| Literature DB >> 30395457 |
Jiagen Li, Yihua Lu, Yanheng Xu, Chongfeng Liu, Yuxiao Tu, Shuqian Ye, Haochen Liu1, Yi Xie2, Huihuan Qian, Xi Zhu.
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.Year: 2018 PMID: 30395457 DOI: 10.1021/acs.jpca.8b10680
Source DB: PubMed Journal: J Phys Chem A ISSN: 1089-5639 Impact factor: 2.781