Poly-NIPAM/Fe3O4/multiwalled carbon nanotube nanocomposites for kerosene removal from water.

Multiwalled carbon nanotubes (MWCNTs) were oxidized using a mixture of H2SO4 and HNO3, and the oxidized MWCNTS were decorated with magnetite (Fe3O4). Finally, poly-N-isopropyl acrylamide-co-butyl acrylate (P-NIPAM) was added to obtain P-NIPAM/Fe/MWCNT nanocomposites. The nanosorbents were characterized by various techniques, including X-ray diffraction, transmission electron microscopy, scanning electron microscopy, thermogravimetric analysis, and Brunauer-Emmett-Teller analysis. The P-NIPAM/Fe/MWCNT nanocomposites exhibited increased surface hydrophobicity. Owing to their higher adsorption capacity, their kerosene removal efficiency was 95%; by contrast, the as-prepared, oxidized, and magnetite-decorated MWCNTs had removal efficiencies of 45%, 55%, and 68%, respectively. The P-NIPAM/Fe/MWCNT nanocomposites exhibited a sorbent capacity of 8.1 g/g for kerosene removal from water. The highest kerosene removal efficiency from water was obtained at a process time of 45 min, sorbent dose of 0.005 g, solution temperature of 40 °C, and pH 3.5. The P-NIPAM/Fe/MWCNTs showed excellent stability after four cycles of kerosene removal from water followed by regeneration. The reason may be the increase in the positive charge of the polymer at pH 3.5 and the increased adsorption affinity of the adsorbent toward the kerosene contaminant. The pseudo second-order model was found to be the most suitable model for studying the kinetics of the adsorption reaction.

V2O5, CeO2 and Their MWCNTs Nanocomposites Modified for the Removal of Kerosene from Water.

In this paper, the application of multiwalled carbon nanotubes (MWCNTs) based on metal oxide nanocomposites as adsorbents for the removal of hydrocarbons such as kerosene from water was investigated. Functionalized MWCNTs were obtained by chemical oxidation using concentrated sulfuric and nitric acids. V2O5, CeO2, and V2O5:CeO2 nanocomposites were prepared using the hydrothermal method followed by deposition of these oxides over MWCNTs. Individual and mixed metal oxides, fresh MWCNTs, and metal oxide nanoparticle-doped MWCNTs using different analysis techniques were characterized. XRD, TEM, SEM, EDX, AFM, Raman, TG/DTA, and BET techniques were used to determine the structure as well as chemical and morphological properties of the newly prepared adsorbents. Fresh MWCNTs, Ce/MWCNTs, V/MWCNTs, and V:Ce/MWCNTs were applied for the removal of kerosene from a model solution of water. GC analysis indicated that high kerosene removal efficiency (85%) and adsorption capacity (4270 mg/g) after 60 min of treatment were obtained over V:Ce/MWCNTs in comparison with fresh MWCNTs, Ce/MWCNTs and V/MWCNTs. The kinetic data were analyzed using the pseudo-first order, pseudo-second order, and intra-particle diffusion rate equations.

Polyethylene over magnetite-multiwalled carbon nanotubes for kerosene removal from water.

In this study, a nano-adsorbent was prepared for kerosene removal from water. Multiwalled carbon nanotubes (MWCNTs) were functionalized with concentrated HNO3 (nitric acid). Subsequently, Fe3O4 (magnetite) nanoparticles were deposited on the MWCNTs to prepare a magnetite/MWCNTs (Fe-MWCNTs) nanocomposite. Then, polyethylene was added to the Fe-MWCNTs to fabricate a polyethylene/magnetite/MWCNTs (PE/Fe-MWCNTs) novel nanocomposite. The nano-adsorbent was characterized using BET, FTIR, Raman, XRD, TEM, and SEM. A kerosene-water model mixture was used for adsorption tests. Several parameters: adsorption time, adsorbent dose, solution pH, solution temperature, and kerosene concentration in the kerosene-water model mixture, were analyzed during adsorption experiments. After each batch experiment, kerosene concentration was determined using high-performance liquid chromatography (HPLC). Magnetic field was used to remove the adsorbent after each experiment. The kerosene adsorption capacity and removal efficiency of the PE/Fe-MWCNTs nanocomposite (3560 mg/g and 71.2 %, respectively) were higher than those of Fe-MWCNTs, ox-MWCNTs, and fresh MWCNTs (3154 mg/g and 63.1 %, 2204 mg/g and 44.0 %, and 2092 mg/g and 41.8 %, respectively). Kerosene adsorption followed a pseudo-second-order kinetic model (R2 = 0.999) and the Langmuir isotherm model, suggesting that adsorption was uniform and homogenous process.

A rapid Fourier-transform infrared (FTIR) spectroscopic method for direct quantification of paracetamol content in solid pharmaceutical formulations.

A transmission FTIR spectroscopic method was developed for direct, inexpensive and fast quantification of paracetamol content in solid pharmaceutical formulations. In this method paracetamol content is directly analyzed without solvent extraction. KBr pellets were formulated for the acquisition of FTIR spectra in transmission mode. Two chemometric models: simple Beer's law and partial least squares employed over the spectral region of 1800-1000 cm(-1) for quantification of paracetamol content had a regression coefficient of (R(2)) of 0.999. The limits of detection and quantification using FTIR spectroscopy were 0.005 mg g(-(1) and 0.018 mg g(-1), respectively. Study for interference was also done to check effect of the excipients. There was no significant interference from the sample matrix. The results obviously showed the sensitivity of transmission FTIR spectroscopic method for pharmaceutical analysis. This method is green in the sense that it does not require large volumes of hazardous solvents or long run times and avoids prior sample preparation.

Estimation of ibuprofen in urine and tablet formulations by transmission Fourier Transform Infrared spectroscopy by partial least square.

A rapid, reliable and cost effective analytical procedure for the estimation of ibuprofen in pharmaceutical formulations and human urine samples was developed using transmission Fourier Transform Infrared (FT-IR) spectroscopy. For the determination of ibuprofen, a KBr window with 500 µm spacer was used to acquire the FT-IR spectra of standards, pharmaceuticals as well as urine samples. Partial least square (PLS) calibration model was developed based on region from 1807 to 1,461 cm(-1) using ibuprofen standards ranging from 10 to 100 µg ml(-1). The developed model was evaluated by cross-validation to determine standard error of the models such as root mean square error of calibration (RMSEC), root mean square error of cross validation (RMSECV) and root mean square error of prediction (RMSEP). The coefficient of determination (R(2)) achieved was 0.998 with minimum errors in RMSEC, RMSECV and RMSEP with the value of 1.89%, 1.63% and 4.07%, respectively. The method was successfully applied to urine and pharmaceutical samples and obtained good recovery (98-102%).