Auto‐Optimized Electro‐Flow Reactor Platform for the in‐situ Reduction of P(V) Oxide to P(III) and Their Application

• Published in: Chemistry, an Asian journal an Asian journal, 2024-09, Vol.19 (18), p.e202400438-n/a
• Main Authors: Purwa, Mandeep, Chandrakanth, Gaykwad, Rana, Abhilash, Mottafegh, Amirreza, Kumar, Sanjeev, Kim, Dong‐Pyo, Singh, Ajay K.
• Format: Article
• Language: English
• Subjects: Artificial intelligence; Batch disabled chemistry; Bayesian optimization; Carbon; Chemical bonds; Corey-Fuchs reaction; Electro-flow reduction reactor; multi-variable optimization; Phosphines; Random variables
• ISSN: 1861-4728; 1861-471X; 1861-471X
• DOI: 10.1002/asia.202400438

Trivalent phosphine catalysis is mostly utilized to activate the carbon‐carbon multiple bonds to form carbanion intermediate species and is highly sensitive to certain variables. Random manual multi‐variables are critical for understanding the batch disabled regeneration of trivalent phosphine chemistry. We need the artificial intelligence‐based system which can change the variable based on previously conducted failed experiment. Herein, we report an auto‐optimized electro‐micro‐flow reactor platform for the in‐situ reduction of stable P(V) oxide to sensitive P(III) and further utilized the method for Corey‐Fuchs reaction. In electrolysis reactions, a series of parameters (voltage, current, reaction time, solution concentration, electrode, conversion, yield, etc.) are interdependent. Additionally, high cell resistivity in batch reactors makes optimizing reaction conditions time‐consuming. For the first time, an AI‐based flow electrolysis setup has been applied to find the best conditions for phosphorus redox chemistry, significantly enhancing process efficiency and outcomes.