Near-field examination of perovskite-based superlenses and superlens-enhanced probe-object coupling

A planar slab of negative index material works as a superlens with sub-diffraction-limited imaging resolution, since propagating waves are focused and, moreover, evanescent waves are reconstructed in the image plane. Here, we demonstrate a superlens for electric evanescent fields with low losses using perovskites in the mid-infrared regime. The combination of near-field microscopy with a tunable free-electron laser allows us to address precisely the polariton modes, which are critical for super-resolution imaging. We spectrally study the lateral and vertical distributions of evanescent waves around the image plane of such a lens, and achieve imaging resolution of wavelength/14 at the superlensing wavelength. Interestingly, at certain distances between the probe and sample surface, we observe a maximum of these evanescent fields. Comparisons with numerical simulations indicate that this maximum originates from an enhanced coupling between probe and object, which might be applicable for multifunctional circuits, infrared spectroscopy, and thermal sensors.Comment: 20 pages, 6 figures, published as open access article in Nature Communications (see http://www.nature.com/ncomms/

Planetary radar studies

Progress made in studying the evolution of Venusian craters and the evolution of infrared and radar signatures of lunar crater interiors is reported. Comparison of radar images of craters on Venus and the Moon present evidence for a steady state Venus crater population. Successful observations at the Arecibo Observatory yielded good data on five nights when data for a mix of inner and limb areas were acquired. Lunar craters with radar bright ejects are discussed. An overview of infrared radar crater catalogs in the data base is included

Classifying GPR images using convolutional neural networks

This thesis focused on classifying GPR cylinders\u27 B-scans according to their depth, size, material, and the dielectric constant of the underlying medium using four different architectures of convolutional neural networks. Two CNNs were newly proposed for this study, while the other two were used by other authors. These CNNs were trained using a couple of adjusted training options including initial learning rate, learn rate drop factor, and learn rate drop period; which had a positive impact on a part of the used models, while the option maximum number of epochs worked good with all of the used models. Results show that the first newly proposed CNN showed a superior performance due to the use of a deep network with a large amount of small filters. Using this model, it was found that the best results were carried out when GPR B-scans were classified according to the cylinders\u27 materials

Assessing the Viability of Complex Electrical Impedance Tomography (EIT) with a Spatially Distributed Sensor Array for Imaging of River Bed Morphology: a Proof of Concept (Study)

This report was produced as part of a NERC funded ‘Connect A’ project to establish a new collaborative partnership between the University of Worcester (UW) and Q-par Angus Ltd. The project aim was to assess the potential of using complex Electrical Impedance Tomography (EIT) to image river bed morphology. An assessment of the viability of sensors inserted vertically into the channel margins to provide real-time or near real-time monitoring of bed morphology is reported. Funding has enabled UW to carry out a literature review of the use of EIT and existing methods used for river bed surveys, and outline the requirements of potential end-users. Q-par Angus has led technical developments and assessed the viability of EIT for this purpose. EIT is one of a suite of tomographic imaging techniques and has already been used as an imaging tool for medical analysis, industrial processing and geophysical site survey work. The method uses electrodes placed on the margins or boundary of the entity being imaged, and a current is applied to some and measured on the remaining ones. Tomographic reconstruction uses algorithms to estimate the distribution of conductivity within the object and produce an image of this distribution from impedance measurements. The advantages of the use of EIT lie with the inherent simplicity, low cost and portability of the hardware, the high speed of data acquisition for real-time or near real-time monitoring, robust sensors, and the object being monitored is done so in a non-invasive manner. The need for sophisticated image reconstruction algorithms, and providing images with adequate spatial resolution are key challenges. A literature review of the use of EIT suggests that to date, despite its many other applications, to the best of our knowledge only one study has utilised EIT for river survey work (Sambuelli et al 2002). The Sambuelli (2002) study supported the notion that EIT may provide an innovative way of describing river bed morphology in a cost effective way. However this study used an invasive sensor array, and therefore the potential for using EIT in a non-invasive way in a river environment is still to be tested. A review of existing methods to monitor river bed morphology indicates that a plethora of techniques have been applied by a range of disciplines including fluvial geomorphology, ecology and engineering. However, none provide non-invasive, low costs assessments in real-time or near real-time. Therefore, EIT has the potential to meet the requirements of end users that no existing technique can accomplish. Work led by Q-par Angus Ltd. has assessed the technical requirements of the proposed approach, including probe design and deployment, sensor array parameters, data acquisition, image reconstruction and test procedure. Consequently, the success of this collaboration, literature review, identification of the proposed approach and potential applications of this technique have encouraged the authors to seek further funding to test, develop and market this approach through the development of a new environmental sensor

Imaging of buried utilities by ultra wideband sensory systems

Third-party damage to the buried infrastructure like natural gas pipelines, water distribution pipelines and fiber optic cables are estimated at $10 billion annually across the US. Also, the needed investment in upgrading our water and wastewater infrastructure over the next 20 years is estimated by Environmental Protection Agency (EPA) at$400 billion, however, non-destructive condition assessment technologies capable of providing quantifiable data regarding the structural integrity of our buried assets in a cost-effective manner are lacking. Both of these areas were recently identified several U.S. federal agencies as \u27critical national need\u27. In this research ultra wideband (UWB) time-domain radar technology was adopted in the development of sensory systems for the imaging of buried utilities, with focus on two key applications. The first was the development of a sensory system for damage avoidance of buried pipes and conduits during excavations. A sensory system which can be accommodated within common excavator buckets was designed, fabricated and subjected to laboratory and full-scale testing. The sensor is located at the cutting edge (teeth), detecting the presence of buried utilities ahead of the cutting teeth. That information can be used to alert the operator in real-time, thus avoiding damage to the buried utility. The second application focused on a sensory system that is capable of detecting structural defects within the wall of buried structures as well as voids in the soil-envelope encasing the structure. This ultra wideband sensory system is designed to be mounted on the robotic transporter that travels within the pipeline while collecting data around the entire circumference. The proposed approach was validated via 3-D numerical simulation as well as full-scale experimental testing

Microwave Sensing and Imaging

In recent years, microwave sensing and imaging have acquired an ever-growing importance in several applicative fields, such as non-destructive evaluations in industry and civil engineering, subsurface prospection, security, and biomedical imaging. Indeed, microwave techniques allow, in principle, for information to be obtained directly regarding the physical parameters of the inspected targets (dielectric properties, shape, etc.) by using safe electromagnetic radiations and cost-effective systems. Consequently, a great deal of research activity has recently been devoted to the development of efficient/reliable measurement systems, which are effective data processing algorithms that can be used to solve the underlying electromagnetic inverse scattering problem, and efficient forward solvers to model electromagnetic interactions. Within this framework, this Special Issue aims to provide some insights into recent microwave sensing and imaging systems and techniques