Sun Yat-sen University

About: Sun Yat-sen University is a education organization based out in Guangzhou, Guangdong, China. It is known for research contribution in the topics: Population & Cancer. The organization has 115149 authors who have published 113763 publications receiving 2286465 citations. The organization is also known as: Zhongshan University & SYSU.

Nitrogen-Doped Co3O4 Mesoporous Nanowire Arrays as an Additive-Free Air-Cathode for Flexible Solid-State Zinc–Air Batteries

Abstract: The kinetically sluggish rate of oxygen reduction reaction (ORR) on the cathode side is one of the main bottlenecks of zinc-air batteries (ZABs), and thus the search for an efficient and cost-effective catalyst for ORR is highly pursued. Co3O4 has received ever-growing interest as a promising ORR catalyst due to the unique advantages of low-cost, earth abundance and decent catalytic activity. However, owing to the poor conductivity as a result of its semiconducting nature, the ORR activity of the Co3O4 catalyst is still far below the expectation. Herein, we report a controllable N-doping strategy to significantly improve the catalytic activity of Co3O4 for ORR and demonstrate these N doped Co3O4 nanowires as an additive-free air-cathode for flexible solid-state zinc-air batteries. The results of experiments and DFT calculations reveal that the catalytic activity is promoted by the N dopant through a combined set of factors, including enhanced electronic conductivity, increased O2 adsorption strength and improved reaction kinetics. Finally, the assembly of all-solid-state ZABs based on the optimized cathode exhibit a high volumetric capacity of 98.1 mAh cm-3 and outstanding flexibility. The demonstration of such flexible ZABs provides valuable insights that point the way to the redesign of emerging portable electronics.

Efficient purification of ethene by an ethane-trapping metal-organic framework

Abstract: Separating ethene (C2H4) from ethane (C2H6) is of paramount importance and difficulty. Here we show that C2H4 can be efficiently purified by trapping the inert C2H6 in a judiciously designed metal-organic framework. Under ambient conditions, passing a typical cracked gas mixture (15:1 C2H4/C2H6) through 1 litre of this C2H6 selective adsorbent directly produces 56 litres of C2H4 with 99.95%+ purity (required by the C2H4 polymerization reactor) at the outlet, with a single breakthrough operation, while other C2H6 selective materials can only produce ca. ⩽ litre, and conventional C2H4 selective adsorbents require at least four adsorption-desorption cycles to achieve the same C2H4 purity. Single-crystal X-ray diffraction and computational simulation studies showed that the exceptional C2H6 selectivity arises from the proper positioning of multiple electronegative and electropositive functional groups on the ultramicroporous pore surface, which form multiple C-H···N hydrogen bonds with C2H6 instead of the more polar competitor C2H4.

Exome sequencing of liver fluke–associated cholangiocarcinoma

Abstract: Bin Tean Teh and colleagues report exome sequencing of Opisthorchis viverrini–related cholangiocarcinoma, a fatal bile duct cancer associated with liver fluke infection. Opisthorchis viverrini–related cholangiocarcinoma (CCA), a fatal bile duct cancer, is a major public health concern in areas endemic for this parasite. We report here whole-exome sequencing of eight O. viverrini–related tumors and matched normal tissue. We identified and validated 206 somatic mutations in 187 genes using Sanger sequencing and selected 15 genes for mutation prevalence screening in an additional 46 individuals with CCA (cases). In addition to the known cancer-related genes TP53 (mutated in 44.4% of cases), KRAS (16.7%) and SMAD4 (16.7%), we identified somatic mutations in 10 newly implicated genes in 14.8–3.7% of cases. These included inactivating mutations in MLL3 (in 14.8% of cases), ROBO2 (9.3%), RNF43 (9.3%) and PEG3 (5.6%), and activating mutations in the GNAS oncogene (9.3%). These genes have functions that can be broadly grouped into three biological classes: (i) deactivation of histone modifiers, (ii) activation of G protein signaling and (iii) loss of genome stability. This study provides insight into the mutational landscape contributing to O. viverrini–related CCA.

Genetic Learning Particle Swarm Optimization

Abstract: Social learning in particle swarm optimization (PSO) helps collective efficiency, whereas individual reproduction in genetic algorithm (GA) facilitates global effectiveness. This observation recently leads to hybridizing PSO with GA for performance enhancement. However, existing work uses a mechanistic parallel superposition and research has shown that construction of superior exemplars in PSO is more effective. Hence, this paper first develops a new framework so as to organically hybridize PSO with another optimization technique for “learning.” This leads to a generalized “learning PSO” paradigm, the *L-PSO. The paradigm is composed of two cascading layers, the first for exemplar generation and the second for particle updates as per a normal PSO algorithm. Using genetic evolution to breed promising exemplars for PSO, a specific novel *L-PSO algorithm is proposed in the paper, termed genetic learning PSO (GL-PSO). In particular, genetic operators are used to generate exemplars from which particles learn and, in turn, historical search information of particles provides guidance to the evolution of the exemplars. By performing crossover, mutation, and selection on the historical information of particles, the constructed exemplars are not only well diversified, but also high qualified. Under such guidance, the global search ability and search efficiency of PSO are both enhanced. The proposed GL-PSO is tested on 42 benchmark functions widely adopted in the literature. Experimental results verify the effectiveness, efficiency, robustness, and scalability of the GL-PSO.