Socratic questioning and chain-of-thought (CoT) prompting share foundational principles that make them naturally aligned for enhancing reasoning in LLMs. Both approaches break down complex problems into manageable steps, using iterative reasoning to refine understanding, address nuances, and uncover deeper insights. They emphasize critical thinking by challenging assumptions, clarifying ambiguities, and exploring alternative perspectives, while ensuring a structured, goal-oriented process. Furthermore, their ability to generalize effectively to new problems enables flexible and transferable problem-solving strategies. Together, these shared principles establish CoT prompting as a computational analogy to Socratic questioning, particularly in tasks requiring analytical depth, such as chemistry discovery. Their reliance on iterative, reflective reasoning underscores their synergy, positioning both approaches as powerful strategies for advancing scientific inquiry through LLM prompting. The follow-up prompts in Table exemplify how Socratic questioning can be extended through CoT prompting to systematically address each of the ten Socratic principles. These prompts are not standalone questions; rather, they function as iterative steps that guide both the language model and the user through deeper exploration, refinement, and synthesis of ideas. Each set of follow-up prompts corresponds to a specific principle, offering tailored approaches to ensure the inquiry remains focused while fostering critical thinking.