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.