Preparation and characterization of new inorganic–organic hybrid catalyst H3PMo12O40/Hyd‐SBA‐15 and its application in the domino multi‐component reaction

We present novel inorganic–organic hybrid catalyst to accomplish domino multi‐component reaction (MCR) for synthesis of 3‐amino‐2′‐oxospiro[benzo[c]pyrano[3,2‐a]phenazine‐1,3′‐indoline]‐2‐carbonitrile/carboxylate derivatives. This methodology offers remarkable development by easy production of H₃PMo₁₂O₄₀/Hyd‐SBA‐15 in regard to solving the problem of using harsh catalysts, also it demonstrates to be impressive and environmentally friendly in term of low reaction times and high yields.     

Nonlocal beam theory for nonlinear vibrations of embedded multiwalled carbon nanotubes in thermal environment

A nonlocal elastic beam model is developed to investigate the small scale effects on the large-amplitude vibration analysis of embedded multiwalled carbon nanotubes (MWCNTs) at an elevated temperature. The nested slender nanotubes are coupled with each other through the van der Waals (vdW) interlayer interaction. The curvature-dependent vdW force employed incorporates not only pairwise nearest-neighbor but also nonneighbor interactions between nested nanotubes. The incremental harmonic balance method is adopted to analytically solve the nonlinear equations that are governed by the vibrations of nested nanotubes. The influences of small scale parameter, geometrical parameters, temperature rise, and the elastic medium are fully examined.     

Predictive control of uncertain nonlinear parabolic PDE systems using a Galerkin/neural-network-based model

In this paper, a model predictive control (MPC) scheme for a class of parabolic partial differential equation (PDE) systems with unknown nonlinearities, arising in the context of transport-reaction processes, is proposed. A spatial operator of a parabolic PDE system is characterized by a spectrum that can be partitioned into a finite slow and an infinite fast complement. In this view, first, Galerkin method is used to derive a set of finite dimensional slow ordinary differential equation (ODE) system that captures the dominant dynamics of the initial PDE system. Then, a Multilayer Neural Network (MNN) is employed to parameterize the unknown nonlinearities in the resulting finite dimensional ODE model. Finally, a Galerkin/neural-network-based ODE model is used to predict future states in the MPC algorithm. The proposed controller is applied to stabilize an unstable steady-state of the temperature profile of a catalytic rod subject to input and state constraints.     

Mo (CO)6‐assisted Pd‐supported magnetic graphene oxide‐catalyzed carbonylation‐cyclization as an efficient way for the synthesis of 4(3H)‐quinazolinones

In this paper, a novel catalyst is introduced based on the immobilization of palladium on modified magnetic graphene oxide nanoparticles. The catalyst is characterized by several methods, including transmission electron microscopy, scanning electron microscopy, X‐ray fluorescence, vibrating‐sample magnetometer, Fourier transform‐infrared and dynamic light scattering (DLS) analysis. The activity of the catalyst was investigated in the synthesis of 4(3H)‐quinazolinones via Pd‐catalyzed carbonylation‐cyclization of N‐(2‐bromoaryl) benzimidamides by Mo (CO)₆. The Mo (CO)₆ is used as a carbon monoxide source for performing the reaction under mild conditions. The catalyst showed good reusability, and no change in activity was observed after 10 cycles of recovery.     

Optimization of cadmium adsorption from aqueous solutions by functionalized graphene and the reversible magnetic recovery of the adsorbent using response surface methodology

Novel functionalized graphene adsorbent was prepared and characterized using different techniques. The prepared adsorbent was applied for the removal of cadmium ions from aqueous solution. A response surface methodology was used to evaluate the simple and combined effects of the various parameters, including adsorbent dosage, pH, and initial concentration. Under the optimal conditions, the cadmium removal performance of 70% was achieved. A good agreement between experimental and predicted data in this study was observed. The experimental results revealed of cadmium adsorption with high linearity follow Langmuir isotherm model with maximum adsorption capacity of 502 mg g^?1, and the adsorption data fitted well into pseudo‐second order model. Thermodynamic studies showed that adsorption process has exothermic and spontaneous nature. The recommended optimum conditions are: cadmium concentration of 970 mg L^?1, adsorbent dosage of 1 g L^?1, pH of 6.18, and T = 25 °C. The magnetic recovery of the adsorbent was performed using a magnetic surfactant to form a noncovalent magnetic functionalized graphene. After magnetic recovery of the adsorbent both components (adsorbent and magnetic surfactant) were recycled by tuning the surface charges through changing the pH of the solution. Desorption behavior studied using HNO₃ solution indicated that the adsorbent had the potential for reusability.     

Starch nanoparticles as a bio-nanocatalyst in synthesis of diheteroaryl thioethers

Nanostarch is shown to be a highly efficient, eco-friendly and heterogenous organocatalyst for the synthesis of the diheteroaryl thioethers via one-pot reaction of methylcarbonyls, thiourea and iodine in DMSO. This method offers significant advantages such as available starting materials, higher purity and excellent yield of products, very easy reaction conditions and absence of any tedious purification. Furthermore, because of employing eco-friendly catalyst without using transition metal catalysts, this novel method emerges as a green-approach leading to less harmful residues. Moreover, a mechanism was proposed to rationalize the reaction and the role of starch nanoparticles was also investigated in these transformations.