Exploration of flow reaction conditions using machine-learning for enantioselective organocatalyzed Rauhut–Currier and [3+2] annulation sequence. Issue 8 (6th January 2020)

• Record Type: Journal Article
• Authors: Kondo, Masaru; Wathsala, H. D. P.; Sako, Makoto; Hanatani, Yutaro; Ishikawa, Kazunori; Hara, Satoshi; Takaai, Takayuki; Washio, Takashi; Takizawa, Shinobu; Sasai, Hiroaki
• Is Part Of: Chemical communications. Volume 56:Issue 8(2020)
• Page Start: 1259
• Page End: 1262
• Publication Date: 2020-01-06
• Subjects: Chemistry -- Periodicals; 540
• DOI: 10.1039/c9cc08526b
• Languages: English
• ISSNs: 1359-7345

Abstract

Abstract : A highly atom-economical enantioselective Rauhut–Currier and [3+2] annulation has been established by flow system and machine-learning-assisted exploration of suitable conditions. Abstract : A highly atom-economical enantioselective organocatalyzed Rauhut–Currier and [3+2] annulation sequence has been established by using a flow system. Suitable flow conditions were explored through reaction screening of multiple parameters using machine learning. Eventually, functionalized chiral spirooxindole analogues were obtained in high yield with good ee as a single diastereomer within one minute.