Pd(II)/Pd(0) Anchored on Magnetic Organic–Inorganic Hybrid Mesoporous Silica Nanoparticles: A Nanocatalyst for Suzuki–Miyaura and Heck–Mizoroki Coupling Reactions

Journal of Inorganic and Organometallic Polymers and Materials - 3-Chloropropyltrimethoxysilane (CPTMS) was grafted on the surface of silica coated Fe3O4 core (Fe3O4@MCM-41) and then condensed with...     

A compact split-step finite difference method for solving the nonlinear Schrödinger equations with constant and variable coefficients

We propose a compact split-step finite difference method to solve the nonlinear Schrödinger equations with constant and variable coefficients. This method improves the accuracy of split-step finite difference method by introducing a compact scheme for discretization of space variable while this improvement does not reduce the stability range and does not increase the computational cost. This method also preserves some conservation laws. Numerical tests are presented to confirm the theoretical results for the new numerical method by using the cubic nonlinear Schrödinger equation with constant and variable coefficients and Gross-Pitaevskii equation.     

Diffuse reflectance behavior of the printed cotton/nylon blend fabrics treated with zirconium and cerium dioxide and citric acid in near- and short-wave IR radiation spectral ranges

Near- and short-wave IR emission spectra of printed cotton/nylon blend fabrics coated with inorganic compounds in order to tune their diffuse reflectance behavior to the ones with woodland and desert backgrounds are investigated. In this regard, cotton/nylon blend fabrics printed with a four-color digital pattern were used as the substrate, and different concentrations of zirconium and cerium dioxide (ZrO₂ and CeO₂) with and without citric acid as a cross-linker were loaded on these fabrics using the pad-dry-cure method. The diffuse reflectance of the coated fabrics with various concentrations of nanoparticles and a cross-linker was first measured by near-infrared (NIR) diffuse reflectance spectroscopy (DRS). Then, fabrics with an optimum concentration of nanoparticles and appropriate reflectivity profiles similar to woodland and desert were investigated by field emission scanning electron microscopy (FE-SEM), energy-dispersive spectroscopy (EDS), washing, and rubbing fastness properties. In general, NIR and short-wave infrared (SWIR) reflectance of fabrics coated with ZrO₂ and CeO₂ nanoparticles in range of 1% to 1.5% (w/v [%]) was suitable for matching with different environments. According to the findings obtained from the durability test, it was concluded that the washing fastness of the treated fabrics with CeO₂ nanoparticles was excellent in both environments. FE-SEM images of the treated fabrics containing ZrO₂ and CeO₂ indicated that the presence of nanoparticles on the surface of fabrics in woodland patterns was greater than the desert ones. However, the coated fabrics with CeO₂ and citric acid in the woodland pattern have shown better dispersion with a mean particle size of 30 to 60 nm.     

Estimating the Aquifer’s Renewable Water to Mitigate the Challenges of Upcoming Megadrought Events

Water Resources Management - In arid and semi-arid regions of the world, the occurrence of prolonged drought events (megadroughts) associated with climate change can seriously affect the balance...     

Hyperspectral imaging as an effective tool for prediction the moisture content and textural characteristics of roasted pistachio kernels

The objective of this study was to develop calibration models for prediction of moisture content and textural characteristics (fracture force, hardness, apparent modulus of elasticity and compressive energy) of pistachio kernels roasted in different conditions (temperatures 90, 120 and 150 °C; times 20, 35 and 50 min and air velocities 0.5, 1.5 and 2.5 m/s) using Vis/NIR hyperspectral imaging and multivariate analysis. The effects of different pre-processing methods and spectral treatments such as normalization [multiplicative scatter correction (MSC), standard normal variate transformation (SNV)], smoothing (median filter, Savitzky–Golay and Wavelet) and differentiation (first derivative, D¹ and second derivative, D²) on the obtained data were investigated. The prediction models were developed by partial least square regression (PLSR) and artificial neural network (ANN). The results indicated that ANN models have higher potential to predict moisture content and textural characteristics of roasted pistachio kernels comparing to PLSR models. High correlation was observed between reflectance data and fracture force (R²?=?0.957 and RMSEP?=?3.386) using MSC, Savitzky–Golay and D¹, compressive energy (R²?=?0.907 and RMSEP?=?15.757) using the combination of MSC, Wavelet and D¹, moisture content (R²?=?0.907 and RMSEP?=?0.179) and apparent modulus of elasticity (R²?=?0.921 and RMSEP?=?2.366) employing combination of SNV, Wavelet and D¹, respectively. Moreover, Vis–NIR data correlated well with hardness (R²?=?0.876 and RMSEP?=?5.216) using SNV, Wavelet and D². These results showed the capability of Vis/NIR hyperspectral imaging and the central role of multivariate analysis in developing accurate models for prediction of moisture content and textural properties of roasted pistachio kernels.     

Photo-induced superhydrophilicity of nanocomposite TiO2-SiO2 thin film

In this work, TiO₂ and TiO₂-SiO₂ thin films on glass substrates were prepared by the sol-gel dip coating process. X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR) and X-ray photoelectron spectroscopy (XPS) were used to evaluate the structural and chemical properties of the films. The super-hydrophilicity was assessed by water contact angle measurement. XRD measurements confirmed the presence of polycrystalline anatase and rutile phases in the films. The water contact angle measurements showed that addition of SiO₂ has a significant effect on the super-hydrophilicity of TiO₂ thin films, especially if they are stored in a dark place.     

Time-splitting pseudo-spectral domain decomposition method for the soliton solutions of the one- and multi-dimensional nonlinear Schrödinger equations

In this paper, we study the simulation of nonlinear Schrödinger equation in one, two and three dimensions. The proposed method is based on a time-splitting method that decomposes the original problem into two parts, a linear equation and a nonlinear equation. The linear equation in one dimension is approximated with the Chebyshev pseudo-spectral collocation method in space variable and the Crank–Nicolson method in time; while the nonlinear equation with constant coefficients can be solved exactly. As the goal of the present paper is to study the nonlinear Schrödinger equation in the large finite domain, we propose a domain decomposition method. In comparison with the single-domain, the multi-domain methods can produce a sparse differentiation matrix with fewer memory space and less computations. In this study, we choose an overlapping multi-domain scheme. By applying the alternating direction implicit technique, we extend this efficient method to solve the nonlinear Schrödinger equation both in two and three dimensions, while for the solution at each time step, it only needs to solve a sequence of linear partial differential equations in one dimension, respectively. Several examples for one- and multi-dimensional nonlinear Schrödinger equations are presented to demonstrate high accuracy and capability of the proposed method. Some numerical experiments are reported which show that this scheme preserves the conservation laws of charge and energy.     

International Environmental Conflict Management in Transboundary River Basins

Despite signing a bilateral water treaty in 1973, water utilization in the Hirmand River Basin (HRB) has been a source of dispute between Iran and Afghanistan for many decades. While Iran accuses Afghanistan of depriving it of the Hirmand water due to dam construction in the upper basin, Afghanistan assures that it enforces the treaty. An evident reduction of the Hirmand River flow to Iran in recent years is fully attributed by Afghanistan to a reduction in precipitation in the basin. Although Iran disagrees and remains unconvinced by this line of reasoning. A fundamental lack of trust in collected and shared hydrological data has hindered dialog between the two neighbors. To address this issue, this study investigates the use of remote sensing information, as an independent source of data, for fact-finding in a highly disputed transboundary river basin. For this purpose, historical data (34 years) from two satellite precipitation products, PERSIANN-CDR and CHIRPS, were used to understand if precipitation characteristics and, subsequently, rainfall-runoff regimes have changed in the HRB. Results reveal that the frequency and amount of heavy precipitation have been increasing over the mountainous areas. The total amount of precipitation has been increasing significantly. The intensity of heavy precipitation, however, has been decreasing over the basin. In the upper basin, the duration of the wet period has increased, although the share of wet months in annual precipitation has been decreasing. In the lower basin, trends in seasonal and annual precipitation and most of the indices are insignificant, indicating water availability issues cannot be attributed to the changes in precipitation in the downstream area itself. These results can be used as an integral part of mutual fact-finding and trust-building exercise that supports water diplomacy to promote environmental cooperation between Iran and Afghanistan.