Sn-adopted fullerene $$(\hbox {C}_{60})$$ nanocage as acceptable catalyst for silicon monoxide oxidation

In recent years, the discovery of metal catalysts for the oxidation of silicon monoxide (SiO) has become extremely important. In first step, the Sn adoption of fullerene (\(\hbox {C}_{60})\) was investigated and then activation of surface of \(\hbox {Sn-C}_{60}\) via \(\hbox {O}_{2}\) molecule was examined. In second step, the SiO oxidation on surface of \(\hbox {Sn-C}_{60}\) via Langmuir Hinshelwood (LH) and Eley Rideal (ER) mechanisms was investigated. Results show that \(\hbox {O}_{2}\hbox {-Sn-C}_{60}\) can oxidize the SiO molecule via \(\hbox {Sn-C}_{60}\hbox {-O-O}^{*} + \hbox {SiO}\rightarrow \hbox {Sn-C}_{60}\hbox {-O-O}^{*}\hbox {-SiO} \rightarrow \hbox {Sn-C}_{60}\hbox {-O}^{*} + \hbox {SiO}_{2}\) and \(\hbox {Sn-C}_{60}\hbox {-O}^{*} + \hbox {SiO}\rightarrow \hbox {Sn-C}_{60} + \hbox {SiO}_{2}\) reactions. Results show that SiO oxidation via the LH mechanism has lower energy barrier than ER mechanism. Finally, \(\hbox {Sn-C}_{60}\) is an acceptable catalyst with high performance for SiO oxidation in normal temperature.     

Position,Jacobian and workspace analysis of a 3-PSP spatial parallel manipulator

This paper investigates the problems of kinematics, Jacobian, singularity and workspace analysis of a spatial type of 3-PSP parallel manipulator. First, structure and motion variables of the robot are addressed. Two operational modes, non-pure translational and coupled mixed-type are considered. Two inverse kinematics solutions, an analytical and a numerical, for the two operational modes are presented. The direct kinematics of the robot is also solved utilizing a new geometrical approach. It is shown, unlike most parallel robots, the direct kinematics problem of this robot has a unique solution. Next, analytical expressions for the velocity and acceleration relations are derived in invariant form. Auxiliary vectors are introduced to eliminate passive velocity and acceleration vectors. The three types of conventional singularities are analyzed. The notion of non-pure rotational and non-pure translational Jacobian matrices is introduced. The non-pure rotational and non-pure translational Jacobian matrices are combined to form the Jacobian of constraint matrix which is then used to obtain the constraint singularity. Finally, two methods, a discretization method and one based on direct kinematics are presented and robot non-pure translation and coupled mixed-type reachable workspaces are obtained. The influence of tool length on workspace is also studied.     

Measurement of low-loss aqueous solutions permittivity with high detection accuracy by a contact and free-label resonance microwave sensor

In this paper, a microwave sensor is designed and built to measure the permittivity of aqueous solutions. The samples used in this experiment are different purities of ethanol mixed with water. Ethanol solution with different purities is a widely used material in industry. Structures of meander, ladder, and T-structure were used to design the sensor. Then the designed sensor is simulated in CST software in range of relative dielectric from 10 to 80. After obtaining the desired answer in the simulation, the proposed sensor is built on the Rogers 4003 substrate, the built-in sensor measured ethanol solution with a purity of 5% to 35% (equivalent to permittivity of 76 to 58), and is showed a sensitivity of 4% and a Q-factor of 3500. The results of simulation and measurement are consistent with each other, and they indicated that the proposed sensor beyond the fluids can be supported and determine their relative dielectrics.     

Optimal ABC inventory classification using interval programming

Inventory classification is one of the most important activities in inventory management, whereby inventories are classified into three or more classes. Several inventory classifications have been proposed in the literature, almost all of which have two main shortcomings in common. That is, the previous methods mainly rely on an expert opinion to derive the importance of the classification criteria which results in subjective classification, and they need precise item parameters before implementing the classification. While the problem has been predominantly considered as a multi-criteria, we examine the problem from a different perspective, proposing a novel optimisation model for ABC inventory classification in the form of an interval programming problem. The proposed interval programming model has two important features compared to the existing methods: it provides optimal results instead of an expert-based classification and it does not require precise values of item parameters, which are not almost always available before classification. Finally, by illustrating the proposed classification model in the form of numerical example, conclusion and suggestions for future works are presented.     

Metrizability on (semi)topological BL-algebras

In this paper we define the notion of quasifilter neighborhoods on (semi)topological BL-algebras and state and prove some of their properties. Finally, using the concept of quasifilter, we find some conditions under which a BL-algebra will become metrizable.     

Green synthesis and characterization of poly(glycerol-azelaic acid) and its nanocomposites for applications in regenerative medicine

A series of novel bio-polyester nanocomposites based on glycerin and azelaic acid as monomers incorporating hydroxyapatite (HA) nanoparticles were fabricated via in situ polymerization method. Chemical structure of the samples was investigated by ¹H-NMR, ¹³C-NMR, and Fourier-transform infrared spectroscopy (FTIR). Energy dispersive X-ray-mapping analysis illustrated that the nanoparticles were well dispersed in the poly (glycerol azelaic acid) (PGAZ) matrix. Viscoelastic properties of the samples under various frequencies were examined in which the PGAZ specimen containing 1.0 wt% of HA nanoparticles (PGAZH1.0) exhibited superlative properties. Furthermore, the alterations in the glass transition temperature of the samples were comprehensively discussed. Thermal gravimetric analysis displayed that nanocomposites generally have a difference in degradation patterns from that of the pristine sample. Dynamic contact angle demonstrated that the presence of HA nanoparticles imposed a significant influence on hydrophilicity. The hydrolytic degradation values at pH = 7 and pH = 11 were measured and determined that the degradation rate for the PGAZ sample containing 1.5 wt% HA (PGAZH1.5) was higher than those of the other samples. Moreover, in vitro studies elucidated that cell attachment on PGAZH1.0 and PAZH1.5 surfaces were acceptable.     

Modeling viscosity of methane,nitrogen, and hydrocarbon gas mixtures at ultra-high pressures and temperatures using group method of data handling and gene expression programming techniques

Accurate gas viscosity determination is an important issue in the oil and gas industries. Experimental approaches for gas viscosity measurement are time-consuming, expensive and hardly possible at high pressures and high temperatures (HPHT). In this study, a number of correlations were developed to esti-mate gas viscosity by the use of group method of data handling (GMDH)-type neural network and gene expression programming (GEP) techniques using a large data set containing more than 3000 experimen-tal data points for methane, nitrogen, and hydrocarbon gas mixtures. It is worth mentioning that unlike many of viscosity correlations, the proposed ones in this study could compute gas viscosity at pressures ranging between 34 and 172 MPa and temperatures between 310 and 1300 K. Also, a comparison was performed between the results of these established models and the results of ten well-known models reported in the literature. Average absolute relative errors of GMDH models were obtained 4.23％, 0.64％, and 0.61％for hydrocarbon gas mixtures, methane, and nitrogen, respectively. In addition, graph-ical analyses indicate that the GMDH can predict gas viscosity with higher accuracy than GEP at HPHT conditions. Also, using leverage technique, valid, suspected and outlier data points were determined. Finally, trends of gas viscosity models at different conditions were evaluated.     

Antimicrobial and antioxidant properties of burgers with quinoa peptide-loaded nanoliposomes

This study was aimed to examine the antioxidant (thiobarbituric acid reactive substances [TBARS], peroxide value [PV], and as well as antimicrobial (total bacterial count, Staphylococcus aureus [S. aureus], mold and yeast counts) activities and spoilage indices (total volatile base nitrogen [TVB-N]) of quinoa peptide-loaded liposomes incorporated into burger during 12 days of refrigerated storage. Among four prepared batches, the lowest TBARS, PV, and TVB-N values (0.281 ± 0.05 mg MDA/kg, 3.25 ± 0.34 mEq/kg and 18.65 ± 0.88%, respectively) were correlated with T3 treatment (5 mg/ml peptide). A significant different in the antimicrobial activity among each treatment after 12 days of storage was noted. At the end of refrigerated storage, the highest mean of total bacterial count, S. aureus, mold and yeast (8.36 ± 0.22, 4.19 ± 0.2, and 3.28 ± 0.05 log CFU/g, respectively) were observed in control group, while the lowest corresponded values (3.95 ± 0.2, 2.52 ± 0.25, and 1.52 ± 0.02 log CFU/g, respectively) were noted in T3 treatment. The results showed that the antimicrobial and antioxidant properties of the examined burgers were improved by incorporation of liposomes quinoa peptides encapsulated.     

Polymeric encapsulation of liquids via plasma surface polymerization

This study introduces a new approach of liquid encapsulation using an atmospheric pressure plasma (APP). The technique is similar to interfacial polymerization, though here one phase is liquid (that contains unsaturated C═C bonds) and the other phase is plasma (that contains free radicals). When combined, the atmospheric plasma can induce surface polymerization of an acrylate-based liquid, resulting in a thin polymeric skin on top of the liquid. Measurements with an atomic force microscope and a spectroscopic ellipsometer estimate the thickness of the skin formed on top of di(ethylene glycol) diacrylate to be 40–50 nm. To demonstrate an application of this method, we encapsulated hemispherical capsules of reactive adhesives on a glass substrate. These adhesives are based on thiol-acrylate and thiol-acrylate-epoxy systems that react in the presence of a strong base catalyst. Plasma-induced polymerization can encapsulate, immobilize, and isolate separate droplets of resin and the catalyst in a latent (nonreactive) state. These capsules remain latent until they rupture in response to physical contact. A tensile testing machine reports an adhesive strength of ~ 2 MPa for the formulated resins after curing. The capsules reported here may be useful for storing functional liquids for just-in-time release, such as contact-sensitive adhesives, on-demand lubricants, or self-healing agents. © 2020 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2020 , 137, 48880.     

Optimization of the Degumming Process for Aqueous-Extracted Wild Almond Oil

Wild almond (Amygdalus scoparia) oil is rich in oleic acid and, considering both nutritional and stability points of view, it can be utilized for future food applications. In the current study, acid degumming was investigated based on a method by response surface methodology using four degumming parameters, namely the amount of phosphoric acid (0.0–0.2%, w/w), the amount of water (1.0–5.0%, w/w), degumming temperature (30–70 °C), and degumming time (10–50 min). Optimum conditions for the minimum phosphorus level in the oil were found to be 0.15% phosphoric acid, 3.0% water, 40 °C degumming temperature, and 28 min degumming time, resulting in an almost complete removal of phosphorus. The final degummed wild almond oil had less than 1 mg kg⁻¹ phosphorus (reduced from an original value of 206 mg kg⁻¹). The experimental value of phosphorus reduction at optimum conditions agreed well with that predicted by the model. Peroxide value, anisidine value, iron, copper, and lead contents, phytosterols, unsaponifiable matter, and color of the oil decreased significantly during the degumming process; however, the fatty acid composition did not change. Also, degumming did not significantly impact the free fatty acid level, refractive index, density, iodine value, and the saponification value of the oil. However, tocopherols and the oxidative stability of the oil increased during degumming. Crude wild almond oil contained a trace level of amygdalin, which was completely eliminated during the degumming process.