Energy-, time-, and labor-saving synthesis of α-ketiminophosphonates: machine-learning-assisted simultaneous multiparameter screening for electrochemical oxidation-Reference-Cited by-同舟云学术

Energy-, time-, and labor-saving synthesis of α-ketiminophosphonates: machine-learning-assisted simultaneous multiparameter screening for electrochemical oxidation

Published:2021 Issue:16 Volume:23 Page:5825-5831
ISSN:1463-9262
Container-title:Green Chemistry
language:en
Short-container-title:Green Chem.

Author:

Kondo Masaru¹²,Sugizaki Akimasa¹,Khalid Md. Imrul¹,Wathsala H. D. P.¹,Ishikawa Kazunori³,Hara Satoshi³,Takaai Takayuki³,Washio Takashi³⁴,Takizawa Shinobu¹⁴^ORCID,Sasai Hiroaki¹⁴^ORCID

Affiliation:

1. Department of Synthetic Organic Chemistry, The Institute of Scientific and Industrial Research (SANKEN), Osaka University, Mihogaoka, Ibaraki, Osaka 567-0047, Japan

2. Department of Materials Science and Engineering, Graduate School of Science and Engineering, Ibaraki University, Hitachi 316-8511, Ibaraki, Japan

3. Department of Reasoning for Intelligence, SANKEN, Osaka University, Japan

4. Artificial Intelligence Research Center, SANKEN, Osaka University, Japan

Abstract

A highly efficient synthesis of α-ketiminophosphonates has been established for the electrochemical oxidation of α-amino phosphonates with the utilization of machine-learning-assisted simultaneous multiparameter screening.

Funder

Hoansha Foundation

NOVARTIS Foundation (Japan) for the Promotion of Science

Daiichi Sankyo Foundation of Life Science

Research Foundation for Opto-Science and Technology

Iketani Science and Technology Foundation

Japan Society for the Promotion of Science

Core Research for Evolutional Science and Technology

Iwatani Naoji Foundation

Publisher

Royal Society of Chemistry (RSC)

Subject