Merge pull request #151 from bznan/patch-4

video and LinkedIn updated typo corrected

_projects/project-40-reation_multi-agents.md → _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: <your-video-id>
+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).