Runtime-Slayers/ai-microfluidic-plasma-separator: AI-Driven Microfluidic Plasma Separator & Deep Learning Surrogate Optimizer
An advanced, end-to-end framework for designing, simulating, and optimizing microfluidic blood plasma separators. By leveraging Deep Learning surrogate modeling, this platform replaces slow, computationally intensive Computational Fluid Dynamics (CFD) solvers with sub-millisecond neural network predictions. This enables real-time parametric optimization via an interactive 3D/2D design dashboard powered by React and Gemini AI.
Resource information
- Format
- zip
- Original repository
- 20838948
- DOI
- 10.5281/zenodo.20838948
- Credit basis
- Creators in Zenodo record metadata
- Access
- Open files available from the original Zenodo deposit
- Last checked
- Nov 5, 2026
- License
- mit-license
- Last record update
- Nov 5, 2026
About this resource
An advanced, end-to-end framework for designing, simulating, and optimizing microfluidic blood plasma separators. By leveraging Deep Learning surrogate modeling, this platform replaces slow, computationally intensive Computational Fluid Dynamics (CFD) solvers with sub-millisecond neural network predictions. This enables real-time parametric optimization via an interactive 3D/2D design dashboard powered by React and Gemini AI.