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Process-monitoring laboratories in the pulp and paper industry generally use a combination of wet chemical analyses and physical measurements to certify the fitness of a production pulp for a specific end-use. These laboratory tests require time and the effort of trained personnel, limiting their utility for real-time process control. Here we show that Raman probes of unrefined cellulosic pulps, well-suited to the online measurement of in-process materials, can predict the quality attributes of manufactured papers. The accuracy of prediction improves when the covariance is modelled in a reduced measurement space selected by a data-driven, feature-selection technique referred to as a Template Oriented Genetic Algorithm (TOGA). TOGA, combined with discrete wavelet transform (DWT), isolates functional-group features that correlate best with mechanical properties paper derived from refined pulp. Paper makers refine market pulps to build sheet strength using a beating process that decreases freeness as it increases fibre-fibre bonding. Methods demonstrated here predict manufactured sheet properties obtainable after any specified degree of refining from the Raman spectrum of an unrefined pulp. This analysis capacity will enable both vendors of market pulp and makers of sheet paper to specify in advance the amount of beating required to produce a desired product, thereby saving cost and conserving resources.

Natural material variations uncorrelated with physical properties of fibre networks hinder the development of robust calibration models by which to predict paper properties from on-line near-infrared (NIR) spectra of production pulps. Such a simple process gauge of product quality would offer attractive advantages for optimized manufacturing. The present work explores the effectiveness of data processing strategies designed to remove uncorrelated variance from calibration models linking NIR spectra with standard measures of paper quality, including tensile, tear, burst index, wet and dry zero span length, freeness, absorption and scattering coefficients. Post-processing of spectra by discrete wavelet transform (DWT) is shown to suppress the baseline and high-frequency noise, and orthogonal signal correction (OSC) substantially improves prediction accuracy by reducing the amplitude of uncorrelated (orthogonal) variations. We find that combined pretreatment by DWT and OSC yields a spectral dataset that exhibits the best prediction accuracy.

A carbon paste electrode for determination of mercury (II) ions in real samples was prepared. The main objective of the present study was to evaluate the concentration of mercury ions in different soil, water, plant, and animal muscle samples by utilizing modified carbon paste electrode. Functionalized nanoporous MCM-48 and multi-walled carbon nanotubes material were used in order to increase the efficiency and selectivity of the electrode for mercury ions determination. The electrode composition material was optimized as graphite powder 57%, Paraffin 22%, modified MCM-48 16% and MWCNTs 5% (W/W). The linear range of the electrode was calculated 5.0×10-8 to 1.0×10-3 mol L-1, and a detection limit was obtained 1.5×10-8 mol L-1. The potential slope was achieved 29.7±1.0 mV, and lifetime for the electrode was investigated about 5 months. The proposed method was applied to a number of natural samples and the amount of mercury was determined.

Solid-phase extraction (SPE) is often used for preconcentration and determination of metal ions from industrial and natural samples. A traditional single variable approach (SVA) is still often carried out for optimization in analytical chemistry. Since there is always a risk of not finding the real optimum by single variation method, more advanced optimization approaches such as multivariable approach (MVA) should be applied. Applying MVA optimization can save both time and chemical materials, and consequently decrease analytical costs. Nowadays, using artificial neural network (ANN) and response surface methodology (RSM) in combination with experimental design (MVA) are rapidly developing. After prediction of model equation in RSM and training of artificial neurons in ANNs, the products were used for estimation of the response of the 27 experimental runs. In the present work, the optimization of SPE using single variation method and optimization by ANN and RSM in combination with central composite design (CCD) are compared and the latter approach is practically illustrated.

We have developed a facile and highly sensitive sorbent for cadmium and lead ions. It is based on Fe₃O₄ nanoparticles functionalized with a derivative of picoline and was characterized by scanning electron microscopy, differential thermographic analysis, and elemental analysis. The material can be applied to the preconcentration of lead and cadmium ions. Factors such as the type, concentration and volume of eluent, the pH of the sample solution, the time for extraction, and the volume of the sample were studied. The effects of a variety of ions on preconcentration and recovery of these ions were also investigated. The ions were determined by FAAS, and the limits of detection are 98.0 % and

A modified SBA-15 mesoporous silica was developed, as an adsorbent, for the removal of Cr(VI) ions from natural-water samples. The effects of experimental parameters, including pH of solution, sample and eluent flow rate, the eluent composition, the eluent volume, and the effect of coexisting ions on the separation and determination of Cr(VI), were investigated. It was shown that Cr(VI) was selectively adsorbed from aqueous solution at pH 3, but Cr(III) could be adsorbed from solution at alkaline pH range. The retained Cr(VI) was eluted with 0.5 mol L−1 KCl solution in 0.1 mol L−1 Na2CO3 subsequently. Under the optimum conditions, the modified mesoporous silica (py-SBA-15) with a high pore diameter exhibited an adsorption capacity of 136 mg g−1 and a lower limit of detection than 2.3 µg L−1 by using diphenylcarbazide as a chromophorous reagent for the determination of Cr(VI) ions. A preconcentration factor as high as 200 was calculated for Cr(VI). The loaded py-SBA-15 can be reactivated with recovery of m...

Nickel is considered as an important toxic pollutant and is continuously released into the biosphere by some anthropogenic activities such as industrial and urban sewage. The main objective of this study was to determine the concentration of nickel in different samples of soil, water, and muscle tissue of fish species which were collected from the Persian Gulf. For this propose, a simple and sensitive solid-phase extraction using pyridine-functionalized Mobil Composition of Matter (MCM)-41 and MCM-48 nanoporous silica was developed and their application in preconcentration and determination of nickel by flame atomic absorption spectrometry was studied. Limit of detection was found to be lower than 3.5 μg L−1. Recovery and precision of the method were above 98.5% and below 1.5%, respectively. To gauge their ability in terms of application to natural samples, the proposed method was applied to a number of natural samples including plants, water, soil and fish species, and the amount of nickel was determined by spiking known concentrations of nickel into the solution. The results show that pollution of soil and water has some effects on bioaccumulation of Ni on marine organisms and plants that could magnify along the food chain.

Nano-alumina modified by 9-aminoacridine was used as a sorbent for separation and determination of dichromate ions from water. Statistical method, based on surface response design, has been used for the optimization of dichromate ions elution from 9-aminoacridine nano-alumina. The adsorbed dichromate ions were found to be eluted quantitatively with 0.8 mol L−1 KCl in 1.6 mol L−1 NaOH which optimized by response surface design. Under optimum conditions, the accuracy, precision (relative standard deviation, RSD%) and R-square of the method were calculated as >98, 94%, respectively. Remarkable agreement between experimental and theoretical data was confirmed the predicted assumption. The method was applied to the simultaneous determination of dichromate in natural and industrial water samples. We also examined the retention of dichromate anions in the presence of Cl−, , and anions at pH 3.

A new, sensitive, and low cost solid-phase extraction method using pyridine-functionalized MCM-48 mesoporous silica for the extraction, pre-concentration, and electrothermal atomic absorption spectrometric determination of nickel and lead in food samples at ng mL −1 levels is described herein. The levels of nickel and lead in different types of vegetables grow in Shiraz–Iran and Rafsanjan–Iran were determined by electrothermal atomic absorption spectrometry. The use of two standard reference materials and also comparing the results to a standard reference procedure ensured the accuracy of this method. Factors, such as flow rate of extraction, and the type, pH, concentration, and volume of eluent, were appraised. The effect of various ions on recovery was also investigated. Detection limits of 0.11 and 0.14 ng mL −1 were obtained for lead and nickel, respectively.

Nanoporous silicas of the type SBA-15 (Santa Barbara Amorphous) and MCM-48 (Mobile Composition of Material) were modified with dipyridylamine (dipy) and used as solid phases for the extraction of Pd(II) ions. The experimental conditions (pH, sample and eluent flow rates, type and quantity of eluent) were optimized. The recovery values were ~ 99.7 and ~ 93.4% for dipy-MCM-48 and dipy-SBA-15, respectively, the limits of detection were 78 mg g−1. The procedure was applied to the preconcentration of Pd(II) in real samples.

A technique for solid-phase extraction utilizing pyridine-functionalized nanoporous silica (MCM-41, MCM-48 and SBA-15) was developed for the determination of gold in different samples using flame atomic absorption spectrometry. The effects of concentration and volume of eluent, pH of the solution, flow rate of extraction, sample volume and of potentially interfering ions on the efficiency of preconcentration and recovery was investigated. The limit of detection is lower than 45 pg mL−1. Under optimal conditions, the accuracy and precision (RSD%) of the method were calculated to be >99.5% and 89.5%, and

Aminopropyl-functionalized mesoporous silicas, NH2-MCM-41 and NH2-SBA-15, as absorbents were utilized for rapid extraction, preconcentration and determination of trace amounts of silver. Flow rates of sample and eluent, pH, eluent solution, type, concentration and the least amount of eluent for desorption of silver ions were optimized; moreover, break through volume and the effect of various cationic interferences on the sorption of silver were evaluated. The extraction efficiency of silver ions was greater than 95% for MCM-41-NH2 and 85% for SBA-15-NH2 and the limit of detection (LOD) was less than 4 ng mL−1 for both functionalized mesoporous silicas. The preconcentration factor was greater than 210 and the relative standard deviation (RSD) was

A new solid phase, nanoparticles of alumina functionalized with pyridine groups, was synthesized and used for extraction and preconcentration of palladium(II) ions from some water samples. The effects of various parameters such as pH, flow rates of sample and eluent, type and volume and concentration of eluent, sample volume, amount of adsorbent and cationic interferences have been studied and optimum conditions for best recovery have been obtained. The limit of detection of the method based on three times the standard deviation of the blank (3S(b)) was obtained: 0.6 ng mL(-1). The preconcentration factor and the adsorption capacity were also calculated to be 60 and 37 mg g(-1), respectively. The recovery of extraction of palladium ions on nano-alumina particles was determined to be 98.5%. The utility of the modified nano-alumina was tested in some samples and showed an RSD value of

We introduce a fast computational method for feature selection that facilitates the accurate spectral analysis of a chemical species of interest in the presence of overlapping uncorrelated variance. Using a genetic algorithm in a data-driven approach, our method assigns predictors according to a template determined to minimize prediction variance in a calibration space. This template-oriented genetic algorithm (TOGA) efficiently establishes features of greatest significance and determines their optimal combination. We demonstrate the efficacy of TOGA using an elementary model system in which we seek to quantify a target monosaccharide in mixtures containing other sugars added in random amounts. The results establish TOGA as an effective and reliable technique for isolating signature spectra of targeted substances in complex mixtures.

Three-phase hollow fiber microextraction technique combined with high performance liquid chromatography-ultra violet (HPLC-UV) was applied for the extraction and determination of gabapentin in biological fluids. Gabapentin (GBP) was derivatized with 1-fluoro-2,4-dinitrobenzene, as a UV absorbent agent in borate buffer (pH 8.2) before extraction. The derivative product of GBP was extracted from the 8.5 mL of acidic solution (source phase) into an organic phase (dihexyl ether) impregnated in the pores of a hollow fiber and finally back-extracted into 24 microL of the basic solution (pH 9.1) located inside the lumen of the hollow fiber (receiving phase). The extraction took place due to pH gradient between the inside and outside of the hollow fiber membrane. In order to achieve maximum extraction efficiency, different parameters affecting the extraction conditions were optimized. Under the optimized conditions, preconcentration factor of 95 and detection limit (LOD) of 0.2 microg L(-1) were obtained. The calibration graph was linear within the range of 0.6-5000 microg L(-1). Finally, the feasibility of the proposed method was successfully confirmed by extraction and determination of GBP in human urine and plasma samples in the range of microgram per liter and suitable results were obtained (RSDs

Experimental design of directly suspended droplet liquid–liquid–liquid microextraction has been used to determine residue of 2,4-D, in environmental water samples. A free suspended droplet of 5.5 μL of receiving phase is delivered to the top-center position of 1-Octanol, which is an immiscible organic solvent, floating on the top of a 2.5 mL aqueous sample while being agitated by a stirring bar to create a mild vortex at the center of the vial. Central composite rotatable design has been used for studying the effect of the parameters, the factors interacting with each other and finding the optimum condition. The chromatographic separation was accomplished on a shim-Pak C18 column using a mixture of 10 mmol L−1 NaH2PO4 (pH = 5.4) : acetonitrile (40 : 60, v/v) as mobile phase at a flow rate 1 mL min−1 with UV detection at λ = 220 nm. In order to achieve the maximum extraction efficiency, different parameters affecting the extraction were optimized. Under the optimized conditions, preconcentration factor of 130 and limit of detection (LOD) of 0.3 μg L−1 were obtained. The calibration graph was linear within the range of 0.8–1500 μg L−1. Finally, the feasibility of the proposed method was successfully confirmed by extraction and determination of 2,4-D in real water samples in the range of microgram per liter and suitable results were obtained (RSDs < 6.4%).