S
Siming You
Researcher at University of Glasgow
Publications - 75
Citations - 3155
Siming You is an academic researcher from University of Glasgow. The author has contributed to research in topics: Biochar & Catalysis. The author has an hindex of 21, co-authored 75 publications receiving 1373 citations. Previous affiliations of Siming You include Massachusetts Institute of Technology & Nanyang Technological University.
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Journal ArticleDOI
Lignin valorization by bacterial genus Pseudomonas: State-of-the-art review and prospects.
Manish Kumar,Siming You,Jingzi Beiyuan,Gang Luo,Juhi Gupta,Sunil Kumar,Lal Singh,Shicheng Zhang,Daniel C.W. Tsang +8 more
TL;DR: The potential of genus Pseudomonas in lignin valorization is critically reviewed along with the advanced genetic techniques and tools to ease the use of lign in/lignin-model compounds for the synthesis of bioproducts.
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Towards practical application of gasification: a critical review from syngas and biochar perspectives
TL;DR: In this article, the selection of gasifiers (fixed bed, fluidized bed, and entrained flow) is highly dependent on scale requirement (e.g., volume of feedstock and energy demand), feedstock characteristics, and the quality of syngas and biochar.
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Techno-economic and greenhouse gas savings assessment of decentralized biomass gasification for electrifying the rural areas of Indonesia
TL;DR: In this article, the feasibility of decentralized gasification of oil palm biomass in Indonesia to relieve its over-dependence on fossil fuel-based power generation and facilitate the electrification of its rural areas was explored.
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Model-based downdraft biomass gasifier operation and design for synthetic gas production
TL;DR: In this paper, a 3D multiphase flow model was applied to investigate the spatial distributions of various parameters (i.e. pressure, gas velocity, temperature, and gas composition) inside the gasifier that are critical to the design of gasifier.
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Optimal design of negative emission hybrid renewable energy systems with biochar production
TL;DR: In this paper, a negative emission hybrid renewable energy system is proposed for the first time, where a stochastic multi-objective decision-support framework is proposed to identify optimal design of the energy mix and discuss the economic and environmental feasibilities.