Metamaterial Technologies (Canada)

In coastal regions and marginal bodies of water, the increase in partial pressure of carbon dioxide (pCO2) in many instances is greater than that of the open ocean due to terrestrial (river, estuarine, and wetland) influences, decreasing buffering capacity and/or increasing water temperatures. Coastal oceans receive freshwater from rivers and groundwater as well as terrestrial-derived organic matter, both of which have a direct influence on coastal carbonate chemistry. The objective of this research is to determine if coastal marshes in Georgia, USA, may be “hot-spots” for acidification due to enhanced inorganic carbon sources and if there is terrestrial influence on offshore acidification in the South Atlantic Bight (SAB). The results of this study show that dissolved inorganic carbon (DIC) and total alkalinity (TA) are elevated in the marshes compared to predictions from conservative mixing of the freshwater and oceanic end-members, with accompanying pH around 7.2 to 7.6 within the marshes and aragonite saturation states (ΩAr) <1. In the marshes, there is a strong relationship between the terrestrial/estuarine-derived organic and inorganic carbon and acidification. Comparisons of pH, TA, and DIC to terrestrial organic material markers, however, show that there is little influence of terrestrial-derived organic matter on shelf acidification during this period in 2014. In addition, ΩAr increases rapidly offshore, especially in drier months (July). River stream flow during 2014 was anomalously low compared to climatological means; therefore, offshore influences from terrestrial carbon could also be decreased. The SAB shelf may not be strongly influenced by terrestrial inputs to acidification during drier than normal periods; conversely, shelf waters that are well-buffered against acidification may not play a significant role in mitigating acidification within the Georgia marshes.

In this paper, a hardware advancement for a microwave multi-static system for breast cancer detection is presented. In particular, we propose a metasurface-enhanced antenna capable of enhancing relevant “weak” signals backscattered by a tumour-mimicking target inserted in a breast phantom. Furthermore, we simulate a radar-based approach in CST Microwave Studio and use our previously developed Huygens principle-based algorithm to produce images of the target. Our results indicate that the proposed metasurface-enhanced antenna can improve target localization and decrease image artefacts.

Over the last two decades, metamaterials (MMs) and metasurfaces (MTSs) have been used to fabricate innovative antenna designs, offering cost-effective solutions compared to conventional radiating systems. This paper investigates the feasibility of combining MM design concepts and imaging techniques to create innovative microwave imaging systems. In particular, we present an experimental study with the aim of enhancing microwave imaging for haemorrhagic stroke detection using a new MTS design. First, we show the improvement in performance for a stand-alone MTS-loaded antenna, by studying its operating characteristics in the near and far fields. Then, we assess the performance of the MTS on the reconstruction results from simulations and measurements on two tissue-mimicking gel-based brain phantoms with a cylindrical target representing the bleeding in haemorrhagic stroke. The brain phantom was immersed inside an imaging tank filled with 90% glycerol matching liquid. To perform the image reconstructions, we used both a Huygens based radar algorithm and a DBIM-TwIST tomography algorithm. Our simulation and measurement results indicate that the proposed MTS design improves target localization and decreases image artefacts for the tomographic algorithm and enables target’s detection through our radar technique, paving the way for a hybrid microwave imaging prototype with MTS enhanced antennas.

We present an experimental validation of the distorted Born iterative method with the two-step iterative shrinkage thresholding (DBIM-TwIST) algorithm for the problem of brain stroke detection and differentiation, using an anatomically accurate, multi-layer head phantom. To this end, we have developed a gelatine-based, anatomically complex head phantom which mimics various brain tissues and also includes a target mimicking hemorrhagic or ischemic stroke. We simulated the model and setup using CST Microwave Studio and then used our experimental imaging setup to collect numerical and measured data, respectively. We then used our DBIM-TwIST algorithm to reconstruct the dielectric properties of the imaging domain for both simulated and measured data. Results from our CST simulations showed that we are able to locate and reconstruct the permittivity of different stroke targets using an approximate initial guess. Our experimental results demonstrated the potential and challenges for successful detection and differentiation of the stroke targets.

We reported measurement results relating to non-invasive glucose sensing using a novel multiwavelength approach that combines radio frequency and near infrared signals in transmission through aqueous glucose-loaded solutions. Data were collected simultaneously in the 37–39 GHz and 900–1800 nm electromagnetic bands. We successfully detected changes in the glucose solutions with varying glucose concentrations between 80 and 5000 mg/dl. The measurements showed for the first time that, compared to single modality systems, greater accuracy on glucose level prediction can be achieved when combining transmission data from these distinct electromagnetic bands, boosted by machine learning algorithms.

Electromagnetic (EM) biomedical sensors in the mm-wave frequency range must detect small changes in signals in the presence of tissues, which are correlated to a pathological condition. These signals, however, can suffer from artifacts due to complex EM wave interactions such as diffraction and surface wave propagation, which are often overlooked in the design phase of these sensors. This paper studies the impact of these wave phenomena on the signals transmitted and received from a pair of antennas designed to sense glucose changes via changes in transmission through a sample. Numerical simulations and controlled experiments with glucose solutions demonstrate for the first time that unwanted signal contributions from mm surface waves along the tissue can dominate the received signals but can be reduced with the use of appropriately placed absorbers around the antenna sensors. As a result, the sensitivity of such a sensing system to glucose changes is increased. This finding can be very useful in the design and development of the glucose sensor under study, as well as for other EM-based diagnostic medical applications.