Department of Chemical Engineering

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IIT Jodhpur

Evolution in material centric devices like batteries and electrocatalytic reactors have predominantly been made possible via the exploitation of the thermodynamic ground state of pristine or defective bulk crystal, referred to as the “Native polymorph” (NP) here. A significant increase in the material search space is possible by utilizing “Non-Native polymorphs (NNP),” which are materials that have different translational symmetry with respect to NP. As the NNP have a distinct coordination structure from that of the NP, critical material properties can be anticipated to be different, making NNP a potential substitute material for the aforementioned applications, which are the focus of this review. To obtain a structure–function relationship, systematic approaches to the synthesis of NNP has been demonstrated. Following certain generalities behind NNP, we classify synthesis techniques into few categories with the hope of rationalizing the underlying mechanism of these synthesis and stabilization strategies. We discuss the utility of NNPs in the context of electrochemical water electrocatalytic reactions. Typically, the NNPs have more open volume space enabling lower lithium-ion diffusion barrier, higher lithium-ion binding energies, thereby making NNP efficient in the context of energy storage material. However, NNP have lesser stability than the NP and methods to calibrate and improve the stability of NNP are important. Overall, the discussion of polymorphic materials by demarcating them as NP and NNP provides a systematic approach towards modulating material properties as a trade-off between thermodynamics and kinetics of physicochemical processes. Finally, the challenges and perspectives in this emerging field are discussed. This article is categorized under: Fuel Cells and Hydrogen > Science and Materials Energy Research & Innovation > Science and Materials Energy and Development > Science and Materials. © 2020 Wiley Periodicals LLC

World University root node

Wiley Interdisciplinary Reviews: Energy and Environment

Stabilization of non-native polymorphs for electrocatalysis and energy storage systems

US Patent App. 17/059,242

System and method facilitating decision making for disinfectant dosing in water in water distribution networks

Bitumen in the oil sands industry is separated from sand using a water-based gravity separation process in a primary separation vessel (PSV). The interface between the froth and the middlings layer is an important parameter to control for optimal operation of the PSV unit. In this paper, a method using computer vision based on convolutional neural networks (CNNs) and Kalman filter (KF) is designed for the detection of the interface in PSV, with the CNN estimating both the interface level and the image quality. The proposed method consists of two parts: An offline and an online stage, wherein the parameters of CNN and KF are trained in the offline stage using the available data. The algorithm is made robust to any new type of occlusions, not present in the training dataset, in the online stage. Experimental results demonstrate that the proposed method is accurate and robust to different abnormalities in the process. © 1963-2012 IEEE.

IEEE Transactions on Instrumentation and Measurement

Kalman Filter-Based Convolutional Neural Network for Robust Tracking of Froth-Middling Interface in a Primary Separation Vessel in Presence of Occlusions

Industrial processes often operate in multiple operating modes. In most cases, the outputs are measured at a slower rate than the inputs due to various reasons, such as the unavailability of real-time sensors. In some cases, measurements of inputs are also not available and/or there are outliers in the measurements due to sensor failures. Furthermore, there can exist different properties of outliers in different variables. Not all of the aforementioned challenges have been considered or considered simultaneously while modeling a probabilistic principal component regression model in the existing literature. In the current paper, a mixture robust semi-supervised probabilistic principal component regression model with missing input data is developed, which can handle all the aforementioned challenges effectively when utilized for online predictions of process variables. The proposed approach is solved using the Expectation-Maximization algorithm, and the performance is demonstrated by a numerical example. An experimental case study of the hybrid tanks system is also utilized to demonstrate the practical applicability of the proposed method. © 2021 Elsevier B.V.

Chemometrics and Intelligent Laboratory Systems

Mixture robust semi-supervised probabilistic principal component regression with missing input data

We explore the effect of sulfur doping in Co3V2O8 on the electrochemical performance of supercapacitors in terms of enhanced lattice spacing, electrochemical surface area (ECSA), electronic conductivity, and density of states. The sulfur-doped Co3V2O8 (S-Co3V2O8) nanosheets were grown in situ as a binder-free synthesis on nickel foam by the hydrothermal method. The electrochemical performance was analyzed in an aqueous alkaline electrolyte where the S-Co3V2O8 electrode exhibited a specific capacity of 410 mAh/g at 2 A/g with enhanced rate capability and capacity retention of 94.2% at 5 A/g specific currents after 4000 cycles, whereas the undoped Co3V2O8 electrode exhibited a specific capacity of 337.8 mAh/g at 2 A/g. The high capacity of S-Co3V2O8 is attributed to the enhanced ECSA (by ∼45%) and improved electrical conductivity (by ∼22%) upon doping with sulfur. Furthermore, these results corroborated with density functional theory results. The calculations suggest an increase in lattice parameters and the introduction of additional density of states near the valence-band edge due to the doping of sulfur, resulting in a decrease in charge-transfer resistance. An asymmetric supercapacitor was fabricated, using S-Co3V2O8 nanosheets as the cathode and activated carbon as the anode, which shows a high specific capacity (or capacitance) value of 485 mAh/g, an energy density of 36.4 W h/kg, and a power density of 740 W/kg at 2 A/g with 98.4% specific capacity retention after 4000 consecutive charge-discharge cycles. Furthermore, the analysis was extended in a nonaqueous medium for Li-ion storage where S-Co3V2O8 exhibits a specific capacity of 994 mA h/g and a specific energy density of 828 W h/kg at 1 A/g making it a promising candidate for future high-energy storage systems. The concept of doping is extended to other chalcogenide (e.g., selenium) doping (Se-Co3V2O8), which also shows improved device performance and makes this a versatile approach for high-performance devices. ©

ACS Applied Energy Materials

Chalcogenide Dopant-Induced Lattice Expansion in Cobalt Vanadium Oxide Nanosheets for Enhanced Supercapacitor Performance

The aldol condensation of acetaldehyde with other carbonyl molecules is a complex reaction wherein there is often formation of multiple undesirable side products. These side products include higher oligomers, which not only reduce the selectivity for the main product but also prevent the use of heterogeneous catalysts due to rapid deactivation. 3-Methylpent-3-en-2-one (MPO) is an important fine chemical used as a key intermediate in the fragrance and flavor industry and is produced by the aldol condensation of acetaldehyde (AcH) with methyl ethyl ketone (MEK). In this work, we investigate the continuous production of MPO in the presence of a cation exchange resin (Amberlyst-15) in a fixed-bed reactor. Our earlier work on batch kinetics reveals that a higher feed molar ratio of AcH:MEK results in a higher yield of MPO. Accordingly, reactions are performed in a laboratory fixed-bed reactor at different feed molar ratios, reaction temperatures, and residence times. The effect of side injection of acetaldehyde into the flow reactor was also investigated and found to favorably influence the selectivity toward MPO. A crucial observation was that maintaining a low concentration of acetaldehyde helps in reducing catalyst deactivation and hence extends its life. Based on the results obtained in the lab-scale reactor, MPO was successfully produced in the pilot-scale fixed-bed reactor by performing the reaction for an extended duration (570 h), indicating that the catalyst is sufficiently active under the conditions of interest without loss of activity. The intrinsic kinetic model developed earlier using the batch reactor data is incorporated in the fixed-bed reactor model and it was found that the predictions agree reasonably well with the experimental results. © 2021 American Chemical Society

Industrial \& Engineering Chemistry Research

Fixed-Bed Reactor with Side Injection: A Promising Option for the Aldol Condensation of Acetaldehyde

Abstract: To monitor and manage hydrological systems such as brooks, streams, rivers, the use of tracers is a well-established process. Limited number of potential tracers such as salts, isotopes and dyes, make study of hydrological processes a challenge. Traditional tracers find limited use due to lack of multiplexed, multipoint tracing and background noise, among others. In this regard, DNA based tracers possess remarkable advantages including, environmentally friendly, stability, and high sensitivity in addition to showing great potential in the synthesis of ideally unlimited number of unique tracers capable of multipoint tracing. To prevent unintentional losses in the environment during application and easy recovery for analysis, we hereby report DNA encapsulation in silica containing magnetic cores (iron oxide) of two different shapes—spheres and cubes. The iron oxide nanoparticles having size range 10–20 nm, have been synthesized using co-precipitation of iron salts or thermal decomposition of iron oleate precursor in the presence of oleic acid or sodium oleate. Physico-chemical properties such as size, zeta potential, magnetism etc. of the iron oxide nanoparticles have been optimized using different ligands for effective binding of dsDNA, followed by silanization. We report for the first time the effect of surface coating on the magnetic properties of the iron oxide nanoparticles at each stage of functionalization, culminating in silica shells. Efficiency of encapsulation of three different dsDNA molecules has been studied using quantitative polymerase chain reaction (qPCR). Our results show that our DNA based magnetic tracers are excellent candidates for hydrological monitoring with easy recoverability and high signal amplification. Graphic Abstract: [Figure not available: see fulltext.]. © 2021, The Author(s).

School of Liberal Arts (SoLA)

Fulltext

Nanoscale Research Letters

Magnetic Nanoparticles to Unique DNA Tracers: Effect of Functionalization on Physico-chemical Properties

Journal of Water Resources Planning and Management

Closure to "influence of Dead-End Sections of Drinking Water Distribution Networks on Optimization of Booster Chlorination Systems" by Ahmed A. Abokifa, Abhilasha Maheshwari, Ravindra D. Gudi, and Pratim Biswas

A method of designing control inputs for tracking problems when models considered in the form of stochastic differential equations is proposed. Using the ideas of control vector parameterization, the control input identification problem is formulated as a parameter identification problem, which is solved using homotopy optimization. To further obtain a control with the least number of switchings, i.e., minimum attention control, a sparse recovery framework is developed. The accuracy of the proposed methods is demonstrated with the help of a linear second-order system and a non-linear quadruple tank system. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature.