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Institution

Nankai University

EducationTianjin, China
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.


Papers
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Journal ArticleDOI
TL;DR: It is indicated that crop straw biochars exhibit distinct sorption capacities to heavy metals due to various surface characteristics, and thus the sorption efficiency should be carefully evaluated specific to target contaminant.

194 citations

Journal ArticleDOI
TL;DR: This review thoroughly summarized the state of the art of strategies used to incorporate biomolecules with metal-organic frameworks (MOFs), and emphasized on the remarkable advances of the applications of Biomolecules-MOFs composites, including the current challenges and potential directions in the future.

194 citations

Proceedings ArticleDOI
01 Oct 2019
TL;DR: This work proposes an online attention accumulation (OAA) strategy which maintains a cumulative attention map for each target category in each training image so that the integral object regions can be gradually promoted as the training goes.
Abstract: Object attention maps generated by image classifiers are usually used as priors for weakly-supervised segmentation approaches. However, normal image classifiers produce attention only at the most discriminative object parts, which limits the performance of weakly-supervised segmentation task. Therefore, how to effectively identify entire object regions in a weakly-supervised manner has always been a challenging and meaningful problem. We observe that the attention maps produced by a classification network continuously focus on different object parts during training. In order to accumulate the discovered different object parts, we propose an online attention accumulation (OAA) strategy which maintains a cumulative attention map for each target category in each training image so that the integral object regions can be gradually promoted as the training goes. These cumulative attention maps, in turn, serve as the pixel-level supervision, which can further assist the network in discovering more integral object regions. Our method (OAA) can be plugged into any classification network and progressively accumulate the discriminative regions into integral objects as the training process goes. Despite its simplicity, when applying the resulting attention maps to the weakly-supervised semantic segmentation task, our approach improves the existing state-of-the-art methods on the PASCAL VOC 2012 segmentation benchmark, achieving a mIoU score of 66.4% on the test set. Code is available at https://mmcheng.net/oaa/.

194 citations

Journal ArticleDOI
TL;DR: After functionalization by catalytic Au NPs, the hybrid sensor exhibited not only faster response and recovery speeds but also a higher response to benzene and toluene than the pristine ZnO sensor at 340 °C, especially showing high selectivity and long-term stability for low concentration toluenes.
Abstract: A novel sensing hybrid-material of Au nanoparticles (Au NPs)-functionalized ZnO nanowires (Au–ZnO NWs) was successfully synthesized by a two-stage solution process. First, ZnO NWs were fabricated via a low-temperature one-pot hydrothermal method with SDSN introduced as a structure-directing agent. Afterward, the as-prepared ZnO NWs were used as supports to load Au NPs with small sizes via precipitating HAuCl4 aqueous solution with ammonia. The obtained samples were characterized by means of XRD, SEM, TEM and EDX. Both pristine and Au–ZnO NWs were practically applied as gas sensors to compare the effect of Au NPs on the sensing performances and the obtained results demonstrated that after functionalization by catalytic Au NPs, the hybrid sensor exhibited not only faster response and recovery speeds but also a higher response to benzene and toluene than the pristine ZnO sensor at 340 °C, especially showing high selectivity and long-term stability for low concentration toluene, which is rarely reported with this method, indicating its original sensor application in detecting benzene and toluene. To interpret the enhanced gas sensing mechanism, the strong spillover effect of the Au NPs and the increased Schottky barriers caused by the electronic interaction between Au NPs and ZnO NW support are believed to contribute to the improved sensor performance.

194 citations

Journal ArticleDOI
TL;DR: A nonlinear photonic diode that breaks time-reversal symmetry is demonstrated to realize the unidirectional excitation of Kerr nonlinearity, which can be regarded as a significant demonstration of a graphdiyne-based prototypical application in non linear photonics and might suggest an important step toward versatile graphdiyah-based advanced passive photonics devices in the future.
Abstract: Graphdiyne is a new carbon allotrope comprising sp- and sp2 -hybridized carbon atoms arranged in a 2D layered structure. In this contribution, 2D graphdiyne is demonstrated to exhibit a strong light-matter interaction with high stability to achieve a broadband Kerr nonlinear optical response, which is useful for nonreciprocal light propagation in passive photonic diodes. Furthermore, advantage of the unique Kerr nonlinearity of 2D graphdiyne is taken and a nonreciprocal light propagation device is proposed based on the novel similarity comparison method. Graphdiyne has demonstrated a large nonlinear refractive index in the order of ≈10-5 cm2 W-1 , comparing favorably to that of graphene. Based on the strong Kerr nonlinearity of 2D graphdiyne, a nonlinear photonic diode that breaks time-reversal symmetry is demonstrated to realize the unidirectional excitation of Kerr nonlinearity, which can be regarded as a significant demonstration of a graphdiyne-based prototypical application in nonlinear photonics and might suggest an important step toward versatile graphdiyne-based advanced passive photonics devices in the future.

194 citations


Authors

Showing all 43397 results

NameH-indexPapersCitations
Yi Chen2174342293080
Peidong Yang183562144351
Jie Zhang1784857221720
Yang Yang1712644153049
Qiang Zhang1611137100950
Bin Liu138218187085
Jun Chen136185677368
Hui Li1352982105903
Jie Liu131153168891
Han Zhang13097058863
Jian Zhou128300791402
Chao Zhang127311984711
Wei Chen122194689460
Xuan Zhang119153065398
Yang Li117131963111
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023186
2022925
20215,270
20204,645
20194,261
20183,520