High-throughput automated platform for thin layer chromatography analysis

Hao Xu; Dongxiao Zhang; Fanyang Mo

doi:10.1016/j.xpro.2022.101893

High-throughput automated platform for thin layer chromatography analysis

STAR Protoc. 2022 Dec 16;3(4):101893. doi: 10.1016/j.xpro.2022.101893. Epub 2022 Dec 5.

Authors

Hao Xu¹, Dongxiao Zhang², Fanyang Mo³

Affiliations

¹ School of Materials Science and Engineering, Peking University, Beijing 100871, China; BIC-ESAT, ERE, and SKLTCS, College of Engineering, Peking University, Beijing 100871, China.
² Department of Mathematics and Theories, Peng Cheng Laboratory, Shenzhen 518000, China; National Center for Applied Mathematics Shenzhen (NCAMS), Southern University of Science and Technology, Shenzhen 518055, China. Electronic address: zhangdx@sustech.edu.cn.
³ School of Materials Science and Engineering, Peking University, Beijing 100871, China. Electronic address: fmo@pku.edu.cn.

Abstract

In this protocol, we detail steps for constructing a high-throughput automated platform for thin layer chromatography (TLC) analysis. We describe robotics and computer vision techniques that can handle 32 compounds under three different elution solvents in about 50 min. The established automated platform can obtain statistically standardized retardation factor (R_f) values and enhance reproducibility while reducing labor and time costs. For complete details on the use and execution of this protocol, please refer to Xu et al. (2022).¹.

Keywords: Chemistry; High Throughput Screening.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Chromatography, Thin Layer* / methods
Reproducibility of Results
Solvents / chemistry

Substances

Solvents