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Late Breaking Results: "describing" Your Way to a Functional Microfluidic Chip
DescriptionMicrofluidic devices enable miniaturized, automated laboratory operations, but their design typically requires specialized expertise and labor-intensive CAD workflows. We present a language-driven framework that synthesizes manufacturable microfluidic designs directly from natural-language prompts. The framework introduces an LLM-based high-level synthesis paradigm, using domain-specific fine-tuned models to translate user intent into a structured JSON design specification for subsequent layout synthesis. An automated validation and correction pipeline detects and fixes geometric and physical inconsistencies to ensure design viability.