Nankai University

About: Nankai University is a education organization based out in Tianjin, China. It is known for research contribution in the topics: Catalysis & Adsorption. The organization has 42964 authors who have published 51866 publications receiving 1127896 citations. The organization is also known as: Nánkāi Dàxué.

Facile magnetization of metal–organic framework MIL-101 for magnetic solid-phase extraction of polycyclic aromatic hydrocarbons in environmental water samples

Abstract: The unusual properties such as high surface area, good thermal stability, uniform structured nanoscale cavities and the availability of in-pore functionality and outer-surface modification make metal–organic frameworks (MOFs) attractive for diverse analytical applications. However, integration of MOFs with magnets for magnetic solid-phase extraction for analytical application has not been attempted so far. Here we show a facile magnetization of MOF MIL-101(Cr) for rapid magnetic solid-phase extraction of polycyclic aromatic hydrocarbons (PAHs) from environmental water samples. MIL-101 is attractive as a sorbent for solid-phase extraction of pollutants in aqueous solution due to its high surface area, large pores, accessible coordinative unsaturated sites, and excellent chemical and solvent stability. In situ magnetization of MIL-101 microcrystals as well as magnetic solid-phase extraction of PAHs was achieved simultaneously by simply mixing MIL-101 and silica-coated Fe3O4 microparticles in a sample solution under sonication. Such MOF-based magnetic solid-phase extraction in combination with high-performance liquid chromatography gave the detection limits of 2.8–27.2 ng L−1 and quantitation limits of 6.3–87.7 ng L−1 for the PAHs. The relative standard deviations for intra- and inter-day analyses were in the range of 3.1–8.7% and 6.1–8.5%, respectively. The results showed that hydrophobic and π–π interactions between the PAHs and the framework terephthalic acid molecules, and the π-complexation between PAHs and the Lewis acid sites in the pores of MIL-101 play a significant role in the adsorption of PAHs.

Layer-by-Layer Assembly of Cross-Functional Semi-transparent MXene-Carbon Nanotubes Composite Films for Next-Generation Electromagnetic Interference Shielding

Abstract: Lightweight, flexible, and electrically conductive thin films with high electromagnetic interference (EMI) shielding effectiveness are highly desirable for next-generation portable and wearable electronic devices. Here, spin spray layer-by-layer (SSLbL) to rapidly assemble Ti3C2Tx MXene-carbon nanotube (CNT) composite films is shown and their potential for EMI shielding is demonstrated. The SSLbL technique allows strategic combinations of nanostructured materials and polymers providing a rich platform for developing hierarchical architectures with desirable cross-functionalities including controllable transparency, thickness, and conductivity, as well as high stability and flexibility. These semi-transparent LbL MXene-CNT composite films show high conductivities up to 130 S cm−1 and high specific shielding effectiveness up to 58 187 dB cm2 g−1, which is attributed to both the excellent electrical conductivity of the conductive fillers (i.e., MXene and CNT) and the enhanced absorption with the LbL architecture of the films. Remarkably, these values are among the highest reported values for flexible and semi-transparent composite thin films. This work could offer new solutions for next-generation EMI shielding challenges.

Epitaxial Heterogeneous Interfaces on N-NiMoO4/NiS2 Nanowires/Nanosheets to Boost Hydrogen and Oxygen Production for Overall Water Splitting

Abstract: Developing bifunctional efficient electrocatalysts for both the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) is in high demand for the development of overall water-splitting devices. In particular, the electrocatalytic performance can be largely improved by designing positive nanoscale-heterojunction with well-tuned interfaces. Herein, a novel top-down strategy is reported to construct the oxide/sulfide heterostructures (N-NiMoO4/NiS2 nanowires/nanosheets) as a multisite HER/OER catalyst. Starting with the NiMoO4 nanowires, nitridation in a controlled manner enables activation of Ni sites in NiMoO4 and then yields oxide/sulfide heterojunction by directly vulcanizing the highly composition-segregated N-NiMoO4 nanowires. The abundant epitaxial heterogeneous interfaces at atomic-level facilitate the electron transfer from N-NiMoO4 to NiS2, which further cooperate synergistically toward both the hydrogen and oxygen generation in alkali solution. Furthermore, with N-NiMoO4/NiS2 grown carbon fiber cloth as the engineering electrode, the assembled N-NiMoO4/NiS2-N-NiMoO4/NiS2 system can deliver a current density of 10 mA cm(-2) with the cell voltage of 1.60 V in the water-splitting reaction. This current density is 3.39 times higher than that of the Pt-Ir set (2.95 mA cm(-2)). The excellent catalytic performance offered of N-NiMoO4/NiS2 nanowires/nanosheets presents a great example to demonstrate the significance of interface engineering in the field of electrocatalysis.

On Layer Normalization in the Transformer Architecture

Abstract: The Transformer is widely used in natural language processing tasks. To train a Transformer however, one usually needs a carefully designed learning rate warm-up stage, which is shown to be crucial to the final performance but will slow down the optimization and bring more hyper-parameter tunings. In this paper, we first study theoretically why the learning rate warm-up stage is essential and show that the location of layer normalization matters. Specifically, we prove with mean field theory that at initialization, for the original-designed Post-LN Transformer, which places the layer normalization between the residual blocks, the expected gradients of the parameters near the output layer are large. Therefore, using a large learning rate on those gradients makes the training unstable. The warm-up stage is practically helpful for avoiding this problem. On the other hand, our theory also shows that if the layer normalization is put inside the residual blocks (recently proposed as Pre-LN Transformer), the gradients are well-behaved at initialization. This motivates us to remove the warm-up stage for the training of Pre-LN Transformers. We show in our experiments that Pre-LN Transformers without the warm-up stage can reach comparable results with baselines while requiring significantly less training time and hyper-parameter tuning on a wide range of applications.

Relativistic equation of state of nuclear matter for supernova explosion

Abstract: We construct the equation of state (EOS) of nuclear matter at finite temperature and density with various proton fractions within the relativistic mean field (RMF) theory for use in supernova simulations. We consider nuclei, alpha-particles, protons and neutrons in equilibrium at densities smaller than about PB '" 10 14 . 2 g/cm 3 by minimizing the free energy of the nuclear matter. The calculation is based on the RMF theory with the parameter set TM1, which has been demonstrated to provide good accounts of the ground state and excited state properties of finite nuclei. We tabulate the outcome for various densities in terms of the pressure, free energy, entropy, etc. at a sufficiently large number of mesh points in the density range PB = 10 5 . 1 '" 10 15 .4 g/cm 3 , the temperature range T = a '" 100 MeV and the proton fraction range Yp = a '" 0.56 to be used for supernova simulations.