition and Cleansing, (3) Feature Extraction and Data Compression, and (4) Statistical Model Development for Feature Discrimination. These processes must be implemented through hardware or software and, in general, some combination of these two approaches will be used. This paper will discuss each portion of the SHM process with particular emphasis on the coupling of a general purpose data interrogation software package for structural health monitoring with a modular wireless sensing and processing platform. More specifically, this paper will address the need to take an integrated hardware/software approach to developing SHM solutions.