Damgaardclifford4634

Plasmon-enhanced sensitive photodetection using plasmonic noble metals has been widely investigated; however, aluminum (Al)-based photoelectric conversion concurrently utilizing photonic and plasmonic approaches is less explored. Here, photodetection driven by quasi-localized plasmon resonance (QLPR) is investigated. Concurrent photonic and plasmonic contributions to strong absorption in the active region require delocalized, slow-propagating resonant electric field to occur around the peripheries of Al nano-structures and depend on the spatial distribution of diffraction efficiencies of all space harmonics. Efficiency limits are shown to be largely determined by the spatial degrees of freedom and the associated traveling distances of hot electrons during carrier transport. With strong absorption and relatively high reaching-emission probabilities structured in the same region, the measured responsivity and the external quantum efficiency of the fabricated device at 638.9 nm are 4.1889 μA/mW and 0.8129% at -0.485 V, respectively. Our results provide physical insights into related problems and may offer a route to more efficient, hot-carrier based photoelectric conversion devices.A multi-aperture solar central receiver system is optically analyzed for increasing the net power to the receiver in a wide temperature range of 600-1800 K. A model system comprises a tower, a multi-aperture receiver with compound parabolic concentrators, and heliostat sub-fields. Optical modeling is performed using in-house developed Monte-Carlo ray-tracing programs. The heliostat sub-field geometrical configuration, the number of receiver apertures and optical properties of reflective surfaces are varied in the parametric study. Increasing the number of apertures from one to four increases the maximum net receiver power from 116 MW to 332 MW. The use of more than four apertures results in only limited further gain of the net receiver power but significantly decreases the overall optical efficiency and the solar-to-thermal efficiency. The optimal temperature for the maximized annual solar-to-exergy efficiency is found in the range of 1100-1200 K. This optimal temperature decreases slightly with an increasing number of apertures.The single-photon scattering by a V-type three-level emitter in a rectangular waveguide is studied. Here the frequency value of input photons can be large beyond the single-transverse-mode region. By using Green's function formalism, the necessary and sufficient conditions of complete transmission as well as complete reflection are derived analytically. In the region of single transverse mode, the physical mechanisms of complete transmission and complete reflection are electromagnetically induced transparency (EIT) and Fano resonance, respectively. In the region of multiple transverse modes, which are induced by the finite cross section, the quantum interference between multiple scattering pathways with different transverse modes can be used to manipulate the single-photon transport. We find that the emitter becomes transparent when the superposition of waveguide modes has zero amplitude at the position of emitter. And the perfect reflection is absent even under Fano resonance unless the input-state is in a coherent superposition state. These results may promote the development of single-photon devices with wide applicable frequency region.In this article we present and describe an online freely accessible software called Multi-Scattering for the modeling of light propagation in scattering and absorbing media. Part II of this article series focuses on the validation of the model by rigorously comparing the simulated results with experimental data. The model is based on the use of the Monte Carlo method, where billions of photon packets are being tracked through simulated cubic volumes. Simulations are accelerated by the use of general-purpose computing on graphics processing units, reducing the computation time by a factor up to 200x in comparison with a single central processing unit thread. By using four graphic cards on a single computer, the simulation speed increases by a factor of 800x. For an anisotropy factor g = 0.86, this enables the transport path of one billion photons to be computed in 10 seconds for optical depth OD = 10 and in 20 minutes for OD = 500. Another feature of Multi-Scattering is the integration and implementation of the Lorenz-Mie theory in the software to generate the scattering phase functions from spherical particles. The simulations are run from a computer server at Lund University, allowing researchers to log in and use it freely without any prior need for programming skills or specific software/hardware installations. There are countless types of scattering media in which this model can be used to predict light transport, including medical tissues, blood samples, clouds, smoke, fog, turbid liquids, spray systems, etc. An example of simulation results is given here for photon propagation through a piece of human head. The software also includes features for modeling image formation by inserting a virtual collecting lens and a detection matrix which simulate a camera objective and a sensor array respectively. The user interface for setting-up simulations and for displaying the corresponding results is found at https//multi-scattering.com/.In this study, we present a new way to predict the Zernike coefficients of optical system. We predict the Zernike coefficients through the function of image recognition in the neural network. It can reduce the mathematical operations commonly used in the interferometers and improve the measurement accuracy. We use the phase difference and the interference fringe as the input of the neural network to predict the coefficients respectively and compare the effects of the two models. In this study, python and optical simulation software are used to confirm the overall effect. As a result, all the Root-Mean-Square-Error (RMSE) are less than 0.09, which means that the interference fringes or the phase difference can be directly converted into coefficients. Not only can the calculation steps be reduced, but the overall efficiency can be improved and the calculation time reduced. For example, we could use it to check the performance of camera lenses.We provide a corrected figure of our previous publication [Opt. Express25, 18017 (2017)10.1364/OE.25.018017].Metasurface-based near perfect absorbers exhibit a wide range of potential applications in the fields of solar energy harvesting, thermal images and sensors due to their unique absorption regulation function. However, absorption characteristics of devices are locked by the device structure, leading to the limitation in real-time dynamic applications. In this work, we integrate the phase change material VO2 thin film into the metal-insulator-metal structured metasurface based absorber, and design a fully visible band switchable dynamically tunable absorber (DTA). By controlling the phase transition of VO2, the DTA can realize a novel switch function in the full band of visible light (400 ∼ 780 nm), with absorption contrast ranges from 42% to 60%. Furthermore, via accurate structural parameter control, the vivid cyan, magenta, and yellow pixels based on the VO2 DTA are designed and proposed in the real-time optical anti-counterfeiting, exhibiting outstanding characteristics of anti-glare interference and real-time encryption ability. The absorption spectrum and local electric field are simulated and analyzed to study the internal operation mechanism of DTA. The dynamic absorption adjustable function is attributed to the synergistic effect of insulator-metal transition of VO2 and Fabry-Pérot resonance of absorber.Coherent absorption, as the time-reversed counterpart to laser, has been widely proposed recently to flexibly modulate light-matter interactions in two-dimensional materials. However, the multiband coherent perfect absorption (CPA) in atomically thin materials still has been elusive. We exploit the multiband CPA in vertically stacked metal/dielectric/graphene heterostructures via ultraconfined acoustic plasmons which can reduce the photon wavelength by a factor of about 70 and thus enable multiple-order resonances on a graphene ribbon of finite width. compound 78c CD markers inhibitor Under the illumination of two counter-propagating coherent beams, the two-stage coupling scheme is used for exciting multispectral acoustic plasmon resonances on the heterostructure simultaneously, thereby contributing to the ultimate multiband CPA in the mid-infrared region. The strong dependence of the nearly linear dispersion of acoustic plasmons on the chemical potential in graphene and the separation between the metal and the graphene allows the tunability in spectral positions of absorption peaks. Intriguingly, the absorption of each resonant peak is continuously tuned by varying the relative amplitude of two counter-propagating beams, and even their phase difference, respectively. The maximum modulation depth of 4.46*105 is observed. The scattering matrix is employed to demonstrate the principle of CPA and the finite-difference time-domain (FDTD) simulations are used for elucidating the flexible tunability. More importantly, the multiband coherent absorber is robust to the incident angle, and thus undoubtedly benefits extensive applications on optoelectronic and engineering technology areas for modulators and optical switches.The response of the optical microfiber sensor has a big difference due to the slight change in fiber structure, which greatly reduces the reliability of microfiber sensors and limits its practical applications. To avoid the nonlinear influences of microfiber deformation and individual differences on sensing performance, a backpropagation neural network (BPNN) is proposed for concentration prediction based on biconical microfiber (BMF) sensors. Microfiber diameter, cone angle, and relative intensity are the key input parameters for detecting the concentration of chlorophyll-a (from ∼0.03 mg/g to ∼0.10 mg/g). Hundreds of relative intensity-concentration data pairs acquired from 32 BMF sensors are used for the network training. The prediction ability of the model is evaluated by the root-mean-square error (RMSE) and the fitness value (F). The prediction performance of BPNN is compared with the traditional linear-fitting line method. link2 After training, BPNN could adapt to the BMF sensors with different structural parameters and predict the nonlinear response caused by the small structural changes of microfiber. The concentration prediction given by BPNN is much closer to the actual measured value than the one obtained by the linear fitting curve (RMSE 1.84×10-3 mg/g vs. 4.6×10-3 mg/g). link3 The numbers of training data and hidden layers of the BPNN are discussed respectively. The prediction results indicate that the one-hidden-layer network trained by more training data provides the best performance (RMSE and fitness values are 1.63×10-3 mg/g and 97.91%, respectively) in our experiments. With the help of BPNN, the performance of the BMF sensor is acceptable to the geometric deformation and fabrication error of microfiber, which provides an opportunity for the practical application of sensors based on micro/nanofibers.