About

Manman Wu is an emerging researcher whose work spans two innovative frontiers: automated environmental water analysis and advanced flexible sensing materials. Wu's most significant contributions lie in developing intelligent, high-throughput systems for detecting organic contaminants in water, addressing the growing challenge of emerging environmental pollutants. Their 2024 paper on automated pretreatment and machine learning-driven non-targeted screening of environmental water samples has already garnered 13 citations, reflecting its timely relevance in modernizing pollution monitoring workflows that traditionally demanded labor-intensive laboratory procedures. Complementing this, Wu has pioneered online sequential analytical platforms integrating robotic sample preparation with cutting-edge two-dimensional gas chromatography and time-of-flight mass spectrometry, enabling comprehensive simultaneous detection of volatile and semivolatile organic compounds. Wu also extends expertise into materials science, having developed a graphene oxide aerogel composite strain sensor featuring a novel interpenetrating dual-network structure capable of ultra-high, tunable sensitivity — a contribution with promising wearable technology applications. Collectively, Wu's research demonstrates a rare interdisciplinary breadth, combining environmental analytical chemistry, automation technology, and advanced functional materials, positioning them as a versatile and impactful voice in both environmental monitoring and sensor engineering communities.

Research Focus

Key Achievements

3
H-Index
4
Papers
23
Total Citations
6
Avg Citations/Paper
🏆 Most Cited Paper
Automated pretreatment of environmental water samples and non-targeted intelligent screening of organic compounds based on machine experiments
13 citations · 2024
📈 Most Prolific Year: 2024 (2 Papers)
🤝 Key Collaborators: 21
🏛 Institutions: South China University of Technology, Shandong University, State Key Laboratory of Luminescent Materials and Devices, Central Pollution Control Board

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago