Nitte Meenakshi Institute of Technology

About: Nitte Meenakshi Institute of Technology is a based out in . It is known for research contribution in the topics: Computer science & Ultimate tensile strength. The organization has 846 authors who have published 644 publications receiving 2702 citations.

Virtual Laboratory: A Boon to the Mechanical Engineering Education During Covid-19 Pandemic

Abstract: The engineering students understand the engineering concepts effectively when they conduct the experiments in the laboratory. Hence, laboratory is as important as theory; however, the ill-equipped ...

Opinion mining and sentiment analysis on online customer review

Abstract: The opinion mining is very much essential in e-commerce websites, furthermore advantageous with individual. An ever increasing amount of results are stored in the web as well as the amount of people would acquiring items from web are increasing. As a result, the users' reviews or posts are increasing day by day. The reviews toward shipper sites express their feeling. Any organization for example, web forums, discourse groups, blogs etc., there will be an extensive add up for information. Records identified with items on the Web, which are functional to both makers and clients. The process of finding user opinion about the topic or product or problem is called as opinion mining. It can also be defined as the process of automatic extraction of knowledge by means of opinions expressed by the user who is currently using the product about some product is called as opinion mining. Analyzing the emotions from the extracted opinions is defined as Sentiment Analysis. The goal of opinion mining and Sentiment Analysis is to make computer able to recognize and express emotion. This work concentrates on mining reviews from the websites like Amazon, which allows user to freely write the view. It automatically extracts the reviews from the website. It also uses algorithm such as Naive Bayes classifier, Logistic Regression and SentiWordNet algorithm to classify the review as positive and negative review. At the end we have used quality metric parameters to measure the performance of each algorithm.

A novel low-temperature solid-state route for nanostructured cubic garnet Li7La3Zr2O12 and its application to Li-ion battery

Abstract: We present a novel approach to the solid-state synthesis of garnet-type cubic Li7La3Zr2O12 (c-LLZO) nanostructured particles with 1.0 mass% Al at 750 °C within 3 h. In contrast to conventional solid-state processes, a highly reactive precursor was prepared in two steps: (i) by homogenizing the stoichiometric mixture without Li, and (ii) subsequent addition of Li in the form of an ethanolic solution of lithium acetate. The actual composition determined by ICP analysis was Li6.61La3Zr2Al0.13O11.98. Sintering these nanoparticles at 1100 °C for 3 h in air after cold isostatic pressing brought a dense ceramic pellet with a relative density of 90.5%. The corresponding ionic conductivity with Au electrodes was 1.6 × 10−4 S cm−1 at room temperature. To study its electrochemical behavior as an electrolyte, a model cell of Li//(1 M LiPF6 + c-LLZO)//LiCoO2 configuration was constructed. Cyclic voltammetry of the cell delivered one set of redox couple with narrow voltage separation (15 mV) with a Li+ diffusion coefficient at room temperature of about 2 × 10−11 cm2 s−1 at the interface between LiCoO2 and 1 M LiPF6 + c-LLZO. The cell received an average discharge capacity of 64.4, 60.3, 56.1, 51.9 and 46.9 μA h cm−2 μm−1 at discharge rates 0.5C, 1C, 2C, 4C and 6C, respectively. The cell exhibited complete oxidation and reduction reactions with an average initial discharge capacity of about 64 μA h cm−2 μm−1, which is 92.7% of LiCoO2 theoretical value. These observations indicate the applicability of the present c-LLZO as an electrolyte for a solid-state Li-ion battery.