Evaluation of synthesized green carbon catalyst from waste date pits for tertiary butylation of phenol

The present study is intended to adopt a facile method for preparing a sulphonated green carbon catalyst from date pits biomass. Catalyst synthesis involves in situ carbonization and sulphonation and it has been characterized by following techniques such as XRD, SEM, EDX, TEM, FTIR, TGA, and BET. Surface and internal morphology results exhibited that the synthesized sulphonated carbon material possesses a mesoporous structure, while activated carbon possesses a microporous structure. Furthermore, the Fourier transform infrared (FTIR) spectra confirmed the presence of acidic groups (OH, COOH, and SO₃H) in synthesized sulphonated carbon material. Sulphonated carbon material exhibited high acidity (4.7 mmol/g) and good thermal stability. The application of this catalyst for the tertiary butylation of phenol without using any solvent has been investigated. The phenol alkylation reaction showed maximum conversion at reaction condition: temperature (140 °C) with 2 bar (nitrogen gas) pressure with maximum phenol conversion 79.27 wt%, with 68.01% selectivity towards 4TBP+2,4TBP, which is used as an intermediate in antioxidants. The catalyst exhibits comparable catalytic performance up to five reaction cycles. Thus it can be concluded that waste date pits can be successfully employed for green catalyst synthesis and used for reactions involving large molecules.     

Rapidly differentiating grape seeds from different sources based on characteristic fingerprints using direct analysis in real time coupled with time‐of‐flight mass spectrometry combined with chemometrics

The seeds of grapevine (Vitis vinifera) are a byproduct of wine production. To examine the potential value of grape seeds, grape seeds from seven sources were subjected to fingerprinting using direct analysis in real time coupled with time‐of‐flight mass spectrometry combined with chemometrics. Firstly, we listed all reported components (56 components) from grape seeds and calculated the precise m/z values of the deprotonated ions [M–H]^–. Secondly, the experimental conditions were systematically optimized based on the peak areas of total ion chromatograms of the samples. Thirdly, the seven grape seed samples were examined using the optimized method. Information about 20 grape seed components was utilized to represent characteristic fingerprints. Finally, hierarchical clustering analysis and principal component analysis were performed to analyze the data. Grape seeds from seven different sources were classified into two clusters; hierarchical clustering analysis and principal component analysis yielded similar results. The results of this study lay the foundation for appropriate utilization and exploitation of grape seed samples. Due to the absence of complicated sample preparation methods and chromatographic separation, the method developed in this study represents one of the simplest and least time‐consuming methods for grape seed fingerprinting.     

Application of heated electrodes operating in a non-isothermal mode for interference elimination with amperometric biosensors

Heated electrodes were applied for the non-isothermal operation of amperometric glucose biosensors based on glucose oxidase immobilised on the electrode surface by entrapment within a polymer layer. The localised deposition of the polymer film under simultaneous entrapment of the enzyme was achieved by an electrochemically induced pH-modulation in the diffusion zone in front of the electrode, thus altering the solubility of the polymer chains. This non-manual sensor preparation protocol could be successfully used for the modification of a novel indirectly heated electrode. The non-isothermal operating mode allows working at the optimum temperature of the enzyme sensors without any thermal distortion of the bulk solution. Increased surface temperature of the sensor thus accelerates transport as well as kinetic processes, resulting in an enhanced amperometric signal.In the presence of interfering compounds such as ascorbic acid, the proposed technique allows use of the diverging thermal impact on the sensing process, for different electrochemically active compounds, for a deconvolution of the amperometric signal at different electrode temperatures. A calculation method for determination of glucose in the presence of one interfering compound is presented as a basis for a calculative interference elimination.     

Gas phase and water solution conformational analysis of the herbicide diuron (DCMU): an ab initio study

In the present work, the conformational equilibrium for the herbicide diuron (DCMU) has been investigated using high level ab initio calculations. The solvent effect was included through two different continuum models: (1) the real cavity IPCM method and (2) the standard dipole Onsager model SCRF. The effect due to solute-solvent hydrogen-bond interactions was analyzed considering a hybrid discreet-continuum model. At the Hartree-Fock level, the gas phase results showed that only the trans forms (A and B) are present in the equilibrium mixture, with the relative concentrations found to be 33% (A) and 67% (B) (HF/6-311+G**//6-31G**). When the electronic correlation effect is included (MP2/6-31G*//HF/6-31G*), a relative stabilization of the cis forms was observed, with the conformational distribution calculated as 38% (A), 50% (B), 6% (C) and 6% (D). The trans conformations were found to be completely planar, which has been considered to be a prerequisite for the herbicide binding. In water solution, the trans conformation A should be the most abundant conformer, the IPCM and SCRF values being ca. 100% and ca. 85% respectively. The IPCM calculations with the isodensity level set to 0.0005 present a conformational distribution close to that obtained from the hybrid model [92% (A) and 8% (B)], which has been considered our best solvent approach. Regarding the biological action of urea-type herbicides, the results presented here are important, because some QSAR studies have suggested that the partition coefficient is related to the herbicide activity, so the conformational equilibrium may play a role in the biological action. Received: 23 February 1998 / Accepted: 28 May 1998 / Published online: 19 August 1998     

Nonwoven polypropylene as a novel extractant phase holder for the determination of insecticides in environmental water samples

In this work, a novel liquid‐phase microextraction approach using nonwoven polypropylene as the extraction solvent holder was developed. Nonwoven polypropylene, a hydrophobic material, is widely used in the cleanup of oil spills. Due to its large surface area, efficient, and full extraction can be achieved. Nonwoven polypropylene containing an ionic liquid was used to extract benzoylurea insecticides (diflubenzuron, teflubenzuron, flufenoxuron, and chlorfluazuron) through vortex‐assisted liquid–liquid microextraction. The parameters that affected the extraction efficiency included the type and volume of the extractant, the extraction time, the time and solvent volume for desorption and the mass and surface area of the nonwoven polypropylene. Under the optimized conditions, good linearity was obtained, with coefficients of determination greater than 0.9996, and the limit of detections of these compounds, calculated at S/N = 3, were in the range of 0.73–5.0 ng/mL. The recoveries of the four insecticides at two spiked levels ranged from 93.3 to 102.0%, with relative standard deviations of less than 4.0%. The proposed method was then successfully used for the rapid determination of benzoylurea insecticides in spiked real water samples before liquid chromatographic analysis. The procedure is simple, inexpensive, easy to execute, and can be widely used.     

Application of a quartz crystal nanobalance and principal component analysis for the detection and determination of histidine

The aim of the present investigation was to develop a biosensor based on a quartz crystal nanobalance (QCN) for the detection of histidine (His). A thin layer of nickel was electrochemically deposited over the gold crystal electrode and exposed to H₂O₂ to form nickel oxide. The composite electrode was then used to determine His. The frequency shifts were linear with respect to the concentration of His in solution. His can be measured in the range of 100–2000 mg L⁻¹. A lower limit of detection of 48 mg L⁻¹ and a sensitivity factor of 0.0307 Hz/mg L⁻¹ was obtained. Some possible interferences were checked for, and the performance of the sensor was found to be unaffected by any interference except for those from arginine, cysteine and NaH₂PO₄. Principal component analysis (PCA) was used to process the frequency response data of the single piezoelectric crystal at various times, considering the different adsorption–desorption dynamics of His and the interfering compounds. Over 85% of the variance in the data was explained by two principal components. A score plot of the data for the first two PCs showed that the modified QCN yields favorable identification and quantification performances for His and the interfering compounds.     

Principal component analysis versus fuzzy principal component analysis A case study: the quality of danube water (1985-1996)

Principal component analysis (PCA) is a favorite tool in environmetrics for data compression and information extraction. PCA finds linear combinations of the original measurement variables that describe the significant variations in the data. However, it is well-known that PCA, as with any other multivariate statistical method, is sensitive to outliers, missing data, and poor linear correlation between variables due to poorly distributed variables. As a result data transformations have a large impact upon PCA. In this regard one of the most powerful approach to improve PCA appears to be the fuzzification of the matrix data, thus diminishing the influence of the outliers. In this paper we discuss and apply a robust fuzzy PCA algorithm (FPCA). The efficiency of the new algorithm is illustrated on a data set concerning the water quality of the Danube River for a period of 11 consecutive years. Considering, for example, a two component model, FPCA accounts for 91.7% of the total variance and PCA accounts only for 39.8%. Much more, PCA showed only a partial separation of the variables and no separation of scores (samples) onto the plane described by the first two principal components, whereas a much sharper differentiation of the variables and scores is observed when FPCA is applied.     

Chemometrics characterisation of the quality of river water

Within the period from autumn 1990 to spring 1999 (from October to April in each period) 207 samples were collected and the measurement of 19 physical and chemical variables of the Mura river, Slovenia, were carried out. These variables are: river flow, water temperature, air temperature, dissolved oxygen, deficit of oxygen, oxygen saturation index, chemical oxygen demand (COD) in unfiltered and filtered samples, and biochemical oxygen demand after 5 days (BOD5) in unfiltered and filtered samples, pH, conductivity, ammonium, nitrite, nitrate, and phosphate concentrations, adsorbable organic halogens (AOX), dissolved organic carbon (DOC), and suspended solids. For handling the results of all measurements different chemometrics methods were employed: (i) the basic statistical methods for the determination of mean and median values, standard deviations, minimal and maximal values of measured variables, and their mutual correlation coefficients, (ii) the principal component analysis (PCA), and (iii) the clustering method based on Kohonen neural network. The influences of season, month, sampling site, and sampling time on the pollutant levels were examined. Before 1993, the pulp and paper industry was the main source of pollutants because of large amounts of chlorine emission as a consequence of industrial treatment, the leaching of cellulose. After the year 1993, the technology was changed and the quality of the river water has improved. The improvement could be detected 1 year after the change of technology. For one part of water samples the river quality classes based on biological parameters were also determined. The correlation between the biologically determined quality classes and chemical measurements was sought. Consequently, the biological classification for the water samples based on the chemical analyses was studied.     

Patterns in the precision of quantitative data from multicomponent gas chromatographic or gas chromatographic-mass spectrometric analysis

The dispersion of the quantitative results in the analysis of volatile compounds from multicomponent mixtures by different fractionation techniques (solid-phase microextraction and direct thermal desorption) followed by GC or GC-MS presents nonrandom patterns related to the existence of different factors in the fractionation process or in the chromatographic separation which affect, to a different extent, the recovery of the sample components. Statistical techniques have been used to show the relative importance of these factors. The improvement in data precision achieved by using volatile compound concentration ratios is discussed.     

Sensitivity improvement in ICP MS analysis of fuels and light petroleum matrices using a microflow nebulizer and heated spray chamber sample introduction

Reasons for signal suppression during the analysis of light petroleum matrices by inductively coupled plasma mass spectrometry (ICP MS) were examined. A decrease of the ionization efficiency of the plasma was found to be the principal factor responsible for this loss of sensitivity. Consequently, an interface based on a total consumption micronebulizer and a heated spray chamber was constructed to alleviate this problem. A method based on flow-injection ICP MS using this interface was developed for the direct multielement analysis of undiluted fuels (gasoline, kerosene) and gas condensates offering an increase in sensitivity by at least a factor of 3-4 in comparison with the existing setups.     

Use of Chemometrics: Principal Component Analysis (PCA) and Principal Component Regression (PCR) for the Authentication of Orange Juice

ABSTRACT

Principal Component Analysis (PCA) was applied to a set of physico-chemical variables obtained from 41 samples of summer orange juice, in order to reduce the number of variables. Working with the covariance matrix, three components (which explained 98.27% of the variance) were taken. With the correlation matrix, four components which explained: 85.65% of the variance were taken. With the scores corresponding to both matrixes a principal component regression (PCR) was carried out against the dependent variable of Brix grades, so as to obtain two statistical models that would allow the detection of adulterations in pure orange juice, based on dilution and later masking by the addition of sugar. The models were tested with simulated dilutions of 41 samples of juice, to assess the effectiveness of each for the detection of adulterations. Both models turned out to be equally effective, detecting adulterations starting from about 15 % of dilution.     

Magnesium oxide microspheres as a novel solid‐phase extraction sorbent for the determination of benzo[a]pyrene in environmental water samples

Magnesium oxide microspheres were developed as a novel SPE sorbent for the determination of benzo[a]pyrene (BaP), one of the most potent carcinogenic agents, in environmental water samples. The parameters controlling the extraction efficiency, such as elution volume, flow rate, pH values, and breakthrough volume, were investigated in detail. Considering the facile preparation and satisfying recovery, a corresponding analytical method has been developed to determine the concentration of BaP in real tap water, river water, and seawater. The recoveries for the spiked BaP were excellent (94–101%).     

A novel thiolysis-high-performance liquid chromatography method for the determination of proanthocyanidins in grape seeds

A novel thiolysis-high-performance liquid chromatography method for the quantitative determination of total proanthocyanidins and the mean degree of polymerization in grape seeds has been developed. Following thiolysis with formic acid and benzyl mercaptan, reaction products were separated and purified. Three proanthocyanidin monomers and three derivatives were obtained and their structures were identified by liquid chromatography-mass spectrometry, FTIR spectroscopy, and NMR spectroscopy. A decomposition model of the thiolysis products and a correction formula for proanthocyanidins concentration were established. This thiolysis-high-performance liquid chromatography method displayed good calibration linearity (R² > 0.999 over the concentration range 0.01 to 10 mg/mL), excellent accuracy (recoveries of 97.9–99.6%), and precision (repeatability relative standard deviations of 0.45–0.75%). This method is suitable for the quantitative analysis of proanthocyanidins in grape seed products.     

Colorimetric sensing of anions in water using ratiometric indicator-displacement assay

The analysis of anions in water presents a difficult challenge due to their low charge-to-radius ratio, and the ability to discriminate among similar anions often remains problematic. The use of a 3 × 6 ratiometric indicator-displacement assay (RIDA) array for the colorimetric detection and identification of ten anions in water is reported. The sensor array consists of different combinations of colorimetric indicators and metal cations. The colorimetric indicators chelate with metal cations, forming the color changes. Upon the addition of anions, anions compete with the indicator ligands according to solubility product constants (K_sp). The indicator–metal chelate compound changes color back dramatically when the competition of anions wins. The color changes of the RIDA array were used as a digital representation of the array response and analyzed with standard statistical methods, including principal component analysis and hierarchical clustering analysis. No confusion or errors in classification by hierarchical clustering analysis were observed in 44 trials. The limit of detection was calculated approximately, and most limits of detections of anions are well below μM level using our RIDA array. The pH effect, temperature influence, interfering anions were also investigated, and the RIDA array shows the feasibility of real sample testing.     

用于三价锕镧分离的萃取剂的合成与表征

以6,6'-二氰-2,2'-联吡啶为原料,经两步反应,合成了6,6'二(5,6二乙基-1,2,4-三嗪-3-基)-2,2'-联吡啶.第一步改变条件使反应时间由17d缩短到3d,得到的中间体和目标产物经元素分析、IR,1 HNMR和MS等表征确认.此外,对反应机理进行了初步探讨.     

Nanometer SiO2 modified with 5-sulfosalicylic acid as selective solid-phase extractant for Fe(III) determination by ICP-AES from biological and natural water samples

A new modified nanometer SiO₂ using 5-sulfosalicylic acid (SSA) as a solid-phase extractant was used for separation, preconcentration and determination of Fe(III) in aqueous solutions by inductively coupled plasma atomic emission spectrometry (ICP-AES). Its adsorption and preconcentration behaviour for Fe(III) in aqueous solutions was investigated using static procedures in detail. The optimum pH value for the separation of Fe(III) on the newly designed sorbent was 3.5. Complete elution of the adsorbed Fe(III) from the nanometer SiO₂-SSA was carried out using 2.0 mL of 0.01 mol L^− 1 of HCl. The time of 90% sorption was less than 2 min for Fe(III) at pH 3.5. Common coexisting ions did not interfere with the separation and determination of Fe(III) at pH 3.5. The maximum static adsorption capacity of the sorbent at optimum conditions was found to be 44.01 mg of Fe(III) per gram of sorbent. The relative standard deviation (RSD) of the method under optimum conditions was 3% (n = 5). The procedure was validated by analyzing three certified reference materials (GBW 08301, GBW 08504, GBW 08511), the results obtained were in good agreement with standard values. The nanometer SiO₂-SSA was successfully employed in the separation and preconcentration of the investigated Fe(III) from the biological and natural water samples yielding 100-folds concentration factor.     

主成分分析在近红外定量分析校正集样本优选中的应用

将主成分分析方法用于近红外定量分析校正集样本的优选,提出一种根据样本光谱第一主成分得分优选校正集样本的方法,并使用本方法从418个烟草样本中优选得到约105个样本的校正集。通过对烟碱成分实际建模与外部验证,与随机法、含量梯度法两种校正集样本挑选方法的性能进行了对比。结果表明,本方法既克服了随机法挑选样本代表性不足的风险,又可避免含量梯度法必须测定所有样本成分含量而造成的人力物力消耗,具有无需编程、操作简单、易于推广的特点。     

Maintenance of a calibration model for near infrared spectrometry by a combined principal component analysis-partial least squares approach

A novel strategy for building and maintaining calibration models has been developed for use when the future boundaries of the sample set are unknown or likely to change. Such a strategy could have an impact on the economics and time required to obtain and maintain a calibration model for routine analysis. The strategy is based on both principal component analysis (PCA) and partial least squares (PLS) multivariate techniques. The principal action of the strategy is to define how “similar” a new sample is to the samples currently defining the calibration dataset. This step is performed by residuals analysis, following PCA. If the new sample is considered to have a spectrum “similar” to previously available spectra, then the model is assumed able to predict the analyte concentration. Conversely, if the new sample is considered “dissimilar”, then there is new information in this sample, which is unknown to the calibration model and the new sample is added automatically to the calibration set in order to improve the model. The strategy has been applied to a real industrial dataset provided by BP Amoco Chemicals. The data consists of spectra of 102 sequential samples of a raw material. The strategy produced an accurate calibration model for both target components starting with only the first four samples, and required a further 17 reference measurements to maintain the model for the whole sampling sequence, which was over a 1-year period.     

A novel silica supported chitosan/glutaraldehyde as an efficient sorbent in solid phase extraction coupling with HPLC for the determination of Penicillin G from water and wastewater samples

In this study, silica@chitosan-glutaraldehyde (Si@Cs-G) was synthesized as a novel adsorbent for extraction of Penicillin G (PG) from the synthetic and real samples followed by HPLC determination. The synthesized adsorbents were characterized by the scanning electron microscopy (SEM), X-ray diffraction (XRD), fourier transform infrared (FTIR), dynamic light scattering (DLS), transmission electron microscopy (TEM) and nitrogen adsorption–desorption techniques. The factors influencing the extraction efficiency including pH, sorbent dose, extraction time, extraction solvent type and its volume were investigated and optimized.Under the optimal conditions (sorbent dosage: 25 mg, desorption solvent (acetonitrile) with volume of 0.75 mL; pH: 6 and extraction time: 50 min), the Si@Cs-G demonstrated high efficiency and linearity (R² > 0.999) with the concentration of penicillin G ranging from 1 to 300 μg L⁻¹. Extraction recovery in synthetic samples was 98.977%, with LOD = 0.493 μg L⁻¹, LOQ = 1.638 μg L⁻¹ and RSD < 1.953%. The method was successfully applied for determination of PG in real water samples (tap, river, lake and well water) and wastewater samples (SH and SHB hospital effluent). The obtained relative recoveries were in the range of 91.31% -123.27% with RSD less than 6.34% for all the real samples. The dominant mechanism in the PG adsorption process was involved in the π-π interaction, hydrogen bonding, and electrostatic interaction.     

A simple method for simultaneous determination of nine triazines in drinking water

A simple, effective, and economic method for determination of nine triazines (ametryn, atrazine, cyanazine, prometryn, propazine, simazine, simetryn, terbuthylazine, and terbutryn) in drinking water based on solid-phase extraction (SPE) followed by high-performance liquid chromatography-diode array detection (HPLC-DAD) was developed. A specialized solid phase (Oasis HLB) was used, and the parameters that may affect the efficiency of SPE were optimized. The limits of detection (ranged from 0.010 to 0.023 µg L^?1) were satisfactory and allow the determination of triazines at the levels required by European Union legislation. Repeatability (2.4–7.6%) and intermediate precision (0.9–11.0%) calculated at 0.1 µg L^?1 (legislation level) were adequate. The accuracy calculated as the average recovery of spiked tap and mineral waters was higher than 86% for all compounds. The developed method also could be used for undergraduate laboratory experiments because it acquaints students with solution preparation, solid phase extraction procedure, and HPLC-DAD technique.