Mingming Wang

Mr. Mingming Wang


Research Focus & Metrics

Academic Career Length

9Years (2018-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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27 April 2018 in Sustainability
Verified
Journal Article
Open access
PDF file
ZBZhongqiang Bai
Zhongqiang Bai
JWJuanle Wang
Juanle Wang
MWMingming Wang
Mingming Wang
MGMengxu Gao
Mengxu Gao
JSJiulin Sun
Jiulin Sun
Population is one of the core elements of sustainable development. Quantifying the estimation accuracy of population spatial distribution has been recognized as a critical and challenging task. This study aims to evaluate the data accuracy of four population datasets in China, including three global gridded population datasets, the Gridded Population of the World (GPW), Global Rural and Urban Mapping Project (GRUMP), and WorldPop project (WorldPop), and a Chinese regional gridded population dataset, the China 1 km Gridded Population (CnPop) dataset. These datasets are assessed using a specific method based on a GIS-linked 2000 census dataset at the township level in China. The results indicate that WorldPop had the highest estimation accuracy, estimating about 60% of the total population. CnPop accurately estimated about half of the total population, showing a good mapping performance. The GPW had an acceptable estimation accuracy in a few plain and basin areas, accounting for about 30% of the total population. Compared to the GPW, GRUMP accurately estimated about 40% of the total population. The relative estimation error analysis discovered the disadvantages of the generation strategies of these datasets. The conclusions are expected to serve as a quality reference for potential dataset users and producers, and promote accuracy assessment for population datasets in other regions and globally.

11 April 2022 in Coatings
Verified
Journal Article
Open access
PDF file
YLYoufu Lu
Youfu Lu
NSNan Shi
Nan Shi
MWMingming Wang
Mingming Wang
XWXinyang Wang
Xinyang Wang
LYLiyang Yin
Liyang Yin
PZPinhui Zhao
Pinhui Zhao
This study aims to prepare a graphene quantum dots (GQDs)/styrene-butadiene segmented copolymer composite (GQDs/SBS) as an asphalt modifier using the Pickering emulsion polymerization method. The physicochemical properties of the GQDs/SBS modifier and their effects on asphalt modification were investigated. In addition, the GQDs/SBS modifier was compared with the pure SBS modifier. Research results demonstrated that GQDs could be evenly dispersed into the SBS phase to form a uniform composite. Adding GQDs brings more oxygen-containing functional groups into the GQDs/SBS modifier, thus strengthening the polarity and making it disperse into the asphalt better. Compared with the SBS modifier, the GQDs/SBS modifier presents better thermostability. Moreover, GQDs/SBS composite-modified asphalt achieves better high-temperature performance than SBS-modified asphalt, which is manifested by the increased softening points, complex shear modulus and rutting factors. However, the low-temperature performance decreases, which is manifested by reductions in cone penetration, viscosity and ductility as well as the increased ratio between creep stiffness (S) and creep rate (m), that is, S/m. Furthermore, adding GQDs can improve the high-temperature performance of asphalt mixture, but it influences low-temperature and water stability slightly. GQDs/SBS also have the advantages of simple preparation techniques, low cost and are environmentally friendly. Therefore, they have become a beneficial choice as asphalt cementing material modifiers.