Isolation of a Series of Fatty Acid Components of Ongokea gore Seed (Isano) Oil and their Detailed Structural Analysis

The total oil production capacity of isano oil is estimated at about 10,000 tons annually. Previous studies of this oil revealed that it is rich in fatty acids including a conjugated diyne moiety. This makes isano oil an excellent candidate for sustainable applications development. However, only a few of its fatty acids have been isolated and identified so far. In this study, we have reinvestigated this oil by characterizing its physicochemical properties and isolating several of its fatty acids as ethyl esters for their detailed structural analysis and identification. Six ethyl esters of fatty acids constituting isanic oil were isolated by flash column chromatography and semipreparative HPLC. The detailed structural analysis of these fatty acid esters by infrared, high resolution, mass spectroscopy, and nuclear magnetic resonance (1‐D and 2‐D) allowed determining unequivocally their chemical structure. The main fatty acid component of the oil (35.7 %) was identified as isanic acid. Four minor acids were found to possess also two conjugated triple bonds, while the sixth fatty acid does not contain carbon–carbon triple bonds nor double bonds but possessed a cis epoxide function. Results obtained in this study are currently being used to explore potential applications of isano oil.     

Experimental Investigation and Model Development for Thermal Conductivity of Glycerol–MgO Nanofluids

This paper presents experimental and theoretical determination of the effective thermal conductivity of three magnesium oxide (MgO) nanoparticles of different sizes dispersed in glycerol. The glycerol-based nanofluids were prepared at volume fractions ranging from 0.5% to 4% and no surfactant. The nanoparticles were dispersed and deagglomerated for 2 hours using an ultrasonic probe. The effective thermal conductivity of nanofluids was measured from 20°C to 45°C using a thermal conductivity analyzer. The experimental results show an increase in the thermal conductivity of MgO–glycerol nanofluids with increasing volume fraction of nanoparticles. The thermal conductivity ratio is unaffected as the temperature increases. In the given volume fraction and temperature range, the thermal conductivity ratio of MgO–glycerol nanofluids decreases with increasing particle size. The obtained experimental data were also compared with some existing theoretical and empirical models that may work for glycerol-based nanofluids. The comparison of experimental data with these available models shows that the data do not agree with the models. Therefore, a new empirical correlation was developed for the MgO–glycerol nanofluids.     

Mapping spatio-temporal water level variations over the central Congo River using PALSAR ScanSAR and Envisat altimetry data

Previous studies using synthetic aperture radar (SAR) backscattering coefficients have been used to distinguish vegetation types, to monitor flood conditions, and to assess soil moisture variations over the wetlands. Here, we attempted to estimate spatio-temporal water level variations over the central Congo mainstem covered with aquatic plants using the backscattering coefficients from the Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) Scanning SAR (ScanSAR) images and water levels from Envisat altimetry data. First, permanent open water, forest, macrophytes, and herbaceous plants have been classified over the central Congo Basin based on statistics of the backscattering coefficient values. Second, we generated multi-temporal water level maps over part of the Congo mainstem based on the relationship between Envisat altimetry-derived river-level changes and PALSAR ScanSAR backscattering coefficient variations. Finally, the water level maps were validated with Ice, Cloud and land Elevation Satellite (ICESat) altimetry-derived water levels. We obtained overall root mean square difference (RMSD) of 67.27 cm at 100-m scale resolution of PALSAR ScanSAR. Our study shows that we can obtain reasonable estimates of water levels of the rivers covered with seasonally floating or emergent macrophytes from backscattering coefficients. Furthermore, it is expected that the generated water level maps can be used as a ‘true’ data set to perform pre-launch study of the Surface Water Ocean Topography (SWOT) mission to be launched in 2021.