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Bisphosphonate (BP) medications can be applied to prohibit the damage of bone density and the remedy of bone illnesses such as osteoporosis. As the metal chelating of phosphonate groups are nearby large with six O atoms possessing the high negative charge, these compounds are active toward producing the chelated complexes through drug design method. BP agents have attracted much attention for the clinical treatment of some skeletal diseases depicted by enhancing of osteoclast-mediated bone resorption.

In this work, it has been accomplished the CAM-B3LYP/6–311+G(d, p)/LANL2DZ to estimate the susceptibility of SWCNT for adsorbing alendronate, ibandronate, neridronate and pamidronate chelated to two metal cations of 2Mg²⁺, 2Ca²⁺, 2Sr²⁺ through nuclear magnetic resonance and thermodynamic parameters. Therefore, the data has explained that the feasibility of using SWCNT and BP agents becomes the norm in metal chelating of drug delivery system which has been selected through alendronate → 2X, ibandronate → 2X, neridronate → 2X and pamidronate → 2X (X = Mg²⁺/Ca²⁺/Sr²⁺) complexes.

The thermodynamic results have exhibited that the substitution of 2Ca²⁺ cation by 2Sr²⁺ cation in the structure of bioactive glasses can be efficient for treating vertebral complex fractures. However, it has been observed the most fluctuation in the Gibbs free energy for BPs → 2Sr²⁺ at 300 K. Furthermore, Monte Carlo simulation has resulted by increasing the dielectric constant in the aqueous medium can enhance the stability and efficiency of BP drugs for preventing the loss of bone density and treating the osteoporosis.

According to this research, by incorporation of chelated 2Mg²⁺, 2Ca²⁺ and 2Sr²⁺ cations to BP drugs adsorbed onto (5, 5) armchair SWCNT, the network compaction would increase owing to the larger atomic radius of Sr²⁺ cation rather than Ca²⁺ and Mg²⁺, respectively.

This study aims to investigate the potential of the decorated boron nitride nanocage (BNNc) with transition metals for capturing carbon monoxide (CO) as a toxic gas in the air.

BNNc was modeled in the presence of doping atoms of titanium (Ti), vanadium (V), chromium (Cr), cobalt (Co), copper (Cu) and zinc (Zn) which can increase the gas sensing ability of BNNc. In this research, the calculations have been accomplished by CAM–B3LYP–D3/EPR–3, LANL2DZ level of theory. The trapping of CO molecules by (Ti, V, Cr, Co, Cu, Zn)–BNNc has been successfully incorporated because of binding formation consisting of C → Ti, C → V, C → Cr, C → Co, C → Cu, C → Zn.

Nuclear quadrupole resonance data has indicated that Cu-doped or Co-doped on pristine BNNc has high fluctuations between Bader charge versus electric potential, which can be appropriate options with the highest tendency for electron accepting in the gas adsorption process. Furthermore, nuclear magnetic resonance spectroscopy has explored that the yield of electron accepting for doping atoms on the (Ti, V, Cr, Co, Cu, Zn)–BNNc in CO molecules adsorption can be ordered as follows: Cu > Co >> Cr > Zn ˜ V> Ti that exhibits the strength of the covalent bond between Ti, V, Cr, Co, Cu, Zn and CO. In fact, the adsorption of CO gas molecules can introduce spin polarization on the (Ti, V, Cr, Co, Cu, Zn)–BNNc which specifies that these surfaces may be used as magnetic-scavenging surface as a gas detector. Gibbs free energy based on IR spectroscopy for adsorption of CO molecules adsorption on the (Ti, V, Cr, Co, Cu, Zn)–BNNc have exhibited that for a given number of carbon donor sites in CO, the stabilities of complexes owing to doping atoms of Ti, V, Cr, Co, Cu, Zn can be considered as: CO →Cu–BNNc >> CO → Co–BNNc > CO → Cr–BNNc > CO → V–BNNc > CO → Zn–BNNc > CO → Ti–BNNc.

This study by using materials modeling approaches and decorating of nanomaterials with transition metals is supposed to introduce new efficient nanosensors in applications for selective sensing of carbon monoxide.

As to different angles of attack and nonlinear problems caused by high temperatures in coexisting hypersonic aircraft, people mainly rely on fluid software for research but lack analysis of flow mechanisms. Owing to computational difficulties, few people use numerical algorithms to combine them for discussion. Hence, this study aims to make a deep inquiry into the laminar flow and heat transfer of compressible Newtonian fluid in hypersonic aircraft with small attack angles.

In this paper, on the basis of mass, momentum and energy conservation laws, the governing equations of the hypersonic boundary layer are established. Viscosity, specific heat capacity and thermal conductivity are considered nonlinear functions concerning temperature. In virtue of the MacCormack finite difference method, the stationary numerical solutions are solved directly, and the validity of the algorithm is verified.

The results demonstrate that at Mach number 5, compared to the 0° attack angle, the maximum temperature near-wall at the 3° attack angle increases by about 25%. An enjoyable phenomenon is discovered, where the position corresponding to the maximum wall shear force shifts back as the attack angle and Mach number increase. The relationship between the near-wall maximum temperature versus attack angle and Mach number is fitted through numerical calculation results.

Empirical formulas can be used to estimate heat transfer characteristics at small attack angles, which will guide the design of aircraft thermal protection systems.

Titanium(IV) oxide nanoparticles (TiO₂ NP) were deposited to cotton denim fabrics using a self-crosslinking acrylate – a polymer dispersion to extend the lifetime of the products. This study aims to determine the optimum conditions to increase abrasion resistance, to provide self-cleaning properties of denim fabrics and to examine the effects of these applications on other physical properties.

The denim samples were first treated with nonionic surfactant to increase their wettability. Three different amounts of the polymer dispersion and two different pH levels were selected for the experimental design. The finishing process was applied to the fabrics with pad-dry-cure method.

The presence of the coatings and the adhesion of TiO₂ NPs to the surfaces were confirmed by scanning electron microscope and Fourier transform infrared spectroscopy analysis. It was ascertained that the most appropriate self-crosslinking acrylate amount and ambient pH level is 10 mL and “2”, respectively, for providing increased abrasion resistance (2,78%) and enhanced self-cleaning properties (363,4%) in the denim samples. The coating reduced the air permeability and softness of the denim samples. Differential scanning calorimetry and thermogravimetry analysis results showed that the treatments increased the crystallization temperatures and melting enthalpy values of the denim samples. Based on the thermal test results, it is clear that mass loss of the denim samples at 370°C decreased as the amount of self-crosslinking acrylate increased (at pH 3).

This study helped us to find out optimum amount of self-crosslinking acrylate and proper pH level for enhanced self-cleaning and abrasion strength on denim fabrics. With this finishing process, an environmentally friendly and long-life denim fabric was designed.

To enhance the performance of hydrostatic bearings, graphene serves as a lubricant additive. Using the high thermal conductivity of graphene, the purpose of this study is to focus on the impact of graphene nano-lubricating oil hydrostatic bearing temperature rise at various speeds and eccentricities.

The thermal conductivity of graphene nano-lubricating oil was calculated by molecular dynamics method and based on the viscosity–temperature effect, the coupled heat transfer finite element model of hydrostatic bearing was established; temperature rise of pure lubricating oil and graphene nano-lubricating oil hydrostatic bearing were analysed at different speed and eccentricity based on computational fluid dynamics method.

With the increase of speed and eccentricity, the temperature rise of 0.2% graphene nano-lubricating oil bearings is lower than that of pure lubricating oil bearings; in addition with the increase of graphene mass fraction, the temperature rise of graphene nano-lubricating oil bearings is always higher than that of pure lubricating oil bearings, and the higher the speed, the more obvious the phenomenon.

The effects of graphene as a lubricant additive on the thermal conductivity of nano-lubricating oil and the variation of the temperature rise of graphene nano-lubricating oil bearings compared to pure lubricating oil bearings were analysed by combining micro and macro methods.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-12-2023-0388

Magnetic hysteresis holds significant technical and physical importance in the design of electromagnetic components. Despite extensive research in this area, modeling magnetic hysteresis remains a challenging task that is yet to be fully resolved. The purpose of this paper is to study vector hysteresis play models for anisotropic ferromagnetic materials in a physical, thermodynamical approach.

In this work, hysteresis play models are implemented to interpret magnetic properties, drawing upon classical rate-independent plasticity principles derived from continuum mechanics theory. By conducting qualitative and quantitative verification and validation, various aspects of ferromagnetic vector hysteresis were thoroughly examined. By directly incorporating the hysteresis play models into the primal formulations using fixed point method, the proposed model is validated with measurements in a finite element (FE) environments.

The proposed vector hysteresis play model is verified with fundamental properties of hysteresis effects. Numerical analysis is performed in an FE environment. Measured data from a rotational single sheet tester (RSST) are validated to the simulated results.

The results of this work demonstrates that the essential properties of the hysteresis effects by electrical steel sheets can be represented by the proposed vector hysteresis play models. By incorporation of hysteresis play models into the weak formulations of the magnetostatic problem in the h-based magnetic scalar potential form, magnetic properties of electrical steel sheets can be locally analyzed and represented.

The aim of this study was to investigate the activity of 4-((4-((2-hydroxyethyl)(methyl)amino)benzylidene) amino)-1,5-dimethyl-2-phenyl-1,2-dihydro-3H-pyrazol-3-one (HEMAP), a Schiff base synthesized and characterized for the first time, to the authors’ knowledge, as a novel inhibitor against corrosion of mild steel (MS) in hydrochloric acid solution.

HEMAP was characterized by some spectroscopic methods including High-Resolution Mass Spectrometry (HRMS), Proton Nuclear Magnetic Resonance (1H NMR), Carbon-13 (C13) nuclear magnetic resonance (13C NMR) and Fourier Transform Infrared Spectroscopy (FT-IR). Then, the inhibition efficiency of HEMAP on MS in a hydrochloric acid solution was investigated by potentiodynamic polarization and electrochemical impedance spectroscopy (EIS). To explain the inhibition mechanism, the surface charge, adsorption isotherms and thermodynamic parameters of MS in the inhibitor solution were studied.

EIS tests displayed that the highest inhibition efficiency was calculated approximately as 99.5% for 5 × 10⁻² M HEMAP in 1 M HCl solution. The adsorption of HEMAP on the MS surface was found to be compatible with the Langmuir model isotherm. The thermodynamic parameter results showed that the standard free energy of adsorption of HEMAP on the MS surface was found to be more chemical than physical.

This study is important in terms of demonstrating the performance of the first synthesized HEMAP molecule as an inhibitor against the corrosion of MS in acidic media. EIS tests displayed that the highest inhibition efficiency was calculated approximately as 99.5% for 5 × 10⁻² M HEMAP in 1 M HCl solution.

Through the case of Blanca Sinchi, the following analysis presents valuation criteria that have resulted in the invisibility of social actors and cultural patrimony (cultural heritage) elements, and some contradictions in their acknowledgment process. In addition, the paper explains how architecture, among other historic assets, has made women and their contributions invisible.

Bibliographic analysis and semi-structured interviews were carried out to theorize about the thermodynamic system of lime to propose a matri-lineal system category and expand the understanding of the participation of women in the receipt, management and transmission of what is called patrimony.

In heritage places, such as Cuenca (Ecuador), cultural richness extends from the Historic Center to the rest of the territory and its actors. However, there are intrinsic elements, such as unknown, but fundamental, oral or family traditions associated with the role of women. The case of Blanca Sinchi and lime is evidence of this, as it shows the typical scenario affected by gender and by disparate power dynamics that do not consider desirable attributes (authenticity, integrity, identity, bequest, option, existence, among others) in the conservation of architectural patrimony. A deep redefinition process, or even a change in the valuation system, is needed. Also, the history behind built heritage items must be explored to find the contributions made by women.

Proposing a matri-lineal system category to expand the understanding of the participation of women in the receipt, management and transmission of what is called patrimony, allows redefining and rewriting local and global history, acknowledging the role of women. In this way, the proposal questions not only the hegemony of the term “cultural patrimony” pigeonholed in paternal legacy but also the term “cultural heritage” as a synonym and framework that, while expanding material values, it does not effectively include, at least for Ibero-Romance language territories, the broad set of tangible and intangible values, as well as the know-how and skills of artisans.

The purpose of this study is to investigate the effects of Ce and Sb doping on the microstructure and thermal mechanical properties of Sn-1.0Ag-0.5Cu lead-free solder. The effects of 0.5%Sb and 0.07%Ce doping on microstructure, thermal properties and mechanical properties of Sn-1.0Ag-0.5Cu lead-free solder were investigated.

According to the mass ratio, the solder alloys were prepared from tin ingot, antimony ingot, silver ingot and copper ingot with purity of 99.99% at 400°C. X-ray diffractometer was adopted for phase analysis of the alloys. Optical microscopy, scanning electron microscopy and energy dispersive spectrometer were used to study the effect of the Sb and Ce doping on the microstructure of the solder. Then, the thermal characteristics of alloys were characterized by a differential scanning calorimeter (DSC). Finally, the ultimate tensile strength (UTS), elongation (EL.%) and yield strength (YS) of solder alloys were measured by tensile testing machine.

With the addition of Sb and Ce, the ß-Sn and intermetallic compounds of solders were refined and distributed more evenly. With the addition of Sb, the UTS, EL.% and YS of Sn-1.0Ag-0.5Cu increased by 15.3%, 46.8% and 16.5%, respectively. The EL.% of Sn-1.0Ag-0.5Cu increased by 56.5% due to Ce doping. When both Sb and Ce elements are added, the EL.% of Sn-1.0Ag-0.5Cu increased by 93.3%.

The addition of 0.5% Sb and 0.07% Ce can obtain better comprehensive performance, which provides a helpful reference for the development of Sn-Ag-Cu lead-free solder.

Nearly 75% of EU buildings are not energy-efficient enough to meet the international climate goals, which triggers the need to develop sustainable construction techniques with high degree of resilience against climate change. In this context, a promising construction technique is represented by ventilated façades (VFs). This paper aims to propose three different VFs and the authors define a novel machine learning-based approach to evaluate and predict their energy performance under different boundary conditions, without the need for expensive on-site experimentations

The approach is based on the use of machine learning algorithms for the evaluation of different VF configurations and allows for the prediction of the temperatures in the cavities and of the heat fluxes. The authors trained different regression algorithms and obtained low prediction errors, in particular for temperatures. The authors used such models to simulate the thermo-physical behavior of the VFs and determined the most energy-efficient design variant.

The authors found that regression trees allow for an accurate simulation of the thermal behavior of VFs. The authors also studied feature weights to determine the most relevant thermo-physical parameters. Finally, the authors determined the best design variant and the optimal air velocity in the cavity.

This study is unique in four main aspects: the thermo-dynamic analysis is performed under different thermal masses, positions of the cavity and geometries; the VFs are mated with a controlled ventilation system, used to parameterize the thermodynamic behavior under stepwise variations of the air inflow; temperatures and heat fluxes are predicted through machine learning models; the best configuration is determined through simulations, with no onerous in situ experimentations needed.