Local and global chirality at surfaces: succinic acid versus tartaric acid on Cu110

A detailed comparison of tartaric acid (HOOC-CHOH-CHOH-COOH) and succinic acid (HOOC-CH(2)-CH(2)-COOH) molecules on a Cu(110) surface is presented with a view to elucidate how the two-dimensional chirality exhibited by such robust, chemisorbed systems is affected when both OH groups of the former molecule are replaced with H groups, a stereochemical change that leaves the metal-bonding functionalities of the molecule untouched but destroys both chiral centers. It is found that this change does not significantly affect the thermodynamically preferred chemical forms that are adopted, namely the doubly deprotonated bicarboxylate at low coverages (theta 相似文献   

The structure and crystallization of thin water films on Pt(111)

When water is adsorbed on Pt(111) above 135 K several different ice structures crystallize, depending on the thickness of the ice layer. At low coverage water forms extended islands of ice with a (square root(37) x square root(37))R25(o) unit cell, which compresses as the monolayer saturates to form a (square root(39) x square root(39))R16(o) structure. The square root(39) low-energy electron diffraction (LEED) pattern becomes more intense as the second layer grows, remaining bright for films up of 10-15 layers and then fading and disappearing for films more than ca. 40 layers thick. The ice multilayer consists of an ordered square root(39) wetting layer, on which ice grows as a crystalline film which progressively loses its registry to the wetting layer. Ice films more than ca. 50 layers thick develop a hexagonal LEED pattern, the entire film and wetting layer reorienting to form an incommensurate bulk ice. These changes are reflected in the vibrational spectra which show changes in line shape and intensity associated with the different ice structures. Thin amorphous solid water films crystallize to form the same phases observed during growth, implying that these structures are thermodynamically stable and not kinetic phases formed during growth. The change from a square root(39) registry to incommensurate bulk ice at ca. 50 layers is associated with a change in crystallization kinetics from nucleation at the Pt(111) interface in thin films to nucleation of incommensurate bulk ice in amorphous solid water films more than 50 layers thick.     

Validated TLC-densitometry method for the simultaneous analysis of pyrethroid insecticides in agricultural and domestic products

ABSTRACT: BACKGROUND: Pyrethroids are widely used for the control of pests and insects, as pyrethroids are believed to pose very little risk to human health and environment. However, exposure to the pyrethroids exceeding the label directions might adversely affect human health and environment. Hence a careful selection of environment friendly household product is required that must contain exactly the label claimed pyrethroids amount. RESULTS: A sensitive and robust TLC-densitometric method for simultaneous quantification of commonly used synthetic pyrethroids including esbiothrin, alpha-cypermethrin and cis/trans permethrin in agricultural and domestic products has been developed and validated. TLC aluminum plates, precoated with 0.2 mm thick layer of silica gel 60 F-254, were used for chromatographic process. Densitometric analysis of chromatoplates was carried out in absorbance mode at corresponding lamdamax of each pyrethroid. Equally valid common mobile phase for all pyrethroids consisted of hexane-dichloromethane-ethylacetate-formic acid (8:1.5:0.4:0.1 v/v/v/v) which provided sharp and symmetrical peaks of esbiothrin, alpha-cypermethrin, trans-permethrin and cis-permethrin, at Rf 0.31, 0.53, 0.6 and 0.65, respectively. Linear regression data for respective calibration curves showed a good linearity for all pyrethroids with r = 0.991-0.996. Limits of detection (LOD) and limits of quantification (LOQ) for all pyrethroids were found in the range of 1.6-2.8 and 4.9-8.5 ng/spot, respectively. CONCLUSIONS: The developed method is applicable for separating the mixture of pyrethroids and at the same time, it is also valid for separating their isomers. The method is reproducible, precise and accurate for the quantitative determination of pyrethroids in agricultural and domestic products.     

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.

     

Offline estimation of 2D crystal lattice parameters by processing the electron diffraction image

Electron diffraction provides useful information about the internal composition of materials and has been in the use of material scientists for more than fifty years. In order to extract useful information from offline diffraction images, they are manually analyzed by using some photometric technique. Manual analysis is however a cumbersome, laborious and difficult task. To reduce the labors of material scientists one can employ image processing techniques to perform automated analysis, due to the well established popularity and clear evidence of widely used image processing techniques. In this work an image processing technique is being proposed for the extraction of 2D unit cell information from diffraction images on one hand and finding the 2D point group contained by the lattices on the other. The technique employs a morphological shrinking operation to find the center of each spot in the underlying preprocessed diffraction image. This is followed by the extraction of eight points with reference to the spot produced by the transmitted electron beam. The resultant nine points, i.e. the extracted eight plus the reference spot generated by the transmitted electron beam, are then subjected to symmetry operations, rotation symmetry and mirror symmetry, in polar coordinate system, to classify the point group of the lattice produced by the electron diffraction. One of the difficult task, even in manual analysis, is to ascertain the exact spot where the transmitted electron beam hit the sample at the time of realization of the image. This has been accurately and intuitively done by employing the notion that the transmitted spot must have greater number of pixels, with the highest gray value, among the diffracted spots. The proposed strategy has been applied to a sample set of various images and the results shows that the technique is efficient in determining the unit cell in 2D and classify the point group with good accuracy.     

Ethylene Glycol as New Mobile Phase for Resolution of Two-Component Mixture of Cationic Surfactants on Alumina Surface

Aqueous ethylene glycol (ethane 1,2 diol) as a green mobile phase has been used for thin layer chromatographic (TLC) studies of cationic surfactants on alumina layers. Nineteen solvent systems were used to examine the mobility of the surfactants and to discover the best TLC system for the selective separation of dodecyl trimethylammonium bromide (DTAB) from multi-component mixture of other surfactants. Among the TLC systems studied, M₃ (ethylene glycol: water, 8:2) was best for achieving the selective separation of DTAB from multi-component mixture of other surfactants because in this mobile phase mobility of all surfactants except DTAB were insignificant. Effect of organic additives in aqueous ethylene glycol mobile phase on the mobility of surfactants was examined. The results obtained on laboratory made alumina TLC plates and commercially available precoated alumina HPTLC plates were compared. The lower limits of detection of DTAB, CPC, CTAB, HDTAC, and TTAB were 0.02, 0.05, 0.04, 0.06, or 0.08 µg per zone respectively. The resolution of mixture of cationic surfactants was also examined in the presence metal cations as an impurity in the analyzed sample.     

Mixed solvents for cellulose derivatization under homogeneous conditions: kinetic,spectroscopic, and theoretical studies on the acetylation of the biopolymer in binary mixtures of an ionic liquid and molecular solvents

Rate constants for the acetylation of microcrystalline cellulose (MCC), by ethanoic anhydride in the presence of increasing concentrations of the ionic liquid (IL), 1-allyl-3-methylimidazolium chloride in dipolar aprotic solvents (DAS), N,N-dimethylacetamide (DMAC), and acetonitrile (MeCN), have been calculated from conductivity data. The third order rate constants showed a linear dependence on [IL]. We explain this result by assuming that the reacting cellulose is hydrogen-bonded to the IL. This is corroborated by kinetic data of the acetylation of cyclohexylmethanol, FTIR of the latter compound and of cellobiose in mixtures of IL/DAS, and conductivity of the binary solvent mixtures in absence, and presence of MCC. Cellulose acetylation is faster in IL/DMAC than in IL/MeCN; this difference is explained based on solvatochromic data (empirical polarity and basicity) and molecular dynamics simulations. Results of the latter indicate hydrogen-bond formation between the hydroxyl groups of the anhydroglucose unit of MCC, (Cl^?) of the IL, and the dipole of the DMAC. Under identical experimental conditions, acetylation in IL/DMAC is faster than that in LiCl/DMAC (2.7–8 times), due to differences in the enthalpies and entropies of activation.     

Analysis of two neutron (proton) transfer reaction data in the Zr-region

The spectroscopic amplitudes, form factors, angular distributions and total cross-sections for two nucleon transfer reactions in Zr-region in the zero range distorted wave Born approximation are calculated using consistent set of shell model wave functions. A single normalisation factor gives a good fit to all the two neutron transfer reaction data whereas the corresponding fit for the two-proton transfer reaction data is less satisfactory.