Developing pressure sensors from impregnated textile sandwiched in inkjet-printed electrodes

Journal of Materials Science: Materials in Electronics - This work presents an interesting fabrication route toward development of pressure sensing patch by utilizing electrically conductive cotton...     

Emergency decision support modeling for COVID-19 based on spherical fuzzy information

Significant emergency measures should be taken until an emergency event occurs. It is understood that the emergency is characterized by limited time and information, harmfulness and uncertainty, and decision-makers are always critically bound by uncertainty and risk. This paper introduces many novel approaches to addressing the emergency situation of COVID-19 under spherical fuzzy environment. Fundamentally, the paper includes six main sections to achieve appropriate and accurate measures to address the situation of emergency decision-making. As the spherical fuzzy set (FS) is a generalized framework of fuzzy structure to handle more uncertainty and ambiguity in decision-making problems (DMPs). First, we discuss basic algebraic operational laws (AOLs) under spherical FS. In addition, elaborate on the deficiency of existing AOLs and present three cases to address the validity of the proposed novel AOLs under spherical fuzzy settings. Second, we present a list of Einstein aggregation operators (AgOp) based on the Einstein norm to aggregate uncertain information in DMPs. Thirdly, we are introducing two techniques to demonstrate the unknown weight of the criteria. Fourthly, we develop extended TOPSIS and Gray relational analysis approaches based on AgOp with unknown weight information of the criteria. In fifth, we design three algorithms to address the uncertainty and ambiguity information in emergency DMPs. Finally, the numerical case study of the novel carnivorous (COVID-19) situation is provided as an application for emergency decision-making based on the proposed three algorithms. Results explore the effectiveness of our proposed methodologies and provide accurate emergency measures to address the global uncertainty of COVID-19.     

Extraction optimisation,antioxidant activity and inhibition on α-amylase and pancreatic lipase of polyphenols from the seeds of Syzygium cumini

The objectives of this study were to determine the optimal extraction conditions of polyphenols from Syzygium cumini seeds by response surface methodology and investigate their antioxidant activity and inhibition on α-amylase and pancreatic lipase. As results, the optimal extraction conditions in the ultrasonic extraction process which maximised total polyphenols content, minimised the IC₅₀ values of α-amylase and pancreatic lipase were determined as follows: extraction time 60 min, ethanol concentration 63% and solvent/solid ratio 44 mL g⁻¹. The main phenolic compounds in partially purified fraction of Syzygium cumini seeds were catechin, epicatechin, kaempferol, gallic, 5-caffeoylquinic, caffeic and ferulic acids. In addition, the partially purified fraction inhibited 87.66 ± 5.55 and 86.61 ± 3.15% of α-amylase and pancreatic lipase, respectively. The results suggested that Syzygium cumini seeds could be explored as a natural antioxidant and could be used as a source of highly antidiabetic and anti-obesity bioactive compounds.     

Thin-film iron-oxide nanobeads as bifunctional electrocatalyst for high activity overall water splitting

Developing only Fe derived bifunctional overall water splitting electrocatalyst both for oxygen evolution reaction (OER) and hydrogen evolution reaction (HER) while performing at low onset overpotential and with high catalytic stability is a rare instance. We present here the first demonstration of unique iron-oxide nanobeads (FeO_x-NBs) based electrocatalyst executing both OER and HER with high activity. Thin-film electrocatalytic FeO_x-NBs assembly is surface grown via simple spray coating (SC). The unique SC/FeO_x-NBs propels OER initiating water oxidation just at 1.49 V_RHE (η = 260 mV) that is the lowest observable onset potential for OER on simple Fe-oxide based catalytic films reported so far. Catalyst also reveals decently high HER activity and competent overall water splitting performance in the FeO_x-NBs two-electrode system as well. Catalyst also presents stable kinetics, with promising high electrochemically active surface area (ECSA) of 1765 cm², notable Tafel slopes of just 54 mV dec^1? (OER) and 85 mV dec^1? (HER), high exchange current density of 1.10 mA cm^2? (OER), 0.58 mA cm^2? (HER) and TOF of 74.29s^1?@1.58V_RHE, 262s^1?@1.62V_RHE (OER) and 82.5s^1?@-0.45V_RHE, 681s^1?@-0.56V_RHE (HER).     

Recent developments in catalyst synthesis using DBD plasma for reforming applications

The catalyst has a significant role in gas processing applications such as reforming technologies for H₂ and syngas production. The stable catalyst is requisite for any industrial catalysis application to make it commercially viable. Several methods are employed to synthesize the catalysts. However, there is still a challenge to achieve a controlled morphology and pure catalyst which majorly influences the catalytic activity in reforming applications. The conventional methods are expansive, and the removal of the impurities are major challenges. Nevertheless, it is not straightforward to achieve the desired structure and stability. Therefore, significant interest has been developed on the advanced techniques to take control of the physicochemical properties of the catalyst through non-thermal plasma (NTP) techniques. In this review, the systematic evolution of the catalyst synthesis using NTP technique is elucidated. The emerging DBD plasma to synthesized and effective surface treatment is reviewed. DBD plasma synthesized catalyst performance in reforming application for H₂ and syngas production is summarised. Furthermore, the status of DBD plasma for catalyst synthesis and proposed future avenues to design environmentally suitable and cost-effective synthesis techniques are discussed.     

Sink-oriented tree based data dissemination protocol for mobile sinks wireless sensor networks

Wireless Networks - Data dissemination toward static sinks causes the nearby nodes to deplete their energy quicker than the other nodes in the field (i.e., this is referred to as the hotspot...     

A simulation study of reduction kinetics for sponge iron production in a rotary hearth furnace

ABSTRACT

A mathematical model has been developed by coupling genetic algorithm (GA) with heat and material balance equations to estimate rate parameters and solid-phase evolution related to the reduction of iron ore-coal composite pellets in a multi-layer bed Rotary hearth Furnace (RHF). The present process involves treating iron ore-coal composite pellets in a crucible over the hearth in RHF. The various solid phases evolved at the end of the process are estimated experimentally, and are used in conjunction with the model to estimate rate parameters. The predicted apparent activation energy for the wustite reduction step is found to be lower than those of the reduction of higher oxides. The thermal efficiency is found to decrease significantly with an increase in the carbon content of the pellet. Thermal efficiency was also found to increase mildly up to three layers. Multilayer bed remains as a potential design parameter to increase thermal efficiency.     

Numerical simulation of the effects of elastic anisotropy and grain size upon the machining of AA2024

Turning modeling and simulation of different metallic materials using the commercially available Finite Element (FE) softwares is getting prime importance because of saving of time and money in comparison to the costly experiments. Mostly, the numerical analysis of machining process considers a purely isotropic behavior of metallic materials; however, the literature shows that the elastic crystal anisotropy is present in most of the ‘so-called’ isotropic materials. In the present work, the elastic anisotropy is incorporated in the FE simulations along with the effect of grain size. A modified Johnson-Cook ductile material model based on coupled plasticity and damage evolution has been proposed to model the cutting process. The simulation results were compared with experimental data on the turning process of Aluminum alloy (AA2024). It was found that the elastic anisotropy influences the average cutting force up to 5% as compared to the isotropic models while the effect of grain size was more pronounced up to 20%.