Kinetic study of propane dehydrogenation and catalyst deactivation over Pt-Sn/Al2O3 catalyst

The kinetics of propane dehydrogenation and catalyst deactivation over Pt-Sn/Al2O3 catalyst were studied.Performance test runs were carried out in a fixed-bed integral reactor.Using a power-law rate expression for the surface reaction kinetics and independent law for deactivation kinetics,the experimental data were analyzed both by integral and a novel differential method of analysis and the results were compared.To avoid fluctuation of time-derivatives of conversion required for differential analysis,the conversion-time data were first fitted with appropriate functions.While the time-zero and rate constant of reaction were largely insensitive to the function employed,the rate constant of deactivation was much more sensitive to the function form.The advantage of the proposed differential method,however,is that the integration of the rate expression is not necessary which otherwise could be complicated or impossible.It was also found that the reaction is not limited by external and internal mass transfer limitations,implying that the employed kinetics could be considered as intrinsic ones.     

Chemometrics-assisted excitation-emission fluorescence spectroscopy for simultaneous determination of ethoxyquin and tert-butylhydroquinone in biological fluid samples

A novel method applying simple, rapid, effective and inexpensive excitation-emission matrix (EEM) fluorescence spectroscopy coupled with second-order calibration method for simultaneous determination of ethoxyquin (EQ) and tert-butylhydroquinone (TBHQ) contents in biological fluid samples was developed. After a simple data preprocessing that was to insert zeros below the first-order Rayleigh scattering, the second-order calibration method based on the alternating normalization-weighed error (ANWE) algorithm was used to deal with EEM data. Via the introduced "second-order advantage", the individual con- centrations of the analytes of interest could be obtained even in the presence of uncalibrated interferences. The experimental concentration ranges for the analytes were as follows: EQ, from 4.58 to 20.6 g mL 1 in plasma and from 6.87 to 20.6 g mL 1 in urine; TBHQ, from 4.49 to 20.2 g mL-1 in plasma and from 6.73 to 22.4 g mL-1 in urine. The recoveries from spiked biological fluid samples were in the ranges of 92.8%-106.2% for EQ and 94.6%-107.2% for TBHQ. These results demonstrate that the three-dimensional EEM fluorescence with second-order calibration method is a powerful tool for obtaining both EQ and TBHQ quantitative results in plasma and urine samples, and could be applied to more complex matrices.     

Prediction of the isothermal behaviour of solid-gas systems from non-isothermal data

A new procedure for the prediction of the isothermal behaviour of the solid-gas system from non-isothermal data is suggested. It bypasses the use of various approximations of the temperature integral that ground the integral methods of prediction. The procedure was checked for: (1) simulated data corresponding to a first order reaction; (2) experimental data obtained in the isothermal and non-isothermal decompositions of ammonium perchlorate. For the simulated data, a very good agreement between calculated isotherms and those evaluated by means of the suggested procedure was obtained. A satisfactory agreement (errors in time evaluation corresponding to a given degradation lower than 18%, for 0.10￡a￡0.37 and lower than 10% for 0.37￡a￡0.70) was obtained for the experimental data corresponding to the decomposition of ammonium perchlorate. In this last case, the mentioned differences between experimental and calculated data can be due both to the inherent errors in the evaluation of the decomposition isotherms and to the dependence of the activation energy on the conversion degree. This revised version was published online in July 2006 with corrections to the Cover Date.     

Simultaneous and interference-free determination of eleven non-steroidal anti-inflammatory drugs illegally added into Chinese patent drugs using chemometrics-assisted HPLC-DAD strategy

In this work, a smart strategy that combines three-way high performance liquid chromatography-diode array detection(HPLCDAD) data with second-order calibration method based on alternating trilinear decomposition(ATLD) algorithm was proposed for simultaneous determination of eleven non-steroidal anti-inflammatory drugs(NSAIDs) illegally added into Chinese patent drugs and health products. All target analytes were rapidly eluted out within 14.5 min under a simple gradient elution. With the aid of the prominent "second-order advantage" of the ATLD algorithm, three HPLC problems, i.e. peak overlaps, unknown interferences and baseline drift, could be mathematically calibrated, and pure signals of target analytes could be extracted out from heavy-interference but information-rich HPLC-DAD data. The average spiked recoveries for all target analytes were in the range of 95.9%–106.4% with standard deviations lower than 7.5%. Validation parameters including sensitivity(SEN), selectivity(SEL), limit of detection(LOD), limit of quantitation(LOQ) and precisions of intra-day and inter-day were calculated to validate the accuracy of the proposed method, quantitative results were further confirmed by the classic HPLC method, which proved that chemometrics-assisted HPLC-DAD analytical strategy was highly efficient, accurate and green for drug-abuse monitoring of NSAIDs in Chinese patent drugs and health products.     

The Adsorption and Photocatalytic Decomposition of Citric Acid on Pt/TiO_2

The adsorption and photocatalutic decomposition of citric acid on both Pt/TiO2 powder and n-TiO2 single crystal electrode were studied in aqueous solutions of various pH. It was found that citrate ions were chemisorbed on TiO2, which could increase the interfacial capacity and the filling factor of photocurrent-potential curves. The quantity of adsorption, slope of mott-Shottky plot and the rate of photocatalytic decomposition of citric acid were found to depend strongly on pH of solution. The phot ocatalytic decomposition of citric acid was discussed in light of its adsorption on TiO2.     

Simultaneous determination of metronidazole and tinidazole in plasma by using HPLC–DAD coupled with second-order calibration

<正>A method using HPLC-DAD coupled with second-order calibration was developed to simultaneously determine metronidazole and tinidazole in plasma samples in this paper.The second-order calibration method based on APTLD(alternating penalty trilinear decomposition) algorithm was proposed to analyze the three-way HPLC-DAD data from both standard and prediction samples, which makes it possible that calibration can be performed even in the presence of unknown interferences with a simple and green chromatographic condition and short analysis time.The results showed that good recoveries were obtained although the chromatographic and spectral profiles of the analytes of interest as well as background were partially overlapped with each other in plasma samples.     

高效液相色谱手性固定相的研究 I:L-缬氨酸-叔丁酰胺型固定相的制备及对映体拆分

A new chiral chemically bonded stationary phase for direct resolution of optical isomers in HPLC was prepared. The experiemental data showed that the chiral stationary phase gave good resolution for the racemic α-amino acid derivatives and that there was no significant influence on the resolution as the eluting rate varied from 0.6 to 2.0 mL/min. The content of isopropanol in the eluent significantly affected the resolution of the enantiomers. The eluent consisting of 1% isopropanol in hexane gave most favorable result, but the retention times were a little longer. It is evident that the resolution was also influenced by the structure of the solute. In all cases, the resolution of N-Ac-DL-Phe-OMe is lower than that of N-Ac-DL-Leu-OMe and N-Ac-DL-Val-OMe. Although the capacity factor of N-Ac-DL-Tyr-Ome varied greatly in different eluting systems, the separation factor and resolution were very close. It was observed that D-amino acid derivatives eluted faster than the corresponding L-isomers. In the above chromatographic conditions N-acetyl-DL-α-phenylethylamine could not be resolved.     

PERFORMANCE IMPROVEMENT OF POLYMERS BY THE ADDITION OF GRAFTED NANO-INORGANIC PARTICLES

An irradiation grafting method was applied for the modification of nanoparticles so that the latter can be added topolymeric materials for improving their mechanical performance using existing compounding techniques. The followingitems are discussed in this paper: (a) chemical interaction between the grafting monomers and the nanoparticles duringirradiation, (b) properties including modulus, yield strength, impact strength and fracture toughness of the resultantcomposites, and (c) possible morphological changes induced by the addition of nanoparticles. Though irradiation graftingpolymerization, nanoparticle agglomerates turn into a nano-composite microstructure (comprised of the nanoparticles and thegrafted, homopolymerized secondary polymer), which in turn builds up a strong interfacial interaction with the surrounding,primary polymeric matrix during the subsequent mixing procedure. Due to the fact that different grafting polymers broughtabout different nanoparticle/matrix interfacial features, microstructures and properties of the ultimate composites could thusbe tailored. It was found that the reinforcing and toughening effects of the nanoparticles on the polymer matrix can be fullybrought into play at a rather low filler loading in comparison to conventional particulate filled composites.     

Hybrid Copolymerization via the Combination of Proton Transfer and Ring-opening Polymerization

Phosphazene base,t-BuP2,was employed to catalyze the proton transfer polymerization(PTP)of 2-hydroxyethyl acrylate(HEA),and PTP was further combined with ring-opening polymerization(ROP)to exploit a new type of hybrid copolymerization.The studies on homopolymerization showed that t-BuP2 was a particularly efficient catalyst for the polymerization of HEA at room temperature,giving an excellent monomer conversion.Throughout the polymerization,transesterification reactions were unavoidable,which increased the randomness in the structures of the resulting polymers.The studies on copolymerization showed that t-BuP2 could simultaneously catalyze the hybrid copolymerization via the combination of PTP and ROP at 25°C.During copolymerization,HEA not only provided hydroxyl groups to initiate the ROP ofε-caprolactone(CL)but also participated in the polymerization as a monomer for PTP.The copolymer composition was approximately equal to the feed ratio,demonstrating the possibility to adjust the polymeric structure by simply changing the monomer feed ratio.This copolymerization reaction provides a simple method for synthesizing degradable functional copolymers from commercially available materials.Hence,it is important not only in polymer chemistry but also in environmental and biomedical engineering.     

DISPERSION AND TENSILE BEHAVIOR OF POLYPROPYLENE/MONTMORILLONITE NANOCOMPOSITES PRODUCED VIA MELT INTERCALATION

Most of the anicles on polymer nanocomposites focus on the importance of chemistry used to modify the surfaceof the clay, usually montmorillonite (MMT), and characterization of the nano-scale structure obtained. The role andimportance of processing were also discussed recently. However, few papers concerning the correlation between morphologyof MMT and mechanical properties were published. In order to understand the tensile behavior of PP/Montmorillonite(MMT) nanocomposites better, and to further improve the reinforcement efficiency, we first prepared the PP nanocompositesvia direct melt intercalation using conventional twin-screw extrusion. The dispersion and tensile property of the compositeswere then investigated by SEM, XRD, TEM and a video-controlled tensile set-up. The macroscopic and microscopicdispersion of MMT in PP matrix was verified by XRD and TEM, combined with SEM. The tensile properties were obtainedby video-controlled tensile set-up, which gives true stress-strain curve. It was found that a partly intercalated and partlyexfoliated structure (also called incomplete exfoliation) existed in the system. Though the tensile strength of PPnanocomposites is not much improved in engineering stress-strain curves, more than 20% increase of true stress was found ina true stress-strain experiment at high true strain, which indicates that only oriented silicate layers can have a big effect ontensile properties. Not only orientation of silicate platelets but also the degree of exfoliation is a key factor to determine thereinforcement efficiency. The reinforcement efficiency of MMT has been discussed based on the "continuum" Halpin-Tsaiequations. A good agreement was found between experimental data and theoretical prediction by changing N value (number of platelets per stack) which corresponding to different state of the dispersion of MMT in PP matrix.     

Overlapping spectra resolution using non-negative matrix factorization

Non-negative matrix factorization (NMF), with the constraints of non-negativity, has been recently proposed for multi-variate data analysis. Because it allows only additive, not subtractive, combinations of the original data, NMF is capable of producing region or parts-based representation of objects. It has been used for image analysis and text processing. Unlike PCA, the resolutions of NMF are non-negative and can be easily interpreted and understood directly. Due to multiple solutions, the original algorithm of NMF [D.D. Lee, H.S. Seung, Nature 401 (1999) 788] is not suitable for resolving chemical mixed signals. In reality, NMF has never been applied to resolving chemical mixed signals. It must be modified according to the characteristics of the chemical signals, such as smoothness of spectra, unimodality of chromatograms, sparseness of mass spectra, etc. We have used the modified NMF algorithm to narrow the feasible solution region for resolving chemical signals, and found that it could produce reasonable and acceptable results for certain experimental errors, especially for overlapping chromatograms and sparse mass spectra. Simulated two-dimensional (2-D) data and real GUJINGGONG alcohol liquor GC-MS data have been resolved soundly by NMF technique. Butyl caproate and its isomeric compound (butyric acid, hexyl ester) have been identified from the overlapping spectra. The result of NMF is preferable to that of Heuristic evolving latent projections (HELP). It shows that NMF is a promising chemometric resolution method for complex samples.     

An algorithm for overlapped chromatogram separation

Non-negative matrix factorization (NMF) is a recently developed method for real time data analysis. In the past it has been used for facial recognition and spectral data analysis. Most of the NMF algorithms do not converge to a stable limit point and uniqueness in results is also a problem in NMF. To improve the convergence, a new NMF algorithm with modified multiplicative update (ML-NMFmse) has been proposed in this work for strongly overlapped and embedded chromatograms separation. To get same results for all the runs, instead of random initialization, three different initialization methods have been used namely, ALS–NMF (robust initialization), NNDSVD based initialization and EFA based initializations. The proposed ML-NMFmse algorithm is applied on the simulated and experimental overlapped chromatograms obtained for acetone and acrolein mixture, using Gas Chromatography–Flame Ionization Detector. Before applying NMF, Principal Component Analysis (PCA) was applied to determine number of components in the mixture taken. The result of proposed ML-NMFmse is compared with that of existing Multivariate Curve Resolution-Alternating Least Squares method in optimal conditions for both the algorithms. In the case of embedded chromatogram, the proposed ML-NMFmse with Robust method (ALS-NMF) of initialization performs better than all other methods. For a resolution of severely overlapped chromatograms, the proposed ML-NMFmse with NNDSVD method of initialization outperforms all other methods.     

Non-negative matrix factorization of two-dimensional NMR spectra: application to complex mixture analysis

A central problem in the emerging field of metabolomics is how to identify the compounds comprising a chemical mixture of biological origin. NMR spectroscopy can greatly assist in this identification process, by means of multi-dimensional correlation spectroscopy, particularly total correlation spectroscopy (TOCSY). This Communication demonstrates how non-negative matrix factorization (NMF) provides an efficient means of data reduction and clustering of TOCSY spectra for the identification of unique traces representing the NMR spectra of individual compounds. The method is applied to a metabolic mixture whose compounds could be unambiguously identified by peak matching of NMF components against the BMRB metabolomics database.     

Nonlinear mixture‐wise expansion approach to underdetermined blind separation of nonnegative dependent sources

Underdetermined blind separation of nonnegative dependent sources consists in decomposing a set of observed mixed signals into greater number of original nonnegative and dependent component (source) signals. That is an important problem for which very few algorithms exist. It is also practically relevant for contemporary metabolic profiling of biological samples, such as biomarker identification studies, where sources (a.k.a. pure components or analytes) are aimed to be extracted from mass spectra of complex multicomponent mixtures. This paper presents a method for underdetermined blind separation of nonnegative dependent sources. The method performs nonlinear mixture‐wise mapping of observed data in high‐dimensional reproducible kernel Hilbert space (RKHS) of functions and sparseness‐constrained nonnegative matrix factorization (NMF) therein. Thus, the original problem is converted into new one with increased number of mixtures, increased number of dependent sources, and higher‐order (error) terms generated by nonlinear mapping. Provided that amplitudes of original components are sparsely distributed, which is the case for mass spectra of analytes, sparseness‐constrained NMF in RKHS yields, with significant probability, improved accuracy relative to the case when the same NMF algorithm is performed on the original problem. The method is exemplified on numerical and experimental examples related respectively to extraction of 10 dependent components from five mixtures and to extraction of 10 dependent analytes from mass spectra of two to five mixtures. Thereby, analytes mimic complexity of components expected to be found in biological samples. Copyright © 2013 John Wiley & Sons, Ltd.     

NMF-Based Approach for Missing Values Imputation of Mass Spectrometry Metabolomics Data

In mass spectrometry (MS)-based metabolomics, missing values (NAs) may be due to different causes, including sample heterogeneity, ion suppression, spectral overlap, inappropriate data processing, and instrumental errors. Although a number of methodologies have been applied to handle NAs, NA imputation remains a challenging problem. Here, we propose a non-negative matrix factorization (NMF)-based method for NA imputation in MS-based metabolomics data, which makes use of both global and local information of the data. The proposed method was compared with three commonly used methods: k-nearest neighbors (kNN), random forest (RF), and outlier-robust (ORI) missing values imputation. These methods were evaluated from the perspectives of accuracy of imputation, retrieval of data structures, and rank of imputation superiority. The experimental results showed that the NMF-based method is well-adapted to various cases of data missingness and the presence of outliers in MS-based metabolic profiles. It outperformed kNN and ORI and showed results comparable with the RF method. Furthermore, the NMF method is more robust and less susceptible to outliers as compared with the RF method. The proposed NMF-based scheme may serve as an alternative NA imputation method which may facilitate biological interpretations of metabolomics data.     

Accurate grading of brain gliomas by soft independent modeling of class analogy based on non‐negative matrix factorization of proton magnetic resonance spectra

Hydrogen magnetic resonance spectroscopy (¹H‐MRS) is a non‐invasive technique which provides a ‘frequency‐signal intensity’ spectrum of biochemical compounds of tissues in the body. Although this method is currently used in human brain studies, accurate classification of in‐vivo ¹H‐MRS is a challenging task in the diagnosis of brain tumors. Problems such as overlapping metabolite peaks, incomplete information on background component and low signal‐to‐noise ratio disturb classification results of this spectroscopic method. This study presents an alternative approach to the soft independent modeling of class analogy (SIMCA) technique, using non‐negative matrix factorization (NMF) for dimensionality reduction. In the adopted strategy, the performance of SIMCA was improved by application of a robust algorithm for classification in the presence of noisy measurements. Total of 219 spectra from two databases were taken by water‐suppressed short echo‐time ¹H‐MRS, acquired from different subjects with different stages of glial brain tumors (Grade II (26 cases), grade III (24 cases), grade IV (41 cases), as well as 25 healthy cases). The SIMCA was performed using two approaches: (i) principal component analysis (PCA) and (ii) non‐negative matrix factorization (NMF), as a modified approach. Square prediction error was considered to assess the class membership of the external validation set. Finally, several figures of merit such as the correct classification rate (CCR), sensitivity and specificity were calculated. Results of SIMCA based on NMF showed significant improvement in percentage of correctly classified samples, 91.4% versus 83.5% for PCA‐based model in an independent test set. Copyright © 2015 John Wiley & Sons, Ltd.     

Component recognition with three‐dimensional fluorescence spectra based on non‐negative matrix factorization

Non‐negative matrix factorization (NMF) is a widely used approach in signal processing. In this work, we apply it to the component recognition of mixtures with multicomponent three‐dimensional fluorescence spectra. Compared with the popular PARAFAC for component recognition, NMF has the following advantages: on one hand, the decomposed spectra are three dimensional, and thus, more information can be obtained, which is beneficial for component recognition; on the other hand, the decomposed spectra are non‐negative and thus have a certain physical significance. More importantly, we propose a type of integrated similarity indices for the three‐dimensional fluorescence spectra, which, by construction, is good at component recognition from overlapping fluorescence spectra. Experiment results demonstrate that NMF combined with integrated similarity index provides an effective method for component recognition of multicomponent three‐dimensional overlapping fluorescence spectra. Copyright © 2011 John Wiley & Sons, Ltd.     

GC-MS分析大蒜中的挥发油和大蒜精油

采用气相色谱—质谱法,分析比较大蒜中的挥发油以及大蒜精油的化学成分,通过非负矩阵因子分解(NMF)方法解析色谱重叠峰,并用峰面积百分比法计算各化学成分的峰面积相对百分含量。确定了大蒜中37种化学成分,其中含硫化合物34种,大蒜精油中的32种化学成分,含硫化合物28种。     

三线性分解方法用于激发-发射矩阵荧光数据中一阶瑞利散射的扣除

由于荧光分析具有检测灵敏度高、数据容易获得等优点,近年来二阶张量校正方法与激发-发射矩阵荧光光谱技术的联用正受到人们越来越多的关注.但是,在三维荧光分析中,经常出现的一阶瑞利散射干扰往往容易导致建立的三线性模型存在较大的偏离,进而直接影响复杂体系中感兴趣组分的定性、定量分析.针对该问题,我们提出了一种基于对组分数不敏感的三线性分解算法扣除一阶瑞利散射干扰的新思路.该方法的特点是根据一阶瑞利散射分别在水平切片矩阵和侧面切片矩阵所处位置相同,沿I-模和J-模同时构建含一阶瑞利散射的三维数据阵,利用三线性分解算法对此各自建模,将一阶瑞利散射当作一个响应组分或因子拟合后从三维数据阵中扣除掉.通过对模拟和实际三维激发发射矩阵荧光光谱实验数据进行讨论,结果表明该方法能有效地扣除体系中的一阶瑞利散射干扰.改进后的方法不仅操作简单,而且不受组分数选取不当的困扰.另外,由于同时从两个方向进行一阶瑞利散射扣除,因此不会出现因边缘瑞利散射峰形不完整而扣除不完全的情况.该方法为三维荧光光谱的无损分析提供了新思路,为进一步进行三维荧光光谱的定量分析奠定了良好的基础.     

A flexible trilinear decomposition algorithm for three-way calibration based on the trilinear component model and a theoretical extension of the algorithm to the multilinear component model

There is a great deal of interest in decompositions of multilinear component models in the field of multi-way calibration, especially the three-way case. A flexible novel trilinear decomposition algorithm of the trilinear component model as a modification of an alternating least squares algorithm for three-way calibration is proposed. The proposed algorithm (constrained alternating trilinear decomposition, CATLD) is based on an alternating approximate least-squares scheme, in which two extra terms are added to each loss function, making it more efficient and flexible. The analysis of simulated three-way data arrays shows that it converges fast, is insensitive to initialization, and is insensitive to the overestimated number of components used in the decomposition. The analysis of real excitation–emission matrix (EEM) fluorescence and real high performance liquid chromatography–photodiode array detection (HPLC–DAD) data arrays confirms the results of the simulation studies, and shows that the proposed algorithm is favorable not only for EEMs but also for HPLC–DAD data. The three-way calibration method based on the CATLD algorithm is very efficient and flexible for direct quantitative analysis of multiple analytes of interest in complex systems, even in the presence of uncalibrated interferents and varying background interferents. Additionally, a theoretical extension of the proposed algorithm to the multilinear component model (constrained alternating multilinear decomposition, CAMLD) is developed.