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AIR-Chem: Authentic Intelligent Robotics for Chemistry

Authors :
Yihua Lu
Huihuan Qian
Chongfeng Liu
Yuxiao Tu
Xi Zhu
Yanheng Xu
Jiagen Li
Yi Xie
Haochen Liu
Shuqian Ye
Source :
The Journal of Physical Chemistry A. 122:9142-9148
Publication Year :
2018
Publisher :
American Chemical Society (ACS), 2018.

Abstract

The new era with prosperous artificial intelligence (AI) and robotics technology is reshaping the materials discovery process in a more radical fashion. Here we present authentic intelligent robotics for chemistry (AIR-Chem), integrated with technological innovations in the AI and robotics fields, functionalized with modules including gradient descent-based optimization frameworks, multiple external field modulations, a real-time computer vision (CV) system, and automated guided vehicle (AGV) parts. AIR-Chem is portable and remotely controllable by cloud computing. AIR-Chem can learn the parametric procedures for given targets and carry on laboratory operations in standalone mode, with high reproducibility, precision, and availability for knowledge regeneration. Moreover, an improved nucleation theory of size focusing on inorganic perovskite quantum dots (IPQDs) is theoretically proposed and experimentally testified to by AIR-Chem. This work aims to boost the process of an unmanned chemistry laboratory from the synthesis of chemical materials to the analysis of physical chemical properties, and it provides a vivid demonstration for future chemistry reshaped by AI and robotics technology.

Details

ISSN :
15205215 and 10895639
Volume :
122
Database :
OpenAIRE
Journal :
The Journal of Physical Chemistry A
Accession number :
edsair.doi.dedup.....62179228489f9a790bc9c2fa2e9bb80c
Full Text :
https://doi.org/10.1021/acs.jpca.8b10680