Effect of the oxygen vacancy electronic state on Ni migration in Li0.5(Ni0.8Mn0.1Co0.1)O2 cathode material.

Cation migration coupled with oxygen vacancy formation is known to drive the layered to disordered spinel/rock-salt phase transformation in the high-Ni layered oxide cathodes of Li-ion batteries. However, the effect of different electronic states of oxygen vacancies on the cation migration still remains elusive. Here, we investigate Ni migration in delithiated Ni-rich Li0.5Ni0.8Mn0.1Co0.1O2 (hence Li0.5NMC811) in the presence of neutral and charged oxygen vacancies by means of first-principles density functional theory (DFT) calculations coupled with the nudged elastic band (NEB) method. We find that oxygen vacancies with neutral or +2 charge favor the Ni migration to Li tetrahedral and/or octahedral sites, both thermodynamically and kinetically. As for the case of +1 charged oxygen vacancies, while they thermodynamicaly favor the Ni migration to the Li site, the relatively high migration barrier suggests that they kinetically prohibit the Ni migration. Our results suggest that controlling the formation of oxygen vacancies is the key to enhancing the Ni-rich NMC structural stability in particular in their charged states.

Surface plasmon resonance biosensor chips integrated with MoS2-MoO3 hybrid microflowers for rapid CFP-10 tuberculosis detection.

This study reports on the modification of surface plasmon resonance (SPR) chips with molybdenum disulfide-molybdenum trioxide (MoS2-MoO3) microflowers to detect the tuberculosis (TB) markers of CFP-10. The MoS2-MoO3 microflowers were prepared by hydrothermal methods with variations in the pH and amount of trisodium citrate (Na3Ct), which were projected to influence the shape and size of microflower particles. The analysis shows that optimum MoS2-MoO3 hybrid microflowers were obtained at neutral pH using 0.5 g Na3Ct. The modified SPR biosensor exhibits a ten times higher response than the bare Au. Moreover, increasing MoS2-MoO3 thickness results in a higher detection response, sensitivity, and a smaller limit of detection (LOD). Using the optimized material composition, the Au/MoS2-MoO3-integrated SPR sensor can demonstrate sensitivity and LOD of 1.005 and 3.45 ng mL-1, respectively. This biosensor also has good selectivity, stability, and reproducibility based on cross-sensitivity characterization with other analytes and repeated measurements on several chips with different storing times and fabrication batch. Therefore, this proposed SPR biosensor possesses high potential to be further developed and applied as a detection technology for CFP-10 in monitoring and diagnosing TB.

Molecular insight into the role of zeolite lattice constraints on methane activation over the Cu-O-Cu active site.

Understanding the factors that influence the activity of a catalyst toward CH4 activation is of high importance for tuning the catalyst performance or designing new, better catalysts. Here, we performed a set of density functional theory (DFT) calculations on the H-CH3 bond cleavage over the Cu-O-Cu active site in the MOR zeolite with various Al-pair arrangements to obtain molecular insight into the structure-activity relation and clarify key parameters that define the Cu-O-Cu reactivity toward CH4. We found that weakening of the Cu-O-Cu bond during CH4 activation is crucial for determining the O-H bond strength and thus the Cu-O-Cu reactivity. In this regard, the zeolite lattice constraints are found to play a significant role as, on the one hand, it strengthens the Cu⋯Cu interaction and consequently weakens the Cu-O-Cu bonds and, on the other hand, it forces the Cu-O-Cu bond elongation process to destabilize the active site structure. The non-planar Cu-O-Cu geometry, due to lattice constraints, is also found to make the CH4 adsorption site, whether positioned closer to the µ-O or the Cu atom, crucial in determining the C-H activation product, i.e., a ˙CH3 radical or a Cu2-CH3- ligand.

How to develop a comprehensive Mangrove Quality Index?

Currently, the available indices to measure mangrove health are not comprehensive. An integrative ecological-socio economic index could give a better picture of the mangrove ecosystem health. This method explored all key biological, hydrological, ecological and socio-economic variables to form a comprehensive mangrove quality index. A total of 10 out of 43 variables were selected based on principal component analysis (PCA). They are aboveground biomass, crab abundance, soil carbon, soil nitrogen, number of phytoplankton species, number of diatom species, dissolved oxygen, turbidity, education level and fishing time spent by fishers. Two types of indices were successfully developed to indicate the health status viz., (1) Mangrove quality index for a specific category (MQISi ) and, (2) Overall mangrove quality index (MQI) to reflect the overall health status of the ecosystem. The indices for the five different categories were mangrove biotic integrity index ( M Q I S 1 ), mangrove soil index ( M Q I S 2 ), marine-mangrove index ( M Q I S 3 ), mangrove-hydrology index ( M Q I S 4 ) and mangrove socio-economic index ( M Q I S 5 ). The quality of the mangroves was classified from 1 to 5 viz. 1 (worst), 2 (bad), 3 (moderate), 4 (good), 5 (excellent). These MQI class could reflect the quality of mangrove forest which could be managed with the objective of improving its quality. Advantages of this method include: •PCA to select metrics from ecological-socioeconomic variables•Formulation of MQI based on selected metrics•Comprehensive index to classify mangrove ecosystem health.

Cytochrome b gene reveals panmixia among Japanese Threadfin Bream, Nemipterus japonicus (Bloch, 1791) populations along the coasts of Peninsular Malaysia and provides evidence of a cryptic species.

We evaluated genetic differentiation among ten presumed Japanese threadfin bream, Nemipterus japonicus populations along the coast of Peninsular Malaysia based on the partial sequence of the mitochondrial cytochrome b gene (982 bp). Genetic divergences (Kimura-2 parameter) ranged from 0.5% to 0.8% among nine of the ten populations while these nine populations were 4.4% to 4.6% diverged from the Kuala Besar population located at the Northeast coast. The constructed Neighbour Joining (NJ) phylogenetic trees based on haplotypes showed the Kuala Besar population forming an isolated cluster. The Analysis of Molecular Variance (AMOVA) of the ten populations a priori assigned into four regions, revealed that most of the variation occurred within population with a fairly low but significant level of regional differentiation (FST = 0.07, p < 0.05, FSC = 0.00, p > 0.05 and FCT = 0.07, p < 0.05) attributed to the Kuala Besar population. p Value after Bonferroni correction revealed that only pairwise FST values involving the Kuala Besar population with the other nine populations were significant. Thus, this study revealed that the N. japonicus populations off Peninsular Malaysia were panmictic. However, the Kuala Besar population, although morphologically identical was composed of a genetically discrete taxon from the rest. These findings are important contributions in formulating sustainable fishery management policies for this important fishery in Peninsular Malaysia.

Capability of integrated MODIS imagery and ALOS for oil palm, rubber and forest areas mapping in tropical forest regions.

Various classification methods have been applied for low resolution of the entire Earth's surface from recorded satellite images, but insufficient study has determined which method, for which satellite data, is economically viable for tropical forest land use mapping. This study employed Iterative Self Organizing Data Analysis Techniques (ISODATA) and K-Means classification techniques to classified Moderate Resolution Imaging Spectroradiometer (MODIS) Surface Reflectance satellite image into forests, oil palm groves, rubber plantations, mixed horticulture, mixed oil palm and rubber and mixed forest and rubber. Even though frequent cloud cover has been a challenge for mapping tropical forests, our MODIS land use classification map found that 2008 ISODATA-1 performed well with overall accuracy of 94%, with the highest Producer's Accuracy of Forest with 86%, and were consistent with MODIS Land Cover 2008 (MOD12Q1), respectively. The MODIS land use classification was able to distinguish young oil palm groves from open areas, rubber and mature oil palm plantations, on the Advanced Land Observing Satellite (ALOS) map, whereas rubber was more easily distinguished from an open area than from mixed rubber and forest. This study provides insight on the potential for integrating regional databases and temporal MODIS data, in order to map land use in tropical forest regions.