The present work highlights the facile synthesis of hydrophobic palm fatty acid functionalized Fe3O4 nanoparticles (MNP-FA) for the efficient removal of oils from the surface of water. An intense hydrophobic layer was introduced on the surface of Fe3O4 nanoparticles functionalized by the palm fatty acid obtained from the hydrolysis of palm olein. Scanning electron microscopy (SEM), vibrating sample magnetometer (VSM), Energy dispersive X-ray spectroscopy (EDX) and water contact angle analysis (WCA) measurements were used to characterize the newly fabricated palm fatty acid adorned magnetic Fe3O4 nanoparticles (MNP-FA). The obtained results confirmed the successful synthesis of palm fatty acid-functionalized magnetic nanoparticles. Oil removal tests performed with MNP-FA revealed that this newly prepared material could selectively adsorb lubricating oil up to 3.5 times of the particles' weight while completely repelling water. The main parameters affecting the adsorption of oil i.e., sorption time, mass of sorbent and pH of water were optimized.
A novel adsorbent, palm fatty acid coated magnetic Fe3O4 nanoparticles (MNP-FA) was successfully synthesized with immobilization of the palm fatty acid onto the surface of MNPs. The successful synthesis of MNP-FA was further confirmed by X-Ray diffraction (XRD), transmission electron microscopy (TEM), Fourier transform infrared spectroscopy (FT-IR) and Energy dispersive X-Ray spectroscopy (EDX) analyses and water contact angle (WCA) measurement. This newly synthesized MNP-FA was applied as magnetic solid phase extraction (MSPE) adsorbent for the enrichment of polycyclic aromatic hydrocarbons (PAHs), namely fluoranthene (FLT), pyrene (Pyr), chrysene (Cry) and benzo(a)pyrene (BaP) from environmental samples prior to High Performance Liquid Chromatography- Diode Array Detector (HPLC-DAD) analysis. The MSPE method was optimized by several parameters such as amount of sorbent, desorption solvent, volume of desorption solvent, extraction time, desorption time, pH and sample volume. Under the optimized conditions, MSPE method provided a low detection limit (LOD) for FLT, Pyr, Cry and BaP in the range of 0.01-0.05 ng mL(-1). The PAHs recoveries of the spiked leachate samples ranged from 98.5% to 113.8% with the RSDs (n = 5) ranging from 3.5% to 12.2%, while for the spiked sludge samples, the recoveries ranged from 81.1% to 119.3% with the RSDs (n = 5) ranging from 3.1% to 13.6%. The recyclability study revealed that MNP-FA has excellent reusability up to five times. Chromatrographic analysis demonstrated the suitability of MNP-FA as MSPE adsorbent for the efficient extraction of PAHs from environmental samples.
Climate change caused by the greenhouse gases CO2 remains a topic of global concern. To mitigate the excessive levels of anthrophonic CO2 in the atmosphere, CO2 capture methods have been developed and among these, adsorption is an especially promising method. This paper presents a series of amine functionalized biochar obtained from desiccated coconut waste (amine-biochar@DCW) for use as CO2 adsorbent. They are ethylenediamine-functionalized biochar@DCW (EDA-biochar@DCW), diethylenetriamine-functionalized biochar@DCW (DETA-biochar@DCW), triethylenetetramine-functionalized biochar@DCW (TETA-biochar@DCW), tetraethylenepentamine-functionalized biochar@DCW (TEPA-biochar@DCW), and pentaethylenehexamine-functionalized biochar@DCW (PEHA-biochar@DCW). The adsorbents were obtained through amine functionalization of biochar and they are characterized using Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), energy dispersive X-ray (EDX) spectroscopy, Brunauer-Emmett-Teller (BET), and thermogravimetric analysis (TGA). The CO2 adsorption study was conducted isothermally and using a thermogravimetric analyzer. From the results of the characterization analyses, a series of amine-biochar@DCW adsorbents had larger specific surface area in the range of 16.2 m2/g-37.1 m2/g as compare to surface area of pristine DCW (1.34 m2/g). Furthermore, the results showed an increase in C and N contents as well as the appearance of NH stretching, NH bending, CN stretching, and CN bending, suggesting the presence of amine on the surface of biochar@DCW. The CO2 adsorption experiment shows that among the amine modified biochar adsorbents, TETA-biochar@DCW has the highest CO2 adsorption capacity (61.78 mg/g) when using a mass ratio (m:m) of biochar@DCW:TETA (1:2). The adsorption kinetics on the TETA-biochar@DCW was best fitted by the pseudo-second model (R2 = 0.9998), suggesting the adsorption process occurs through chemisorption. Additionally, TETA-biochar@DCW was found to have high selectivity toward CO2 gas and good reusability even after five CO2 adsorption-desorption cycles. The results demonstrate the potential of novel CO2 adsorbents based on amine functionalized on desiccated coconut waste biochar.
The importance of nanotechnology in medical applications especially with biomedical sensing devices is undoubted. Several medical diagnostics have been developed by taking the advantage of nanomaterials, especially with electrical biosensors. Biosensors have been predominantly used for the quantification of different clinical biomarkers toward detection, screening, and follow-up the treatment. At present, ovarian cancer is one of the severe complications that cannot be identified until it becomes most dangerous as the advanced stage. Based on the American Cancer Society, 20% of cases involved in the detection of ovarian cancer are diagnosed at an early stage and 80% diagnosed at the later stages. The patient just has a common digestive problem and stomach ache as early symptoms and people used to ignore these symptoms. Micro ribonucleic acid (miRNA) is classified as small non-coding RNAs, their expressions change due to the association of cancer development and progression. This article reviews and discusses on the currently available strategies for the early detection of ovarian cancers using miRNA as a biomarker associated with electrical biosensors. A unique miRNA-based biomarker detections are specially highlighted with biosensor platforms to diagnose ovarian cancer.