钛宝石激光泵浦的1.06μm和1.34μm高效连续掺钕氟钒酸锶激光器

利用钛宝石激光作为泵浦源,实现了掺钕氟钡酸锶（ＮｄＳＶＡＰ）晶体在１．０６μｍ和１．３４μｍ的高效连续激光运转。在１．０６μｍ和１．３４μｍ处得到的最低泵浦阈值分别为２ｍＷ和２．４ｍＷ,最高斜效率分别为４９．４％和３７．４％,最大输出功率分别为３３６ｍＷ和１６５ｍＷ。     

Neural-network-based motor rolling bearing fault diagnosis

Motor systems are very important in modern society. They convert almost 60% of the electricity produced in the US into other forms of energy to provide power to other equipment. In the performance of all motor systems, bearings play an important role. Many problems arising in motor operations are linked to bearing faults. In many cases, the accuracy of the instruments and devices used to monitor and control the motor system is highly dependent on the dynamic performance of the motor bearings. Thus, fault diagnosis of a motor system is inseparably related to the diagnosis of the bearing assembly. In this paper, bearing vibration frequency features are discussed for motor bearing fault diagnosis. This paper then presents an approach for motor rolling bearing fault diagnosis using neural networks and time/frequency-domain bearing vibration analysis. Vibration simulation is used to assist in the design of various motor rolling bearing fault diagnosis strategies. Both simulation and real-world testing results obtained indicate that neural networks can be effective agents in the diagnosis of various motor bearing faults through the measurement and interpretation of motor bearing vibration signatures     

Improved semiconductor-laser dynamics from induced population pulsation

This paper investigates theoretically the modification of dynamical properties in a semiconductor laser by a strong injected signal. It is found that enhanced relaxation oscillations are governed by the pulsations of the intracavity field and population at frequencies determined by the injected field and cavity resonances. Furthermore, the bandwidth enhancement is associated with the undamping of the injection-induced relaxation oscillation and strong population pulsation effects. There are two limitations to the modulation-bandwidth enhancement: Overdamping of relaxation oscillation and degradation of flat response at low frequencies. The injected-laser rate-equations used in the investigation reproduce the relevant aspects of modulation-bandwidth enhancement found in the experiment on injection-locked vertical-cavity surface-emitting lasers.     

Dual-window dual-bandwidth spectroscopic optical coherence tomography metric for qualitative scatterer size differentiation in tissues

This study investigates the autocorrelation bandwidths of dual-window (DW) optical coherence tomography (OCT) k-space scattering profile of different-sized microspheres and their correlation to scatterer size. A dual-bandwidth spectroscopic metric defined as the ratio of the 10% to 90% autocorrelation bandwidths is found to change monotonically with microsphere size and gives the best contrast enhancement for scatterer size differentiation in the resulting spectroscopic image. A simulation model supports the experimental results and revealed a tradeoff between the smallest detectable scatterer size and the maximum scatterer size in the linear range of the dual-window dual-bandwidth (DWDB) metric, which depends on the choice of the light source optical bandwidth. Spectroscopic OCT (SOCT) images of microspheres and tonsil tissue samples based on the proposed DWDB metric showed clear differentiation between different-sized scatterers as compared to those derived from conventional short-time Fourier transform metrics. The DWDB metric significantly improves the contrast in SOCT imaging and can aid the visualization and identification of dissimilar scatterer size in a sample. Potential applications include the early detection of cell nuclear changes in tissue carcinogenesis, the monitoring of healing tendons, and cell proliferation in tissue scaffolds.     

The role of ion characteristics in determining the structural and electrical quality of InN grown by metalorganic molecular beam epitaxy

The effects of growth temperature and nitrogen plasma biasing on the electrical and structural properties of InN grown using electron cyclotron resonance metalorganic molecular beam epitaxy (ECR MOMBE) have been investigated. These results are compared to those found from InN grown using a higher energy radio frequency (rf) plasma source (rf MOMBE). By varying the bias of the nitrogen plasma or the growth temperature, it is possible to achieve smooth surface morphologies. However, biasing can also be used to increase the mobility by a factor of two while the growth temperature has only a small effect. By contrast, use of an rf plasma improves mobility by nearly a factor of ten. None of the growth conditions investigated were found to significantly alter the electron concentration, which was measured to be 1−5 × 10²⁰ cm⁻³.     

Nonequilibrium many-body theory of intersubband lasers

We present a theory for intersubband lasers, based on the solution of the Maxwell-semiconductor Bloch equations for the laser field and active medium. The collision contributions are treated within the relaxation rate approximation, where the relaxation rates are determined by microscopic scattering calculations. The theory is suitable for investigating steady-state as well as dynamical laser characteristics. As examples of applications of the theory, we examine the thermal dependence of the laser output versus current density curve and the response to modulation of the injection current, for a three-subband laser. The influence of the nonparabolicity of the conduction band and Hartree-Fock many-body effects are investigated.     

Serial dark soliton for 100-gb/s applications

We analyze the performance through numerical simulations of a new modulation format: serial dark soliton (SDS) for wide-area 100-Gb/s applications. We compare the performance of the SDS with conventional dark soliton, amplitude-modulation phase-shift keying (also known as duobinary), nonreturn-to-zero, and return-to-zero modulation formats, when subjected to typical wide-area-network impairments. We show that the SDS has a strong chromatic dispersion and polarization-mode-dispersion tolerance, while maintaining a compact spectrum suitable for strong filtering requirement in ultradense wavelength-division-multiplexing applications. The SDS can be generated using commercially available components for 40-Gb/s applications and is cost efficient when compared with other 100-Gb/s electrical-time-division-multiplexing systems.     

Quantification of Temperature-Dependent Charge Separation and Recombination Dynamics in Non-Fullerene Organic Photovoltaics

Transient optical spectroscopy is used to quantify the temperature-dependence of charge separation and recombination dynamics in P3TEA:SF-PDI₂ and PM6:Y6, two non-fullerene organic photovoltaic (OPV) systems with a negligible driving force and high photocurrent quantum yields. By tracking the intensity of the transient electroabsorption response that arises upon interfacial charge separation in P3TEA:SF-PDI₂, a free charge generation rate constant of ≈2.4 × 10¹⁰ s⁻¹ is observed at room temperature, with an average energy of ≈230 meV stored between the interfacial charge pairs. Thermally activated charge separation is also observed in PM6:Y6, and a faster charge separation rate of ≈5.5 × 10¹⁰ s⁻¹ is estimated at room temperature, which is consistent with the higher device efficiency. When both blends are cooled down to cryogenic temperature, the reduced charge separation rate leads to increasing charge recombination either directly at the donor-acceptor interface or via the emissive singlet exciton state. A kinetic model is used to rationalize the results, showing that although photogenerated charges have to overcome a significant Coulomb potential to generate free carriers, OPV blends can achieve high photocurrent generation yields given that the thermal dissociation rate of charges outcompetes the recombination rate.     

Approximation of dynamical time-variant systems by continuous-time recurrent neural networks

This paper studies the approximation ability of continuous-time recurrent neural networks to dynamical time-variant systems. It proves that any finite time trajectory of a given dynamical time-variant system can be approximated by the internal state of a continuous-time recurrent neural network. Given several special forms of dynamical time-variant systems or trajectories, this paper shows that they can all be approximately realized by the internal state of a simple recurrent neural network.