Dinuclear copper (II) and nickel (II) systems with planar M2N2O2 bridge

The tridentate ligand systemb (abbreviated as inkR₂) readily yield copper (II) and nickel (II) species of the formula M₂ (inkR₂)₂(CLO₄)₂. 2xH₂O (x=0–1). Dinuclear formulation is based on variable temperature magnetic susceptibility and conductivity data and on the known structure of some related systems. The Cu₂ (inkR₂) ₂ ²⁺ species are strongly antiferromagnetic (?2J=600–800 cm^?1) while the Ni₂(inkR₂) ₂ ²⁺ species are diamagnetic. The major coordination sphere is planar around each metal (II). The metal ions in a dimer are linked by planar M₂N₂O₂ bridge. The copper (II) and nickel (II) species freely form solid solutions. In these statistical scrambling of copper and nickel occur among the metal ion sites of the dimeric structure. Powder epr spectra of such mixed crystals are indicative of axial geometry around copper (II) ion.     

Artificial neural network‐based modeling of snow properties using field data and hyperspectral imagery

This study attempts to model snow wetness and snow density of Himalayan snow cover using a combination of Hyperspectral image processing and Artificial Neural Network (ANN). Initially, a total of 300 spectral signature measurements, synchronized with snow wetness and snow density, were collected in the field. The spectral reflectance of snow was then modeled as a function of snow properties using ANN. Four snow wetness and three snow density models were developed. A strong correlation was observed in near‐infrared and shortwave‐infrared region. The correlation analysis of ANN modeled snow density and snow wetness showed a strong linear relationship with field‐based data values ranging from 0.87–0.90 and 0.88–0.91, respectively. Our results indicate that an Artificial Intelligence (AI) approach, using a combination of Hyperspectral image processing and ANN, can be efficiently used to predict snow properties (wetness and density) in the Himalayan region. Recommendations for resource managers

• Snow properties, such as snow wetness and snow density are mainly investigated through field‐based survey but rugged terrains, difficult weather conditions, and logistics management issues establish remote sensing as an efficient alternative to monitor snow properties, especially in the mountain environment.
• Although Hyperspectral remote sensing is a powerful tool to conduct the quantitative analysis of the physical properties of snow, only a few studies have used hyperspectral data for the estimation of snow density and wetness in the Himalayan region. This could be because of the lack of synchronized snow properties data with field‐based spectral acquisitions.
• In combination with Hyperspectral image processing, Artificial Neural Network (ANN) can be a useful tool for effective snow modeling because of its ability to capture and represent complex input‐output relationships.
• Further research into understanding the applicability of neural networks to determine snow properties is required to obtain results from large snow cover areas of the Himalayan region.

     

An Amino‐Acid‐Based Self‐Healing Hydrogel: Modulation of the Self‐Healing Properties by Incorporating Carbon‐Based Nanomaterials

An amino‐acid‐based (11‐(4‐(pyrene‐1‐yl)butanamido)undecanoic acid) self‐repairing hydrogel is reported. The native hydrogel, as well as hybrid hydrogels, have been thoroughly characterized by using various microscopic techniques, including transmission electron microscopy (TEM), atomic force microscopy (AFM), Raman spectroscopy, fluorescence spectroscopy, FTIR spectroscopy, X‐ray diffraction, and by using rheological experiments. The native hydrogel exhibited interesting fluorescence properties, as well as a self‐healing property. Interestingly, the self‐healing, thixotropy, and stiffness of the native hydrogel can be successfully modulated by incorporating carbon‐based nanomaterials, including graphene, pristine single‐walled carbon nanotubes (Pr‐SWCNTs), and both graphene and Pr‐SWCNTs, within the native gel system. The self‐recovery time of the gel was shortened by the inclusion of reduced graphene oxide (RGO), Pr‐SWCNTs, or both RGO and Pr‐SWCNTs. Moreover, hybrid gels that contained RGO and/or Pr‐SWCNTs exhibited interesting semiconducting behavior.     

Diffusion and transport phenomena in a collisional magnetoplasma having both streaming and temperature anisotropy: Collisional kinetics

Boltzmann-transport equation is analytically solved for two-component magnetoplasma using Chapman-Enskog analysis to include collisional diffusion transport having anisotropies in both streaming velocity and temperature components. The modified collisional integrals are analytically solved with flux integrals and perturbed kinetic equation to arrive at drift diffusion velocity and resulting transport coefficients which are markedly affected by both streaming and temperature anisotropy. The early isotropic results are recovered in the limit V ₀ = 0 and T _‖ = T _⊥ which reduce to eqs (11.30) and (11.31) of [1] and eqs (2.7) and (2.13) of [2]. The electrical resistivity (η_⊥) diminishes sharply in fusion temperature limit kT _⊥ = 1 keV. The shape of the curves for both electrical resistivity and thermal conductivity is rectangular hyperbolic. However, for low thermal ratio (T _‖/T _⊥ < 1), the curves are raised up and for high thermal ratio (T _‖/T _⊥ > 1), they are lowered down the isotropic case (T _‖/T _⊥ > 1), showing comparatively diminished magnitudes of the quantities.      

Confinement resonances in photoionization of Xe@C₆₀+

Experimental evidence is presented for confinement resonances associated with photoabsorption by a Xe atom in a C60 cage. The giant 4d resonance in photoionization of Xe is predicted to be redistributed into four components due to multipath interference of photoelectron waves reflected by the cage. The measurements were made in the photon energy range 60-150 eV by merging a beam of synchrotron radiation with a mass/charge selected Xe@C??+ ion beam. The phenomenon was observed in the Xe@C(58)(3+) product ion channel. [corrected]     

Perspective and Prospective of Pretreatment of Corn Straw for Butanol Production

Corn straw, lignocellulosic biomass, is a potential substrate for microbial production of bio-butanol. Bio-butanol is a superior second generation biofuel among its kinds. Present researches are focused on the selection of butanol tolerant clostridium strain(s) to optimize butanol yield in the fermentation broth because of toxicity of bio-butanol to the clostridium strain(s) itself. However, whatever the type of the strain(s) used, pretreatment process always affects not only the total sugar yield before fermentation but also the performance and growth of microbes during fermentation due to the formation of hydroxyl-methyl furfural, furfural and phenolic compounds. In addition, the lignocellulosic biomasses also resist physical and biological attacks. Thus, selection of best pretreatment process and its parameters is crucial. In this context, worldwide research efforts are increased in past 12 years and researchers are tried to identify the best pretreatment method, pretreatment conditions for the actual biomass. In this review, effect of particle size, status of most common pretreatment method and enzymatic hydrolysis particularly for corn straw as a substrate is presented. This paper also highlights crucial parameters necessary to consider during most common pretreatment processes such as hydrothermal, steam explosion, ammonia explosion, sulfuric acid, and sodium hydroxide pretreatment. Moreover, the prospective of pretreatment methods and challenges is discussed.     

Spectroscopic, potentiometric and theoretical studies on the binding properties of a novel tripodal polycatechol-imine ligand towards iron(III)

A novel multidentate tripodal ligand, cis,cis-1,3,5-tris[(2,3-dihydroxybenzylidene)aminomethyl]cyclohexane (TDBAC, L) containing one catechol unit in each arms of a tripodal amine, cis,cis-1,3,5-tris(aminomethyl)cyclohexane was investigated as a chelator for iron(III) through potentiometric and spectrophotometric methods in an aqueous medium of 0.1N ionic strength and 25+/-1 degrees C as well as in ethanol by continuous variation method. From pH metric in water, three protonation constants characterized for the three-hydroxyl groups of the catechol units at ortho were used as input data to evaluate the stability constants of the complexes. Formation of monomeric complexes FeLH3, FeLH2, FeLH and FeL were depicted. In ethanol, formation of complexes FeL, Fe2L and Fe3L were characterized. Structures of the complexes were explained by using the experimental evidences and predicted through molecular modeling calculations. The ligand showed potential to coordinate iron(III) through three imine nitrogens and three catecholic oxygens at ortho to form a tris(iminocatecholate) type complex.