This research introduces a novel multi-LLM framework that tackles the challenge of information overload in scientific research by leveraging the complementary strengths of multiple large language models.

• Combines various LLMs to overcome the limitations of single-model approaches
• Enables more effective literature reviews and research planning across domains
• Demonstrates practical application through a case study on dropwise condensation enhancement
• Addresses a critical need for scalable AI research assistance in engineering disciplines

For engineering organizations, this framework offers a pathway to accelerate R&D processes, stay current with rapidly expanding literature, and generate innovative solutions to complex technical challenges.

Accelerating Scientific Research Through a Multi-LLM Framework