Nankai University

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

Solution-Processed Organic Solar Cells Based on Dialkylthiol-Substituted Benzodithiophene Unit with Efficiency near 10%

Abstract: A small molecule named DR3TSBDT with dialkylthiol-substituted benzo[1,2-b:4,5-b′]dithiophene (BDT) as the central unit was designed and synthesized for solution-processed bulk-heterojunction solar cells. A notable power conversion efficiency of 9.95% (certified 9.938%) has been achieved under AM 1.5G irradiation (100 mW cm–2), with an average PCE of 9.60% based on 50 devices.

Self‐Supported Cobalt Phosphide Mesoporous Nanorod Arrays: A Flexible and Bifunctional Electrode for Highly Active Electrocatalytic Water Reduction and Oxidation

Abstract: Water splitting for the production of hydrogen and oxygen is an appealing solution to advance many sustainable and renewable energy conversion and storage systems, while the key fact depends on the innovative exploration regarding the design of efficient electrocatalysts. Reported herein is the growth of CoP mesoporous nanorod arrays on conductive Ni foam through an electrodeposition strategy. The resulting material of well-defined mesoporosity and a high specific surface area (148 m2 g−1) can be directly employed as a bifunctional and flexible working electrode for both hydrogen and oxygen evolution reactions, showing superior activities as compared with noble metal benchmarks and state-of-the-art transition-metal-based catalysts. This is intimately related to the unique nanorod array electrode configuration, leading to excellent electric interconnection and improved mass transport. A further step is taken toward an alkaline electrolyzer that can achieve a current density of 10 mA cm−2 at a voltage around 1.62 V over a long-term operation, better than the combination of Pt and IrO2. This development is suggested to be readily extended to obtain other electrocatalysis systems for scale-up water-splitting technology.

Sub-10 nm rutile titanium dioxide nanoparticles for efficient visible-light-driven photocatalytic hydrogen production

Abstract: Titanium dioxide is a promising photocatalyst for water splitting, but it suffers from low visible light activity due to its wide band gap Doping can narrow the band gap of titanium dioxide; however, new charge-carrier recombination centres may be introduced Here we report the design of sub-10 nm rutile titanium dioxide nanoparticles, with an increased amount of surface/sub-surface defects to overcome the negative effects from bulk defects Abundant defects can not only shift the top of the valence band of rutile titanium dioxide upwards for band-gap narrowing but also promote charge-carrier separation The role of titanium(III) is to enhance, rather than initiate, the visible-light-driven water splitting The sub-10 nm rutile nanoparticles exhibit the state-of-the-art activity among titanium dioxide-based semiconductors for visible-light-driven water splitting and the concept of ultra-small nanoparticles with abundant defects may be extended to the design of other robust semiconductor photocatalysts

Recent advances in MXene: Preparation, properties, and applications

Abstract: Owing to the exceptional properties of graphene, intensive studies have been carried out on novel two-dimensional (2D) materials. In the past several years, an elegant exfoliation approach has been used to successfully create a new family of 2D transition metal carbides, nitrides, and carbonitrides, termed MXene, from layered MAX phases. More recently, some unique properties of MXene have been discovered leading to proposals of potential applications. In this review, we summarize the latest progress in development of MXene from both a theoretical and experimental view, with emphasis on the possible applications.

Adapting ranking SVM to document retrieval

Abstract: The paper is concerned with applying learning to rank to document retrieval. Ranking SVM is a typical method of learning to rank. We point out that there are two factors one must consider when applying Ranking SVM, in general a "learning to rank" method, to document retrieval. First, correctly ranking documents on the top of the result list is crucial for an Information Retrieval system. One must conduct training in a way that such ranked results are accurate. Second, the number of relevant documents can vary from query to query. One must avoid training a model biased toward queries with a large number of relevant documents. Previously, when existing methods that include Ranking SVM were applied to document retrieval, none of the two factors was taken into consideration. We show it is possible to make modifications in conventional Ranking SVM, so it can be better used for document retrieval. Specifically, we modify the "Hinge Loss" function in Ranking SVM to deal with the problems described above. We employ two methods to conduct optimization on the loss function: gradient descent and quadratic programming. Experimental results show that our method, referred to as Ranking SVM for IR, can outperform the conventional Ranking SVM and other existing methods for document retrieval on two datasets.