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Yong Sun

Researcher at The University of Nottingham Ningbo China

Publications -  102
Citations -  3095

Yong Sun is an academic researcher from The University of Nottingham Ningbo China. The author has contributed to research in topics: Catalysis & Adsorption. The author has an hindex of 26, co-authored 88 publications receiving 2060 citations. Previous affiliations of Yong Sun include Edith Cowan University & Chinese Academy of Sciences.

Papers
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Journal Article

[Analysis of trace elements in corn stover by ICP-AES].

Yong Sun, +3 more
- 01 Feb 2007 - 
TL;DR: The contents of trace elements of Zn, Mg, Mn, Sr, Fe, Co, Ni and Se in the corn stover collected from Shanxi, Beijing, Xinjiang, Shandong, Neimeng, Gansu, Shaanxi, Jilin, Yunnan and Jiangsu, 10 different provinces in China, were determined by ICP-AES using nitrifying method of high pressure nitrify pot.
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Efficient naphthalene degradation in FeS2-activated nano calcium peroxide system: Performance and mechanisms.

Yulong Liu, +7 more
- 01 Mar 2022 - 
TL;DR: In this article , the effect of reagents dosage, pH, air conditions (with or without N2 purge), and different solution matrixes on Naphthalene degradation has been investigated.
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Insights into the role of nanoscale zero‐valent iron in Fenton oxidation and its application in naphthalene degradation from water and slurry systems

Ruming Yang, +9 more
- 23 Mar 2022 - 
TL;DR: In this paper , the role of zero-valent iron (nZVI) in Fenton-like process for polycyclic aromatic hydrocarbons (PAHs) removal was investigated.
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A critical review on microbial degradation of petroleum-based plastics: quantitatively effects of chemical addition in cultivation media on biodegradation efficiency

Yong Sun, +9 more
- 13 Jan 2022 - 
TL;DR: The binary effect (PO43-/Mg2+) is found to be the most statistically significant towards the microbial degradation of PBP and the optimal preparation conditions based upon the range of collected literature reports are recommended.
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Kinetic Study of Product Distribution Using Various Data-Driven and Statistical Models for Fischer-Tropsch Synthesis.

Yixiao Wang, +11 more
TL;DR: In this paper, a radial basis function neural network (RBFNN), a comprehensive kinetic with genetic algorithm (CKGA), and a response surface methodology (RSM) were used to study the kinetics of Fischer-Tropsch (FT) synthesis.