Dr Guohang Tang | Sustainability in Material Science | Best Researcher Award

Dr Guohang Tang | Sustainability in Material Science | Best Researcher Award

Dr. Guohang Tang is a doctoral researcher at Tongji University, specializing in geotechnical engineering and environmental sustainability πŸ—οΈ. His research focuses on COβ‚‚ geological sequestration and the adsorption behavior of clay minerals, particularly illite ⛏️. His work provides critical insights into how moisture content and temperature influence COβ‚‚ storage efficiency, contributing to climate change mitigation 🌱. He has published in SCI-indexed journals, such as Applied Clay Science and Measurement πŸ“š. With expertise in carbon capture and storage (CCS) technologies, his research is paving the way for sustainable environmental engineering solutions πŸ†.

Dr Guohang Tang, Tongji University, China

Profile

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Academic and Professional BackgroundπŸŽ“πŸŒ

Dr. Guohang Tang is a doctoral researcher at Tongji University, specializing in geotechnical engineering and environmental sustainability πŸ—οΈ. His research focuses on COβ‚‚ geological sequestration and the adsorption behavior of clay minerals, particularly illite ⛏️. His studies provide critical insights into COβ‚‚ interactions with geological materials, helping to improve carbon capture and storage (CCS) strategies 🌱. With extensive experience in environmental geotechnics, his work aims to enhance the efficiency of COβ‚‚ sequestration under different moisture and temperature conditions πŸ”¬. His contributions to sustainable engineering solutions are vital for addressing climate change challenges πŸ†βœ¨.

Research and Innovations🌱

Dr. Guohang Tang’s research focuses on COβ‚‚ geological sequestration, clay mineralogy, and adsorption mechanisms πŸ—οΈ. He is currently working on a project analyzing COβ‚‚ interactions with clay minerals, particularly illite ⛏️. His studies explore moisture content and temperature effects on COβ‚‚ sequestration efficiency, aiding in the optimization of geological storage strategies 🌱. He has published in SCI-indexed journals such as Applied Clay Science and Measurement πŸ“š. With a citation index of 10.5, his research significantly contributes to sustainable carbon capture solutions, addressing global climate change challenges πŸ†βœ¨.

Research FocusπŸ”¬

Dr. Guohang Tang’s research primarily focuses on COβ‚‚ geological sequestration, soil mechanics, and environmental geotechnics πŸ—οΈ. His work explores adsorption mechanisms in clay minerals, particularly illite, and how moisture content and temperature affect COβ‚‚ storage efficiency ⛏️. He also investigates soil freezing phase transitions, moisture migration, and soil suction measurement using polymer optical fiber (POF) sensors 🌱. His studies on soft soil composite foundations and geotechnical stability contribute to sustainable infrastructure and environmental protection 🏭. Through advanced experimental techniques and numerical simulations, his research enhances carbon capture, soil mechanics, and ground engineering strategies πŸ†βœ¨.

PublicationsπŸ“š

1️⃣ Real-time determination of soil suction in unsaturated clay based on POF sensor
πŸ–ŠοΈ Authors: Tang, G., Ma, X., Zhang, H., Liu, Z., He, Y.
πŸ“– Journal: Measurement: Journal of the International Measurement Confederation (2025)

2️⃣ Visualization of soil freezing phase transition and moisture migration using polymer optical fibers
πŸ–ŠοΈ Authors: Zhang, H., Zhang, H., Liu, Z., Tang, G., Ma, X.
πŸ“– Journal: Measurement: Journal of the International Measurement Confederation (2024)

3️⃣ Load-bearing response of deep content mixing soft soil composite foundation based on the geotechnical centrifugal model test
πŸ–ŠοΈ Authors: Lin, Y., Tang, G., Ma, X., Ma, C.Y., Wang, Z.
πŸ“– Journal: IOP Conference Series: Earth and Environmental Science (2024)

4️⃣ Numerical analysis of failure mechanism and stability of reinforced embankment with DCM soft soil composite foundation
πŸ–ŠοΈ Authors: Ma, X.F., Ma, C.Y., Lin, Y.G., Tang, G.H., Wang, Z.H.
πŸ“– Journal: IOP Conference Series: Earth and Environmental Science (2024)

5️⃣ Experimental study on influence of filter mesh size on radial permeability of sand
πŸ–ŠοΈ Authors: Tang, G., Wang, N., Liu, S., Jie, Y.
πŸ“– Journal: Journal of Beijing University of Aeronautics and Astronautics (2023)

6️⃣ One-dimensional pot cover effect for migration of gaseous water based on PDV model
πŸ–ŠοΈ Authors: Tang, G.-H., Wang, N.-D., Yao, Y.-P.
πŸ“– Journal: Chinese Journal of Geotechnical Engineering (2022)

These publications reflect Dr. Tang’s expertise in soil mechanics, COβ‚‚ sequestration, and geotechnical engineering πŸŒπŸ—οΈβœ¨.

Mr Sicheng Wang | Smart Materials | Best Researcher Award

Mr Sicheng Wang | Smart Materials | Best Researcher Award

Mr Sicheng Wang, Beijing University of Posts and Telecommunications, China

Mr. Sicheng Wang, a graduate in Information and Computing Science from Beijing University of Posts and Telecommunications, excels in applying artificial intelligence and machine learning to energy systems. He has authored three notable papers, including one published in the SCI-indexed journal Computers and Electrical Engineering, focusing on spatio-temporal PV prediction. Recognized with multiple national awards, such as the Second Prize in Mathematical Modeling and the Bronze Award in Innovation Competitions, Mr. Wang showcases exceptional research and problem-solving skills. His work in energy management and smart grids highlights his vision for sustainable technology solutions. πŸ†βš‘πŸ“š

Publication Profile

ORCID

Academic Excellence πŸŽ“πŸ“Š

Mr. Sicheng Wang holds a degree in Information and Computing Science from Beijing University of Posts and Telecommunications, demonstrating a solid foundation in computational methods and data-driven research. His academic journey is distinguished by multiple prestigious awards, including the Second Prize in the National Undergraduate Mathematical Modeling Contest and the Bronze Award in the China International College Students’ Innovation Competition. These achievements reflect his exceptional analytical thinking, problem-solving abilities, and commitment to academic excellence. His dedication to applying advanced computational techniques makes him a standout in his field. πŸ…πŸ”¬βœ¨

Awards and Competitions πŸ†πŸ“š

Mr. Sicheng Wang has earned multiple prestigious awards in national and provincial competitions, highlighting his excellence in innovation and problem-solving. In September 2023, he secured the Second Prize in the National Undergraduate Mathematical Modeling Contest. He later achieved the Bronze Award in the China International College Students’ Innovation Competition in September 2024. Additionally, he won the Third Prize in the National Undergraduate Computer Design Contest (June 2024) and the First Prize in the Beijing Division of the Innovation Competition (July 2024). His accolades also include a Second Prize in the National Undergraduate Mathematics Contest (October 2023). πŸ…πŸ”’βœ¨

Academic Engagement πŸŽ“πŸ’Ό

He has been actively engaged in advanced studies and research in Information and Computing Science, focusing on innovative applications of artificial intelligence and machine learning. His academic involvement includes participation in high-impact research projects and national competitions, showcasing his dedication to both theoretical and practical advancements in technology. His ongoing commitment to research and learning reflects his drive for excellence in the field of computing. πŸ§ πŸ”¬πŸ“Š

Research Focusβš‘πŸ”¬

Mr. Sicheng Wang’s research focuses on the application of artificial intelligence and machine learning in energy systems and smart grids. He has authored several high-impact papers, including a study on spatio-temporal PV prediction using a convolutional-based hybrid network, published in Computers and Electrical Engineering (SCI Q3, IF 4.0). His other notable works include an AI diagnostic model presented at AUTEEE 2023 and a multi-task learning framework for medium-term load forecasting accepted at APPEEC 2024. His research addresses critical challenges in energy prediction and management, contributing to sustainable technological advancements. πŸ§ πŸ“Šβš‘