Mild and Efficient Synthesis of Benzo-Fused Seven- and Eight-membered Ring Lactams: A Convenient Approach to Biologically Interesting Chemotypes

A general and efficient method for the synthesis of benzo-fused 7- and 8-membered ring lactams via the Beckmann rearrangement of cyclic oximes is presented.

Supplemental materials are available for this article. Go to the publisher's online edition of Synthetic Communications® to view the free supplemental file.     

Efficient computation of operator‐type response sensitivities for uncertainty quantification and predictive modeling: illustrative application to a spent nuclear fuel dissolver model

This work honors the 75th birthday of Professor Ionel Michael Navon by presenting original results highlighting the computational efficiency of the adjoint sensitivity analysis methodology for function‐valued operator responses by means of an illustrative paradigm dissolver model. The dissolver model analyzed in this work has been selected because of its applicability to material separations and its potential role in diversion activities associated with proliferation and international safeguards. This dissolver model comprises eight active compartments in which the 16 time‐dependent nonlinear differential equations modeling the physical and chemical processes comprise 619 scalar and time‐dependent model parameters, related to the model's equation of state and inflow conditions. The most important response for the dissolver model is the time‐dependent nitric acid in the compartment furthest away from the inlet, where measurements are available at 307 time instances over the transient's duration of 10.5 h. The sensitivities to all model parameters of the acid concentrations at each of these instances in time are computed efficiently by applying the adjoint sensitivity analysis methodology for operator‐valued responses. The uncertainties in the model parameters are propagated using the above‐mentioned sensitivities to compute the uncertainties in the computed responses. A predictive modeling formalism is subsequently used to combine the computational results with the experimental information measured in the compartment furthest from the inlet and then predict optimal values and uncertainties throughout the dissolver. This predictive modeling methodology uses the maximum entropy principle to construct an optimal approximation of the unknown a priori distribution for the a priori known mean values and uncertainties characterizing the model parameters and the computed and experimentally measured model responses. This approximate a priori distribution is subsequently combined using Bayes' theorem with the “likelihood” provided by the multi‐physics computational models. Finally, the posterior distribution is evaluated using the saddle‐point method to obtain analytical expressions for the optimally predicted values for the parameters and responses of both multi‐physics models, along with corresponding reduced uncertainties. This work shows that even though the experimental data pertains solely to the compartment furthest from the inlet (where the data were measured), the predictive modeling procedure used herein actually improves the predictions and reduces the predicted uncertainties for the entire dissolver, including the compartment furthest from the measurements, because this predictive modeling methodology combines and transmits information simultaneously over the entire phase‐space, comprising all time steps and spatial locations. Copyright © 2016 John Wiley & Sons, Ltd.     

Computational-Based Approach for Predicting Porosity of Electrospun Nanofiber Mats Using Response Surface Methodology and Artificial Neural Network Methods

Comparative studies between response surface methodology (RSM) and artificial neural network (ANN) methods to find the effects of electrospinning parameters on the porosity of nanofiber mats is described. The four important electrospinning parameters studied included solution concentration (wt.%), applied voltage (kV), spinning distance (cm) and volume flow rate (mL/h). It was found that the applied voltage and solution concentration are the two critical parameters affecting the porosity of the nanofiber mats. The two approaches were compared for their modeling and optimization capabilities with the modeling capability of RSM showing superiority over ANN, having comparatively lower values of errors. The mean relative error for the RSM and ANN models were 1.97% and 2.62% and the root mean square errors (RMSE) were 1.50 and 1.95, respectively. The superiority of the RSM-based approach is due to its high prediction accuracy and the ability to compute the combined effects of the electrospinning factors on the porosity of the nanofiber mats.     

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.     

Study and optimization of the ultrasound-enhanced cleaning of an ultrafiltration ceramic membrane through a combined experimental–statistical approach

Membrane fouling is one of the main drawbacks of ultrafiltration technology during the treatment of dye-containing effluents. Therefore, the optimization of the membrane cleaning procedure is essential to improve the overall efficiency. In this work, a study of the factors affecting the ultrasound-assisted cleaning of an ultrafiltration ceramic membrane fouled by dye particles was carried out. The effect of transmembrane pressure (0.5, 1.5, 2.5 bar), cross-flow velocity (1, 2, 3 m s⁻¹), ultrasound power level (40%, 70%, 100%) and ultrasound frequency mode (37, 80 kHz and mixed wave) on the cleaning efficiency was evaluated. The lowest frequency showed better results, although the best cleaning performance was obtained using the mixed wave mode.A Box–Behnken Design was used to find the optimal conditions for the cleaning procedure through a response surface study. The optimal operating conditions leading to the maximum cleaning efficiency predicted (32.19%) were found to be 1.1 bar, 3 m s⁻¹ and 100% of power level.Finally, the optimized response was compared to the efficiency of a chemical cleaning with NaOH solution, with and without the use of ultrasound. By using NaOH, cleaning efficiency nearly triples, and it improves up to 25% by adding ultrasound.     

Comparison of microwave‐assisted and conventional extraction of mangiferin from mango (Mangifera indica L.) leaves

Mangiferin is the main bioactive component in mango leaves, which possesses anti‐inflammatory, antioxidative, antidiabetic, immunomodulatory, and antitumor activities. In the present study, a microwave‐assisted extraction method was developed for the extraction of mangiferin from mango leaves. Some parameters such as ethanol concentration, liquid‐to‐solid ratio, microwave power, and extraction time were optimized by single‐factor experiments and response surface methodology. The optimal extraction conditions were 45% ethanol, liquid‐to‐solid ratio of 30:1 (mL/g), and extraction time of 123 s under microwave irradiation of 474 W. Under optimal conditions, the yield of mangiferin was 36.10 ± 0.72 mg/g, significantly higher than that of conventional extraction. The results obtained are beneficial for the full utilization of mango leaves and also indicate that microwave‐assisted extraction is a very useful method for extracting mangiferin from plant materials.     

Optimization of microwave‐assisted extraction for anthocyanins,polyphenols, and antioxidants from raspberry (Rubus Coreanus Miq.) using response surface methodology

Anthocyanins (Acys), polyphenols, and antioxidants were extracted from raspberry (Rubus Coreanus Miq.) using a highly efficient microwave‐assisted extraction technique. Different solvents, including methanol, ethanol, and acetone, were tested. The colors of the extracts varied from light yellow to purple red or dark red. SEM and other nutrient analyses verified that ethanol was the most favorable medium for the microwave‐assisted extraction of raspberry due to its high output and low toxicity. Effects of process parameters, including microwave power, irradiation time, and solvent concentration, were investigated through response surface methodology. Canonical analysis estimated that the highest total Acys content, total polyphenols content, and antioxidant activity of raspberry were 17.93 mg cyanidin‐3‐O‐glucoside equivalents per gram dry weight, 38.57 mg gallic acid equivalents per gram dry weight, and 81.24%, respectively. The polyphenol compositions of raspberry extract were identified by HPLC with diode array detection, and nine kinds of polyphenols were identified and quantified, revealing that chlorogenic acid, syringic acid, and rutin are the major polyphenols contained in raspberry fruits. Compared with other fruits and vegetables, raspberry contains higher Acy and polyphenol contents with stronger antioxidant activity, suggesting that raspberry fruits are a good source of natural food colorants and antioxidants.     

Efficient eco-friendly approach towards bimetallic nanoparticles synthesis and characterization using Exiguobacterium aestuarii by statistical optimization

ABSTRACT

Biogenic synthesis of bimetallic nanoparticles (gold – AuNp and selenium – SeNp) using inexpensive Tryptophan Enriched Banana Peel Media for the growth of marine isolate (Exiguobacterium aestuarii SBG4 MH185868). The response surface methodology is employed for optimizing production conditions. The surface plasmon resonance band showed λ_max at 540?nm (AuNp) and 284?nm (SeNp). FTIR and zeta potential analysis confirmed the stability, whereas XRD spectra revealed the nature of nanoparticles obtained at optimum conditions. SEM micrographs showed nanospheres of the following size: AuN, 30?±?5 nm and SeNp, 50?±?5 nm. Biocompatibility of Np evaluated by the hemolytic activity showed <20% hemolysis even at highest concentrations (100?µg/ml). AuNp showed the least cytotoxicity, whereas SeNp showed considerable cytotoxicity against the breast cancer cell lines MCF – 7 and MDA-MB-231. Hence, we utilized the environment-friendly growth media for the controlled synthesis of dual Np using single bacterial strain involving feasible steps in downstream processing.     

Synthesis, structure and luminescence properties of metal-organic frameworks based on benzo-bis(imidazole)

Metal-organic frameworks(MOFs)constructed from conjugated organic ligands are candidates for hybrid photoactive materials with potential applications.Compared to that from the ligands only,the intensity and wavelength of the luminescence could be tuned after they were incorporated in extended framework.In this report,by using an organic ligand with azolate moiety,benzo-bis(imidazole)(H2BBI),we synthesized two new MOF structures.Framework 1([Co(H2BBI)(DMSO)2Cl2]n,DMSO=dimethyl sulfoxide),constructed from tetrahedral Co(II)and H2BBI,exhibits zigzag 1D structure.Meanwhile,framework 2([Cu2(H2BBI)3(DMSO)6(NO3)4]n),a layered structure with hcb topology,was assembled from tetragonal pyramidal Cu(II)and H2BBI.Furthermore,2 exhibits strong luminescence emission(ex=280 nm).A blue shift of 40 nm(from 359 nm to 319 nm)was observed in framework 2 compared to the free ligand,which could be explained by the ligand-to-metal charge transfer in the network.