Numerical study of hydrodynamic flow of a Casson nanomaterial past an inclined sheet under porous medium

The main aim of the current paper is to investigate the mass and heat transportation of a Casson nanomaterial generated by the inclination of the surface. The magnetic field effect along with suction or injection are considered. The working nanomaterial is taken into consideration based on the concept of the Buongiorno nanofluid theory, which explores the thermal efficiencies of liquid flows under movement of Brownian and thermophoretic phenomena. The emergent system of differential expressions is converted to dimensionless form with the help of the appropriate transformations. This system is numerically executed by the implementation of Keller–Box and Newton's schemes. A good agreement of results can be found with the previous data in a limiting approach. The behavior of the physical quantities under concern, including energy exchange, Sherwood number, and wall shear stress are portrayed through graphs and in tabular form. The Nusselt number and Sherwood number are found to diminish against the altered magnitudes of Brownian motion and the inclination parameter. Moreover, the velocity profile decreases with the growth of the inclination effect. In the same vein, the buoyancy force and solutal buoyancy effects show a direct relation with the velocity field. The outcomes have promising technological uses in liquid‐based systems related to stretchable constituents.     

Melting heat transfer analysis of electrically conducting nanofluid flow over an exponentially shrinking/stretching porous sheet with radiative heat flux under a magnetic field

Modern magnetic nanomaterial processing operations are progressing rapidly and require increasingly sophisticated mathematical models for their optimization. Stimulated by such developments, in this paper, a theoretical and computational study of a steady magnetohydrodynamic nanofluid over an exponentially stretching/shrinking permeable sheet with melting (phase change) and radiative heat transfer is presented. Besides, wall transpiration, that is, suction and blowing (injection), is included. This study deploys Buongiorno's nanofluid model, which simulates the effects of the Brownian motion and thermophoresis. The transport equations and boundary conditions are normalized via similarity transformations and appropriate variables, and the similarity solutions are shown to depend on the transpiration parameter. The emerging dimensionless nonlinear coupled ordinary differential boundary value problem is solved numerically with the Newton-Fehlberg iteration technique. Validation with special cases from the literature is included. The increase in the magnetic field, that is, the Hartmann number, is observed to elevate nanoparticle concentration and temperature, whereas it dampens the velocity. Higher values of the melting parameter consistently decelerate the boundary layer flow and suppress temperature and nanoparticle concentration. A higher radiative parameter strongly increases temperature (and thermal boundary layer thickness) and weakly accelerates the flow. The increase in the Brownian motion reduces nanoparticle concentrations, whereas a greater thermophoretic body force strongly enhances them. The Nusselt number and Sherwood number are observed to be decreased with an increasing Hartmann number, whereas they are elevated with a stronger wall suction and melting parameter.     

Catalytic steam reforming of tar for enhancing hydrogen production from biomass gasification: a review

Presently, the global search for alternative renewable energy sources is rising due to the depletion of fossil fuel and rising greenhouse gas (GHG) emissions. Among alternatives, hydrogen (H₂) produced from biomass gasification is considered a green energy sector, due to its environmentally friendly, sustainable, and renewable characteristics. However, tar formation along with syngas is a severe impediment to biomass conversion efficiency, which results in process-related problems. Typically, tar consists of various hydrocarbons (HCs), which are also sources for syngas. Hence, catalytic steam reforming is an effective technique to address tar formation and improve H₂ production from biomass gasification. Of the various classes in existence, supported metal catalysts are considered the most promising. This paper focuses on the current researching status, prospects, and challenges of steam reforming of gasified biomass tar. Besides, it includes recent developments in tar compositional analysis, supported metal catalysts, along with the reactions and process conditions for catalytic steam reforming. Moreover, it discusses alternatives such as dry and autothermal reforming of tar.     

Preliminary Structural Data Revealed That the SARS-CoV-2 B.1.617 Variant's RBD Binds to ACE2 Receptor Stronger Than the Wild Type to Enhance the Infectivity

The evolution of new SARS-CoV-2 variants around the globe has made the COVID-19 pandemic more worrisome, further pressuring the health care system and immunity. Novel variations that are unique to the receptor-binding motif (RBM) of the receptor-binding domain (RBD) spike glycoprotein, i. e. L452R-E484Q, may play a different role in the B.1.617 (also known as G/452R.V3) variant's pathogenicity and better survival compared to the wild type. Therefore, a thorough analysis is needed to understand the impact of these mutations on binding with host receptor (RBD) and to guide new therapeutics development. In this study, we used structural and biomolecular simulation techniques to explore the impact of specific mutations (L452R-E484Q) in the B.1.617 variant on the binding of RBD to the host receptor ACE2. Our analysis revealed that the B.1.617 variant possesses different dynamic behaviours by altering dynamic-stability, residual flexibility and structural compactness. Moreover, the new variant had altered the bonding network and structural-dynamics properties significantly. MM/GBSA technique was used, which further established the binding differences between the wild type and B.1.617 variant. In conclusion, this study provides a strong impetus to develop novel drugs against the new SARS-CoV-2 variants.     

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.     

Direct Formation of Titanium Carbide via In Situ Carbothermal Reduction of TiO2/Carbon Cladding for Coating Application

Protection of Metals and Physical Chemistry of Surfaces - In situ direct formation of titanium carbide (TiC) was realized via tungsten inert gas (TIG) arc surface cladding using titanium dioxide...     

Innovative nano silicone wax coatings for the conservation of bronze artifacts from corrosion

Journal of Applied Electrochemistry - Herein we studied the efficiency of a protective transparent and reversible nano silicone wax coatings (NSW) to protect bronze artifacts extracted from...     

Performance analysis of three advanced controllers for polymerization batch reactor: An experimental investigation

The performances of three advanced non-linear controllers are analyzed for the optimal set point tracking of styrene free radical polymerization (FRP) in batch reactors. The three controllers are the artificial neural network-based MPC (NN-MPC), the artificial fuzzy logic controller (FLC) as well as the generic model controller (GMC). A recently developed hybrid model (Hosen et al., 2011a. Asia-Pac. J. Chem. Eng. 6(2), 274) is utilized in the control study to design and tune the proposed controllers. The optimal minimum temperature profiles are determined using the Hamiltonian maximum principle. Different types of disturbances are introduced and applied to examine the stability of controller performance. The experimental studies revealed that the performance of the NN-MPC is superior to that of FLC and GMC.