Synthesis of New Pyrimidine,Quinazoline and Diazatricyclo Derivatives by Multicomponent Reaction and Evaluation of Their Biological Activity

Abstract

A series of new pyrimidine and quinazoline derivatives was synthesized by a Biginelli-like reaction of urea/thiourea, aldehyde, and ketone in the presence of hydrochloric acid as a catalyst. In a similar way, some novel diazatricyclo derivatives were obtained via a Biginelli-like reaction followed by an intramolecular Michael-type addition. The yields of products were reasonable after recrystallization from ethanol. All newly synthesized compounds were characterized using IR and NMR (¹H and ¹³C) spectroscopy and elemental analysis. The antibacterial activity of these compounds was investigated against Staphylococcus aureus (RTCC, 1885), and Escherichia Coli (ATCC, 35922).

Supplemental materials are available for this article. Go to the publisher's online edition of Phosphorus, Sulfur, and Silicon and the Related Elements to view the free supplemental file.     

1,3-Migration of Trimethylsilyl Group from Carbon to Oxygen in Highly Sterically Hindered Silanol of the Type (Me 3 Si) 3 CSi(C 6 H 4 Me- p )MeOH and Reaction of the Related Iodide with Iodine Monochloride and Iodine Monobromide

The silanol (Me 3 Si) 3 CSi(C 6 H 4 Me- p )MeOH has been shown to isomerize to (Me 3 Si) 2 CHSi(C 6 H 4 Me- p )(Me)(OSiMe 3 ) when it was kept at room temperature for 10 h in 0.2 M NaOMe/MeOH. Corresponding isomerizations of the above silanol (to give (Me 3 Si) 2 CHSi(C 6 H 4 Me- p ) (Me)(OSiMe 3 )) are complete after 26 h under reflux in pyridine. The reaction involve 1,3-migration from carbon to oxygen within a silanolate ion to give a carbanion, which rapidly acquires a proton from the solvent. Treatment of (Me 3 Si) 3 CSi(C 6 H 4 Me- p )MeOH with MeLi in Et 2 O/THF give, by the same rearrangement, the organolithium reagent (Me 3 Si) 2 CLiSi(C 6 H 4 Me- p )(Me)(OSiMe 3 ) which on treatment with Me 2 SiHCl gives (Me 3 Si) 2 C(SiMe 2 H)Si(C 6 H 4 Me- p )(Me)(OSiMe 3 ) and (Me 3 Si) 2 CHSi(C 6 H 4 Me- p )(Me)(OSiMe 3 ). When the experiment was repeated, but with Me 3 SiCl in place of Me 2 SiHCl, it gives exclusively (Me 3 Si) 2 CHSi(C 6 H 4 Me- p )(Me)(OSiMe 3 ). Treatment of the organolithium reagent (Me 3 Si) 2 CLiSi(C 6 H 4 Me- p )(Me)(OSiMe 3 ) with Mel gives exclusively (Me 3 Si) 2 CMeSi(C 6 H 4 Me- p )(Me)(OSiMe 3 ). The related iodide (Me 3 Si) 3 CSi(C 6 H 4 Me- p )Mel reacts with ICI and IBr to give rearranged (Me 3 Si) 2 C(SiMe 2 X)Si(C 6 H 4 Me- p )Me 2 and unrearranged products (Me 3 Si) 3 CSi(C 6 H 4 Me- p )MeX, (X = Cl, Br) respectively. The rearranged bromide (Me 3 Si) 2 C(SiMe 2 Br)Si(C 6 H 4 Me- p )Me 2 reacts with a range of silver [I] salts AgY (Y = OOCCH 3 , SO 4 2 m ) and Mercury [II] salt HgY 2 (Y = OOCCH 3 , SO 4 2 m ) in glacial CH 3 COOH to give the corresponding species (Me 3 Si) 2 C(SiMe 2 OOCCH 3 )Si(C 6 H 4 Me- p )Me 2 . The reaction of the bromide with AgBF 4 in MeOH or i -PrOH give the corresponding rearranged products (Me 3 Si) 2 C(SiMe 2 Y)Si(C 6 H 4 Me- p )Me 2 (Y = --OMe, --OPr i ).     

The Formation of Porous Membranes by Filtration of Aerosol Nanoparticles

Flame-generated aerosol particles of Al₂O₃ were deposited by gas filtration on two types of porous and ceramic tubes of -Al₂O₃ with mean pore diameters of 450 and 2700nm, respectively. The particles were aggregates with average mobility diameters in the range of 30–100nm and primary particle diameters of 4–8nm. The particles are characterized by differential mobility analysis, transmission electron microscopy, and by their specific surface area. The deposited membranes are characterized by gas permeability measurements, scanning electron microscopy, and by their pore size distribution from nitrogen capillary condensation. The particles form a distinct, homogeneous membrane layer with a porosity of 90% on top of the substrate surface and only penetrate slightly into the substrate structure. The mean pore sizes of the deposited membranes determined by nitrogen condensation agree approximately with those determined by gas permeation and the specific surface area. The mean pore diameter varies in the range of 30–70nm. The gas permeability of the deposited membranes is related to the specific surface area but influenced by the high porosity. The mean pore size and the permeability of the membranes are almost independent of the substrate structure.The development of a membrane with uniform properties is preceded by a short initial period in which the deposited particles, with an equivalent membrane thickness of roughly 2m, have a significantly lower permeability than the ultimately developed uniform membrane layer. This effect is particularly significant for the aerosol particles with the lowest mean size, probably due to particles deposited in the pore mouths of the substrate.The particles and the deposited membranes are X-ray amorphous but retain their specific surface area on heating to even high temperatures. When the membranes are heated to 1473K for 10h, X-ray diffraction shows a mixture of - and -alumina, accompanied by a partial disintegration of the membrane and a considerable loss of surface area.     

Evaluation of fuzzy regression models by fuzzy neural network

In this paper, a novel hybrid method based on fuzzy neural network for approximate fuzzy coefficients (parameters) of fuzzy linear and nonlinear regression models with fuzzy output and crisp inputs, is presented. Here a neural network is considered as a part of a large field called neural computing or soft computing. Moreover, in order to find the approximate parameters, a simple algorithm from the cost function of the fuzzy neural network is proposed. Finally, we illustrate our approach by some numerical examples.     

Fuzzy polynomial regression with fuzzy neural networks

Recently, fuzzy linear regression is considered by Mosleh et al. [1]. In this paper, a novel hybrid method based on fuzzy neural network for approximate fuzzy coefficients (parameters) of fuzzy polynomial regression models with fuzzy output and crisp inputs, is presented. Here a neural network is considered as a part of a large field called neural computing or soft computing. Moreover, in order to find the approximate parameters, a simple algorithm from the cost function of the fuzzy neural network is proposed. Finally, we illustrate our approach by some numerical examples.     

Community detection in social networks based on improved Label Propagation Algorithm and balanced link density

Nowadays, community detection has been raised as one of the key research areas in the online social networks mining. One of the most common algorithms in this field is label propagation algorithm (LPA). Even though the LPA method has advantages such as simplicity in understanding and implementation, as well as linear time complexity, it has an important disadvantage of the uncertainty and instability in outcomes, that is, the algorithm detects and reports different combinations of communities in each run. This problem originates from the nature of random selection in the LPA method. In this paper, a novel method is proposed based on the LPA method and the inherent structure, that is, link density feature, of the input network. The proposed method uses a sensitivity parameter (balance parameter); by choosing the appropriate values for it, the desired qualities of the identified communities can be achieved. The proposed method is called Balanced Link Density-based Label Propagation (BLDLP). In comparison with the basic LPA, the proposed method has an advantage of certainty and stability in the output results, whereas its time complexity is still comparable with the basic LPA and of course lowers than many other approaches. The proposed method has been evaluated on real-world known datasets, such as the Facebook social network and American football clubs, and by comparing it with the basic LPA, the effectiveness of the proposed method in terms of the quality of the communities found and the time complexity has been shown.     

A reduced-order model manifold technique for automated structural defects judging using the PGD with analytical validation

Automation is conquering new fields on a daily basis. Aiming for faster and more reliable products, industrials as well as researchers are oriented into automation. Non-destructive testing as well as defect quantification is not an exception. In fact, decisions with minimum allowable error are sought in real-time when facing any potential defect. In this work, we suggest a comprehensive method based on model order reduction techniques to judge if a structure shall be salvaged. The real-time decision is based on multidimensional parametric simulation, performed offline, using the Proper Generalized Decomposition (PGD). The PGD is a model order reduction technique that allows circumventing the curse of dimensionality by using domain decomposition. Therefore, the 6D simulation illustrated in this paper is performed within a few minutes on a standard laptop. Later on, a stress concentration manifold is built and used online for decision-making. The manifold is validated on a few selected solutions solved analytically using an analytical procedure. The aforementioned procedure is developed, in this paper, to calculate the tangential stress around circular holes of different sizes, in an infinite isotropic plate containing any number of holes and subjected to in-plane pressure loading at the tip of the infinite plate. The procedure is based on determining two Muskhelishvili complex potentials in terms of complex Fourier series, and applying the Schwartz alternating method repeatedly until the boundary conditions on the contour of every hole are satisfied.     

Sonophotocatalytic treatment of diazinon using visible light‐driven Ce:Cu‐1,4‐BDOAH2 photocatalyst in a batch‐mode process: Response surface methodology and optimization

Cu–1,4‐benzenedioxyacetic acid (Cu‐1,4‐BDOAH₂) with a narrow band gap (2.52 eV) was synthesized and doped with Ce to afford Ce:Cu‐1,4‐BDOAH₂ as an efficient photocatalyst with narrower band gap (2.39 eV). The prepared Cu‐1,4‐BDOAH₂ and Ce:Cu‐1,4‐BDOAH₂ were characterized using Fourier transform infrared, energy‐dispersive X‐ray, diffuse reflectance spectroscopies, scanning electron microscopy and X‐ray diffraction. The sonophotocatalytic degradation of diazinon was carried out in a batch‐mode reactor using visible light‐driven Ce:Cu‐1,4‐BDOAH₂ photocatalyst as well as ultrasonic irradiation. The narrow band gap of the photocatalyst means that it can be activated under visible light illumination. The effects of operational parameters such as initial diazinon concentration (5–25 mg l^?1), pH (2–10), photocatalyst dosage (10–30 mg) and irradiation time (10–30 min) on the sonophotocatalytic degradation efficiency were investigated using central composite design under response surface methodology. The optimization process was studied using desirability function and the results indicated 99.8% degradation, which was obtained at optimum values of 25 mg l^?1, 6, 20 mg and 20 min for the initial concentration of diazinon, pH, photocatalyst dosage and irradiation time, respectively. Reusability experiments of Ce:Cu‐1,4‐BDOAH₂ photocatalyst showed that it is quite stable with excellent catalytic activity even after five cycles.     

A review on the applications of micro-/nano-encapsulated phase change material slurry in heat transfer and thermal storage systems

Journal of Thermal Analysis and Calorimetry - In modern heat transfer systems, thermal storage not only causes the balance between demand and supply, but also improves the heat transfer efficiency...