Fengqing Chen | Polymer Composites | Best Researcher Award
Dr. Fengqing Chen at Zhejiang A&F University | China
Dr. Fengqing Chen is a Lecturer at the School of Chemistry and Materials Engineering, Zhejiang A&F University, specializing in polymer composites, flame retardancy, and data-driven materials design. He earned his Ph.D. in Materials Chemistry from Shanghai University, where he developed expertise in designing advanced polymer nanocomposites and sustainable materials. His research integrates traditional materials science with modern computational and machine learning approaches, leading to impactful publications in prestigious journals including ACS Applied Materials & Interfaces, Composites Science and Technology, and Computational Materials Science. Dedicated and innovative, Dr. Chen actively contributes to advancing sustainable and high-performance materials engineering.
Professional Profile
SCOPUS
Education
Dr. Fengqing Chen obtained his Ph.D. in Materials Chemistry from Shanghai University, focusing on the structural design and optimization of flame-retardant polymer nanocomposites through experimental and computational approaches.
Experience
Dr. Chen currently serves as a Lecturer in the School of Chemistry and Materials Engineering at Zhejiang A&F University. He is actively involved in teaching and mentoring students while continuing his research on polymer composites, nanomaterials, and machine learning-driven material innovation.
Professional Development
Dr. Fengqing Chen has consistently pursued professional growth through active research, collaborations, and academic publications. He has contributed significantly to the fields of flame-retardant polymer composites, nanostructured materials, and sustainable solutions. His interdisciplinary research approach bridges experimental techniques with computational optimization frameworks. Alongside his research, Dr. Chen is committed to mentoring students and fostering innovation within his department. His work exemplifies a balance between theoretical understanding and practical application, supporting the advancement of next-generation materials that address industrial challenges while aligning with environmental and safety standards.
Research Interests
Dr. Chen’s research is centered on the design and optimization of flame-retardant polymer composites and sustainable nanomaterials. He combines experimental polymer science with computational and machine learning techniques to accelerate material discovery and enhance performance. His studies explore structure–property relationships in polymer nanocomposites, applying green chemistry and eco-friendly design strategies to achieve improvements in flame retardancy, mechanical strength, and thermal properties. With a strong emphasis on sustainability and innovation, Dr. Chen’s work contributes to the development of multifunctional composites that address industrial demands while reducing environmental impact, advancing the future of materials engineering.
Awards and Recognitions
Although specific awards are not listed, Dr. Fengqing Chen’s recognition is reflected through his impactful research contributions published in leading international journals. His pioneering work in combining materials chemistry with machine learning frameworks has established him as a promising early-career researcher in polymer composites and sustainable materials. His innovative methodologies, growing influence, and recognition within the scientific community highlight his role as an emerging scholar dedicated to advancing flame-retardant materials, eco-friendly solutions, and data-driven material innovation.
Top Noted Publications
Title: Miscanthus fforidulus-based intumescent flame retardant by green self-assembly for fully biological EP composites with commendable flame retardancy, smoke suppression and mechanical properties
Year: 2024
Title: One-pot solvent-free green strategy to fabricate ultra-efficient polyphosphoester flame retardant for Poly(Lactic acid)
Year: 2024
Title: An adaptive framework to accelerate optimization of high flame retardant composites using machine learning
Year: 2022
Title: Simple large-scale method of recycled graphene films vertical arrangement for superhigh through-plane thermal conductivity of epoxy composites
Year: 2021
Title: Machine Learning and Structural Design to Optimize the Flame Retardancy of Polymer Nanocomposites with Graphene Oxide Hydrogen Bonded Zinc Hydroxystannate
Year: 202
Title: Accelerated feasible screening of flame-retardant polymeric composites using data-driven multi-objective optimization
Year: 2023
Conclusion
Dr. Fengqing Chen is an emerging scholar whose research bridges advanced materials chemistry, polymer science, and machine learning-based design. With strong expertise in flame-retardant composites, sustainable nanomaterials, and structure–property optimization, he is contributing to both scientific knowledge and practical innovation. His commitment to sustainability, interdisciplinary collaboration, and academic mentorship underscores his role as a forward-thinking researcher. Through impactful publications and growing recognition, Dr. Chen continues to shape the future of materials engineering, positioning himself as a promising leader in developing high-performance and eco-friendly solutions for global challenges.








She has developed cutting-edge methods like intelligent safety analysis of formwork, evacuation route planning in dynamic environments, and parameter identification systems using computer vision.
Her leadership extends beyond academia to industry collaborations, where she has championed high-impact projects improving construction safety and efficiency. Through her work, she bridges the gap between research, education, and real-world applications. 

and digital transformation of the building industry. Her innovations include safety monitoring using AI, dynamic evacuation planning for construction sites, and defect detection with computer vision. 
Second Prize – China Technology Market Golden Bridge Award, 2024
Engineering Construction Science and Technology Award, 2024
Innovation Award – China Urban Rail Transit Science and Technology Innovation Competition, 2022
Classification and Application of Deep Learning in Construction Engineering and Management – A Systematic Literature Review and Future Innovations (2024)
Study on the Influence of the Fully Enclosed Barrier on the Vortex-Induced Vibration Performance of a Long-Span Highway–Railway Double-Deck Truss Bridge (2024)
Research on Intelligent Prefabricated Reinforced Concrete Staircase Lifting Point Setting Method Considering Multidimensional Spatial Constraint Characteristics (2024)
Study on the Influence of Wind Fairing Parameters on the Aerodynamic Performance of Long-Span Double-Deck Steel Truss Suspension Bridge (2024)
Multiobject Real-Time Automatic Detection Method for Production Quality Control of Prefabricated Laminated Slabs (2024)
Conception Design of a Novel Vibration Damping Mechanism for Vibration Reduction of a High-Rise Wind Tower (2023)
Study on the Suppression Effect on Vortex-Induced Vibration of Double-Deck Truss Girder by the Spatial Position of the Deflector Plate (2023)