Refractive index (RI) measurements find extensive use in biochemical sensing field. However, currently available RI sensors exhibit excessive temperature crosstalk and have low sensitivity in the low RI range. To solve this, a high-sensitivity and temperature-insensitive refractometer based on a tapered no-core-hollow-core fiber (TNHF) structure is proposed for low-range RI measurement. The TNHF comprises two Mach-Zehnder interferometers that are introduced within the tapered no-core fiber and hollow-core fiber, thereby establishing a composite interference. The results of an experimental evaluation demonstrate that maximum sensitivities of 482.74 nm/RIU within an RI range of 1.335~1.3462 can be achieved, which is greater than that achieved using a traditional modal interferometer structure. Significantly, the refractometer exhibits ultra-low temperature sensitivities of 0.062 dB/°C and 6.5 pm/°C, which can alleviate the temperature crosstalk. The refractometer can be realistically applied in many fields requiring high precision RI measurement due to its advantages of low cost, ease of manufacture, high sensitivity, and temperature insensitivity.
The spectral functions are studied in conjunction with the dyadic Green's functions for various media. The dyadic Green's functions are found using the eigenfunction expansion method for homogeneous, inhomogeneous, periodic, lossless, lossy, and anisotropic media, guided by the Bloch-Floquet theorem. For the lossless media cases, the spectral functions can be directly related to the photon local density of states, and hence, to the electromagnetic energy density. For the lossy case, the spectral function can be related to the field correlation function. Because of these properties, one can derive properties for field correlations and the Langevin-source correlations without resorting to the fluctuation dissipation theorem. The results are corroborated by the fluctuation dissipation theorem. An expression for the local density of states for lossy, inhomogeneous, and dispersive media has also been suggested.
Datacenters become an important part of technical infrastructure. The Datacom traffic grows exponentially to satisfy the demands in IT services, storage, communications, and networking to the growing number of networked devices and users. High bandwidth and energy efficient optical interconnects are critical to improve overall productivity and efficiency in data centers. Mega-data centers are expected to address the power consumption and the cost in which optical interconnects contribute quite a large part. Silicon photonics is a promising platform to offer savings in power and potential increase in bandwidth for Datacom. Several modulation techniques are developed in silicon photonics to reduce the optical mode volume or enhance the light matter effectto further improve the modulation efficiency. Many other materials such as III-V and LiNbO3 are integrated on silicon photonics to maximize the optical link performance. This paper reviews several modulation techniques for Datacom, from VCSEL direct modulation to silicon photonics modulators then to hybrid silicon modulators.
Layered molybdenum disulphide (MoS2) can efficiently emit photoluminescence (PL) excited by visible light. However, one-photon PL of MoS2 for bioimaging purposes suffers from strong autofluorescence and ion-induced PL quenching. Herein, we report single layer chitosan decorated MoS2 nanosheets as nonbleaching and nonblinking optical nanoprobes under near infrared femtosecond laser excitation and their applications for two photon luminescence (TPL) and second harmonic generation (SHG) bioimaging. The TPL can resist the ion-induced quenching by the cellular membrane. The proposed TPL and SHG of singlelayer MoS2 show great potential for real-time, deep and multiphoton bioimaging.
An inverse method for parameters estimation of dielectric cylinders (dielectric properties, location, and radius) from amplitude-only microwave information is presented. To this end two different Artificial Neural Networks (ANN) topologies were compared; a Multilayer Perceptron (MLP) and a Convolutional Neural Network (CNN). Several two-dimensional (2D) simulations, with different sizes and locations of homogeneous dielectric cylinders employing the Finite Differences Time Domain (FDTD) method, were performed to generate training, validation, and test sets for both ANN models. The prediction errors were lower for the CNN in high Signal-to-Noise Ratio (SNR) scenarios, although the MLP was more robust in low SNR situations. The CNN model performance was also tested for 2D simulations of dielectrically homogeneous and heterogeneous cylinders placed in acrylic holders showing potential experimental applications. Moreover, the CNN was also tested for a three-dimensional model simulated as realistic as possible, showing good results in predicting all parameters directly from the S-parameters.
This study investigates the sensitivity of L-band (1.41 GHz) polarimetric brightness temperature signatures to oriented permittivity patterns, which can occur for example in the case of row and interrow soil moisture differences in agricultural fields. A field experiment and model simulations are conducted to verify the effects of such patterns on all four Stokes parameters. We find that for an artificial target resembling idealized model conditions, permittivity patterns lead to systematic brightness temperature modulations in dependency of the azimuthal look angle. For the specific field setup, modulations reach amplitudes of ~4 K and mostly affect h-polarized brightness temperatures as well as the first, second and third Stokes parameters. Simulations of soil moisture patterns under idealized model conditions indicate even higher amplitudes (up to 60 K for extreme cases). However, the effects occur only for permittivity layer widths of up to 8 cm (given the observing wavelength of 21 cm), which is lower than the row and interrow widths typically observed in agricultural settings. For this reason, and due to the idealized model geometry investigated here, future studies are needed to transfer the findings of this study to potential applications such as the sensing of oriented soil moisture patterns. Particular interest might lie in radiometry and reflectometry in lower frequency ranges such as P-band, where according to the threshold established here (8/21 wavelengths), permittivity layer widths of up to ~45 cm could be observed.
Accurate measurement of atmospheric particulate matter (PM) absorption coefficient is highly required for study of earth climate change and for monitoring of air quality. In addition, multi-wavelength measurements of PM absorption can provide information on the PM chemical composition (black carbon or brown carbon). A multi-wavelengths photoacoustic (MW-PA) spectrophone operating at 444, 532 and 660 nm was developed and deployed for filter-free characterization of wavelength-dependent optical properties of PM mass absorption coefficient (MAC) and absorption Ångström coefficient (AAC). It is worth noting that to date no any AAC of volcanic ashes determined by filter-free measurement have been reported. The developed MW-PA spectrophone was deployed to an intensive field campaign measurement of environmental PM in Grenoble (France). Side-by-side inter-comparison measurements of ambient PM showed a good correlation between the developed MW-PA spectrophone and a reference instrument aethalometer (Magee scientific, AE33).
In this paper, the Compressive Sampling Matching Pursuit Algorithm (CoSaMP) is applied to microwave reconstruction of a 2-dimensional non-sparse object. First, an adaptive discretization method, DistMesh method, is applied to discretize the image domain based on the region of interest. The dual-mesh method is able to provide denser and smaller discretized cells in more important areas of the object and larger cells in other areas, thereby providing more details in the interest domain and keeping the computational burden at a reasonable level. Another benefit of using the dual-mesh method is that it automatically generates size functions and adapts to the curvature and the feature size of the geometry. In addition, the size of each cell changes gradually. Next, the inverse scattering problem is solved in frame of Distorted Born Iterative Method (DBIM). During each iteration of DBIM, the near field scattering problem is modeled as a set of linear equations. Furthermore, a compressive sensing (CS) method called the Compressive Sampling Matching Pursuit Algorithm is applied to solve the nonlinear inverse problem. During this process, two innovative steps are applied. First, for the reconstruction of the non-sparse object, the signal input to our algorithm is processed via a wavelet transformation to obtain sparsity. Second, as the dual-mesh method discretizes more important cells in smaller sizes, these cells have high potential to be filtered by the threshold of CoSaMP. As a result, a regularization matrix is introduced to reduce the effect of size. Finally, we present numerical experiment results based on our dual-mesh method combined with the regularized CoSaMP algorithm.
In this paper, the reconstruction problem of inaccessible objects buried into a three-part space with locally rough interfaces is solved by Distorted Born Iterative Method (DBIM). DBIM requires the calculation of the background electric field and Green's function in every iteration step via the solution of the direct scattering problem. Here, they are calculated numerically by using the buried object approach (BOA) which is very useful in the solutions of the problems including stratified media with locally rough interfaces. Various numerical applications have been performed to demonstrate the applicability and efficiency of the method. The method was found to be very successful in reconstructing moderate contrast objects when they were buried in the middle space. In this case, the method works effectively even if the buried objects and interface roughnesses have complex geometric structures. Moreover, the multiplicity of buried objects has no negative effect on the reconstruction results. Nevertheless, the results of reconstruction deteriorate when objects are buried in the bottom space. However, the accuracies of them are still on an acceptable level in this situation.
Recently we derived generalized sheet transition conditions (GSTCs) for electromagnetic fields at the surface of a metascreen (a metasurface with a ``fishnet'' structure, i.e., a periodic array of arbitrary spaced apertures in a relatively impenetrable surface). The parameters in these GSTCs are interpreted as effective surface susceptibilities and surface porosities, which themselves are related to the geometry of the apertures that constitute the metascreen. In this paper, we use these GSTCs to derive the plane-wave reflection (R) and transmission (T) coefficients of a symmetric metascreen, expressed in terms of these surface parameters. From these equations, we develop a retrieval approach for determining the uniquely defined effective surface susceptibilities and surface porosities that characterize the metascreen from measured or simulated data for the R and T coefficients. We present the retrieved surface parameters for metascreens composed of five different types of apertures (circular holes, square holes, crosses, slots, and a square aperture filled with a high-contrast dielectric). The last example exhibits interesting resonances at frequencies where no resonances exist when the aperture is not filled, which opens up the possibility of designing metasurfaces with unique filtering properties. The retrieved surface parameters are validated by comparing them to other approaches.