Overcoming interfacial affinity issues in natural fiber reinforced polylactide biocomposites by surface adsorption of amphiphilic block copolymers

This work demonstrates that the interfacial properties in a natural fiber reinforced polylactide biocomposite can be tailored through surface adsorption of amphiphilic and biodegradable poly (ethylene glycol)-b-poly-(L-lactide) (PEG-PLLA) block copolymers. The deposition from solvent solution of PEG-PLLA copolymers onto the fibrous substrate induced distinct mechanisms of molecular organization at the cellulosic interface, which are correlated to the hydrophobic/hydrophilic ratios and the type of solvent used. The findings of the study evidenced that the performance of the corresponding biocomposites with polylactide were effectively enhanced by using these copolymers as interfacial coupling agents. During the fabrication stage, diffusion of the polylactide in the melt induced a change in the environment surrounding block copolymers which became hydrophobic. It is proposed that molecular reorganization of the block copolymers at the interface occurred, which favored the interactions with both the hydrophilic fibers and hydrophobic polylactide matrix. The strong interactions such as intra- and intermolecular hydrogen bonds formed across the fiber−matrix interface can be accounted for the enhancement in properties displayed by the biocomposites. Although the results reported here are confined, this concept is unique as it shows that by tuning the amphiphilicity and the type of building blocks, it is possible to control the surface properties of the substrate by self-assembly and disassembly of the amphiphiles for functional materials.

Analysis of residues of prometryne and acetochlor in soil-water system by solid-phase extraction and gas chromatography/mass spectrometry

A highly sensitive and simple analytical method was developed for analyzing the binary mixed pesticides of prometryne and acetochlor in soil–water system by gas chromatography/mass spectrometry (GC/MS). The sample solution was first purified by C18 solid-phase extraction column, which was leached by acetone. The leachate was enriched to 1.0 mL by pressure blowing concentrator and then analyzed by GC/MS. The linear calibration curves were showed in the range of 1–15 μg/mL with a correlation coefficient of 0.9991. The average recoveries (n = 5) were between 95.3 and 115.7%, with relative standard deviations ranged from 1.71 and 7.95%. The limits of detection of Prometryne/Acetochlor were up to 0.06 and 0.17 μg/mL, respectively. This method provides a reliable approach to examine and evaluate the residues of prometryne and acetochlor in the soil–water system.

The impact of column connection on band broadening in very high pressure liquid chromatography

A series of experiments was conducted to evaluate the degree of band broadening in very high pressure LC due to column connections. Different column manufacturers use slightly different designs for their column fittings. If the same column connections are repeatedly used to attach columns of different origins, different void volumes form between capillary tubes and column inlets. An Agilent Ultra Low Dispersion Kit (tubing id 75 μm) was installed on an Agilent Infinity 1290 ultra HPLC and used to connect successively an Agilent, a Phenomenex, and a Waters column. A series of uracil (unretained) samples were injected and eluted at a wide range of flow rates with a water/acetonitrile mixture as eluent. In order to determine the variance contribution from column connections as accurately as possible a nonretained probe compound was selected because the variance contribution from the column is the smallest for analytes, which have very low k values. Yet, this effect still has an impact on the resolution for moderately retained compounds (k > 2) for narrow-bore columns packed with fine particles, since variance contributions are additive for linear chromatographic systems. Each injection was replicated five times under the same experimental conditions. Then NanoViper column connections (tubing id 75 μm) were used and the same injections were made. This system was designed to minimize connection void volumes for any column. Band variances were calculated as the second central moment of elution peaks and used to assess the degree of band broadening due to the column connections. Band broadening may increase from 3.8 to 53.9% when conventional metal ferrules were used to join columns to connection sites. The results show that the variance contribution from improper connections can generate as much as 60.5% of the total variance observed. This demonstrates that column connections can play a larger role than the column packing with respect to band dispersion.

Improving peak shapes with counter gradients in two-dimensional high performance liquid chromatography

To achieve the greatest peak capacity in two-dimensional high performance liquid chromatography (2D-HPLC) a gradient should be operated in both separation dimensions. However, it is known that when an injection solvent that is stronger than the initial mobile phase composition is deleterious to peak performance, thus causing problems when cutting a portion from one gradient into another. This was overcome when coupling hydrophilic interaction with reversed phase chromatography by introducing a counter gradient that changed the solvent strength of the second dimension injection. It was found that an injection solvent composition of 20% acetonitrile in water gave acceptable results in one-dimensional simulations with an initial composition of 5% acetonitrile. When this was transferred to a 2D-HPLC separation of standards it was found that a marked improvement in peak shape was gained for the moderately retained analytes (phenol and dimethyl phthalate), some improvement for the weakly retained caffeine and very little change for the strongly retained n-propylbenzene and anthracene which already displayed good chromatographic profiles. This effect was transferred when applied to a 2D-HPLC separation of a coffee extract where the indecipherable retention profile was transformed to a successful application multidimensional chromatography with peaks occupying 71% of the separation space according to the geometric approach to factor analysis.

Determination of neurotransmitters and their metabolites using one- and two-dimensional liquid chromatography with acidic potassium permanganate chemiluminescence detection

High-performance liquid chromatography with chemiluminescence detection based on the reaction with acidic potassium permanganate and formaldehyde was explored for the determination of neurotransmitters and their metabolites. The neurotransmitters norepinephrine and dopamine were quantified in the left and right hemispheres of rat hippocampus, nucleus accumbens and prefrontal cortex, and the metabolites vanillylmandelic acid, 3,4-dihydrophenylacetic acid, 5-hydroxyindole-3-acetic acid and homovanillic acid were identified in human urine. Under optimised chemiluminescence reagent conditions, the limits of detection for these analytes ranged from 2.5 × 10−8 to 2.5 × 10−7 M. For the determination of neurotransmitter metabolites in urine, a two-dimensional high-performance liquid chromatography (2D-HPLC) separation operated in heart-cutting mode was developed to overcome the peak capacity limitations of the one-dimensional separation. This approach provided the greater separation power of 2D-HPLC with analysis times comparable to conventional one-dimensional separations.

A framework for identifying affinity classes of inorganic materials binding peptide sequences

With the rapid development of bionanotechnology, there has been a growing interest recently in identifying the affinity classes of the inorganic materials binding peptide sequences. However, there are some distinct characteristics of inorganic materials binding sequence data that limit the performance of many widely-used classification methods. In this paper, we propose a novel framework to predict the affinity classes of peptide sequences with respect to an associated inorganic material. We first generate a large set of simulated peptide sequences based on our new amino acid transition matrix, and then the probability of test sequences belonging to a specific affinity class is calculated through solving an objective function. In addition, the objective function is solved through iterative propagation of probability estimates among sequences and sequence clusters. Experimental results on a real inorganic material binding sequence dataset show that the proposed framework is highly effective on identifying the affinity classes of inorganic material binding sequences.