Experimental investigation for stability and surface properties of TiO2 and Al2O3 water-based nanofluids

Journal of Thermal Analysis and Calorimetry - Nanofluids have gained recent attention because of their potential applications in diverse engineering fields like enhancing thermal transport,...     

Height in splittings of relatively hyperbolic groups

Geometriae Dedicata - Given a finite graph of relatively hyperbolic groups with its fundamental group relatively hyperbolic and edge groups quasi-isometrically embedded and relatively quasiconvex...     

Fibrillar Networks of Glycyrrhizic Acid for Hybrid Nanomaterials with Catalytic Features

Self‐assembly of the naturally occurring sweetening agent, glycyrrhizic acid (GA) in water is studied by small‐angle X‐ray scattering and microscopic techniques. Statistical analysis on atomic force microscopy images reveals the formation of ultralong GA fibrils with uniform thickness of 2.5 nm and right‐handed twist with a pitch of 9 nm, independently of GA concentration. Transparent nematic GA hydrogels are exploited to create functional hybrid materials. Two‐fold and three‐fold hybrids are developed by introducing graphene oxide (GO) and in situ‐synthesized gold nanoparticles (Au NPs) in the hydrogel matrix for catalysis applications. In the presence of GO, the catalytic efficiency of Au NPs in the reduction of p‐nitrophenol to p‐aminophenol is enhanced by 2.5 times. Gold microplate single crystals are further synthesized in the GA hydrogel, expanding the scope of these hybrids and demonstrating their versatility in materials design.     

Atomically flat single terminated oxide substrate surfaces

Scientific interest in atomically controlled layer-by-layer fabrication of transition metal oxide thin films and heterostructures has increased intensely in recent decades for basic physics reasons as well as for technological applications. This trend has to do, in part, with the coming post-Moore era, and functional oxide electronics could be regarded as a viable alternative for the current semiconductor electronics. Furthermore, the interface of transition metal oxides is exposing many new emergent phenomena and is increasingly becoming a playground for testing new ideas in condensed matter physics. To achieve high quality epitaxial thin films and heterostructures of transition metal oxides with atomically controlled interfaces, one critical requirement is the use of atomically flat single terminated oxide substrates since the atomic arrangements and the reaction chemistry of the topmost surface layer of substrates determine the growth and consequent properties of the overlying films. Achieving the atomically flat and chemically single terminated surface state of commercially available substrates, however, requires judicious efforts because the surface of as-received substrates is of chemically mixed nature and also often polar. In this review, we summarize the surface treatment procedures to accomplish atomically flat surfaces with single terminating layer for various metal oxide substrates. We particularly focus on the substrates with lattice constant ranging from 4.00 Å to 3.70 Å, as the lattice constant of most perovskite materials falls into this range. For materials outside the range, one can utilize the substrates to induce compressive or tensile strain on the films and explore new states not available in bulk. The substrates covered in this review, which have been chosen with commercial availability and, most importantly, experimental practicality as a criterion, are KTaO₃, REScO₃ (RE = Rare-earth elements), SrTiO₃, La_0.18Sr_0.82Al_0.59Ta_0.41O₃ (LSAT), NdGaO₃, LaAlO₃, SrLaAlO₄, and YAlO₃. Analyzing all the established procedures, we conclude that atomically flat surfaces with selective A- or B-site single termination would be obtained for most commercially available oxide substrates. We further note that this topmost surface layer selectivity would provide an additional degree of freedom in searching for unforeseen emergent phenomena and functional applications in epitaxial oxide thin films and heterostructures with atomically controlled interfaces.     

Synthesis and biological evaluation of novel 4-(6-substituted quinolin-4-yl)-N-aryl thiazol-2-amine derivatives as potential antimicrobial agents

Cyclocondensation reaction of 4-(2-bromoacetyl)quinolin-1-ium bromide ( 4a–d ) with substituted arylthiourea, ( 5a–g ) afforded 4-(6-substituted quinolin-4-yl)-N-aryl/pyridyl thiazol-2-amine ( 6a-ab ). These newly synthesized derivatives were evaluated for in vitro antibacterial activity against Escherichia coli (NCIM 2574), Proteus mirabilis (NCIM 2388) (Gram-negative strains), Bacillus subtilis (NCIM 2063), Staphylococcus albus (NCIM 2178) (Gram-positive strains) and in vitro antifungal activity against Aspergillus niger (ATCC 504) and Candida albicans (NCIM 3100). Compounds 6a , 6b , 6d , 6f , 6k , and 6l showed moderate to good antibacterial activity against S. albus. Ten derivatives 6c , 6q , 6r , 6s , 6t , 6v , 6w , 6x , 6y , and 6aa , showed moderate to good activity against A. niger. N-[4-(Quinolin-4-yl)-1,3-thiazol-2-yl]pyridin-2-amine presented comparable activity against A. niger with respect to standard drug Rouconazole.     

Association reaction between SiH3 and H2O2: a computational study of the reaction mechanism and kinetics

The association reaction between silyl radical (SiH₃) and H₂O₂ has been studied in detail using high-level composite ab initio CBS-QB3 and G4MP2 methods. The global hybrid meta-GGA M06 and M06-2X density functionals in conjunction with 6-311++G(d,p) basis set have also been applied. To understand the kinetics, variational transition-state theory calculation is performed on the first association step, and successive unimolecular reactions are subjected to Rice–Ramsperger–Kassel–Marcus calculations to predict the reaction rate constants and product branching ratios. The bimolecular rate constant for SiH₃–H₂O₂ association in the temperature range 250–600 K, k(T) = 6.89 × 10^?13 T ^?0.163exp(?0.22/RT) cm³ molecule^?1 s^?1 agrees well with the current literature. The OH production channel, which was experimentally found to be a minor one, is confirmed by the rate constants and branching ratios. Also, the correlation between our theoretical work and experimental literature is established. The production of SiO via secondary reactions is calculated to be one of the major reaction channels from highly stabilized adducts. The H-loss pathway, i.e., SiH₂(OH)₂ + H, is the major decomposition channel followed by secondary dissociation leading to SiO.     

H2-release from alcohols,diols, and compounds with amino functionality promoted by titanium(II) sandwich complex, [Cp2Ti]: a theoretical approach

Structural Chemistry - The role of Ti(II) sandwich complex, [Cp2Ti], generated by the combination of [Cp2TiCl2] and two equivalents of nBuLi, in situ, in toluene has been investigated theoretically...     

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.