Determination of vitamin C and preservatives in beverages by conventional capillary electrophoresis and microchip electrophoresis with capacitively coupled contactless conductivity detection

The separation and detection of commonly used preservatives (benzoate, sorbate) and vitamin C by both conventional CE and microchip electrophoresis with capacitively coupled contactless conductivity detection is presented. The separation was optimized by adjusting the pH-value of the buffer and the use of hydroxypropyl-beta-CD (HP-beta-CD) and CTAB as additives. For conventional CE, optimal separation conditions were achieved in a histidine/tartrate buffer at pH 6.5, containing 0.025% HP-beta-CD and 0.1 mM CTAB. LOD ranged from 0.5 to 3 mg/L (S/N = 3) and the RSDs for migration time and peak area were less than 0.1 and 2%, respectively. A considerable reduction of analysis time can be accomplished by using microchip electrophoresis without significant loss in sensitivity under optimal separation conditions. A histidine/tartrate buffer at pH 6.5, incorporating 0.06% HP-beta-CD and 0.25 mM CTAB, gave detection limits ranging between 3 and 10 mg/L and satisfactory reproducibilities of < or =0.4% for the migration time and < or =3.5% for the peak area. The methods developed are useful for the quantitative determination of food additives in real samples such as soft drinks and vitamin C tablets.     

The fluorobasicities of ReF7 and IF7 as measured by the enthalpy change ΔH°(EF7(g) → EF6+(g) + F−(g))

Iridium hexafluoride oxidizes ReF₆ (via an ReF₆⁺ salt) and at room temperatures IrF₆, ReF₆, ReF₇ and (IrF₅)₄ are each present in the equilibrium mixture. From these and related findings: ΔH°(ReF₆ → ReF₆⁺ + e^?) 1092 ± 27 kj mole^?1(261 ± 6 kcal mole^?1), and thermodynamic data are selected to yield ΔH°(ReF_7(g) → ReF₆⁺_(g) + F^?_(g))=893 ± 33 kj mole^?1(213 ± 8 kcal mole^?1). From observations on the stability of IF₆⁺BF₄^? and the lattice enthalpy evaluation for the salt, ΔH°(IF_7(g) → IF₆⁺_(g) + F^?_(g))= 870 ± 24 kj mole^?1(208 ± 6 kcal mole^?1).     

Preparation of water‐soluble,syndiotacticity‐rich,low molecular weight poly(vinyl alcohol) microfibrils in high yields with the low‐temperature polymerization of vinyl pivalate in tetrahydrofuran and saponification

To prepare water‐soluble, syndiotacticity‐rich poly(vinyl alcohol) (PVA) microfibrils for various industrial applications, we synthesized syndiotacticity‐rich, low molecular weight PVA by the solution polymerization of vinyl pivalate (VPi) in tetrahydrofuran (THF) at low temperatures with 2,2′‐azobis(2,4‐dimethylvaleronitrile) (ADMVN) as an initiator and successive saponification of poly(vinyl pivalate) (PVPi). Effects of the initiator and monomer concentrations and the polymerization temperature were investigated in terms of the polymerization behaviors and molecular structures of PVPi and the corresponding syndiotacticity‐rich PVA. The polymerization rate of VPi in THF was proportional to the 0.91 power of the ADMVN concentration, indicating the heterogeneous nature of THF polymerization. The low‐temperature solution polymerization of VPi in THF with ADMVN proved to be successful in obtaining water‐soluble PVA with a number‐average degree of polymerization (P_n) of 300–900, a syndiotactic dyad content of 60–63%, and an ultimate conversion of VPi into PVPi of over 75%. Despite the low molecular weight of PVA with P_n = 800, water‐soluble PVA microfibrillar fibers were prepared because of the high level of syndiotacticity. In contrast, for PVA with P_n = 330, shapeless and globular morphologies were observed, indicating that molecular weight has an important role in the in situ fibrillation of syndiotacticity‐rich PVA. © 2002 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 40: 1103–1111, 2002     

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.     

Application of flammability limit criteria on non-ASTM standard equipment

Journal of Thermal Analysis and Calorimetry - Accurate data of flammability limits for flammable gases and vapors are needed to prevent fires and explosions. The flammability limit, which is the...     

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.

     

Lignin Biodegradation by a Cytochrome P450 Enzyme: A Computational Study into Syringol Activation by GcoA

A recently characterized cytochrome P450 isozyme GcoA activates lignin components through a selective O-demethylation or alternatively an acetal formation reaction. These are important reactions in biotechnology and, because lignin is readily available; it being the main component in plant cell walls. In this work we present a density functional theory study on a large active site model of GcoA to investigate syringol activation by an iron(IV)-oxo heme cation radical oxidant (Compound I) leading to hemiacetal and acetal products. Several substrate-binding positions were tested and full energy landscapes calculated. The study shows that substrate positioning determines the product distributions. Thus, with the phenol group pointing away from the heme, an O-demethylation is predicted, whereas an initial hydrogen-atom abstraction of the weak phenolic O-H group would trigger a pathway leading to ring-closure to form acetal products. Predictions on how to engineer P450 GcoA to get more selective product distributions are given.     

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.