Mount Zion College of Engineering and Technology

Photonic sensing technology is a new and accurate measurement technology for bio-sensing applications. In this paper, a two-dimensional photonic crystal ring resonator based sensor is proposed and designed to detect the glucose concentration in urine over the range of 0 gm/dl-15 gm/dl. The proposed sensor is consisted of two inverted “L” waveguides and a ring resonator. If the glucose concentration in urine is varied, the refractive index of the urine is varied, which in turn the output response of sensor will be varied. By having the aforementioned principle, the glucose concentration in urine, glucose concentration in blood, albumin, urea, and bilirubin concentration in urine are predicted. The size of the proposed sensor is about 11.4 µm×11.4 µm, and the sensor can predict the result very accurately without any delay, hence, this attempt could be implemented for medical applications.

In this paper, a photonic crystal ring resonator based bio sensor is designed to sense different blood constituents in blood in the wavelength range of 1530 nm-1615 nm for biomedical applications. The blood constituents such as hemoglobin white blood cell, red blood cell, blood sugar, blood urea, albumin, serum bilirubin direct, and ammonia are sensed for the corresponding transmission output power, Q factor, and refractive index changes. As the blood constituent has unique refractive index, the resonant wavelength and output power are varied from one to another, which are used to identify the blood constituents.

In this paper, a two-dimensional photonic crystal (2DPC) based pressure sensor is proposed and designed, and the sensing characteristics such as the sensitivity and dynamic range are analyzed over the range of pressure from 0 GPa to 7 GPa. The sensor is based on 2DPC with the square array of silicon rods surrounded by air. The sensor consists of two photonic crystal quasi waveguides and L3 defect. The L3 defect is placed in between two waveguides and is formed by modifying the radius of three Si rods. It is noticed that through simulation, the resonant wavelength of the sensor is shifted linearly towards the higher wavelength region while increasing the applied pressure level. The achieved sensitivity and dynamic range of the sensor is 2 nm/GPa and 7 Gpa, respectively.

This paper presents a system for automated, non-contact, and flexible prediction of surface roughness of end-milled parts through a machine vision system which is integrated with an artificial neural network (ANN). The images of milled surface grabbed by the machine vision system could be extracted using the algorithm developed in this work, in the spatial frequency domain using a two-dimensional Fourier transform to get the features of image texture (major peak frequency F 1, principal component magnitude squared value F 2, and the average gray level G a). Since F1 is the distance between the major peak and the origin, it is a robust measure to overcome the effect of lighting of the environment. The periodically occurring features such as feed marks and tool marks present in the gray-level image can be easily observed from the principal component magnitude squared value F 2. The experimental machining variables speed S, feedrate F, depth of cut D, and the response extracted image variables F 1, F 2, and G a could be used as input data, and the response surface roughness R a measured by Surfcorder SE-1100 (traditional stylus method) could be used as output data of an ANN ability to construct the relationships between input and output variables. The ANN was trained using the back-propagation algorithm developed in this work due to its superior strength in pattern recognition and reasonable speed. Using the trained ANN, the experimental result had shown that the surface roughness of milled parts predicted by machine vision system over a wide range of machining conditions could be got with a reasonable accuracy compared with those measured by traditional stylus method. Compared with the stylus method, the constructed machine vision system is a useful method for prediction of the surface roughness faster, with a lower price, and lower environment noise in manufacturing process. Experimental results have shown that the proposed machine vision system can be implemented for automated prediction of surface roughness with accuracy of 97.53%. The results are encouraging that machine vision system can be extended to many real-time industrial prediction applications.

3D printing, also called additive manufacturing (AM), is a method of creating 3D solid parts from a digital document. By utilizing additive routes, the fabrication of 3D‐printed objects can be made. These layers can be viewed as a gently cut level cross‐area of the manifest object. 3D printing is somewhat in obstruction to subtractive manufacture, which is expelling/discharging out a touch of metal or plastic for the occurrence of a milling machine. 3D printing authorizes creating multifarious profiles employing fewer materials than conventional fabrication systems. This review article provides the general idea of 3D printing production techniques, materials used, and applications in the aircraft and automobile industry and biomedical fields.

In the present paper, we study the transmission of the two-dimensional photonic crystal (PC) superellipse ring resonator. The fast growing applications of optomechanical systems lead to strong demands in new sensing mechanism in order to design the sensing elements to nanometer scale. The photonic crystal based resonator has been investigated as promising solutions because the band gap structure and resonator characteristics are extremely sensitive to the deformation and position shift of rod / cavity in PC resonators. This structure opens a single channel filter. The study is extended for tuning of channel filter’s wavelength with a temperature of this structure. The transmission of the channel filter shows a red shift with temperature linearly. This wavelength shift of the channel filter is used for the sensor application. The sensitivity for the proposed structure is found to be 65.3 pm/°C. The outstanding sensing capability renders PC resonators as a promising optomechanical sensing element to be integrated into various transducers for temperature sensing applications.

In this paper, the metamaterial based rectangular microstrip patch antenna is proposed and designed for THz applications. The circular split ring resonator is implemented as metamaterial. By incorporating metamaterial in the conventional microstrip patch antenna, the size is reduced and the performance of antenna is improved. The proposed antenna has the dimensions of 180 × 212 ×10 μm3 which is designed on Quartz substrate which is fed by microstrip line feed technique. Additionally, the performance of the metamaterial antenna is analyzed by varying unit cell gap size and thickness. The antenna resonates at 1.02 THz which gives the return loss of −65 dB. Thus, the proposed antenna can be utilized in THz region.

Recent years, the design of photonic crystal (PC) based optical devices is receiving keen interest in research and scientific community. In this paper, two dimensional (2D) PC based eight channel demultiplexer is proposed and designed and the functional characteristics of demultiplexer namely resonant wavelength, transmission efficiency, quality factor, spectral width, channel spacing and crosstalk are investigated. The demultiplexer is designed to drop the wavelength centred at 1537.6 nm, 1538.5 nm, 1539.4 nm, 1540.4 nm, 1541.2 nm, 1541.9 nm, 1542.6 nm and 1543.1 nm. The proposed demultiplexer is primarily composed of bus waveguide, drop waveguide and quasi square ring resonator. The quasi square ring resonator and square ring micro cavity (inner rods) are playing a vital role for a desired channel selection. The operating range of the devices is identified through a photonic band gap (PBG) which is obtained using a plane wave expansion (PWE) method. The functional characteristics of the proposed demultiplexer are attained using a 2D finite difference time domain (FDTD) method. The proposed device offers low crosstalk and high transmission efficiency with ultra-compact size, hence, it is highly desirable for DWDM applications.

The add drop filter (ADF) is one of the most significant devices for coarse wavelength division multiplexing (CWDM) systems to add and/ or drop a required channel individually from multiplexed output channels without disturbing other channels. The important parameters of the ADF are coupling efficiency, dropping efficiency, passband width and Q factor. Photonic crystal (PC)-based optical devices have attracted great interest due to their compactness, speed of operation, long life period, suitability for photonic integrated circuits, and future optical networks. Here, an extensive overview of a photonic crystal ring resonator (PCRR)-based ADF using a different shape of ring resonator is presented, and its corresponding functional parameters are discussed. Finally, the designed circular PCRR-based ADF for an ITU-T G 694.2 CWDM system is presented. Approximately 100% of coupling efficiency and dropping efficiency, 114.69 of Q factor, and 13 nm of passband width is obtained through simulation, which outperforms the reported one.

The interference method is used to achieve all-optical logic gate operations. This has been realized with a single design of photonic crystal ring resonator at different wavelengths rather than designing separate for all the logic gates. Such a single design can be used to perform all optical operations as AND, OR, and XOR logic gates at different wavelengths. Further operating wavelength, contrast ratio (CR), response time (RT), and bit rate have been analyzed for all three logic gates. The highest CR is obtained as about 22.06 dB with fast RT about 0.14 ps and high bit rate of 7.14 Tb / s for proposed XOR logic gate in comparison to all the other logic gates with single-design structure, which may lead us to construct on-chip logic circuits.

Particle Reinforced Metal Matrix Composites are generally utilized for various mechanical applications. The main objective of this study is on obtaining uniform particle distribution in metal matrix composites using the stir casting method. The significant part of this work is the experimental investigation of the stir casting technique in a crucible and the effect of stir casting parameter on uniform distribution of particles. The main challenge facing this project is the enhancement of the distribution of particles in molten metal. Silicon Carbide (SiC) and Aluminum alloy (Al-8011) have been proposed as reinforcement and matrix materials respectively. The effect of various parameters such us holding time, blade angle, impeller position and volume concentration for two different viscosity levels (1.24mPa-s and 1.04mPa-s) have been investigated. Composite microstructure has been characterized using Optical Microscope and Scanning Electron Microscope (SEM) in order to find the particle distribution in the composite. The mechanical behavior of the MMC has been assessed based on optimized stir casting parameter for uniform particle distribution.

Early diagnosis of pandemic diseases such as COVID-19 can prove beneficial in dealing with difficult situations and helping radiologists and other experts manage staffing more effectively. The application of deep learning techniques for genetics, microscopy, and drug discovery has created a global impact. It can enhance and speed up the process of medical research and development of vaccines, which is required for pandemics such as COVID-19. However, current drugs such as remdesivir and clinical trials of other chemical compounds have not shown many impressive results. Therefore, it can take more time to provide effective treatment or drugs. In this paper, a deep learning approach based on logistic regression, SVM, Random Forest, and QSAR modeling is suggested. QSAR modeling is done to find the drug targets with protein interaction along with the calculation of binding affinities. Then deep learning models were used for training the molecular descriptor dataset for the robust discovery of drugs and feature extraction for combating COVID-19. Results have shown more significant binding affinities (greater than -18) for many molecules that can be used to block the multiplication of SARS-CoV-2, responsible for COVID-19.

Vanadates of transition metal found its potential applications in the fields of lithium ion batteries, gas sensors, photo catalysts, solar cells and so on. Among the metal vanadates, Iron vanadate is vital as an organic pollutant remedying, gas sensor material, and selective catalytic reduction material. This current research focuses on synthesizing iron vanadate nanoparticles by wet chemical synthesis with controlled pH using ammonia solution. The nanostructured FeVO4 particle were characterized structurally with the powder XRD studies. Strong crystal planes were formed at Miller indices (111), (0-12), and (-220) which is confirmed from the intensity of the diffraction peaks. FT- IR and micro Raman studies was taken to identify the molecular vibrations present in the material and it shows that the sharpest apex at 508 cm–1 obtained is attributed to the stretching oscillations of Fe–O and V–O–V modes.The Raman spectrum confirmed the separation of Fe−O, V−O, and different stretching fashions of V− O−Fe.The V–O stretching mode increases the intense bands showing the very high strongest peak of FeVO4 because of electro negativity of iron the metal. The morphology of iron vanadate was confirmed with SEM analysis showing that particles are much isolated and cubical with few polyhedron structures. The electrochemical response of FeVO4 evaluated the specific capacitance at 10 mV/s as 402 Fg-1.Energy density values were calculated as 16.08 Whkg-1, 13.08 Whkg-1, 10.2 Whkg-1, 8.76 Whkg-1, 7.64 Whkg-1 and 6.92 Whkg-1 from the cyclic voltammetry profile at the slow rates varying from 10 -100 mV/s.The magnetic properties were analyzed by measuring the magnetic susceptibility and magnetization using a VSM magnetometer and the results evident that the material exhibits the paramagnetic behavior.

In this attempt, Two Dimensional Photonic Crystal (2DPC) Quasi Square Ring Resonator (QSRR) based four channel demultiplexer is proposed and designed for Wavelength Division Multiplexing systems. The performance parameters of the demultiplexer such as transmission efficiency, passband width, line spacing, Q factor and crosstalk are investigated. The proposed demultiplexer is composed of bus waveguide, drop waveguide and QSRR. In the proposed demultiplexer, the output ports are arranged separately in odd and even number, where an odd number of ports are located on the right side and even number of ports are located on the left side of the bus waveguide that are used to reduce the channel interference or crosstalk. Further, the refractive index of rods around the center rod is increased linearly one to another in order to improve the signal quality. The resonant wavelengths of the proposed demultiplexer are of 1521.1 nm, 1522.0 nm, 1523.2 nm and 1524.3 nm, respectively. The footprint of the device is of 180.96 μm2. Then, a four channel point to point network is designed and the proposed four channel demultiplexer is implemented by replacing a conventional demultiplexer. Finally, functional parameters of the network, namely, BER, receiver sensitivity and Q factor are estimated by varying the link distance. This attempt could create new dimensions of research in the domain of photonic networks.

We study the two-dimensional photonic crystal (PC) square lattice structure to design a channel drop filter. The channel drop filter (CDF) is designed using a PC ring resonator structure because of its better response. The variation in the shape of scatterer rods causes the shift in resonant wavelength and also shows an improvement in quality factor as well as dropping efficiency. The dropping efficiency is improved from 92.7% to 99.5% for a particular wavelength at 1531 nm, which is especially used in telecommunication. The designed CDF structure is useful for coarse wavelength division multiplexer. The size of the device is very small, so these devices can play an important role in optical communication networks and photonic integrated circuits.

The basic idea of this project is to create an electronic voting machine that will help to eradicate defrauding of the manual voting systems and prior versions of electronic voting. The thesis looks into and proposes a system that includes multiple layers of verifications to ensure the reliability of the device. With the inclusion of biometric fingerprint sensor, each voter is entered into the system only after being recognized and checked with the given database of enlisted voters. Once the corresponding fingerprint is matched with the information provided, the voter will be allowed to proceed for choosing their preferred candidate from the panel of buttons. The final vote is then displayed onto a LCD for the satisfaction of voters. The proposed project displays transparency and also carries the feature of being autonomous during the course of operation.

A BN-TiB2-TiN composite was produced via reactive sintering of the hexagonal BN (hBN) with 20 wt% Ti. Spark plasma sintering (SPS) was used as the fabrication method and the sample was characterized by X-ray diffractometry, energy-dispersive X-ray spectroscopy, and scanning electron microscopy. According to the results, the Ti was utterly consumed during the SPS, led to the in-situ TiB2 and TiN0.9 formations. Additionally, the microstructural study revealed the nucleation and growth of new hBN platelets from the initial fine hBN particles. Anyway, the final composite reached a relative density of 95%, because of the remaining free spaces between the hBN platelets. It was found that some nitrogen and boron atoms could leave the TiN and TiB2 microstructures, respectively, and diffuse into the opposing phase.

Five titanium-based alloys containing 4, 8, 12, 16, and 20 wt% molybdenum additive were fabricated by spark plasma sintering process at 1200 ˚C. The samples were scrutinized in terms of relative density, phase evolution, and microstructural development. The relative density reached 99.9% with the molybdenum addition up to 16 wt% but slightly dropped in the sample with 20 wt% additive. In the specimens with 4 wt% Mo, molybdenum solved completely in the matrix and three different phase morphologies were observed, namely continuous α-Ti, laminar α-Ti, and very thin laminar β-Ti. With increasing Mo content to 20 wt%, widespread single β-Ti appeared alongside remained Mo and α-Ti. Ductile fracture mode was dominant in the samples with low Mo contents whilst it changed to brittle in the specimens with higher content of molybdenum.

A novel reconfigurable, reversible and multifunctional nanostructure platform is designed with ultracompact size, high extinction ratio, large bandwidth and low optical loss. The proposed structure consists of a ring resonator and photonic crystal waveguides. The single nanoscale structure is used to realize the five different high-performance photonic devices such as, electro-optic tunable filter, reconfigurable switch, 1 × 5 power splitter, 4 × 2 reversible encoder and SR flip-flop. These miniature optical device performance parameters are numerically analyzed and optimized by finite-difference-time-domain (FDTD) method. A multifunctional ring resonator coupled waveguide structure is designed with a very small footprint of 179 μm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> , large bandwidth of 45.2 nm, the fast response time of 215 fs and high data rate of 4.651 Tbps. Hence, the proposed nanostructure can be highly suitable for photonic interconnects, lightwave communication networks and quantum computing.

Bio sensing techniques using photonic crystals in recent days is marked as the latest and the best method with accurate measured results. Photonic crystal-based biosensors are best responsive devices for detection and analysis of bio-substance that combines biological components with a physiochemical indicator. In this paper, cervical cancer cells are diagnosed using 2D photonic crystal-based biosensor. The sensor design consists of a `L' and an inverted `L' shaped linear waveguides with sensing holes. The photonic band gap ranges from 1225nm to 1656nm. The refractive index of the normal cell and the cervical cancer cell led to the corresponding shift in the intensity. The sensor design consists of reduced bandwidth, the results measured are accurate with good efficiency.