Optical biosensors are highly sensitive devices for detection and analysis of bio-analytes that combines biological components with a physicochemical detector. Biosensors have vast applications in biomedical research, environmental monitoring, healthcare, and pharmaceuticals. In this paper we have demonstrated a 2-dimensional photonic crystal based biosensor with line defect which can detect different blood components. Simulation and analysis has been done for Biotin-Streptavidin, Bovine Serum Albumin, Cytop (polymer), Ethanol, Glucose solution (40gm/100ml), Hemoglobin, Blood plasma, Polyacrylamide, Sylgard184, Urethane Dimethacrylate, Water and peak has been observed. Finite Difference Time Domain (FDTD) method has been used for the analysis. MEEP (MIT Electromagnetic Equation Propagation) and MPB (MIT Photonic Bands) simulation tools have been used for modeling and designing of photonic crystal. It has been observed from the band structure that for little change in refractive index (RI) there will be a moderate shift in the frequency and hence it acts as a sensor. This indicates that it is highly sensitive for the change in refractive index.

The world is facing an unprecedented problem in safeguarding 0.4 % of potable water, which is gradually depleting day-by-day. From a literature survey it has been observed that the refractive index (RI) of water changes with a change in salinity or total dissolved solids (TDS). In this paper we have proposed an automatic system that can be used for real-time evaluation of salinity or TDS in drinking water. A photonic crystal (PhC) based ring resonator sensor has been designed and simulated using the MEEP (MIT Electromagnetic Equation Propagation) tool and the finite difference time domain (FDTD) algorithm. The modelled and designed sensor is highly sensitive to the changes in the RI of a water sample. This work includes a real-time-based natural sequence follower, which is a machine learning algorithm of the naive Bayesian type, a sequence of statistical algorithms implemented in MATLAB with reference to training data to analyse the sample water. Further interfacing has been done using the Raspberry Pi device to provide an easy display to show the result of water analysis. The main advantage of the designed sensor with an interface is to check whether the salinity or TDS in drinking water is less than 1000 ppm or not. If it is greater than or equal to 2000 ppm, the display shows “High Salinity/TDS Observed”, and if ppm are less than or equal to 1000 ppm, then the display shows “Low salinity/TDS Observed”. The proposed sensor is highly sensitive and it can detect changes in TDS level because of the influence of any dissolved substance in water.

Enediynes continue to fascinate scientists working in various domains because of their structural complexity and fascinating biological mode of action. They represent a masterpiece of natures ingenuity. Besides the warhead which is the enediyne moiety, these molecules are equipped with a locking device, a delivery system and a chemical trigger for activation. Upon triggering, the molecules become active and undergo a thermal rearrangement that was disclosed in the early 70 by Masamune and Bergman and commonly known as Bergman cyclization. The reaction is believed to precede through a diradical benzenoid species (a p-benzyne). This review describes the various strategies employed for the synthesis of highly strained enediynes and dienediynes, both naturally occurring and the designed ones.

Integrated Photonics is an emerging innovative approach which has opened new ways to access to new conditions and measurement possibilities. The Photonic sensor technology can be explored to develop miniaturized, highly integrated, high performing, photonic sensors for underwater environment. Photonic crystal is periodic structure which allows engineering of light. The light propagation in photonic crystal is influenced by dielectric constant of the material. In this paper, we propose a design of a 2-D photonic crystal based-sensor with line defect which can detect and quantify the constituents in water. The sensor will detect the harmful chemicals like arsenic, lead, mercury and others. Analytical work has been done using Finite Difference Time Domain (FDTD) and with help of simulation tools MEEP and MPB.