Showing papers by "Birla Institute of Technology and Science published in 2023"

Non-cytotoxic zinc/f-graphene nanocomposite for tunable degradation and superior tribo-mechanical properties: Synthesized via modified electro co-deposition route

Abstract: Zinc (Zn) alloys and composites have recently been recognized as potential biodegradable materials for bone implants and vascular stents. Although new class of Zn-based materials have superior mechanical integrity than polymeric materials during biodegradation, the reinforcement of biocompatible form of graphene nanoplatelets (GNPs) in Zn matrix can be utilized to further enhance their effectiveness for loadbearing implants. In this work, pristine GNPs were functionalized with polyethelene glycol to reduce their toxicity and reinforced in Zn matrix using modified electro co-deposition (M-ECD) method. The influence of various concentrations of functionalized GNPs (f-GNPs) in ECD bath on microstructure, interface bonding of functional groups, morphology, and elemental composition, corrosion resistance, and tribo-mechanical behavior of Zn/f-GNP nanocomposite have been studied. The Zn/f-GNP nanocomposites were also screened systemically for biological responses by in-vitro cytotoxicity and antibacterial studies. The nanocomposite sample of 100 mg/L of f-GNPs concentration in ECD bath has demonstrated a uniform slow in-vitro degradation rate of 26 ± 0.8 × 10−3 mm/year. The primary degradation products included zinc oxide [ZnO], zinc hydroxide [Zn(OH)2], and simonkolleite [Zn5(OH)8Cl2H2O] observed from x-ray diffraction of corroded nanocomposites. The microhardness, compressive yield strength and ultimate compressive strength of Zn/f-GNP (100 mg/L) nanocomposite were 108.5 HV, 284.9 MPa, and 292.6 MPa, respectively, which were significantly higher than pure Zn. In addition, the good in-vitro human keratinocyte cell viability and effective antibacterial activity of Zn/f-GNP nanocomposite render it a very attractive biodegradable implant material for future implication in orthopedic fixation (screw, pins, sutures, and plates) and stents (coronary and cardiovascular stents) applications.

Synthesis, Characterization, DNA/HSA Interaction, and Cytotoxic Activity of a Copper(II) Thiolate Schiff Base Complex and Its Corresponding Water-Soluble Stable Sulfinato–O Complex Containing Imidazole as a Co-ligand

Abstract: A Cu(II) thiolato complex [CuL(imz)] (1) (H2L = o-HOC6H4C(H)=NC6H4SH-o) and the corresponding water-soluble stable sulfinato-O complex [CuL'(imz)] (2) (H2L' = o-HOC6H4C(H)=NC6H4S(=O)OH) were synthesized and characterized using physicochemical techniques. Compound 2 is found to be a dimer in the solid state as characterized using single-crystal X-ray crystallography. XPS studies clearly showed the differences in the sulfur oxidation states in 1 and 2. Both compounds are found to be monomers in solution as revealed from their four-line X-band electron paramagnetic resonance spectra in CH3CN at room temperature (RT). 1-2 were tested to assess their ability to exhibit DNA binding and cleavage activity. Spectroscopic studies and viscosity experiments suggest that 1-2 bind to CT-DNA through the intercalation mode having moderate binding affinity (Kb ∼ 104 M-1). This is further supported by molecular docking studies of complex 2 with CT-DNA. Both complexes display significant oxidative cleavage of pUC19 DNA. Complex 2 also showed hydrolytic DNA cleavage. The interaction of 1-2 with HSA revealed that they have strong ability to quench the intrinsic fluorescence of HSA by a static quenching mechanism (kq ∼ 1013 M-1 s-1). This is further complemented by Förster resonance energy transfer studies that revealed binding distances of r = 2.85 and 2.75 nm for 1 and 2, respectively, indicating high potential for energy transfer from HSA to complex. 1-2 were capable of inducing conformational changes of HSA at secondary and tertiary levels as observed from synchronous and three-dimensional fluorescence spectroscopy. Molecular docking studies with 2 indicate that it forms strong hydrogen bonds with Gln221 and Arg222 located near the entrance of site-I of HSA. 1-2 showed potential toxicity in human cervical cancer HeLa cells, lung cancer A549 cells, and cisplatin-resistant breast cancer MDA-MB-231 cells and appeared to be most potent against HeLa cells (IC50 = 2.04 μM for 1 and 1.86 μM for 2). In HeLa cells, 1-2 mediated cell cycle arrest in S and G2/M phases, which progressed into apoptosis. Apoptotic features seen from Hoechst and AO/PI staining, damaged cytoskeleton actin viewed from phalloidin staining, and increased caspase-3 activity upon treatment with 1-2 collectively suggested that they induced apoptosis in HeLa cells via caspase activation. This is further supported by western blot analysis of the protein sample extracted from HeLa cells treated with 2.

An Algorithm for Customizing Slicing Floor Plan Design

Abstract: This paper proposes a linear time algorithm for the customization of a slicing floor plan design, which can be done by customizing its modules in the following two ways: Both of the aforementioned approaches demonstrate that a slicing floor plan can be generated for any aspect ratio and area while preserving the module adjacencies of the original floor plan. A demonstration has been provided for a devised prototype to validate the viability of the aforementioned approaches.

Nature-Inspired Optimization Algorithm-Assisted Optimal Sensor Node Positioning for Precision Agriculture Applications in Asymmetric Fields

Abstract: Precision agriculture has recently become the need of the hour due to an unprecedented rate of world population increment. Through fine-tuned crop activities, the crop yield can be significantly increased for a given crop season from the same field. However, these fine-tuned crop activities majorly rely on the information received from the field through various sensing nodes. With proper integration and placement of sensing nodes in crop fields, a large proportion of pre-harvest activities can be dealt in a better manner. As the area of agricultural fields can be quite large, thereby identification of the optimal positioning of sensing nodes can become a cumbersome task. Improper placement of sensing nodes may result in suboptimal usage of available resources. To overcome this issue, the current work investigates the use of metaheuristic optimization algorithms to optimally place the sensing nodes on the field. This is done by minimizing an innovatively designed cost function which is an indication of the un-scrutinized field area and overlapping coverage area of the sensor nodes. Five different nature-inspired optimization algorithms are applied in this paper for the said task, and it was found that Particle Swarm Optimization provided the most optimal sensing node placement in comparison to the Cuckoo search algorithm, Salp swarm algorithm, Water cycle algorithm, and Life choice-based optimization algorithm.

Impact of Protein Nanoparticles on Beer Foam

Abstract: Beer foam adds a visual aesthetic to the beer- a good beer foam layer presents the beer as fresh and tasty and attracts customers. Beer foam also helps in maintaining the flavor of the beer by acting as an airtight blanket preventing the escape of CO2 from the beer. Thus, stable, long-lasting beer foam is preferred in the final product irrespective of consumer preferences. Beer foam stability is impacted by the proteins and protein nanoparticles. This work encompasses the effects that proteins and protein nanoparticles have on foaming in beer. Studies regarding the impact of protein nanoparticles on the quality of beer foam are also discussed.

Pan Coating

Abstract: Coating a tablet provides different features to the dosage form. Pan coating is the traditional method for film, enteric, or sugar coating of tablets. The coating process is dependent upon the advances in the techniques, equipment, and material used for coating. Despite advancements in the rules for scale-up of the pan-coating process, the laboratory scale process possesses several gaps leading to differences in the results observed on large scale. The chapter describes the thermodynamic factors, pan and spray-related factors that affect the pan-coating process, and determines the quality of the product. The final section of the chapter explains the scale-up of the pan-coating process.

Analysis of the NH3 Adsorption on Boron-Arsenic Co-doped Monolayer Graphene: A First Principle Study

Abstract: Two-dimensional (2D) graphene has drawn significant attention for its potential application in the detection of inorganic gas molecules when doped with appropriate dopants. As of yet, these effects of non-metallic co-doping at the different sub-lattice sites are yet to be observed systematically from a theoretical perspective for gas-molecule detection on graphene. The study investigates molecular adsorption of ammonia (NH3) on boron/arsenic (B/As) monolayer graphene using density functional theory (DFT). In this paper, we evaluate the influence of arsenic impurity on the molecular adsorption of boron-doped graphene in the same and different sub-lattice sites. In the present context, three doping configurations are identified that possess distinct electronic properties and respond characteristically to individual gas molecules. Due to orbital overlaps from the adsorbed gas molecules, molecular adsorption has a considerable impact on the spatial distribution of electronic states along the band edges, resulting in large modulations in the energy bandgaps and effective masses of the co-doped lattices. Co-doping techniques appear to be particularly suitable for electrochemical gas sensing because they result in a significant semiconducting bandgap opening while preserving the inherent nature of graphene. For co-doped lattices, the subsequent molecular adsorptions result in substantial charge transfer between the gas molecules and the host lattice, as well as a significant increase in the density of electronic states around the Fermi level.

Neural Network Model for Automated Prediction of Avalanche Danger Level

Abstract: Abstract. Snow avalanches cause danger to human lives and property worldwide in high-altitude mountainous regions. Mathematical models based on past data records can predict the danger level. In this paper, we are proposing a neural network model for predicting avalanches. The model is trained with a quality-controlled sub-dataset of Swiss Alps. Training accuracy of 79.75 % and validation accuracy of 76.54 % have been achieved. Comparative analysis of neural network and random forest models concerning metrics like precision, recall, and F1 has also been carried out.

Compression

Abstract: Compaction of powder involves compression and consolidation of the solids on the application of pressure. The forces involved in these processes play an important role in the design and development of solid oral dosage forms including tablets, filling of the hard-gelatin capsule, and in the handling of powders. Assessment of the forces on punches, axial forces, radial forces, frictional forces, and ejection forces gives us information regarding the compaction behaviour of the powder. Several mathematical terms to describe the compaction processes are studied such as the heckle plot. Optimizing the parameters that affect these forces would produce a product of the desired quality. In this chapter, we have discussed in detail about compression, consolidation, and forces involved in compaction and their impact on the quality of the product.

Efficient ASIC Implementation of Artificial Neural Network with Posit Representation of Floating-Point Numbers

Abstract: This paper presents a low-power ASIC architecture of a feedforward Artificial Neural Network using Posit representation. The ASIC Posit shows 50% improvement over ASIC using IEEE 754 format in terms of Power and Silicon Area and is also 13% faster while achieving the same accuracy. The same design using the FPGA platform consumes more power than the ASIC design. The designs are done using Cadence RTL Encounter with TSMC 180 nm technology node.

Drying

Abstract: Drying is a vital process in pharmaceutical formulation involving removal of moisture from solids by applying heat, thus resulting in both heat and mass transfer. The process when theoretically studied utilizes various terms such as absolute humidity, saturation humidity, dew point, relative humidity, drying capacity, wet bulb temperature and the dry bulb temperature which can be understood with the help of psychometric chart. The process of drying of solids when graphically plotted as drying rate versus moisture content is known as drying rate curve. The drying rate curve can be classified as initial adjustment period, constant rate period, first falling rate period and second falling rate period as per the trends of curve. Various types of equipment are used for drying the pharmaceutical solids. The most basic amongst them is a tray drier where the solids are kept on a tray and are dried with hot air. Whereas in fluidized bed dryer, the solids are dried by suspending in air by a constant stream of hot air. On the other hand, when the fluid content is higher, spray drying can be used where the mixture is pumped on a hot drying environment leading to atomization and further leaving particulate solid residue of the mixture. Freeze drying and vacuum drying are the specialized drying processes where drying is achieved by freezing samples or by reducing the pressure around the samples, thus resulting in drying without heating.

A Study on DC Fast Charging of Electric Vehicles

Abstract: As the penetration of electric vehicles (EVs) is increasing, their efficient charging becomes very important. This paper presents the simulation of various charging algorithms for the Li-Ion Batteries of EVs and their comparison with each other. Various charging algorithms like Constant Current (CC), Constant Voltage (CV), and Constant Current-Constant Voltage (CC/CV) algorithms have been discussed along with various DC-DC charging topologies like the Buck converters and the LLC Resonant Converter have been discussed. Finally, voltage matching algorithm has been proposed, simulated, and incorporated into the CC/CV algorithm and compared to previous results.

Using deep learning to analyse behaviour in video surveillances

Abstract: The use of video survemance has become crucial in, addressing the growing concerns of crime and terrorism in the world, leading to an increased need for automated data processing. This study focuses on the application of Deep Learning (DL) models to extract data from video sequences captured by police cameras. Specifically, it explores the use of DL models for crowd behavior analysis and anomaly detection. The study examines publicly available datasets and cutting-edge studies to classify abnormal behaviors accurately. The practical aspect of the study involves developing a 3D anomaly detection system based on a convolutional feature extractor that combines the strengths of 2D CNNs and RNNs. The proposed feature extractor’s complexity and ability to preserve temporal information improve the quality of data extraction, leading to better classification results than the original model, supporting our hypothesis. Overall, this study demonstrates the effectiveness of DL models in addressing the challenges of anomaly detection in crowds and highlights the potential for future research in this area.

Investigation of the Contents of the Stack Emissions of Iron Ore Sinter Plants With and Without Bag Filter

Abstract: This investigation aims to identify the reasons for the plumes' visibility, compare the stacks with other sinter plant stacks worldwide, and suggest countermeasures to completely stop the visibility of emissions. The appearance of the sinter plant stack emission changes with time and the background color of the sky due to the scattering effect of the sunlight and incidence angle. The flue gas samples were collected at the outlet of the emission control equipment and observed under optical and scanning electron microscopes. The characterization was performed with the help of an electron dispersive spectroscope and mapping technique. The contents of the stack of a sinter plant without a bag filter had much higher levels of PM10, SO2, and NOx. The emissions from all the sinter plants were invariably found to have particulates of SO2 and NOx of size less than 2.5 microns. It is suggested to opt for state-of-the-art fabric filter technology to eliminate PM2.5 emissions also.

Design, Development and Analysis of Aperture monopole patch Antenna for UWB Communication with multiple notched capabilities

Abstract: Abstract Present work illustrate CPW fed apertured monopole patch antenna having multiple interfering bands filtering capabilities. The proposed antenna contains three complementary improved inverted U-shaped slots on the radiating patch to filter out interfering signals namely WiMAX (3.3 to 3.6 GHz), C-band now extended for 5G application (3.7 GHz to 4.2 GHz) and WLAN (5.15 to 5.85 GHz) (combined lower 5.15–5.35 GHz and upper 5.725–5.825 GHz, WLAN). The ground plane is surrounded over the radiator with few modifications on the top corner to enhance impedance matching and hence to obtain optimized overall bandwidth. The projected antenna is made up on substrate of FR-4 (er=4.4) with height of 1.6mm and all the characteristics has been studied with VNA in anechoic chamber environment. The simulated and physically verified responses are in very close treaty to each other. Filtering capability is cross verified with ADS systematic software and lumped-equivalent circuit model also proposed with respective values of all the elements used. Time domain and current distribution analysis has also been undertaken to strengthen the functioning of antenna.

Metasurface-Based Tunable Radar Absorbing Structure for Broadband Applications

Abstract: In this paper, two potential configurations of active tunable metasurface-based radar absorbing structures (RAS) are presented for broadband applications. The proposed meta-atoms have a thin profile with a total thickness of 3.146 mm (approximately λ/10 at 10 GHz) and are composed of resistive patterns etched on RO4835 substrate. Active tuning has been accomplished via PIN diodes loaded at appropriate points on the metasurface. The number of diodes and their locations directly vary the impedance of the unit cell, and consequently, the absorptivity changes due to alteration in the overall quality factor. The proposed RAS models provide superior power absorption over a broad frequency range of 5.5–16.2 GHz (approximately covering C, X, and Ku bands) by adjusting the ON and OFF states of PIN diodes. They have excellent angular stability for oblique incident angles from 0° to 40° and are polarization independent as well due to the symmetric configuration. Further, an insight into the working principle of RAS is also included via an equivalent circuit model (ECM).

Size Reduction

Abstract: Size reduction refers to the process of the formation of small particles with a large surface area. The stress-strain curve of the material determines the energy needed for size reduction with a desirable particle size distribution. The study of equipment used for size reduction and their process parameters helps to reduce the energy supply. In this chapter, we have discussed the theories describing the energy required during milling, and the equipment used for milling including the ball mill, hammer mill, fluid energy mill, cutter mill, and oscillating granulator. Further, we have explained the factors affecting the size reduction process.

Mixing

Abstract: Mixing is an important process in the pharmaceutical industry; it ensures the uniformity of composition among all components by blending them; it is a vital step to achieve dose uniformity. To achieve optimal mixing, factors such as particle size, density, and shape need to be considered, as these can affect the mixing process. The main forces driving the mixing process are convection, diffusion, and shear. The goal of mixing is to reach a state known as a perfect mixture, where the concentration gradient of the drug is zero across the entire mixture. However, this state is unattainable in practice and instead, an acceptable mixture where the concentration gradient is minimal is desired. The rate of mixing follows first-order kinetics. The common equipment used for mixing is a rotating shell blender with and without an agitator, and a stationary shell. Difficulty in achieving blend uniformity of low-dose active ingredients with other excipients is often observed, which could be resolved by using customized approaches. Scale-up is also a significant consideration, and trial-and-error or prior experience are the primary methods for achieving the desired outcome. Another approach, the Froude number method, is a mathematical model that has its own advantages and limitations in the scale-up of mixtures.

Production of Feni Beverage from Cashew Apple and Assessment of Bioethanol Production Potential from the Residual Pulp

Abstract: The cashew tree (Anacardium occidentale), which originated in Brazil but is now grown in many countries, including India, goes by the common name of the cashew nut. In addition to being a delectable snack in many areas of the world, cashew nuts are also rich in protein, fiber, and minerals, including iron, magnesium, and zinc. The cashew nut develops right beneath the pseudofruit (cashew apple) of the cashew plant. Although cashew apples are a very good source of vitamin C and have excellent antioxidant properties, they are usually discarded and not used to make any valuable products since they are so readily perishable. However, the alcoholic drink Feni is made in the Indian state of Goa using discarded ripe cashew apples. Feni has gained extensive popularity due to its unique natural taste, aroma, and high alcohol concentration. Traditionally, cashew Feni production is a relatively laborious and lengthy process that does not require specialized equipment. It is a four-step process consisting of the harvesting of cashew apples, juice extraction through stomping with feet, natural fermentation in earthen pots, and subsequent distillation and condensation in a clay still over a low wood fire. The distilled Feni is then aged for a couple of months and bottled. Over time, due to the underlying drawbacks of the conventional production process, like economic unfeasibility, modifications in its steps have been made by many Feni manufacturers. In this chapter, three such case studies have been elaborately discussed, highlighting some of the process upgradation made by Feni producers to the traditional process. Moreover, the authors examine potential modifications proposed in this chapter to individual steps of the existing process to enhance its yield and augment its economics. In the end, the utilization of residual cashew pulp waste after juice extraction to produce value-added products, including bioethanol, is discussed.

Fluid Bed Processing Technology

Abstract: Fluid bed processing technology is widely used in the pharmaceutical industry for the processing of multiparticulates. The chapter describes the theory of fluidization followed by the components of a fluidized bed processor and their functioning. Further, the formulation, process and equipment-related factors that affect product quality are described in detail. Being a complex process, the process scale-up principles of the processor are discussed.

Effect of Viscoelasticity on the Solidification and Melting of a Phase Change Material

Abstract: In the current work, we simulate the solidification of a phase change material (PCM) inside a square cavity. We consider two different cases: (i) the solidification of a Newtonian fluid and (ii) the solidification of a viscoelastic fluid. The objective is to study the effect of viscoelasticity on the solidification pattern of the fluid. The enthalpy-porosity approach is used for modeling the solidification phenomenon. The log conformation approach is used to calculate the viscoelastic stresses in a stable manner. The numerical method used is second-order accurate in space and time. The results indicate that the viscoelasticity present in the fluid promotes the solidification processes. This can be partly attributed to the extra polymer viscosity and partly due to the elastic stresses present in the viscoelastic fluid. Due to the viscoelastic nature of the fluid, smaller fluid velocities are created in the domain under natural convection. As a result, the hot fluid is circulated at a slower rate in the domain causing faster solidification. The results also show higher values of viscoelastic stresses near the liquid–solid interface and near the hot wall.