Beyond chemistry, Socratic prompting holds immense promise for transforming LLM utilization across scientific disciplines. Understanding the underlying structure of prompts-including their types, sequential interactions, and strategic flow-remains an open question, inviting further research into how Socratic reasoning can shape LLM-driven inquiry. By extending this framework to new domains and exploring automated generation of Socratic prompts, we envision a future where LLMs, guided by structured Socratic reasoning, drive innovation and discovery at an unprecedented scale. While this study establishes a structured approach to Socratic prompting, future work could further refine and justify these methods, ensuring a more philosophically grounded and systematic approach to prompt engineering. This work sets the stage for a paradigm shift in AI-assisted research, offering a pathway for integrating human-like critical inquiry into the capabilities of advanced language models to tackle the most complex scientific challenges.