Literature DB >> 30395457

AIR-Chem: Authentic Intelligent Robotics for Chemistry.

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


  5 in total

1.  Self-driving laboratory for accelerated discovery of thin-film materials.

Authors:  B P MacLeod; F G L Parlane; T D Morrissey; F Häse; L M Roch; K E Dettelbach; R Moreira; L P E Yunker; M B Rooney; J R Deeth; V Lai; G J Ng; H Situ; R H Zhang; M S Elliott; T H Haley; D J Dvorak; A Aspuru-Guzik; J E Hein; C P Berlinguette
Journal:  Sci Adv       Date:  2020-05-13       Impact factor: 14.136

2.  Autonomous discovery of optically active chiral inorganic perovskite nanocrystals through an intelligent cloud lab.

Authors:  Jiagen Li; Junzi Li; Rulin Liu; Yuxiao Tu; Yiwen Li; Jiaji Cheng; Tingchao He; Xi Zhu
Journal:  Nat Commun       Date:  2020-04-27       Impact factor: 14.919

3.  Using simulation to accelerate autonomous experimentation: A case study using mechanics.

Authors:  Aldair E Gongora; Kelsey L Snapp; Emily Whiting; Patrick Riley; Kristofer G Reyes; Elise F Morgan; Keith A Brown
Journal:  iScience       Date:  2021-03-02

4.  Automated solubility screening platform using computer vision.

Authors:  Parisa Shiri; Veronica Lai; Tara Zepel; Daniel Griffin; Jonathan Reifman; Sean Clark; Shad Grunert; Lars P E Yunker; Sebastian Steiner; Henry Situ; Fan Yang; Paloma L Prieto; Jason E Hein
Journal:  iScience       Date:  2021-02-12

5.  A review on quantum computing and deep learning algorithms and their applications.

Authors:  Fevrier Valdez; Patricia Melin
Journal:  Soft comput       Date:  2022-04-07       Impact factor: 3.643

  5 in total

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