Separation of Leather, Synthetic Leather and Polymers Using Handheld Laser-Induced Breakdown Spectroscopy.

Genuine leather is produced from animal skin by chemical tanning using chemical or vegetable agents, while synthetic leather is a combination of fabric and polymer. The replacement of natural leather by synthetic leather is becoming more difficult to identify. In this work, Laser Induced Breakdown Spectroscopy (LIBS) is evaluated to separate between very similar materials: leather, synthetic leather, and polymers. LIBS is now widely employed to provide a specific fingerprint from the different materials. Animal leathers processed with vegetable, chromium, or titanium tanning were analyzed together with polymers and synthetic leather from different origins. The spectra exhibited typical signatures from the tanning agents (Cr, Ti, Al) and the dyes and pigments, but also from polymer characteristic bands. The principal factor analysis allowed to discriminate between four main groups of samples representing the tanning processes and the polymer or synthetic leather character.

Fast quantitative determination of platinum in liquid samples by laser-induced breakdown spectroscopy.

The potential of laser-induced breakdown spectroscopy (LIBS) for the rapid determination of platinum in liquid silicone oils has been evaluated in the framework of on-line process control. A comparison of LIBS sensitivity between three setups designed for liquid analysis (static, liquid jet and flowing liquid) was performed using a 266 nm Nd/YAG laser irradiation. Best results were obtained using the flowing liquid setup and a similar limit of detection was obtained using the liquid jet. The effect of different buffer gases (Ar, He, N(2), etc.) on the signal sensitivity was studied in liquid jet analysis and best values were obtained with a nitrogen sheath gas. Detection limits were in the 100 mg/kg range for both setups. Quantitative determination of platinum in real liquid samples was also investigated using both liquid jet and flowing liquid setups. Calibration curves were plotted for Pt with the liquid jet and the flowing liquid setups under optimised temporal acquisition parameters (delay time and gate width). A normalisation using a silicon line was applied and recovery ranged from 3 to 15% for Pt in catalyst samples with both setups showing that LIBS is a sensitive and accurate method for on-line applications.

Investigating the metal contamination status from recycling e-waste sites from Dakar, Senegal.

In Senegal, processes employed for recycling e-wastes result in release of so-called heavy metals in the environment. In this study, the metal distribution and concentrations of soils collected from four e-waste recycling areas located in the Dakar area are presented. Measurements are performed using portable X-ray fluorescence and laser-induced breakdown spectroscopy (LIBS) to obtain a complete analysis of the soil, including major and trace elements (i.e., mg/kg). Levels of zinc, copper, manganese, and iron in soils are high but contrasted ranging from 66 mg/kg for Cu in Mbeubeuss landfill to more than 1000 mg/kg for Mn and 10,000 mg/kg for Zn. Lower values are obtained for chromium and lead (Cr = 207 mg/kg and Pb = 181 mg/kg). The most elevated average lead values (i.e., 2935 mg/kg and 1427 mg/kg) are obtained from the e-waste recycling sites located in the urban area of Dakar: Reubeuss and Pikine, respectively. Specific element fingerprints are obtained from each of the studied areas. To evaluate human exposure to the main metals, vegetables grown outside the large e-waste landfill were analyzed. The values obtained for Cr, Cu, Fe, Mn, Sr, and Zn are low, ranging from 0.11 to 9.66 mg/kg for chromium in turnip and iron in beetroots, respectively. The calculated health risk index remains below unit for all vegetables, which means no potential risk of vegetable consumption for human health. The data provided useful information to estimate contaminations and their origin. Therefore, in order to ensure food safety, continuous monitoring of the vegetables grown in the vicinity of recycling areas is needed.

Speciation of metals by sequential extractions of agricultural soils located near a dumpsite for prediction of element availability to vegetables.

In this paper heavy metal pollution has been investigated by comparing total concentrations and speciation of heavy metals (Cr, Cu, Mn, Zn, Pb and Sr) in soils from four agricultural fields (S1, S2, S3, S4) located in the direct vicinity of the largest landfill in Senegal. The sequential test allowed discriminating between various fractions of heavy metals, namely the acid-extractable fraction, the fraction bound to Fe oxides, the fraction bound to organic matter and the residual fraction. It was proven that the most important fractions of metals (Cr, Cu, Pb, Mn, Sr and Zn) are bound to the residual fraction, more than 50% for most sites, and thus they may be relatively hardly liberated into the environment. The results also showed that the metal pollution in S3 and S4 were more severe than in other sampling sites, especially for Mn and Zn. In addition, the exchangeable fraction, which is the most available, represents from 10 to 47% of the total concentration for Sr, Mn and Zn, indicating that a non-negligible part of these elements may be easily released. Matrix correlation between soil characteristics and the elemental concentrations was tested to study and to detect a possible trend of metal mobilization from organic matter or oxides to agricultural soils. Vegetable grown from the four sampling sites were analyzed, Cr, Zn and Pb concentrations were high in many studied foodstuffs, (up to 54 mg/kg; 45.8 mg/kg and 3.4 mg/kg for Mn, Zn and Pb respectively) and higher than the threshold values of FAO/WHO. Calculation of hazard indexes suggested no potential health risks associated with consuming the vegetables with the exception of cassava and cassava leaves.

Electroless growth of silver nanoparticles into mesostructured silica block copolymer films.

Silver nanoparticles and silver nanowires have been grown inside mesostructured silica films obtained from block copolymers using two successive reduction steps: the first one involves a sodium borohydride reduction or a photoreduction of silver nitrate contained in the film, and the second one consists of a silver deposit on the primary nanoparticles, carried out by silver ion solution reduction with hydroxylamine chloride. We have demonstrated that the F127 block copolymer ((PEO)(106)(PPO)(70)(PEO)(106)), "F type", mesostructured silica film is a suitable "soft" template for the fabrication of spherical silver nanoparticles arrays. Silver spheres grow from 7 to 11 nm upon the second reduction step. As a consequence, a red shift of the surface plasmon resonance associated with metallic silver has been observed and attributed to plasmonic coupling between particles. Using a P123 block copolymer ((PEO)(20)(PPO)(70)(PEO)(20)), "P type", mesostructured silica film, we have obtained silver nanowires with typical dimension of 10 nm x 100 nm. The corresponding surface plasmon resonance is blue-shifted. The hydroxylamine chloride treatment appears to be efficient only when a previous chemical reduction is performed, assuming that the first sodium borohydride reduction induces a high concentration of silver nuclei in the first layer of the porous silica (film/air interface), which explains their reactivity for further growth.

Tea geographical origin explained by LIBS elemental profile combined to isotopic information.

The combined LIBS and ICP HRMS analysis of 13 tea samples are studied in view of identification of tea geographical origin. The elemental signature provided by LIBS spectra is treated by principal component analysis followed by partial least square discriminant analysis and factorial discriminant analysis. Selected element lines are found efficient to discriminate most sample groups. Data analysis model is improved by variable selection and the isotopic ratio 11B/10B was employed to improve the prediction capacity of the model. The alkaline earth: Ba, Ca, Mg, Sr and alkaline Rb, Na are easily detected by the LIBS system and these elements are important to classify sample according to their geographical origin. Minor elements like P, S, Fe, B … also bring discriminant information. A five clusters model gave best correct identification in a cross validation test (94.2%). This method also allowed to identify the origin of four unknown teas. In this study the use of FDA or PLS DA after the PCA examination of the LIBS/ICP MS data led to similar conclusions for fast classification of the tea samples and identification of the geographical origin of the four unknown teas.

Machine Learning Allows Calibration Models to Predict Trace Element Concentration in Soils with Generalized LIBS Spectra.

Determination of trace elements in soils with laser-induced breakdown spectroscopy is significantly affected by the matrix effect, due to large variations in chemical composition and physical property of different soils. Spectroscopic data treatment with univariate models often leads to poor analytical performances. We have developed in this work a multivariate model using machine learning algorithms based on a back-propagation neural network (BPNN). Beyond the classical chemometry approach, machine learning, with tremendous progresses the last years especially for image processing, is offering an ensemble of powerful and constantly renewed algorithms and tools efficient for the different steps in the construction of a spectroscopic data treatment model, including feature selection and neural network training. Considering the matrix effect as the focus of this work, we have developed the concept of generalized spectrum, where the information about the soil matrix is explicitly included in the input vector of the model as an additional dimension. After a brief presentation of the experimental procedure and the results of regression with a univariate model, the development of the multivariate model will be described in detail together with its analytical performances, showing average relative errors of calibration (REC) and of prediction (REP) within the range of 5-6%.

Determination of Metal Elements in Wine Using Laser-Induced Breakdown Spectroscopy (LIBS).

We developed a method for sensitive elemental analysis of wines using laser-induced breakdown spectroscopy (LIBS). In order to overcome the inefficiency of direct ablation of bulk wine (an organic liquid), a thin layer of wine residue was prepared on a metallic target according to an appropriated heating procedure applied to an amount of liquid wine dropped on the target surface. The obtained ensemble was thus ablated. Such a sample preparation procedure used a very small volume of 2 mL of wine and took only 30 min without reagent or solvent. The results show the detection of tens of metal and non-metal elements including majors (Na, Mg, K, Ca), minors, and traces (Li, B, Si, P, Ti, Mn, Fe, Cu, Zn, Rb, Sr, Ba, and Pb) in wines purchased from local supermarkets and from different production places in France. Commercially available wines were then spiked with certified standard solutions of Ti and Fe. Three series of laboratory reference samples were thus prepared using three different wines (a red wine and a white wine from a same production region and a red wine from another production region) with concentrations of Ti and Fe in the range of 1-40 mg/L. Calibration graphs established with the spiked samples allowed extracting the figures-of-merit parameters of the method for wine analysis such as the coefficient of determination ( R2) and the limits of detection and quantification (LOD and LOQ). The calibration curves built with the three wines were then compared. We studied the residual matrix effect between these wines in the determination of the concentrations of Ti and Fe.

Evaluation of porous graphitic carbon stationary phase for simultaneous preconcentration and separation of organic and inorganic selenium species in "clean" water systems.

A high performance liquid chromatography procedure, based on porous graphitic carbon stationary phase, was evaluated for simultaneous on-line preconcentration and separation of organic and inorganic selenium species. Detection was achieved by inductively coupled plasma mass spectrometry with collision/reaction cell (ICP-CRC-MS). Different concentrations of formic acid were tested as mobile phase. A 240 mmol L(-1) concentration with pH adjusted to 2.6, allowed the separation of five species, i.e. selenite, selenate, selenomethionine, selenocystine and selenoethionine. On-line preconcentration of these five species was achieved when heptafluorobutyric acid was used as injection medium, inducing an enrichment of solutes at the top of the column which allowed large volumes (up to 1 mL) to be injected. Combining these injection conditions and 80Se monitoring with ICP-CRC-MS, detection limits between 2 and 8 ng (Se)L(-1), depending on the species, were obtained. Because of the extremely low detection limits obtained, the method was successfully applied to mineral waters.