A critical review of fabrication challenges and reliability issues in top/bottom gated MoS2field-effect transistors.

The voyage of semiconductor industry to decrease the size of transistors to achieve superior device performance seems to near its physical dimensional limitations. The quest is on to explore emerging material systems that offer dimensional scaling to match the silicon- based technologies. The discovery of atomic flat two-dimensional materials has opened up a completely new avenue to fabricate transistors at sub-10 nanometer level which has the potential to compete with modern silicon-based semiconductor devices. Molybdenum disulfide (MoS2) is a two-dimensional layered material with novel semiconducting properties at atomic level seems like a promising candidate that can possibly meet the expectation of Moore's law. This review discusses the various 'fabrication challenges' in making MoS2based electronic devices from start to finish. The review outlines the intricate challenges of substrate selection and various synthesis methods of mono layer and few-layer MoS2. The review focuses on the various techniques and methods to minimize interface defect density at substrate/MoS2interface for optimum MoS2-based device performance. The tunable band-gap of MoS2with varying thickness presents a unique opportunity for contact engineering to mitigate the contact resistance issue using different elemental metals. In this work, we present a comprehensive overview of different types of contact materials with myriad geometries that show a profound impact on device performance. The choice of different insulating/dielectric gate oxides on MoS2in co-planar and vertical geometry is critically reviewed and the physical feasibility of the same is discussed. The experimental constraints of different encapsulation techniques on MoS2and its effect on structural and electronic properties are extensively discussed.

Segmentation of Brain MRI Images using Multi-Kernel FCM EHO Method.

BACKGROUND: In image processing, image segmentation is a more challenging task due to different shapes, locations, image intensities, etc. Brain tumors are one of the most common diseases in the world. So, the detection and segmentation of brain tumors are important in the medical field. OBJECTIVE: The primary goal of this work is to use the proposed methodology to segment brain MRI images into tumor and non-tumor segments or pixels. METHODS: In this work, we first selected the MRI medical images from the BraTS2020 database and transferred them to the contrast enhancement phase. Then, we applied thresholding for contrast enhancement to enhance the visibility of structures like blood arteries, tumors, or abnormalities. After the contrast enhancement process, the images were transformed into the image denoising phase. In this phase, a fourth-order partial differential equation was used for image denoising. After the image denoising process, these images were passed on to the segmentation phase. In this segmentation phase, we used an elephant herding algorithm for centroid optimization and then applied the multi-kernel fuzzy c-means clustering for image segmentation. RESULTS: Peak signal-to-noise ratio, mean square error, sensitivity, specificity, and accuracy were used to assess the performance of the proposed methods. According to the findings, the proposed strategy produced better outcomes than the conventional methods. CONCLUSION: Our proposed methodology was reported to be a more effective technique than existing techniques.

InGaAs based gratings for UV-VIS spectrometer in prospective mRNA vaccine research.

During the outbreak of the COVID-19 illness, mRNA (messenger RNA) injections proved to be effective vaccination. Among the presently available analytical techniques, UV/VIS spectrophotometry is a trustworthy and practical instrument that may provide information on the chemical components of the vaccine at the molecular level. In this paper, we will present a one-dimensional grating of InGaAs as a prospect grating structure for UV-VIS spectrometer that can be used for mRNA vaccine development. The main parameters and the wavelength region used in mRNA vaccine development lies in the range of 200 nm to 700 nm (UV-VIS Range). The incorporation of new materials that are excellent for cutting-edge semiconductor industry procedures for MEMS manufacture, as well as new optimal parameters, will improve the grating and spectrometer's performance which will enhance the mRNA vaccine development and manufacturing workflows enabled by UV-VIS spectroscopy. Hence we evaluated the feasibility of the materials, Si (Silicon), GaN (Gallium Nitride), InGaAs (Indium Gallium Arsenide) and InP (Indium Phosphide) as a grating material. Reflection spectrum of the proposed structure shows 48% increase compared to the grating made up of Silicon. In order to model wave propagation in one grating unit cell, electromagnetic waves frequency domain interface is used. The periodic constraints of floquet periodicity are used for simulation at both faces of the unit cell. The reflectance of grating with each material as functions of the angle of incidence was plotted. Also we evaluated the effect of grating thickness, groove density, spectral resolution and efficiency over different materials namely Si, GaN, InGaAs and InP. After optimizing geometric parameters, the designed InGaAs based grating achieved a efficiency of 87.45% and can be a reliable prospect for mRNA based vaccine development.