Bayesian Optimization-Assisted Screening to Identify Improved Reaction Conditions for Spiro-Dithiolane Synthesis

Autor:	Takizawa, Masaru Kondo, Hettiarachchige Dona Piyumi Wathsala, Kazunori Ishikawa, Daisuke Yamashita, Takeshi Miyazaki, Yoji Ohno, Hiroaki Sasai, Takashi Washio, Shinobu
Jazyk:	angličtina
Rok vydání:	2023
Předmět:	Bayesian optimization (BO) Gaussian process regression (GPR) random screening Latin hypercube sampling (LHS) spiro-dithiolane process chemistry scalable synthesis
Zdroj:	Molecules; Volume 28; Issue 13; Pages: 5180
ISSN:	1420-3049
DOI:	10.3390/molecules28135180
Popis:	Bayesian optimization (BO)-assisted screening was applied to identify improved reaction conditions toward a hundred-gram scale-up synthesis of 2,3,7,8-tetrathiaspiro[4.4]nonane (1), a key synthetic intermediate of 2,2-bis(mercaptomethyl)propane-1,3-dithiol [tetramercaptan pentaerythritol]. Starting from the initial training set (ITS) consisting of six trials sampled by random screening for BO, suitable parameters were predicted (78% conversion yield of spiro-dithiolane 1) within seven experiments. Moreover, BO-assisted screening with the ITS selected by Latin hypercube sampling (LHS) further improved the yield of 1 to 89% within the eight trials. The established conditions were confirmed to be satisfactory for a hundred grams scale-up synthesis of 1.
Databáze:	OpenAIRE
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