Team Leader
Nhu Vu
Texas A&M University
Biomedical Engineering
nvu1@tamu.edu
Project Type
Research
Who Can Join
Undergraduate Students
Project Description
Nanoparticles possess unique optical and chemical properties, making them highly valuable in various fields such as biomedical biosensing. However, traditional synthesis methods often face issues with reproducibility and scalability, limiting their broader application. Continuous synthesis provides a more controlled and reproducible alternative, enabling better control over particle size and shape, which is essential for tailoring nanoparticles to specific needs.
This research focuses on developing and optimizing the continuous synthesis of nanoparticles. The goal is to improve the precision and reproducibility of particle production, ensuring consistent control over size and morphology. In addition, a comprehensive dataset will be generated from the synthesis parameters and outcomes. This dataset will be used to support future machine learning applications in nanoparticle synthesis, enabling predictive modeling for improved nanoparticle design.
By optimizing continuous synthesis methods and building a data foundation for machine learning, this project aims to contribute to scalable, reproducible production of nanoparticles with application-specific properties, supporting their use in diverse technological and biomedical areas.
Team Needs
Knowledge in chemistry and data science
Must commit to at least 5 hours of lab work per week
Special Opportunities
Opportunities include co-authoring publications, presenting research at conferences, and gaining experience in a professional lab setting.