Pyrazinium Di(hydrogen sulfate) as a Novel,Highly Efficient and Homogeneous Catalyst for the Condensation of Enolizable Ketones with Aldehydes,Acetonitrile and Acetyl Chloride

A highly efficient protocol for the synthesis of β‐acetamido ketone or ester derivatives in the presence of pyrazinium di(hydrogen sulfate) {Py(OSO₃H)₂} as a novel, green and homogeneous solid acid catalyst at room temperature is described. One‐pot multi‐component condensation of enolizable ketones or alkyl acetoacetates with aldehydes, acetonitrile and acetyl chloride affords the title compounds in high to excellent yields and in relatively short reaction times. In this work, the efficiency of our recently reported solid acid catalyst, saccharin sulfonic acid (Sa‐SO₃H), in the synthesis of β‐acetamido ketones/esters is also studied. Moreover, in this research, some new β‐acetamido ketones and esters (i.e. one complex structure) are prepared.     

An approach to improve the efficiency of polymerization and enhance biological activity of poly(lactide‐co‐ethylene oxide fumarate) hydrogels

The synthesis and purification of poly(lactide ethylene oxide fumarate) (PLEOF) involved using organic solvents and triethylamine, an acid scavenger that produces toxic complexes. These issues were addressed by using potassium carbonate as an alternative acid scavenger and CO₂ gas expanded solution as a media for reaction. Conducting the reaction at these conditions resulted in reducing the number of stages for purification, enhancing the yield of polymerization by 31%, and increasing the fumarate fraction by 110% compared with conventionally produced polymers. Therefore, the capacity of polymer for crosslinking was significantly promoted that resulted in elevating the compression modulus of hydrogel by 119%. Eliminating the toxic chemical residues and strengthening the mechanical property of PLEOF led to enhancement in primary osteoblast cell proliferation on this hydrogel. The new strategy for the synthesis of PLEOF had paramount impact on the characteristics of this polymer and enhanced its biocompatibility for tissue engineering applications, particularly bone repair. © 2014 Wiley Periodicals, Inc. J. Polym. Sci., Part A: Polym. Chem. 2014 , 52, 1291–1299     

Noncommutative Geometry and Classical Orbits of Particles in a Central Force Potential

We investigate the effect of the noncommutative geometry on the classical orbits of particles in a central force potential The relation is implemented through the modified commutation relations [xi,xj] = iθij. Comparison with observations places severe constraints on the value of the noncommutativity parameter.     

Image-guided optical spectroscopy provides molecular-specific information in vivo: MRI-guided spectroscopy of breast cancer hemoglobin, water, and scatterer size

A multimodality instrument that integrated optical or near-infrared spectroscopy into a magnetic resonance imaging (MRI) breast coil was used to perform a pilot study of image-guided spectroscopy on cancerous breast tissue. These results are believed to be the first multiwavelength spectroscopic images of breast cancer using MRI-guided constraints, and they show the cancer tumor to have high hemoglobin and water values, decreased oxygen saturation, and increased subcellular granularity. The use of frequency-domain diffuse tomography methods at many wavelengths provides the spectroscopy required for recovering maps of absorbers and scattering spectra, but the integration with MRI allows these data to be recovered on an image field that preserves high resolution and fuses the two data sets together. Integration of molecular spectroscopy into standard clinical MRI can be achieved with this approach to spectral tomography.     

A New Two-Stage Algorithm for Solving Optimization Problems

Optimization seeks to find inputs for an objective function that result in a maximum or minimum. Optimization methods are divided into exact and approximate (algorithms). Several optimization algorithms imitate natural phenomena, laws of physics, and behavior of living organisms. Optimization based on algorithms is the challenge that underlies machine learning, from logistic regression to training neural networks for artificial intelligence. In this paper, a new algorithm called two-stage optimization (TSO) is proposed. The TSO algorithm updates population members in two steps at each iteration. For this purpose, a group of good population members is selected and then two members of this group are randomly used to update the position of each of them. This update is based on the first selected good member at the first stage, and on the second selected good member at the second stage. We describe the stages of the TSO algorithm and model them mathematically. Performance of the TSO algorithm is evaluated for twenty-three standard objective functions. In order to compare the optimization results of the TSO algorithm, eight other competing algorithms are considered, including genetic, gravitational search, grey wolf, marine predators, particle swarm, teaching-learning-based, tunicate swarm, and whale approaches. The numerical results show that the new algorithm is superior and more competitive in solving optimization problems when compared with other algorithms.     

Modeling adsorption in binary associating solvents using the extended MPTA model

Application of the MPTA model has been extended to associative liquid adsorption. The MPTA model describes fluid–fluid interactions using an equation of state (EoS) term, and fluid–solid interactions using a potential equation. In order to extend the application to associative liquid adsorption, an association term has been considered for fluid–fluid interactions. Sixteen binary mixtures containing associating and non-associating components in equilibrium with various adsorbents have been studied; fluid–fluid interactions have been modeled using the Peng–Robinson, Soave–Redlich–Kwong, volume-translated SRK and CPA equations of state, while the effects of fluid–solid interactions have been taken into account using Dubinin–Radushkevich–Astakhov (DRA) and Steele potential functions. The model parameters have been obtained by fitting the model to experimental data on surface excess. For the studied systems, the accuracy of fitted isotherms has been found to be more dependent on the fluid–solid potential equation rather than the applied EoS. Calculations show that the SRK equation is a suitable choice for non-associating systems, while the CPA equation is found to be more appropriate for associating systems, as would be expected. The results also show that the Steele potential function is in better agreement with experimental data than the DRA potential function.     

Preparation and characterization of multi-walled carbon nanotubes (MWCNTs), functionalized with phosphonic acid (MWCNTs–C–PO3H2) and its application as a novel,efficient, heterogeneous,highly selective and reusable catalyst for acetylation of alcohols,phenols, aromatic amines,and thiols

A novel, efficient, heterogeneous, and reusable multi-walled carbon nanotubes (MWCNTs), functionalized with phosphonic acid (MWCNTs–C–PO₃H₂) has been synthesized. The synthesized CNTs were characterized using some electron microscopic techniques such as scanning electron microscopy (SEM), atomic force microscopy (AFM), Energy dispersive X-ray spectroscopy (EDAX), and also some thermal and spectroscopic methods such as thermogravimetry (TG). The nitrogen adsorption behavior of the MWCNTs–C–PO₃H₂ catalyst was evaluated using the TG instrumentation system at 25 °C. The catalyst was applied successfully for highly efficient and selective acetylation of alcohols, phenols, thiols and aromatic amines with acetic anhydride at room temperature under solvent-free conditions. The reusability of the catalyst was checked and the recovered catalyst was reused for five runs without significant loss in activity.     

A new colorimetric assay for amylase based on starch-supported Cu/Au nanocluster peroxidase-like activity

In this paper, we present a new colorimetric technique as a novel assay for the easy and direct detection of α-amylase activity. This detection system utilizes the interaction of α-amylase with starch that is supporting copper/gold (Cu/Au) nanoclusters. The Cu/Au nanoclusters are synthesized using starch as a stabilizing agent at room temperature. These nanoclusters show robust peroxidase-like activity and are able to catalyze the oxidation of TMB (3,3,5,5-tetramethylbenzidine) in the presence of hydrogen peroxide (H₂O₂), leading to the generation of a blue-colored solution. The α-amylase detection mechanism is based on the digestion of the starch by α-amylase, which results in nanocluster aggregation, leading to increased nanoparticle size and thus decreased peroxidase-like activity of the Cu/Au NCs. Experiments showed that the gradual addition of α-amylase causes the peroxidase activity to decrease step by step in a linear fashion. Using this method, colorimetric sensing of α-amylase was achieved with a detection limit (LOD) of 0.04 U/mL and a linear range of 0.1–10 U/mL. This method is significantly selective for α-amylase and could be affordably and conveniently applied to the detection of α-amylase in blood serum.

Graphical Abstract

     

Theoretical insight to the complexation of some transition metals with cryptand

The most practicable complexes formed between Cryptand[2.2.2] and hydrated Mn(II), Fe(II), Co(II), Ni(II), Cu(II), and Zn(II) cations (denoted as [ML]⁺²) were modeled using computational chemistry methods. The energies of complexation reactions were calculated in both gas phase and solution at B3LYP/6-31+G(d) and B3LYP/6-311++G(3df,2pd) levels of theory. The accuracy of selected computational methods was confirmed with comparison between available X-ray data and computational results. The results suggested that [CuL]⁺² and [CoL]⁺² structures could be the most and the least stable systems, respectively. The nature of metal-ligand interactions based on quantum theory of atoms in molecule (QTAIM) was discussed for all the complexes. This analysis confirmed the ionic nature of metal-ligand interactions due to electron density values for M-O bonds and M-N interactions. Natural bond orbital (NBO) and natural energy decomposition analysis (NEDA) were utilized to explain more details of interaction between divalent cations and donor atoms of the ligand.

     

Nickel and cobalt ferrites nanoparticles: synthesis,study of magnetic properties and their use as magnetic adsorbent for removing lead(II) ion

Nano-sized nickel ferrite (NiFe₂O₄) and cobalt ferrite particles (CoFe₂O₄) were successfully synthesized using a hydrothermal method. Techniques of X-ray diffraction, scanning electron microscope, Fourier transform infrared spectrometer, energy dispersive X-ray spectroscopy, vibrating sample magnetometer and transmission electron microscope have been used to characterize and study the as-synthesized NiFe₂O₄ and CoFe₂O₄ products. The results showed that the average size of the nickel and cobalt ferrite nanoparticles is smaller than 10 and 100 nm, respectively. The results of magnetic measurement showed that the synthesized NiFe₂O₄ and CoFe₂O₄ nanoparticles were superparamagnetic and soft ferromagnetic materials, respectively. Study of adsorption behavior showed that these nanoparticles can act as a good adsorbent for removing Pb²⁺.