Showing papers by "Indian Institute of Technology Madras published in 2022"
TL;DR: A detailed literature study has been performed in this paper highlighting the challenges and strategies for utilization of ammonia as a fuel for compression ignition engines in dual fuel combustion mode with secondary fuels like diesel, dimethyl ether, kerosene, hydrogen and other alternate fuels.
73 citations
TL;DR: This review highlights the fabrication of different surface-modified nanocellulose to deliver active molecules, such as drugs, proteins, and plasmids, and its composites in tissue engineering.
59 citations
TL;DR: In this paper, the effects of materials' dielectric properties and penetration depth, MW hotspots and non-thermal effects, MW absorbers and catalysts, temperature, sample size, retention time and MW power on product characteristics are addressed in detail.
Abstract: Microwave (MW)-assisted heating is one of the emerging technologies for biomass conversion into energy, fuels, and chemicals. It is claimed to be energy efficient, time-saving, and improves throughput compared to conventional processing systems mainly due to its unique heating nature. Yet, the issues hindering the scale-up of MW biomass processing technology has not been discussed much in the open literature. Previous review articles have mainly focused on the pyrolysis process parameters and product yields. This paper aims to present the challenges faced to scale-up the MW technology for biomass processing. The effects of materials’ dielectric properties and penetration depth, MW hotspots and non-thermal effects, MW absorbers and catalysts, temperature, sample size, retention time and MW power on product characteristics are addressed in detail. Importantly, energy analysis, batch vs continuous MW operation, and reactor/cavity design are presented to advance the scale-up of MW technology for processing a wide variety of biomass wastes. The article also covers different biomass thermo-chemical processes such as pyrolysis, gasification, liquefaction and torrefaction.
40 citations
TL;DR: In this article , the energy absorption behavior of lattice structures derived from the hexactinellida sea sponge Euplectella aspergillum is studied for the first time.
36 citations
TL;DR: Wang et al. as discussed by the authors proposed an IoT-based Efficient Data Visualization Framework (IoT- EDVF) to strengthen leaks' risk, analyze multiple data sources, and data quality management for business intelligence in corporate finance.
Abstract: Business intelligence (BI) incorporates business research, data mining, data visualization, data tools,infrastructure, and best practices to help businesses make more data-driven choices.Business intelligence's challenging characteristics include data breaches, difficulty in analyzing different data sources, and poor data quality is consideredessential factors. In this paper, IoT-based Efficient Data Visualization Framework (IoT- EDVF) has been proposed to strengthen leaks' risk, analyze multiple data sources, and data quality management for business intelligence in corporate finance.Corporate analytics management is introduced to enhance the data analysis system's risk, and the complexity of different sources can allow accessing Business Intelligence. Financial risk analysis is implemented to improve data quality management initiative helps use main metrics of success, which are essential to the individual needs and objectives. The statistical outcomes of the simulation analysis show the increasedperformance with a lower delay response of 5ms and improved revenue analysis with the improvement of 29.42% over existing models proving the proposed framework's reliability.
36 citations
TL;DR: In this paper, a textile sludge based activated carbon (TSBAC) adsorbent and its performance for the treatment of textile dyeing effluent, have been explained.
31 citations
TL;DR: In this article , the authors proposed a data fusion based framework for bearing fault diagnosis and prognosis, where the selected features are fused by fourteen dimensionality reduction techniques to extract 2D fault features and health indicators, and a comparison is made between the techniques to identify the most efficient technique.
29 citations
01 Jan 2022
TL;DR: In this paper, a gray wolf optimization (GWO) architecture is used to learn the operation of resource allocation in an optimal manner in a multi-cloud environment, where the deep neural network operates in such a way that it reduces the delay in processing and storage of data to cloud that ensures flexible operations across the cloud.
Abstract: In recent decades, there exists a wide increase in traffic of clouds due to the enormous increase of media content. The popularity of cloud is gaining its attention due to its ease of use and flexible model but suffers from poor resource2 management and its minimal extendibility of service portfolio. However, with recent advancement, the services are effectively managed, and its discovery is made further possible. To handle larger amounts of multimedia contents in a standalone cloud, deployment of wide operable systems is yet required that handles the data effectively with increasing demands of the user. A resource allocation framework is designed in this paper that uses a gray wolf optimization (GWO) architecture to effectively learn the operation of resource allocation in an optimal manner. For optimal service provisioning and scalability, the cloud at times communicates with each other based on the resource allocated by the deep neural network, and then the resources are shared. Such a scenario forms the multi-cloud computing, and the resource management using the deep neural network ensures trivial solutions on poor scalability. The deep neural network acts as a model for controlling the routing capabilities based on the input data rate and the storage space available in the multi-clouds. The deep neural network operates in such a way that it reduces the delay in processing and storage of data to cloud that ensures flexible operations across the cloud. The entire operation is divided into two modules: the first module operates on data processing and routing operations, and the second module acts as a control plane using the deep neural network that ensures optimal allocation of resources based on the data obtained and processed in the first module. These two models ensure better delivery of data to the cloud with proper allocation and storage of resources in the multi-cloud environment. The simulation is conducted using Java (netbeans) platform, and it is evaluated further using CloudSim toolkit. The results are experimented on various performance metrics that includes time delay and cost of resource allocation on multi-cloud.
25 citations
TL;DR: In this paper, the synergetic effect between algae biomass in co-pyrolysis with synthetic plastics (polypropylene (PP), polyethylene (PE), and expanded polystyrene (EPS)) was investigated.
24 citations
TL;DR: In this article, the authors extend the refined versions of the Bohr inequality for the class of the quasi-subordinations which contains both the classes of majorization and subordination as special cases.
21 citations
TL;DR: In this paper, the efficacy of utilizing emulsification and water injection methods to mitigate the higher NOx emissions with biodiesel is investigated in the light-duty diesel engine at rated speed, varying load conditions with neat biodiesel, biodiesel-water emulsion, and biodiesel water injection.
TL;DR: In this article, the fabrication and characterization of a mechanically robust super-hydrophobic (SHP) surface with enhanced corrosion resistance and reduced biofouling was reported, which consists of a top hydrophobic layer of hexamethyldisilazane modified nano-silica and a middle connecting layer of hydrolyzed glycidoxypropyltrimethoxysilane that is covalently bonded to the SHP surface and hydrophilic aluminum substrate.
TL;DR: In this article, the influence of graphene reinforcement on the coefficient of thermal expansion (CTE) and thermal conductivity (TC) of 3D printed graphene/AlSi10Mg composite was evaluated in the temperature range of 25°C to 500°C.
TL;DR: In this paper , a review of the recent trends in surface modification by thin films of implants has been discussed in detail, which is an ideal surface treatment to the permanent implant materials to enhance properties such as biodegradation resistance, better mechanical strength and biocompatibility.
TL;DR: A critical analysis of approaches and models available in the literature to predict biodiesel properties that are important for fuel quality specifications, storage, handling, and durability of the fuel injection systems is provided in this article .
Abstract: The engine fuel properties of biodiesel are required for fuel quality assessment, spray and combustion modelling studies and engine optimization studies. Experimental measurement of biodiesel fuel properties over a broad range of temperatures is cost-intensive, laborious, time-consuming, and requires skilled labour. Thus, there have been sustained interests to develop models for predicting biodiesel fuel properties using various approaches for the past 50 years. The models developed for predicting fuel properties are based on various approaches that have advantages and limitations. The present review provides a critical analysis of approaches and models available in the literature to predict biodiesel properties that are important for fuel quality specifications, storage, handling, and durability of the fuel injection systems. The reliability of any empirical model depends on the number of data points considered in calibrating the model. The review articles available in the literature neither discussed the number of calibration samples nor the number of validation samples used for model development. Also, it is essential to validate the prediction models using additional data set which are not considered in calibrating the models. The present review addresses these limitations wherein the favourable features and limitations of models available to predict biodiesel properties are discussed in terms of reported deviations, validation method, model simplicity, applicable range and the number of data points used in calibrating and validating the models. Thus, the analysis provided therein helps to choose appropriate property prediction models based on the intended application. Further, poor oxidative stability is one of the significant drawbacks with biodiesel, and no literature discusses the models to predict oxidative stability of biodiesel. This limitation is also addressed in the present review. Biodiesel composition-based models are suggested to predict the calorific value provided a more comprehensive range, and the type of methyl esters are considered in the model calibration. Due to simplicity, estimating biodiesel density based on the predicted density of methyl esters and applying suitable mixing law is suggested. Accurate models to predict biodiesel flashpoint temperature and oxidative stability need to be developed considering their significance. Models involving composition-based indicators are recommended to predict biodiesel cold filter plugging point and kinematic viscosity due to model simplicity and better accuracy. • Various approaches and models to predict biodiesel properties are reviewed. • The shortcomings of each model are outlined. • Biodiesel composition-based models are more suitable to predict calorific value. • Mixing-law based approach is suggested to predict biodiesel density. • Accurate models to predict biodiesel flashpoint and oxidative stability are needed.
TL;DR: In this paper, a MATLAB-based extended finite elements method (XFEM) model has been utilized to analyze experimental results of fatigue, fracture, and tensile properties of AM fabricated Ti6Al4V alloy to avoid expensive, destructive mechanical characterisation.
TL;DR: In this paper, the stabilizing role of Zr is shown in single-phase fluorite type high entropy oxides (F-HEOs) and the presence of specific cations like Pr/Tb in the Zr-FEOs allows for a substantial and fully reversible tuning of the band gap within 2 −eV −4 eV.
27 Jan 2022
TL;DR: A review of precursors used in Scholl reaction and their accompanying rearrangements that include aryl migration, migration followed by cyclization and skeletal rearrangement involving ring expansion, ring contraction and both under the reaction conditions is presented in this article .
Abstract: Rearrangements in Scholl reaction are mostly serendipitous. The design of molecular precursors is what seems to guide the course of rearrangement. This review consolidates different classes of precursors used in Scholl reaction and their accompanying rearrangements that include aryl migration, migration followed by cyclization and skeletal rearrangements involving ring expansion, ring contraction and both, under the reaction conditions. The attempt in collating heretofore-reported examples in this review is to guide designing appropriate precursors to predictably achieve complex molecular structures or nanographenes or defect-nanographenes via rearrangement.
TL;DR: Point-of-care drug testing devices have become the need of the hour for many sections such as the law enforcement agencies, the workplaces, etc. as mentioned in this paper, which can result in serious safety breaches at critical workplaces.
TL;DR: In this paper , a polydopamine-reduced graphene oxide (PD-RGO) reinforced 3D printed PLA scaffold was used for bone tissue construction and the fabricated scaffold showed antioxidant property along with pro-angiogenic and osteoinductive potential.
Abstract: Successful regeneration of load-bearing bone defects remains a major challenge in clinical orthopaedics. Designing biologically active 3-dimensional scaffolds possessing physiological responsiveness can potentially overcome current limitations. Here, we have described a novel approach to fabricate scaffolds with modified nanosheets reinforced on mechanically customized thermoplastic polymer-based 3D printed constructs. In this article, we have developed polydopamine-reduced graphene oxide (PD-RGO) reinforced 3D printed PLA scaffold for bone tissue construction. RGO was synthesized by reduction of GO under alkaline conditions using dopamine. 3D printed polylactic acid (PLA) scaffold with defined porosity was doped with PD-RGO. The designed scaffold was studied for its physiochemical properties and human umbilical cord-derived mesenchymal stem cell (hMSC) behaviour within the scaffold. In vitro hMSC studies revealed the influence of fibre direction and nanocoating on directional cell growth and proliferation. The fabricated scaffold showed antioxidant property along with pro-angiogenic and osteoinductive potential. The designed scaffold also successfully prevented the formation of biofilm. In vivo heterotopic implantation of the differentiated hMSC loaded scaffold confirmed the biocompatibility and bio functionality of the scaffold. In summary, the designed nanoplates doped 3D printed scaffold displays stem cell responsive, integrative and pro-regenerative multi functionalities, thereby, exhibiting potential application as bone tissue regeneration treatment alternative.
TL;DR: In this paper, the structural and micro-structural analyzes reveal a near-complete NiO reduction with three phases of face-centered-cubic structured nanocomposites.
TL;DR: In this article , the authors performed hydrothermal liquefaction of red macroalgae species, Kappaphycus alvarezii (KA) and Eucheuma denticulatum (ED), at 350 °C in the presence of 5 wt% neutral and alkali catalysts like Na2CO3, K2 CO3, CaCO 3, Na2SO4, NaOH, and KOH.
TL;DR: In this article, a new auxetic structure was designed with rigid diamonds incorporated to enhance the strength of a star-shaped auxiliary structure along with the symmetry in the present work, which was fabricated through Multi-Jet Fusion process and subjected to quasi-static compression tests for static analysis.
TL;DR: In this paper, the authors present an approach for running analytics on the live video on embedded or mobile devices, e.g., mobile phones, tablets, and computers, where the authors propose a framework for video streaming over the network.
Abstract: Videos take a lot of time to transport over the network, hence running analytics on the live video on embedded or mobile devices has become an important system driver. Considering such devices, e.g...
TL;DR: In this article , a CFD simulation setup of diesel-methane dual fuel combustion in a single-cylinder research engine (SCRE) is used to provide insight about dual fuel combustions at low-load operation.
TL;DR: In this paper , a nonlinear model predictive controller for path following of a surface vessel in the presence of regular waves was developed for a 3DoF unified manoeuvring model of the KVLCC2 crude oil tanker.
TL;DR: In this paper, a method to track the solid-liquid interface during the melting of a phase change material using liquid crystal thermography is presented, where the melt front movement is captured simultaneously through temperature influenced color variation in Thermochromic Liquid Crystal (TLC) sheet and direct visualization.
TL;DR: In this paper, three different plasma reactors, namely, sequential flow plasma reactor (SFR), continuous flow top discharge plasma (TDPR) and continuous flow side discharge (SDPR), are designed and fabricated for their performance evaluation with respect to PhAC degradation.
TL;DR: In this paper , the authors provide a molecular understanding of existing theories about nucleation and growth of gas hydrate and further, factors affecting decomposition and the analysis techniques that are used to quantify such mechanism are also discussed.
TL;DR: In this paper , the authors investigated three nonlinear equations that describe waves on the oceans which are the Kadomtsev Petviashvili-modified equal width (KP-MEW) equation, the coupled Drinfel-d-Sokolov-Wilson (DSW) equation and the Benjamin-Ono (BO) equation using the modified (G′G2)-expansion approach.