Chemical synthesis is inherently a complex, time-sensitive endeavor that involves not just selecting a starting substrate but also precisely configuring reaction conditions, equipment, and procedural steps. To address these challenges, we introduce DeepSyn, an advanced chemical notation transformation system that integrates the DeepSeek R1 model with reactive generation (RAG) techniques. DeepSyn is meticulously engineered to process critical experimental details and dynamically leverage a comprehensive knowledge database. This system is designed to formulate executable experimental protocols, meticulously outlining each step, pathway, and condition tailored to specific hardware requirements and enhancing reproducibility and precision. Our evaluations demonstrate that DeepSyn consistently delivers precise experimental design recommendations across a variety of conditions, which is substantiated by its integration with lab automation tools. This validation underscores DeepSyn's significant potential in advancing new material discovery, presenting a robust platform for methodical, machine-oriented experimental design.