King Abdullah University of Science and Technology

About: King Abdullah University of Science and Technology is a education organization based out in Jeddah, Saudi Arabia. It is known for research contribution in the topics: Catalysis & Membrane. The organization has 6221 authors who have published 22019 publications receiving 625706 citations. The organization is also known as: KAUST.

Vertical stratification of microbial communities in the Red Sea revealed by 16S rDNA pyrosequencing

Abstract: The ecosystems of the Red Sea are among the least-explored microbial habitats in the marine environment. In this study, we investigated the microbial communities in the water column overlying the Atlantis II Deep and Discovery Deep in the Red Sea. Taxonomic classification of pyrosequencing reads of the 16S rRNA gene amplicons showed vertical stratification of microbial diversity from the surface water to 1500 m below the surface. Significant differences in both bacterial and archaeal diversity were observed in the upper (2 and 50 m) and deeper layers (200 and 1500 m). There were no obvious differences in community structure at the same depth for the two sampling stations. The bacterial community in the upper layer was dominated by Cyanobacteria whereas the deeper layer harbored a large proportion of Proteobacteria. Among Archaea, Euryarchaeota, especially Halobacteriales, were dominant in the upper layer but diminished drastically in the deeper layer where Desulfurococcales belonging to Crenarchaeota became the dominant group. The results of our study indicate that the microbial communities sampled in this study are different from those identified in water column in other parts of the world. The depth-wise compositional variation in the microbial communities is attributable to their adaptations to the various environments in the Red Sea.

Catalytic mechanisms of direct pyrrole synthesis via dehydrogenative coupling mediated by PNP-Ir or PNN-Ru pincer complexes: crucial role of proton-transfer shuttles in the PNP-Ir system

Abstract: Kempe et al. and Milstein et al. have recently advanced the dehydrogenative coupling methodology to synthesize pyrroles from secondary alcohols (e.g., 3) and β-amino alcohols (e.g., 4), using PNP-Ir (1) and PNN-Ru (2) pincer complexes, respectively. We herein present a DFT study to characterize the catalytic mechanism of these reactions. After precatalyst activation to give active 1A/2A, the transformation proceeds via four stages: 1A/2A-catalyzed alcohol (3) dehydrogenation to give ketone (11), base-facilitated C–N coupling of 11 and 4 to form an imine-alcohol intermediate (18), base-promoted cyclization of 18, and catalyst regeneration via H2 release from 1R/2R. For alcohol dehydrogenations, the bifunctional double hydrogen-transfer pathway is more favorable than that via β-hydride elimination. Generally, proton-transfer (H-transfer) shuttles facilitate various H-transfer processes in both systems. Notwithstanding, H-transfer shuttles play a much more crucial role in the PNP-Ir system than in the PNN-Ru...

Efficient Coordinated Recovery of Sparse Channels in Massive MIMO

Abstract: This paper addresses the problem of estimating sparse channels in massive MIMO-OFDM systems. Most wireless channels are sparse in nature with large delay spread. In addition, these channels as observed by multiple antennas in a neighborhood have approximately common support. The sparsity and common support properties are attractive when it comes to the efficient estimation of large number of channels in massive MIMO systems. Moreover, to avoid pilot contamination and to achieve better spectral efficiency, it is important to use a small number of pilots. We present a novel channel estimation approach which utilizes the sparsity and common support properties to estimate sparse channels and requires a small number of pilots. Two algorithms based on this approach have been developed that perform Bayesian estimates of sparse channels even when the prior is non-Gaussian or unknown. Neighboring antennas share among each other their beliefs about the locations of active channel taps to perform estimation. The coordinated approach improves channel estimates and also reduces the required number of pilots. Further improvement is achieved by the data-aided version of the algorithm. Extensive simulation results are provided to demonstrate the performance of the proposed algorithms.

Surface Passivation of GaN Nanowires for Enhanced Photoelectrochemical Water-Splitting.

Abstract: Hydrogen production via photoelectrochemical water-splitting is a key source of clean and sustainable energy. The use of one-dimensional nanostructures as photoelectrodes is desirable for photoelectrochemical water-splitting applications due to the ultralarge surface areas, lateral carrier extraction schemes, and superior light-harvesting capabilities. However, the unavoidable surface states of nanostructured materials create additional charge carrier trapping centers and energy barriers at the semiconductor–electrolyte interface, which severely reduce the solar-to-hydrogen conversion efficiency. In this work, we address the issue of surface states in GaN nanowire photoelectrodes by employing a simple and low-cost surface treatment method, which utilizes an organic thiol compound (i.e., 1,2-ethanedithiol). The surface-treated photocathode showed an enhanced photocurrent density of −31 mA/cm2 at −0.2 V versus RHE with an incident photon-to-current conversion efficiency of 18.3%, whereas untreated nanowires...