Ultraviolet semiconductor lasers are widely used for applications in photonics, information storage, biology and medical therapeutics. Although the performance of gallium nitride ultraviolet lasers has improved significantly over the past decade, demand for lower costs, higher powers and shorter wavelengths has motivated interest in zinc oxide (ZnO), which has a wide direct bandgap and a large exciton binding energy. ZnO-based random lasing has been demonstrated with both optical and electrical pumping, but random lasers suffer from reduced output powers, unstable emission spectra and beam divergence. Here, we demonstrate electrically pumped Fabry-Perot type waveguide lasing from laser diodes that consist of Sb-doped p-type ZnO nanowires and n-type ZnO thin films. The diodes exhibit highly stable lasing at room temperature, and can be modelled with finite-difference time-domain methods.

The cooling effect on structural, electrical, and optical properties of epitaxial a-plane ZnO:Al on r-plane sapphire grown by pulsed laser deposition Appl. Phys. Lett. 101, 151907 (2012) Multiphonon scattering and photoluminescence of two dimensional ZnS nanosheets grown within Na-4 mica J. Appl. Phys. 112, 074321 (2012) Growth study of nonpolar Zn1−xMgxO epitaxial films on a-plane bulk ZnO by plasma-assisted molecular beam epitaxy Appl. Phys. Lett. 101, 122106 (2012) Mechanical and electrical characterization of semiconducting ZnO nanorings by direct nano-manipulation Appl. Phys. Lett. 101, 081910 (2012) Observation of magnetism, low resistivity, and magnetoresistance in the near-surface region of Gd implanted ZnO Appl.

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One of the key issues in vibration-based structural health monitoring is to extract the damage-sensitive but environment-insensitive features from sampled dynamic response measurements and to carry out the statistical analysis of these features for structural damage detection. A new damage feature is proposed in this paper by using the system matrices of the forward innovation model based on the covariance-driven stochastic subspace identification of a vibrating system. To overcome the variations of the system matrices, a non-singularity transposition matrix is introduced so that the system matrices are normalized to their standard forms. For reducing the effects of modeling errors, noise and environmental variations on measured structural responses, a statistical pattern recognition paradigm is incorporated into the proposed method. The Mahalanobis and Euclidean distance decision functions of the damage feature vector are adopted by defining a statistics-based damage index. The proposed structural damage detection method is verified against one numerical signal and two numerical beams. It is demonstrated that the proposed statistics-based damage index is sensitive to damage and shows some robustness to the noise and false estimation of the system ranks. The method is capable of locating damage of the beam structures under different types of excitations. The robustness of the proposed damage detection method to the variations in environmental temperature is further validated in a companion paper by a reinforced concrete beam tested in the laboratory and a full-scale arch bridge tested in the field.