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As a result of the risks that waterborne bacteria bring to the human body, identifying them in drinking water has become a global concern. In this article, a highly sensitive surface plasmon resonance (SPR) biosensor consisting of prism, Ag, graphene, affinity layer and sensing medium is proposed for rapid detection of the waterborne bacteria. Four SPR‐based sensors are first studied with the structures prism/Ag/sensing medium, prism/Ag/affinity layer/sensing medium, prism/Ag/graphene/sensing medium, and prism/Ag/graphene/affinity layer/sensing medium. The latter structure is found to have the highest sensitivity so it is considered for further investigations. Four different commonly used prisms are then demonstrated which are N‐FK51A, 2S2G, SF10 and BK7. The structure with the prism N‐FK51A is found to correspond to the highest sensitivity so it is considered for further investigations. The structure parameters are then optimized. The proposed SPR sensor can achieve high sensitivity of about 221.63 °/RIU for Escherichia coli and 178.12 °/RIU for Vibrio cholera bacteria with an average value of 199.87 °/RIU. We believe that the proposed structure will open a new window in the field of microorganism detections.

Today, detecting processes of waterborne bacteria in drinking water is a global challenge because these bacteria can lead to dangerous diseases to the human body. In this paper, we have developed a new sensor for the detection of waterborne bacteria based on a one-dimensional (1D) defective binary photonic crystal. The defect layer is taken as a water sample located in the middle of the photonic crystal structure. A resonant peak is then created within the photonic bandgap. The sensing mechanism of the proposed detector is based on the refractive index difference between pure water and waterborne bacteria samples. This index change leads to a shift in the resonant peak position in the transmission spectrum. The effects of many parameters, such as incident angle, defect layer thickness, thicknesses of periodic layers and the number of periods on the sensitivity are investigated. At the optimum conditions, the proposed sensor exhibits a sensitivity of 3639.53 nm/RIU which is ultra-high compared with recently published biosensor papers. The proposed design could distinguish between the different types of waterborne bacteria although the minute difference between their refractive indices. In addition to that, it has a simple design so that it can be easily fabricated.

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Diabetes is rapidly becoming a serious and life-threatening disease. It affects 415 million persons worldwide and is a leading cause of death among those aged 20 to 59. It is essential to develop a rapid-detection, accurate and sensitive glucose detector. In this work, a biosensor based on surface plasmon resonance (SPR) is proposed theoretically for the detection of glucose concentration. To realize higher sensitivity, the proposed SPR sensor contains a barium titanate layer placed between the metal (Ag) thin film and the molybdenum disulphide layer. Barium titanate material shows notable dielectric properties, such as low loss and a high index of refraction. It is expected to give a large shift in the resonance angle caused by a tiny change in the analyte refractive index. By optimizing the thicknesses of barium titanate and Ag and the number of molybdenum disulphide layers, the proposed biosensor can exhibit an ultra-high sensitivity of 307.36 deg/RIU. The extremely high sensitivity makes the proposed SPR-based biosensor encouraging to be used in many fields of biosensing.

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The aim and scope of the paper is to simulate the signal propagation parameters estimation through designed multi-layer fibre with higher dominant modes by using OptiFibre simulation software. The multi-layer fibre profile has a length of 1000 m is designed and clarified with six layers. RI difference profile variations are clarified with radial distance variations. Modal/group index, group delay, dispersion, mode field diameter and total fibre losses are demonstrated with the fibre wavelength variations. All the dominant mode field distribution for multi-layer fibre are simulated and demonstrated. The other modes for designed multi-layer fibre with the theoretical fibre cutoff values for the different modes based the designed multi-layer fibre are analyzed and clarified clearly in details.

Today, cancer disease is a significant reason for the death of many patients. In many cases, cancer is diagnosed after metastasized during the body. Thus, the earlier detection gives a better opportunity for treatment and cure. A simple 1-D binary photonic crystal with a defect layer is proposed with the structure (Si/ SiO2) N /Defect/(Si/ SiO2) N as a detector for cancerous cells. The defect layer is taken here as the patient's blood sample. Compared with the normal blood sample, the cancerous samples lead to a considerable change in the refractive index. This index variation leads to a shift in the resonant mode position which can be used to diagnose cancer cells. The transfer matrix method is employed to analyze the structure. The number of periods, defect layer thickness and incident angle are investigated to maximize the sensitivity. The sensitivity is calculated at optimized conditions and found as 2400.08 nm/RIU. This sensitivity is extremely high when compared to the most recent biosensors. All the sensor performance parameters are calculated and discussed.