Indian Institute of Technology Palakkad&nbsp;(IIT Palakkad or IIT PKD) is a public autonomous&nbsp;engineering&nbsp;and&nbsp;research&nbsp;institute located in&nbsp;Palakkad,&nbsp;Kerala. It was&nbsp;one of the five new&nbsp;IITs&nbsp;proposed in the&nbsp;2014 Union budget of India. The campus was inaugurated on 3 August 2015. The institute has 94 faculty, 978 students, and 63 non-teaching staffs.

IT Palakkad currently offers four-year Bachelor of Technology (B.Tech) and two years MS programmes in 8 different engineering disciplines including&nbsp;Computer Science, Electrical, Mechanical, Civil among others.

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IIT Palakkad

Wire breakages and spark absence are two typical machining failures that occur during wire electric discharge machining (wire-EDM), if appropriate parameter settings are not maintained. Even after several attempts to optimize the process, machining failures cannot be eliminated completely. An offline classification model is presented herein to predict machining failures. The aim of the current study is to develop a multiclass classification model using an artificial neural network (ANN). The training dataset comprises 81 full factorial experiments with three levels of pulse-on time, pulse-off time, servo voltage and wire feed rate as input parameters. The classes are labeled as normal machining, spark absence and wire breakage. The model accuracy is tested by conducting 20 confirmation experiments and the model is discovered to be 95% accurate in classifying the machining outcomes. The effects of process parameters on the process failures are discussed and analyzed. A microstructural analysis of the machined surface and worn wire surface is conducted. The developed model proved to be an easy and fast solution for verifying and eliminating process failures.

World University root node

Department of Mechanical Engineering

Advances in Manufacturing

Prediction and analysis of process failures by ANN classification during wire-EDM of Inconel 718

Recently generative models have focused on combining the advantages of variational autoencoders (VAE) and generative adversarial networks (GAN) for good reconstruction and generative abilities. In this work we introduce a novel hybrid architecture, Implicit Discriminator in Variational Autoencoder (IDVAE), that combines a VAE and a GAN, which does not need an explicit discriminator network. The fundamental premise of the IDVAE architecture is that the encoder of a VAE and the discriminator of a GAN utilize common features and therefore can be trained as a shared network, while the decoder of the VAE and the generator of the GAN can be combined to learn a single network. This results in a simple two-tier architecture that has the properties of both a VAE and a GAN. The qualitative and quantitative experiments on real-world benchmark datasets demonstrate that IDVAE performs better than the state of the art hybrid approaches. We experimentally validate that IDVAE can be easily extended to work in a conditional setting and demonstrate its performance on complex datasets.

Department of Data Science

Proceedings of the International Joint Conference on Neural Networks

Implicit Discriminator in Variational Autoencoder

The increase of B4C addition into an AA6061-B4C composite system will not be always an ideal choice for improved properties because of the issues related to incorporation, distribution and interfacial wetting while stir-casting. In such a case, ultrasonication is considered to be an alternative to get the advantage of microstructural changes which in turn improve the properties. In the present study individual B4C distribution and the refinement of microstructure was achieved at 4wt.%B4C. The improved specific ultimate and compressive strengths at 4wt.%B4C were observed as 36.32% and 43.92% whereas specific Vicker's and Brinell hardness as 53.41% and 50.89% respectively.2009 Elsevier Ltd. All rights reserved.

Fulltext

Engineering Science and Technology, an International Journal

Enhanced mechanical properties of AA6061-B4C composites developed by a novel ultra-sonic assisted stir casting

Additive manufacturing makes parts with greater speed and gives freedom for designer. LENSTMis an additive manufacturing method which uses three dimensional CAD model designed by CAD software for depositing metal products directly from metal powder. The effect of process parameters for wear resistance, corrosion resistance for LENSTMdeposited components and the values are compared with wrought alloy. The optimized Values of corrosion and wear resistance are superior to wrought SS 316L alloy. © 2020 Elsevier Ltd. All rights reserved.

Materials Today: Proceedings

Comparison of wear and corrosion resistance behaviour of LENS TMdeposited SS 316L alloy and wrought alloy

Sugarcane bagasse ash is an abundantly available waste material from sugar plants in India. Even though the beneficial properties of bagasse ash as a cement replacement material have been reported in several studies, its large-scale utilization in Indian cement plants is not yet achieved. This is partly due to a lack of proper quantification of the available sugarcane bagasse ash and its accessibility from sugar plants to the existing cement plants. A detailed sugarcane bagasse ash availability database in the five major sugar-producing states and their precise geographical distribution have been presented in this study. The proximity of the bagasse ash sources to existing cement plants in these five states is quantified using a GIS-based network analysis approach. Additionally, the accessibility of bagasse ash is compared with currently used fly ash and slag. Results from the study show that the probability of finding a bagasse ash source at near distances from cement plants is higher than the probability of having fly ash or slag sources in three out of the five states considered in the study. © 2020, Society for Sugar Research & Promotion.

Department of Civil Engineering

Sugar Tech

Availability and Accessibility of Sugarcane Bagasse Ash for its Utilization in Indian Cement Plants: A GIS-Based Network Analysis

According to the American Society of Anesthesiologists Closed Claims Database, one of three drug-related errors is the result administrating an incorrect dose. Directly measuring drug concentration removes the uncertainty in the dose-concentration relationship and addresses inter- and intra-subject variabilities that affect the pharmacokinetics of anesthetics. Here we describe a dual-analyte microcatheter-based electrochemical sensor capable of simultaneous real-time continuous monitoring of fentanyl (FTN) and propofol (PPF) drugs simultaneously in the operating rooms. Such a dual PPF/FTN catheter sensor relies on embedding two different modified carbon paste (CP)-packed working electrodes along with Ag/AgCl microwire reference electrodes within a mm-wide Teflon tube, and uses a square wave voltammetric (SWV) technique. The composition of each working electrode was judiciously tailored to cover the concentration range of interest for each analyte. A polyvinyl chloride (PVC) organic polymer coating on the surface of CP electrode enabled selective and sensitive PPF measurements in μM range. The detection of nM FTN levels was achieved through a multilayered nanostructure-based surface modification protocol, including a CNT-incorporated CP transducer modified by a hybrid of electrodeposited Au nanoparticles and electrochemically reduced graphene oxide (erGO) and a PVC outer membrane. The long-term monitoring capability of the dual sensor was demonstrated in a protein-rich artificial plasma medium. The promising antibiofouling behavior of the catheter-based multiplexed sensor was also illustrated in whole blood samples. The new integrated dual-sensor microcatheter platform holds considerable promise towards real-time, in-vivo detection of the anesthetic drugs, propofol and fentanyl, during surgical procedures towards significantly improved safe delivery of anesthetic drugs. © 2020 Elsevier B.V.

Department of Chemistry

Talanta

An integrated microcatheter-based dual-analyte sensor system for simultaneous, real-time measurement of propofol and fentanyl

Quantum error correction procedures have the potential to enable faithful operation of large-scale quantum computers. They protect information from environmental decoherence by storing it in logical qubits, built from ensembles of entangled physical qubits according to suitably tailored quantum error correcting encodings. To date, no generally accepted framework to characterise the behaviour of logical qubits as quantum memories has been developed. In this work, we show that generalisations of well-established figures of merit of physical qubits, such as relaxation times, to logical qubits fail and do not capture dynamics of logical qubits. We experimentally illustrate that, in particular, spatial noise correlations can give rise to rich and counter-intuitive dynamical behavior of logical qubits. We show that a suitable set of observables, formed by code space population and logical operators within the code space, allows one to track and characterize the dynamical behaviour of logical qubits. Awareness of these effects and the efficient characterisation tools used in this work will help to guide and benchmark experimental implementations of logical qubits.

Department of Physics

arXiv preprint arXiv:2012.

Relaxation times do not capture logical qubit dynamics

A series of neutral, bulky diazabutadienediyl-substituted beryllacycles [Be(DipDAB)(L)] (DipDAB = [(DipNCH)2]2-, Dip = 2,6-diisopropylphenyl; L = OEt2, THF,:C(RNCH)2; R = Me (TMC), Pri(IPriMe)) have been prepared and characterized by multinuclear NMR spectroscopy and X-ray crystallography. The preparation of similar complexes bearing the smaller tert-butyl-substituted diazabutadienediyl ligand ([(ButNCH)2]2-, viz. ButDAB) was attempted but gave rise to complex product mixtures, several components of which were isolated in trace yields. This phase of the study did, however, lead to the preparation of the homoleptic beryllium diradical complex [Be(ButDAB•)2], which was characterized by X-ray crystallography and EPR spectroscopy. In efforts to access BeI-BeI-bonded dianions, [(DipDAB)Be-Be(DipDAB)]2-, reductions of [Be(DipDAB)(L)] were pursued, but these instead afforded largely intractable product mixtures. Treating ethereal solutions of [Be(DipDAB)(OEt2)] with lithium alkyls afforded highly reactive, heterocyclic beryllate salts, [Li(OEt2)2,1][Be(DipDAB)R] (R = Me, Bun). Subsequent treatment of [Li(OEt2)][Be(DipDAB)Bun] with either N,N,N′,N′-tetramethylethylenediamine (tmeda) or N,N,N′,N′′,N′′-pentamethyldiethylenetriamine (pmdeta) led to the formation of [Li(tmeda)2][Be(DipDAB)Bun] and [Li(pmdeta)][Be(DipDAB)Bun]. Reactions between two of the heterocyclic beryllate salts and [BeX2(OEt2)2] (X = Br, I) did not lead to clean salt metathesis reactions but gave mixtures of many products, several of which were isolated in very low yields. While the noninnocent nature of the diazabutadienediyl ligands of [Be(DipDAB)(L)] and the [Be(DipDAB)R]-anions, hampered explorations of their further reactivity, these heterocycles hold promise as synthons for beryllium coordination chemistry. © 2020 American Chemical Society. All rights reserved.

Organometallics

Neutral, Anionic and Paramagnetic 1, 3, 2-Diazaberyllacyles Derived from Reduced 1, 4-Diazabutadienes

A new fouling-resistant mixed-matrix nanofiltration membrane based on a covalently cross-linked Ti3C2TX (MXene)/cellulose acetate (MXene@CA) composite was fabricated by phase inversion followed by formaldehyde cross-linking. The physicochemical properties of the prepared MXene@CA composite membranes were studied by field emission scanning electron microscopy (FESEM), energy dispersive spectroscopy (EDS), X-ray diffraction (XRD) and water contact angle techniques. The performance of the prepared membranes was evaluated with respect to the water flux, bacterial growth inhibition and rejection properties. The 10%MXene@CA (10:90 wt % of MXene:CA) composite membrane shows high pure water flux of $\sim$256.85 L m−2 h−1 bar−1, 123.28% water uptake and 69.7% porosity. The 10%MXene@CA membrane, exhibited more than 92% and 98% rejection of rhodamine B (RhB) and methyl green (MG), respectively. Furthermore, 10%MXene@CA membrane exhibited more than 98% and 96% growth inhibition for E. coli and B. subtilis, respectively. Also, the optimal membrane showed a significantly improved hydrophilicity (water contact angle = 60.8°), which has favored good antifouling properties. The reported nanofiltration membrane, especially 10%MXene@CA, can be suggested for water purification and biomedical applications.

Biological Sciences and Engineering

Journal of Membrane Science

A fouling-resistant mixed-matrix nanofiltration membrane based on covalently cross-linked Ti3C2TX (MXene)/cellulose acetate

The functional application of RNA-guided CRISPR-associated Cas9 protein, a bacterial immune system-based protein complex, via which in vivo, highly specific, and well-regulated, gene-editing processes are being monitored at an unprecedented level, has led to remarkable progress in genetic engineering and technology. The complicated in vivo process of genome interrogation followed by gene editing by the Cas9 complex was recently reported by Knight et al. (Science, 2015, 350, 823-826) using an elegant single-particle tracking method, aided by the two-photon fluorescence correlation spectroscopic technique. In contrast to the usually observed fast target-searching and protein-binding events in biophysical systems, an interesting slow genome-interrogation process by the RNA-guided CRISPR-Cas9 system through a crowded chromatin environment of a mammalian cell has been revealed in Knight et al.'s study. Motivated by this experiment, in this paper, we provide a generalized theoretical framework to capture this particular target-searching mechanism of the CRISPR-Cas9 protein complex. We show that an analysis on the basis of 3D subdiffusion under a cylindrical volume, created by several nonspecific off-target interactions from the DNA strands, can capture the essential details of the process. Moreover, on the basis of this model, we quantify the dynamics of this process and estimate the survival probability, first passage time, and the intensity correlation function of the tagged proteins of the experiment. The results from our theoretical predictions are found to be consistent with the experimental observations, and hence, seem to provide a plausible microscopic picture of the process. © 2020 American Chemical Society.