A link between impact sensitivity of energetic compounds and their activation energies of thermal decomposition

A new relationship is introduced between impact sensitivity of energetic compounds and their activation energies of thermal decomposition. In this relationship, the impact sensitivity of an energetic compound with general formula C_aH_bN_cO_d is a function of its activation energy of thermal decomposition as well as the ratio of \( \left( {\frac{{n_{\text{H}} }}{{n_{\text{O}} }}} \right) \) and the contribution of specific molecular structural parameters. The new correlation can help us to elucidate the mechanism of initiation of energetic materials by impact. It can be used to predict the magnitude of impact sensitivity of new energetic materials. The new correlation has the root mean square and the average deviations of 2.22 and 1.79 J, respectively, for 40 energetic compounds with different molecular structures. The proposed new method is also tested for 11 energetic compounds, which have complex molecular structures, e.g., 4,10-dinitro-2,6,8,12-tetraoxa-4,10-diazaisowurtzitane and 1,3,7,9-tetranitrophenoxazine.     

Chemometrics study of the kinetics of the Griess reaction

The kinetics of the Griess reaction in which 3‐nitroaniline acts as a nitrosation agent and 1‐naphtylamine as a coupling reagent was studied by chemometrics methods. The kinetic reaction was investigated under pH 1.0 and 25°C by UV‐vis spectrophotometry. The concentrations of nitrite, 3‐nitroaniline and 1‐naphtylamine were such that a second‐order kinetic reaction took place. Data explorations based on principal component analysis and multivariate curve resolution–alternating least squares were performed to obtain information about the reaction. Calculation of band boundaries of the multivariate curve resolution–alternating least squares solutions showed that the rotational ambiguities associated with the calculation of spectra and concentration profiles have been completely removed. The decrease in the ambiguity of the recovered solutions was closely related to the application of the equality constraint. The results of the exploratory data analysis showed that the kinetic reaction proceeds through a two‐step mechanism. Moreover, the two‐steps are second order. Data analysis approaches based on hard modeling and global hard modeling were used to resolve profiles of the reactants, intermediates and products and to evaluate the rate constants. Copyright © 2013 John Wiley & Sons, Ltd.     

Hiyama cross‐coupling reaction catalyzed by a palladium salt of 1‐benzyl‐4‐aza‐1‐azoniabicyclo[2.2.2]octane chloride under microwave irradiation

An efficient catalytic system using 1‐benzyl‐4‐aza‐1‐azoniabicyclo[2.2.2]octane chloride ((BeDABCO)₂Pd₂Cl₆) was developed for the Hiyama cross‐coupling reaction of various aryl halides with triethoxy(phenyl)silane. The substituted biaryls were produced in excellent yields in short reaction times using a catalytic amount of this catalyst in NMP at 100 °C. Copyright © 2014 John Wiley & Sons, Ltd.     

The Novel Synthesis of Functionalized Indenopyrazolones Using Fe3O4 nanoparticles stabilized on MMT: An Efficient Magnetically Recoverable Heterogeneous Nanocomposite Catalyst

A practical and simple approach for the one‐pot multicomponent synthesis of indenopyrazolones is described via the condensation of ninhydrin (indan‐1,2,3‐trione), phenylhydrazine, and various aldehydes in the presence of MMT@Fe₃O₄ as an environmentally benign core/shell nanocomposite catalyst. The catalyst could be recycled using an external magnet easily and reused several times without remarkable loss of its catalytic activity. Furthermore, avoiding hazardous solvents, reusability of the catalyst, easy work‐up, short reaction times, room temperature, and mild reaction conditions are the advantages of this new eco‐friendly protocol.     

Prediction of retinopathy in diabetic patients using type-2 fuzzy regression model

Due to the small sample size of data available in medical research and the levels of uncertainty and ambiguity associated with medical data, some researchers have employed fuzzy regression models to find the relationship between outcomes and explanatory variables in medical decision-making. The advantages of regression models are their ability to handle small sample sizes while fuzzy logic can model vagueness, thus making fuzzy regression a popular model among researchers. In addition, the high levels of uncertainty in medical data encourage the use of type-2 fuzzy which is capable of handling such uncertainty. The current paper proposes an interval type-2 fuzzy regression model for predicting retinopathy in diabetic patients. The results of the present work shall prevent unnecessary testing of diabetic patient. This study also aims to assist patients and the healthcare community to reduce the cost of diabetes control and treatment by optimizing the number of check-ups.     

Investigation of the Effect of Various Substituents on the Density of Tetrazolium Nitrate Salts as Green Energetic Materials

The substitution effect of various functional groups such as –NO₂, –CN, –N₃, –NF₂, and –NH₂ on the density of tetrazolium nitrate salts is investigated through multiple linear regression method. The methodology of this work introduces a new model, which related density of tetrazolium nitrate salts to the number of fluorine and nitrogen atoms, the presence of NF₂ groups, NO₂ groups, as well as CH₃ groups in the structural formula. The new reliable correlation shows that the NF₂ and NO₂ group can cause increasing the density of tetrazolium nitrate salts, especially NO₂, whereas the CH₃ group can decrease their density. The new proposed relationship has good reliability and predictability, so it can be used to design new rich nitrogen compounds based on tetrazolium nitrate salts as green energetic materials. These results are also tested for N,N′‐azo‐1,2,4‐triazolium nitrate salts, which is caused to derive another correlation. This correlation shows that the presence of NF₂ functional groups increases the density of N,N′‐azo‐1,2,4‐triazolium nitrate salts as well as the value of n_O/n_C.     

Cyanide Hydratase Modification Using Computational Design and Docking Analysis for Improved Binding Affinity in Cyanide Detoxification

Cyanide is a hazardous and detrimental chemical that causes the inactivation of the respiration system through the inactivation of cytochrome c oxidase. Because of the limitation in the number of cyanide-degrading enzymes, there is a great demand to design and introduce new enzymes with better functionality. This study developed an integrated method of protein-homology-modelling and ligand-docking protein-design approaches that reconstructs a better active site from cyanide hydratase (CHT) structure. Designing a mutant CHT (mCHT) can improve the CHT performance. A computational design procedure that focuses on mutation for constructing a new model of cyanide hydratase with better activity was used. In fact, this study predicted the three-dimensional (3D) structure of CHT for subsequent analysis. Inducing mutation on CHT of Trichoderma harzianum was performed and molecular docking was used to compare protein interaction with cyanide as a ligand in both CHT and mCHT. By combining multiple designed mutations, a significant improvement in docking for CHT was obtained. The results demonstrate computational capabilities for enhancing and accelerating enzyme activity. The result of sequence alignment and homology modeling show that catalytic triad (Cys-Glu-Lys) was conserved in CHT of Trichoderma harzianum. By inducing mutation in CHT structure, MolDock score enhanced from −18.1752 to −23.8575, thus the nucleophilic attack can occur rapidly by adding Cys in the catalytic cavity and the total charge of protein in pH 6.5 is increased from −6.0004 to −5.0004. Also, molecular dynamic simulation shows a stable protein-ligand complex model. These changes would help in the cyanide degradation process by mCHT.     

A First-Principles Study of CO2 Hydrogenation on a Niobium-Terminated NbC (111) Surface

As promising materials for the reduction of greenhouse gases, transition-metal carbides, which are highly active in the hydrogenation of CO₂, are mainly considered. In this regard, the reaction mechanism of CO₂ hydrogenation to useful products on the Nb-terminated NbC (111) surface is investigated by applying density functional theory calculations. The computational results display that the formation of CH₄, CH₃OH, and CO are more favored than other compounds, where CH₄ is the dominant product. In addition, the findings from reaction energies reveal that the preferred mechanism for CO₂ hydrogenation is thorough HCOOH^*, where the largest exothermic reaction energy releases during the HCOOH^* dissociation reaction (2.004 eV). The preferred mechanism of CO₂ hydrogenation towards CH₄ production is CO₂^*→t,c-COOH^*→HCOOH^*→HCO^*→CH₂O^*→CH₂OH^*→CH₂^*→CH₃^*→CH₄^*, where CO₂^*→t,c-COOH^*→HCOOH^*→HCO^*→CH₂O^*→CH₂OH^*→CH₃OH^* and CO₂^*→t,c-COOH^*→CO^* are also found as the favored mechanisms for CH₃OH and CO productions thermodynamically, respectively. During the mentioned mechanisms, the hydrogenation of CH₂O^* to CH₂OH^* has the largest endothermic reaction energy of 1.344 eV.     

Designing an efficient supply chain network with uncertain data: a robust optimization—data envelopment analysis approach

Designing a supply chain network (SCN) is an important issue for organizations in competitive markets. In this paper, a novel robust SCN that considers the efficiencies and costs simultaneously is proposed. In order to estimate the efficiency of the producers and distributors, data envelopment analysis (DEA) model is incorporated into SCN. Moreover, to handle the uncertainty in data, a scenario-based robust optimization approach is applied. The proposed model finds out the efficient location of producers and distributors and determines the amount of purchases from each supplier in uncertain conditions. To illustrate the application of the proposed model, a numerical example is solved and results are analyzed.     

Investigation of vacancy defects effects on the buckling behavior of SWCNTs via a structural mechanics approach

In this paper, the influence of various vacancy defects on the critical buckling loads and strains in carbon nanotubes under axial compression is investigated via a new structural model in ABAQUS software. The necessity of desirable conditions and expensive tests for experimental methods, in addition to the time expenditure required for atomic simulations, are the motivation for this work, which, in addition to yielding accurate results, avoids the obstacles of the previous methods. In fact, this model is a combination of other structural models designed to eliminate the deficiencies inherent in individual approaches. Because the present model is constructed in the CAE space of ABAQUS, there is no need to program for different loading and boundary conditions. A nonlinear connector is considered for modeling of stretching and torsional interactions, and a nonlinear spring is used for modeling of the angle variation interactions. A Morse potential is employed for stretching and bending potentials, and a periodic type of bond torsion is used for torsion interactions. The effect of different types of vacancy defects at various locations on the critical buckling loads and strains is studied for zigzag and armchair nanotubes with various aspect ratios (Length/Diameter). Comparison of our results with those of buckling of shells with cutouts indicates that vacancy defects in the carbon nanotubes can most likely be modeled as cutouts of the shells. Finally, results of the present structural model are compared with those from molecular dynamics (MD) simulation and show good agreement between our model and the MD model.