Method development for compositional analysis of low molecular weight poly(vinyl acetate) by matrix-assisted/laser desorption-mass spectrometry and its application to analysis of chewing gum

The influence of the sample preparation parameters (the choice of the solvent and of the matrix:analyte ratio) was investigated and optimal conditions were established for MALDI mass spectrometry analysis of the pristine low molecular weight polyvinyl acetate (PVAc). It was demonstrated that comparison of polymer’s and solvent’s Hansen solubility parameters could be used as a guide when choosing the solvent for MALDI sample preparation. The highest intensity PVAc signals were obtained when ethyl acetate was used as a solvent along with the lowest matrix–analyte ratio (2,5-dihydroxybenzoic acid was used as a matrix in all experiments). The structure of the PVAc was established with high accuracy using the matrix-assisted laser desorption/ionization-Fourier transform mass spectrometry (MALDI-FTMS) analysis. It was demonstrated that PVAc undergoes unimolecular decomposition by losing acetic acid molecules from its backbone under the conditions of FTMS measurements. Number and weight average molecular weights as well as polydispersity indices were determined with both MALDI-TOF and MALDI-FTMS methods. The sample preparation protocol developed was applied to the analysis of a chewing gum and the molecular weight and structure of the polyvinyl acetate present in the sample were established. Thus, it was shown that optimized MALDI mass spectrometry could be used successfully for characterization of polyvinyl acetate in commercially available chewing gum.     

Experimental designs characterizing seasonal variations and solvent effects on the quantities of coumarin and related metabolites from Mikania laevigata

Statistical design mixtures of acetone, chloroform, dichloromethane and ethanol were used to study the effects of different solvents and their mixtures on the quantities of coumarin and related metabolites extracted from Mikania laevigata samples harvested in each of the four seasons. RP-HPLC-DAD and both positive and negative modes of UPLC-MS analyses were used to determine relative quantities of coumarin, o-coumaric acid and melilotic acids in each season for all the mixture design extracts. The existence and measurement of the relative abundances of melilotic acid in Mikania laevigata have not been reported previously. Highest coumarin concentrations were encountered in the summer whereas its o-coumaric acid precursor and melilotic acid were most abundant in the spring. O-coumaric and melilotic acids concentrations were strongly correlated during the year. Also solvent effects were seen to be significant. Ethanol and 1:1 binary mixtures of ethanol and acetone extracted the largest quantities of coumarin whereas ethanolic binary and ternary mixtures with chloroform and dichloromethane provided the best yields of o-coumaric and melilotic acids. Statistical mixture models indicated that synergic binary interactions, especially those involving ethanol with acetone or chloroform, are important in the Mikania extraction process.     

Estimation of rotation ambiguity in multivariate curve resolution with charged particle swarm optimization (cPSO‐MCR)

Rotation ambiguity (RA) in multivariate curve resolution (MCR) is an undesirable case, when the physicochemical constraints are not sufficiently strong to provide a unique resolution of the data matrix of the mixtures into spectra and concentration profiles of individual chemical components. RA is often met in MCR of overlapped chromatographic peaks, kinetic and equilibrium data, and fluorescence two‐dimensional spectra. In case of RA, a single candidate solution has little practical value. So, the whole set of feasible solutions should be characterized somehow. It is a quite intricate task in a general case. In the present paper, a method was proposed to estimate RA with charged particle swarm optimization (cPSO), a population‐based algorithm. The criteria for updating the particles were modified, so that the swarm converged to the steady state, which spanned the set of feasible solutions. The performance of cPSO‐MCR was demonstrated on test functions, simulated datasets, and real‐world data. Good accordance of the cPSO‐MCR results with the analytical solutions (Borgen plots) was observed. cPSO‐MCR was also shown to be capable of estimating the strength of the constraints and of revealing RA in noisy data. As compared with analytical methods, cPSO‐MCR is simpler to implement, expands to more than three chemical compounds, is immune to noise, and can be easily adapted to virtually all types of constraints and objective functions (constraint based or residue based). cPSO‐MCR also provides natural visual information about the level of RA in spectra and concentration profiles, similar to the methods of two extreme solutions (e.g., MCR‐BANDS). Copyright © 2014 John Wiley & Sons, Ltd.     

维布妥昔单抗关键中间体的合成工艺优化

本研究对维布妥昔单抗关键中间体(1)的合成工艺进行了改进与优化。以芴甲氧羰基-L-缬氨酸琥珀酰亚胺酯(2)为起始原料,先后经酯的氨解反应、酰胺化、Fmoc脱保护、酰胺化与酯交换反应制得目标产品1,总收率11.6%,纯度99.2%,产物结构经1H NMR, 13C NMR和HRMS表征。优化后的工艺路线具有反应条件温和、可操作性强、生产过程更安全的特点。在初步放大试验中,首步投料量达百克级别,并已完成三批工艺验证,适合于工业化生产。     

A theoretical investigation on optimal structures of ethane clusters (C2H6)n with n ≤ 25 and their building-up principle

Geometry optimization of ethane clusters (C(2)H(6))(n) in the range of n ≤ 25 is carried out with a Morse potential. A heuristic method based on perturbations of geometries is used to locate global minima of the clusters. The following perturbations are carried out: (1) the molecule or group with the highest energy is moved to the interior of a cluster, (2) it is moved to stable positions on the surface of a cluster, and (3) orientations of one and two molecules are randomly modified. The geometry obtained after each perturbation is optimized by a quasi-Newton method. The global minimum of the dimer is consistent with that previously reported. The putative global minima of the clusters with 3 ≤ n ≤ 25 are first proposed and their building-up principle is discussed.     

Accordion-optimized DEPT experiments

In this contribution, a pulse sequence is described for recording accordion-optimized DEPT experiments. The proposed ACCORDEPT experiment detects a wide range of one-bond coupling constants using accordion optimization. As a proof of concept, this strategy has been applied to a mesogen containing a large range of one-bond (1)J(CH) coupling constants associated with the various structural elements. The ACCORDEPT experiment afforded significant enhancements for the resonances with the larger (1)J(CH) couplings, similar SNR for aliphatic resonances, but reduced SNR for aliphatic resonances as compared with the standard DEPT experiment. In addition, the ACCORDEPT is straightforward to implement, does not require any supplementary calibration procedures and can be used under automated conditions without difficulty by inexperienced users.     

Desirability-based optimization and its sensitivity analysis for the perindopril and its impurities analysis in a microemulsion LC system

In the current paper the application of multiobjective optimization (MOOP) technique, via Derringer's desirability function, to a microemulsion liquid chromatographic (MELC) method is described. Chromatographic separation of perindopril tert-butylamine and its four impurities was selected as the case study. Central composite design (CCD) with fractional factorial design, ± 0.5 α star design and four replications in central point was applied for a response surface study, in order to examine in depth the effects of the most important factors. As factors that influence the system mostly (i) content of ethyl acetate and (ii) butyl acetate in composite internal phase, (iii) content of sodium dodecyl sulfate (surfactant) and (iv) n-butanol (co-surfactant), as well as (v) pH of the mobile phase were selected. Retention factor of (a) perindoprilat and (b) impurity Y 31 and (c) resolution factor for impurities Y 32 and 33 were chosen for simultaneous optimization. By adjustment of the importance coefficients and weights, according to defined objectives, the optimal mobile phase composition was predicted to be: 0.24% w/v butyl acetate, 0.3% w/v ethyl acetate, 2% w/v SDS, 7.75% w/v n-butanol and pH of the mobile phase 3.7. The sensitivity analysis of desirability function for these optimal conditions was conducted for the first time in LC separations, by applying a sensitivity procedure. The performed sensitivity analysis confirmed that the higher overall desirability does not necessarily mean a better solution. The accuracy of prediction might be affected if the optimal levels of input variables, achieved from several design points, end up with equal settings and different corresponding overall desirability. In our study this was not the issue, which confirmed the adequacy of predicted optimum.     

A new and efficient variable selection algorithm based on ant colony optimization. Applications to near infrared spectroscopy/partial least-squares analysis

A new variable selection algorithm is described, based on ant colony optimization (ACO). The algorithm aim is to choose, from a large number of available spectral wavelengths, those relevant to the estimation of analyte concentrations or sample properties when spectroscopic analysis is combined with multivariate calibration techniques such as partial least-squares (PLS) regression. The new algorithm employs the concept of cooperative pheromone accumulation, which is typical of ACO selection methods, and optimizes PLS models using a pre-defined number of variables, employing a Monte Carlo approach to discard irrelevant sensors. The performance has been tested on a simulated system, where it shows a significant superiority over other commonly employed selection methods, such as genetic algorithms. Several near infrared spectroscopic experimental data sets have been subjected to the present ACO algorithm, with PLS leading to improved analytical figures of merit upon wavelength selection. The method could be helpful in other chemometric activities such as classification or quantitative structure-activity relationship (QSAR) problems.     

Multiobjective optimization scheme for industrial synthesis gas sweetening plant in GTL process

In industrial amine plants the optimized operating conditions are obtained from the conclusion of occurred events and challenges that are normal in the working units. For the sake of reducing the costs, time consuming, and preventing unsuitable accidents, the optimization could be performed by a computer program. In this paper, simulation and parameter analysis of amine plant is performed at first. The optimization of this unit is studied using Non-Dominated Sorting Genetic Algorithm-II in order to produce sweet gas with CO 2 mole percentage less than 2.0% and H 2 S concentration less than 10 ppm for application in Fischer-Tropsch synthesis. The simulation of the plant in HYSYS v.3.1 software has been linked with MATLAB code for real-parameter NSGA-II to simulate and optimize the amine process. Three scenarios are selected to cover the effect of (DEA/MDEA) mass composition percent ratio at amine solution on objective functions. Results show that sour gas temperature and pressure of 33.98 ? C and 14.96 bar, DEA/CO 2 molar flow ratio of 12.58, regeneration gas temperature and pressure of 94.92 ? C and 3.0 bar, regenerator pressure of 1.53 bar, and ratio of DEA/MDEA = 20%/10% are the best values for minimizing plant energy consumption, amine circulation rate, and carbon dioxide recovery.