We propose a quarter-wave plate based on nanoslits and analyze it using a semianalytical theory and simulations. The device comprises two nanoslits arranged perpendicular to one another where the phases of the fields transmitted by the nanoslits differ by $\lambda /4$. In this way, the polarization state of the incident light can be changed from linear to circular or vice versa. The plasmonic nanoslit wave plate is thin and has a subwavelength lateral extent. We show that the predictions for the phase shift obtained from a semianalytical model are in very good agreement with simulations by the finite difference time domain method.

In this paper, machine learning models for an effective estimation of soil moisture content using a microwave short-range and wideband radar sensor are proposed. The soil moisture is measured as the volumetric water content using a short-range off-the-shelf radar sensor operating at 3–10 GHz. The radar captures the reflected signals that are post processed to determine the soil moisture which is mapped to the input features extracted from the reflected signals for the training of the machine learning models. In addition, the results are compared and analyzed with a contact-based Vernier soil sensor. Different machine learning models trained using neural network, support vector machine, linear regression and k-nearest neighbor are evaluated and presented in this work. The efficiency of the model is computed using root mean square error, co-efficient of determination and mean absolute error. The RMSE and MAE values of KNN, SVM and Linear Regression are 11.51 and 9.27, 15.20 and 12.74, 3.94 and 3.54, respectively. It is observed that the neural network gives the best results with an R2 value of 0.9894. This research work has been carried out with an intention to develop cost-effective solutions for common users such as agriculturists to monitor the soil moisture conditions with improved accuracy.

In this paper, symmetric and asymmetric tapering on the arms of the gammadion nanostructure is proposed to enhance both local field distribution and extinction difference (ED). The asymmetric tapered gammadion with tapering fraction (TF) of 0.67 is seen to have the largest ED and spatial local field distribution, producing a large wavelength shift of more than 50 percent as compared to the untapered gammadion nanostructures when immersed in a solution of actin molecules and filaments. The optical chirality, ζ shows that the larger local field amplitudes produced by the asymmetric designs increases the rate of chiral molecules excitation. This enhanced field is strongly rotating and highly sensitive to single molecules and larger filaments. Here, we show that the ED, optical chirality, sensitivity and rate of chiral molecules excitation can be improved by incorporating asymmetric designs into chiral gammadion nanostructures through tapering.

In this letter, the extraction efficiency of light energy from an elliptically shaped microcavity laser is enhanced with external magnetic field. The magnetic field causes electrons to accumulate on the minor arc edge of the elliptical microcavity due to Lorentz force. As a result, the field amplitude at the minor arc edge is higher, and this improves light energy tunneling mechanism from the edge. The extraction efficiency from the microcavity increases by more than 30% after the application of magnetic field. Alternating the direction of the magnetic field allows the elliptical microcavity to function as a switching device.