diff --git a/_projects/project-40-reation_multi-agents.md b/_projects/project-40-reaction_multi-agents.md similarity index 79% rename from _projects/project-40-reation_multi-agents.md rename to _projects/project-40-reaction_multi-agents.md index 579bff2..39a42e3 100644 --- a/_projects/project-40-reation_multi-agents.md +++ b/_projects/project-40-reaction_multi-agents.md @@ -3,21 +3,23 @@ number: 40 # leave as-is, maintainers will adjust title: Optimizing Chemical Reaction Conditions with Multi-Agent Systems Using Large Language Models and Bayesian Optimization topic: general team_leads: - - Bozhao Nan (University of Notre Dame) - - Taicheng Guo (University of Notre Dame) + - Bozhao Nan (University of Notre Dame) @bznan + - Taicheng Guo (University of Notre Dame) @taichengguo # Comment these lines by prepending the pound symbol (#) to each line to hide these elements contributors: - - Kehan Guo (University of Notre Dame) - - Yanqiao Zhu (UCLA) + - Kehan Guo (University of Notre Dame) @KehanGuo2 + - Yanqiao Zhu (UCLA) @SXKDZ -# github: AC-BO-Hackathon/project-reation_BO_agents -# youtube_video: +github: AC-BO-Hackathon/project-reaction_BO_agents +youtube_video: xf6rfyUQeZQ --- This project is focused on enhancing the efficiency of the Suzuki reaction process through an advanced multi-agent system, incorporating large language models (LLMs) and Bayesian Optimization (BO). The innovation lies in the employment of specialized sub-agents, each with expertise in a crucial domain of the reaction: catalyst design, solvent effects, and base selection. These agents work in concert with a supervisory agent, which integrates their insights and findings. This collaborative framework aims to optimize reaction conditions iteratively, leveraging both prior knowledge and experimental data to navigate the chemical space effectively. +Check out [our submission post on X](https://x.com/Bozhao95501764/status/1777029207857451508)! + References: 1. Perera, Damith, et al. "A platform for automated nanomole-scale reaction screening and micromole-scale synthesis in flow." Science 359.6374 (2018): 429-434. 2. Guo, Taicheng, et al. "Large language model based multi-agents: A survey of progress and challenges." arXiv preprint arXiv:2402.01680 (2024).