Y
Yu Mo
Researcher at University of Maryland, College Park
Publications - 21
Citations - 661
Yu Mo is an academic researcher from University of Maryland, College Park. The author has contributed to research in topics: Marsh & Environmental science. The author has an hindex of 10, co-authored 17 publications receiving 502 citations. Previous affiliations of Yu Mo include Sun Yat-sen University & Nanyang Technological University.
Papers
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Start a research on biopolymer polyhydroxyalkanoate (PHA) : a review
Giin-Yu Amy Tan,Chia-Lung Chen,Ling Li,Liya Ge,Lin Wang,Indah Mutiara Ningtyas Razaad,Yanhong Li,Lei Zhao,Yu Mo,Jing-Yuan Wang +9 more
TL;DR: This review aims to facilitate the start-up of PHA research by providing a summary of commercially available PHA-accumulating microbial cultures, PHA biosynthetic pathways, and methods for PHA detection, extraction and analysis.
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Enhanced styrene recovery from waste polystyrene pyrolysis using response surface methodology coupled with Box-Behnken design.
TL;DR: RSM-BBD is an effective approach for yield optimization of styrene recovery from WPS pyrolysis and was 12% more than the highest reported yield for reactors of similar size.
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Enhanced gas chromatography-mass spectrometry method for bacterial polyhydroxyalkanoates analysis
Giin-Yu Amy Tan,Chia-Lung Chen,Liya Ge,Ling Li,Lin Wang,Lei Zhao,Yu Mo,Swee Ngin Tan,Jing-Yuan Wang +8 more
TL;DR: A gas chromatography-mass spectrometry method for quantification of polyhydroxyalkanoates (PHAs), containing 4-carbon to 16-carbon monomers, was developed in this article.
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Comparative pyrolysis upcycling of polystyrene waste: thermodynamics, kinetics, and product evolution profile
TL;DR: In this article, a comparative pyrolysis study of virgin polystyrene (VPS) and two types of commonly used poly styrene products (EPS) was carried out, suggesting distinct thermal degradation characteristics of these materials.
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Quantifying moderate resolution remote sensing phenology of Louisiana coastal marshes
TL;DR: In this paper, the landscape-level phenologies of the coastal marshes under different climatic conditions, using Landsat-derived Normalized Difference Vegetation Index (NDVI) records (30 × 30 m 2 spatial resolution) and a nonlinear mixed model, were studied.