Chirality plays an essential role in life, providing unique functionalities to a wide range of biomolecules, chemicals, and drugs, which makes chiral sensing and analysis critically important. The wider application of chiral sensing continues to be constrained by the involved chiral signals being inherently weak. To remedy this, plasmonic and dielectric nanostructures have recently been shown to offer a viable route for enhancing weak circular dichroism (CD) effects, but most relevant studies have thus far been ad hoc, not guided by a rigorous analytical methodology. Here, we report the first analytical treatment of CD enhancement and extraction from a chiral biolayer placed on top of a nanostructured substrate. We derive closed-form expressions of the CD and its functional dependence on the background-chiroptical response, substrate thickness and chirality, as well as on the optical chirality and intensity enhancement provided by the structure. Our results provide key insights into the trade-offs that are to be accommodated in the design and conception of optimal nanophotonic structures for enhancing CD effects for chiral molecule detection. Based on our analysis, we also introduce a practical, dielectric platform for chiral sensing featuring large CD enhancements while exhibiting vanishing chiroptical background noise.

Detection and differentiation of enantiomers in small quantities are crucially important in many scientific fields, including biology, chemistry, and pharmacy. Chiral molecules manifest their handedness in their interaction with the chiral state of light (e.g., circularly polarized light), which is commonly leveraged in circular dichroism (CD) spectroscopy. However, compared to the linear refractive index molecular chirality is extremely weak, resulting in low detection efficiencies. Recently, it has been shown that these weak chiroptical signals can be enhanced by increasing the optical chirality of the electromagnetic fields interacting with chiral samples. Here, we show numerically and analytically that dielectric structures can provide an optimum chiral sensing platform by offering uniform superchiral near-fields. To illustrate this, we first study a simple dielectric dimer and show that circularly polarized light can induce parallel and out of phase electric and magnetic fields, which are spectrally and spatially overlapped, and therefore produce superchiral fields at the midpoint of the dimer. This behavior is in contrast to, for example, a plasmonic dimer, where the optical chirality is limited by the electric dipolar field, which is not completely out of phase with the incident magnetic field. With the insights gained from this analysis, next we develop an approach for overlapping electric and magnetic fields in a single particle, based on Kerker effect. In particular, we introduce a Kerker-inspired metasurface consisting of holey dielectric disks, which offers uniform and accessible superchiral near-fields with CD signal enhancements of nearly 24 times.

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Automatic extraction of geospatial features has been the subject of extensive research in the past three decades. Here, an approach based on fuzzy logic and mathematical morphology is proposed, to extract main road centrelines from pan‐sharpened IKONOS images. In the IKONOS images, a standard deviation of 10 grey levels has been measured for the road classes. In the proposed fuzzy logic system, just one arbitrary pixel (up to a maximum of 3 pixels) provides an adequate initial value. Road identification requires neither the numbers of the classes nor the corresponding mean values; then, using advanced morphological concepts, the road centreline is extracted. The method is applied to pan‐sharpened IKONOS images of urban, suburban and rural areas around the Pyramids in Egypt, and Rasht City and Kish Island in Iran. The extracted road centrelines have an average error of 0·504 pixel and root mean square error of 0·036 pixel. The method is more accurate at road intersections and on curves than on straight sections of road. The extracted road is then used as a direct input to a geographical information system (GIS).