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.     

Study of pure and semileptonic decays of Ds meson within R-parity violating supersymmetric model

We present the comaprative study of semileptonic and leptonic decays of Ds, D±and D0meson（D →M l＋-αl-β, D → l＋αlβ, D → l＋αvα;α,β=e,μ） within the framework of R-parity violating the（ Rp） Minimal Supersymmetric Standard Model（MSSM）. The comparison shows that combination and product couplings,（λβiα λ＊ ij qor λβqkλ＊αj k）contribution to the branching fractions of the said processes（under consideration） is consistent with or comparable to the experimental measurements in most of the cases. However, some cases exist where these contributions are highly suppressed. We identify such cases in our analysis and single out the important ones suitable for exploring in the future and current experiments.     

Recent Developments in Flow Injection/Sequential Injection Liquid-Liquid Extraction for Atomic Spectrometric Determination of Metals and Metalloids

Abstract

This review aims to provide a critical overview of automated flow injection and sequential injection liquid-liquid extraction for preconcentration and/or separation of ultra-trace metal and metalloid species hyphenated with atomic spectrometric detection systems, including some new trends and applications in the subbranches of cloud point extraction (CPE), wetting film extraction (WFE), supported liquid membrane extraction (SLME), extraction chromatography (EChr), and liquid-phase microextraction (LPME) techniques. The analytical performance of flow-injection/sequential injection liquid-liquid extraction methods is markedly affected by the components of the flow network such as segmentor, extraction coil, and phase separator. Thus, an overall presentation of system components along with some novel strategies for interface with atomic spectrometers is discussed and exemplified with selected applications.     

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.     

Synthesis and design of polyurethane and its nanocomposites derived from canola-castor oil: Mechanical,thermal and shape memory properties

The recent global pandemic and its tremendous effect on the price fluctuations of crude oil illustrates the side effects of petroleum dependency more evident than ever. Over the past decades, both academic and industrial communities spared endless efforts in order to replace petroleum-based materials with bio-derived resources. In the current study, a series of shape memory polymer composites (SMPC's) was synthesized from epoxidized vegetable oils, namely canola oil and castor oil fatty acids (COFA's) as a 100% bio-based polyol and isophorone diisocyanate (IPDI) as an isocyanate using a solvent/catalyst-free method in order to eventuate polyurethanes (PU's). Thereafter, graphene oxide (GO) nanoplatelets were synthesized and embedded in the neat PU in order to overcome the thermomechanical drawbacks of the neat matrix. The chemical structure of the synthesized components, as well as the dispersion and distribution levels of the nanoparticles, was characterized. In the following, thermal and mechanical properties as well as shape memory behavior of the specimens were comprehensively investigated. Likewise, the thermal conductivity was determined. This study proves that synthesized PU's based on vegetable oil polyols, including graphene nanoparticles, exhibit proper thermal and mechanical properties, which make them stand as a potential candidate to compete with traditional petroleum-based SMPC's.