Self-aligned passivated copper interconnects: a novel technique for making interconnections in ultra large scale integration device applications

Journal ArticleWe have developed a technique to grow self-aligned epitaxial Cu/MgO films on Si (100) using a Pulsed Laser Deposition Method. In this method we deposit a uniform film of Cu/Mg (5-7%) alloy over Si (100) at room temperature using TiN as an intermediate buffer layer. As a result of HRTEM (with spatial resolution of 0.18 nm) and STEM-Z investigations we observed that when this film is annealed at 500?C (in a controlled oxygen environment), in less than 30 minutes time, all the Mg segregates at the top and at the bottom surface of Cu. This is understood to be the consequence of lower surface energy of Mg. At 500?C Mg is quite sensitive to oxygen and a thin layer of MgO is immediately formed at the top surface, we also observed a thin layer of MgO at the Cu/TiN interface. Thickness of the upper MgO layer was found to be 15 nm while that of lower layer was 10 nm. MgO underneath layer acts as a diffusion barrier and inhibits the diffusion of Cu in the system. Upper MgO layer acts as a passivating layer and improves the quality of copper against oxidation. Electrical resistivity measurements (in the temperature range 12-300 K) showed MgO/Cu/MgO/TiN/Si (100) sample to be highly conducting. We also observed that the resistivity of the system is insensitive to ambient oxygen environment. Self-aligned MgO (100) layer also provides a means to grow several interesting materials over it. This technique can be used to integrate high temperature superconductors like YBa2Cu3O7 with silicon chip

Design Simulation and Assessment of Computer Based Cancer Diagnosis Accuracy using ART 1.0 Algorithm

Today Cancer is spreading heavily and become the most dangerous disease in the world. This disease causes death if not diagnoses before the major stage. Small changes or illness in the human body may transform to the cancer in the body. The main thing in this disease is it is not easily detected in its earlier stage. So this causes the aim to design a computer operated system that can make distinguish between benign (non-cancerous) and malignant (cancerous) mammogram. The proposed system helps doctors to increase the diagnosis accuracy. The above propose system shall be simulated by MATLAB. The ART 1.0 algorithm shall be studied and modified to improve the accuracy of existing ART 1.0 system. The simulation shall be done by obtaining cancer data set from UCI repository. The reason behind choosing ART algorithm because of its characteristic to work on three phases i.e., Recognition, Comparison, Search Phase.  The winning neuron is obtained by finding the dot product of input and weight vector. The neuron having largest dot product be the winner.&nbsp

AN OVERVIEW ON TUBULARCULOSIS TREATMENT IN CURRENT SCENARIO

The causative agent of tuberculosis (TB) is Mycobacterium tuberculosis, which mainly infects lungs and causes severe, fever, weight loss, chest pain, etc. It is an extremely transmittable disease spreaded throughout the world as per the WHO. It has emerged as new threat and drug resistance strains of Mycobacterium are emerging throws a challenge to human’s health like Covid-19 in current scenario. TB is now come in the form of bone TB, which is very difficult to diagnosis due to very slow-growing characteristics of Mycobacterium. This review highlights the history, drug development, current treatment both allopathic and Ayurvedic, as well as novel drugs available for the treatment of drug resistance Mycobacterium

Composite Topological Structures in SO(10)

We explore a variety of composite topological structures that arise from the spontaneous breaking of $SO(10)$ to $SU(3)_c \times U(1)_{em}$ via one of its maximal subgroups $SU(5) \times U(1)_\chi$, $SU(4)_c \times SU(2)_L \times SU(2)_R$, and $SU(5) \times U(1)_X$ (also known as flipped $SU(5)$). They include i) a network of $\mathbb{Z}$ strings which develop monopoles and turn into necklaces with the structure of $\mathbb{Z}_2$ strings, ii) dumbbells connecting two different types of monopoles, or monopoles and antimonpoles, iii) starfish-like configurations, iv) polypole configurations, and v) walls bounded by a necklace. We display these structures both before and after the electroweak breaking. The appearance of these composite structures in the early universe and their astrophysical implications including gravitational wave emission would depend on the symmetry breaking patterns and scales, and the nature of the associated phase transitions

On the robustness of ultra-high voltage 4H-SiC IGBTs with an optimized retrograde p-well

The robustness of ultra-high voltage (>10kV) SiC IGBTs comprising of an optimized retrograde p-well is investigated. Under extensive TCAD simulations, we show that in addition to offering a robust control on threshold voltage and eliminating punch-through, the retrograde is highly effective in terms of reducing the stress on the gate oxide of ultra-high voltage SiC IGBTs. We show that a 10 kV SiC IGBT comprising of the retrograde p-well exhibits a much-reduced peak electric field in the gate oxide when compared with the counterpart comprising of a conventional p-well. Using an optimized retrograde p-well with depth as shallow as 1 μm, the peak electric field in the gate oxide of a 10kV rated SiC IGBT can be reduced to below 2 MV.cm -1 , a prerequisite to achieve a high-degree of reliability in high-voltage power devices. We therefore propose that the retrograde p-well is highly promising for the development of>10kV SiC IGBTs

A Bibliographic Study on Artificial Intelligence Research: Global Panorama and Indian Appearance

The present study identifies and assesses the bibliographic trend in Artificial Intelligence (AI) research for the years 2015-2020 using the science mapping method of bibliometric study. The required data has been collected from the Scopus database. To make the collected data analysis-ready, essential data transformation was performed manually and with the help of a tool viz. OpenRefine. For determining the trend and performing the mapping techniques, top five open access and commercial journals of AI have been chosen based on their citescore driven ranking. The work includes 6880 articles published in the specified period for analysis. The trend is based on Country-wise publications, year-wise publications, topical terms in AI, top-cited articles, prominent authors, major institutions, involvement of industries in AI and Indian appearance. The results show that compared to open access journals; commercial journals have a higher citescore and number of articles published over the years. Additionally, IEEE is the prominent publisher which publishes 84% of the top-cited publications. Further, China and the United States are the major contributors to literature in the AI domain. The study reveals that neural networks and deep learning are the major topics included in top AI research publications. Recently, not only public institutions but also private bodies are investing their resources in AI research. The study also investigates the relative position of Indian researchers in terms of AI research. Present work helps in understanding the initial development, current stand and future direction of AI.Comment: 21 pages, 9 figures, 6 table

EFFECT OF BASTI KARMA IN GRIDHRASI-A CASE STUDY

Gridhrasi is one of the Nanatmajavyadhis of Vatadosha. The term Gridhrasi indicates the typical gait that resembles of Gridhra i.e. vulture. Ruka (pain), Toda (pricking sensation), Stambha (stiffness) in waist, hip, back of the thigh, knee, calf and foot respectively are the main symptoms. Gridhrasi can be correlated with sciatica in modern science. Improper sitting posture, continuous and over exertion, jerking movements produce structural abnormality in spine may cause sciatica. A 48 years old female patient approached the OPD with radiating pain from lumbar region to left lower limb and difficulty in walking since one year and was diagnosed with Gridhrasi. As Gridhrasi is Vatajavyadhi, Basti is the best treatment for Gridhrasi. Hence for this patient line of treatment was Sarvangaabhyanga with Sahachartail, Sarvangabashpaswed with Dashamoolkwath, Basti in the form of Erandmooladiniruhabasti and Sahachar tail Anuvasanbasti followed by Panchatikta ksheer basti with Guggultikta ghrut is chosen here along with some oral medications Sahacharadikashay Ghana vati, Prasarnyadikashay Ghana vati, Vishatindukvati, Guggultiktakashay was given. This treatment provided marked improvement in signs and symptoms of Gridhrasi. Before treatment Ruka was 4, Aruchi was 1, Toda was 3, Stambha was 4, Gaurav was 2, Spandana was 2, SLRT left side was 4 and right side was 1, walking distance was 3 which turns after treatment to 2,0,1,0,1,1,0, left side-1, right side-0,1 respectively

Towards Subject Agnostic Affective Emotion Recognition

This paper focuses on affective emotion recognition, aiming to perform in the subject-agnostic paradigm based on EEG signals. However, EEG signals manifest subject instability in subject-agnostic affective Brain-computer interfaces (aBCIs), which led to the problem of distributional shift. Furthermore, this problem is alleviated by approaches such as domain generalisation and domain adaptation. Typically, methods based on domain adaptation confer comparatively better results than the domain generalisation methods but demand more computational resources given new subjects. We propose a novel framework, meta-learning based augmented domain adaptation for subject-agnostic aBCIs. Our domain adaptation approach is augmented through meta-learning, which consists of a recurrent neural network, a classifier, and a distributional shift controller based on a sum-decomposable function. Also, we present that a neural network explicating a sum-decomposable function can effectively estimate the divergence between varied domains. The network setting for augmented domain adaptation follows meta-learning and adversarial learning, where the controller promptly adapts to new domains employing the target data via a few self-adaptation steps in the test phase. Our proposed approach is shown to be effective in experiments on a public aBICs dataset and achieves similar performance to state-of-the-art domain adaptation methods while avoiding the use of additional computational resources.Comment: To Appear in MUWS workshop at the 32nd ACM International Conference on Information and Knowledge Management (CIKM) 202