Design Solid-State Liquid-Like Conductors
Inspired by the recent discovery of organic molecules that maintain liquid-like ion conductivity within a solid lattice, this challenge task you with building a sophisticated discovery pipeline. You will utilize DeepSeek-R1, a reasoning-focused LLM, to hypothesize structural motifs that enable high cation mobility in crystalline states. By leveraging DSPy for programmatic prompt optimization, you will refine the model's ability to extract specific molecular descriptors from chemical literature stored in a ChromaDB vector database. The goal is to automate the identification of candidate electrolytes that bridge the gap between high-safety solid-state batteries and high-performance liquid systems. You will implement a Retrieval-Augmented Generation (RAG) system that doesn't just find text, but reason over chemical constraints such as lattice energy, packing density, and ionic radius to suggest novel derivatives of the discovered molecules.
AI Research & Mentorship
What you are building
The core problem, expected build, and operating context for this challenge.
Inspired by the recent discovery of organic molecules that maintain liquid-like ion conductivity within a solid lattice, this challenge task you with building a sophisticated discovery pipeline. You will utilize DeepSeek-R1, a reasoning-focused LLM, to hypothesize structural motifs that enable high cation mobility in crystalline states. By leveraging DSPy for programmatic prompt optimization, you will refine the model's ability to extract specific molecular descriptors from chemical literature stored in a ChromaDB vector database. The goal is to automate the identification of candidate electrolytes that bridge the gap between high-safety solid-state batteries and high-performance liquid systems. You will implement a Retrieval-Augmented Generation (RAG) system that doesn't just find text, but reason over chemical constraints such as lattice energy, packing density, and ionic radius to suggest novel derivatives of the discovered molecules.
Shared data for this challenge
Review public datasets and any private uploads tied to your build.
What you should walk away with
Master the implementation of DSPy Assertions to enforce chemical constraints during LLM generation
Implement DeepSeek-R1 reasoning loops to analyze the tradeoff between solid-state stability and ion mobility
Design a semantic search strategy in ChromaDB tailored for SMILES strings and chemical nomenclature
Orchestrate a multi-stage pipeline where DSPy optimizes a 'Signature' for molecular property extraction
Deploy a validation layer that compares LLM-suggested candidates against existing databases of solid electrolytes
Optimize token usage in reasoning-heavy models by summarizing dense chemical research papers before final synthesis
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