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Institution

Nanjing Tech University

EducationNanjing, China
About: Nanjing Tech University is a education organization based out in Nanjing, China. It is known for research contribution in the topics: Catalysis & Membrane. The organization has 21827 authors who have published 21794 publications receiving 364050 citations. The organization is also known as: Nangongda & Nánjīng Gōngyè Dàxúe.


Papers
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Journal ArticleDOI
TL;DR: The cheap carbon and nitrogen sources, as well as the mixed alkaline neutralize could be efficiently used instead of expensive composition for industrial succinic acid production.

94 citations

Journal ArticleDOI
TL;DR: A highly bright fluorophore with long‐wavelength absorption and aggregation‐induced near‐infrared (NIR) emission is designed for intravital two‐photon fluorescence (2PF) imaging of a mouse brain and tumor vasculatures under NIR‐II light (1200 nm) excitation.
Abstract: Intravital fluorescence imaging of vasculature morphology and dynamics in the brain and in tumors with large penetration depth and high signal-to-background ratio (SBR) is highly desirable for the study and theranostics of vascular-related diseases and cancers. Herein, a highly bright fluorophore (BTPETQ) with long-wavelength absorption and aggregation-induced near-infrared (NIR) emission (maximum at ≈700 nm) is designed for intravital two-photon fluorescence (2PF) imaging of a mouse brain and tumor vasculatures under NIR-II light (1200 nm) excitation. BTPETQ dots fabricated via nanoprecipitation show uniform size of around 42 nm and a high quantum yield of 19 ± 1% in aqueous media. The 2PF imaging of the mouse brain vasculatures labeled by BTPETQ dots reveals a 3D blood vessel network with an ultradeep depth of 924 µm. In addition, BTPETQ dots show enhanced 2PF in tumor vasculatures due to their unique leaky structures, which facilitates the differentiation of normal blood vessels from tumor vessels with high SBR in deep tumor tissues. Moreover, the extravasation and accumulation of BTPETQ dots in deep tumor (more than 900 µm) is visualized under NIR-II excitation. This study highlights the importance of developing NIR-II light excitable efficient NIR fluorophores for in vivo deep tissue and high contrast tumor imaging.

94 citations

Journal ArticleDOI
TL;DR: In this article, an atomic layer deposition (ALD) technique is used to decorate pore walls of polymeric porous membranes by coating the membrane surface and pore wall with a uniform and conformal layer of aluminum oxide.

94 citations

Journal ArticleDOI
Xiaojiang Liu1, Yang Xu1, Keyang Ben1, Zao Chen1, Yan Wang1, Zisheng Guan1 
TL;DR: In this paper, a simple modification-free process for the preparation of transparent super-hydrophobic surfaces by calcining candle-soot-coated polydimethylsiloxane (PDMS) films was reported.

94 citations

Journal ArticleDOI
TL;DR: Air-stable and convenient amidobenziodoxolones as an amidating reagent were disclosed to enable direct amidation on a wide range of C(sp2)–H bonds of (hetero)arenes and alkenes, as well as unactivated C( sp3)-H bonds under RhIII catalysis.
Abstract: Air-stable and convenient amidobenziodoxolones as an amidating reagent were disclosed to enable direct amidation on a wide range of C(sp2)–H bonds of (hetero)arenes and alkenes, as well as unactivated C(sp3)–H bonds under RhIII catalysis. The approach to access 49 examples of structurally diverse amides is featured by mild conditions, complete chemoselectivity and regioselectivity, broad substrate scope (not limited to strongly heterocyclic coordinating groups), and tolerance of valuable functional substituents, such as unprotected amine and hydroxyl groups. The synthetic applicability of this protocol is also demonstrated by late-stage functionalization of biologically important scaffolds.

94 citations


Authors

Showing all 22047 results

NameH-indexPapersCitations
Yi Chen2174342293080
Richard H. Friend1691182140032
Hua Zhang1631503116769
Wei Huang139241793522
Jian Zhou128300791402
Haiyan Wang119167486091
Jian Liu117209073156
Lain-Jong Li11362758035
Hong Wang110163351811
Jun-Jie Zhu10375441655
Stefan Kaskel10170536201
Hong Liu100190557561
Dirk De Vos9664233214
Peng Li95154845198
Feng Liu95106738478
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023125
2022502
20212,924
20202,572
20192,340
20181,967