Evidence map›Paper›PMID 36903478›Full record

ReviewMolecules (Basel, Switzerland)2023

Machine Learning in Unmanned Systems for Chemical Synthesis.

Guoqiang Wang, Xuefei Wu, Bo Xin, Xu Gu, Gaobo Wang, Yong Zhang, Jiabao Zhao, Xu Cheng, Chunlin Chen, Jing Ma

Full text readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Molecules (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Guoqiang WangKey Laboratory of Mesoscopic Chemistry of MOE, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, China.
Xuefei WuDepartment of Control Science and Intelligent Engineering, School of Management and Engineering, Nanjing University, Nanjing 210093, China.
Bo XinDepartment of Control Science and Intelligent Engineering, School of Management and Engineering, Nanjing University, Nanjing 210093, China.
Xu GuKey Laboratory of Mesoscopic Chemistry of MOE, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, China.
Gaobo WangKey Laboratory of Mesoscopic Chemistry of MOE, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, China.
Yong ZhangKey Laboratory of Mesoscopic Chemistry of MOE, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, China.
Jiabao ZhaoDepartment of Control Science and Intelligent Engineering, School of Management and Engineering, Nanjing University, Nanjing 210093, China.ORCID 0000-0002-2186-3177
Xu ChengKey Laboratory of Mesoscopic Chemistry of MOE, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, China.
Chunlin ChenDepartment of Control Science and Intelligent Engineering, School of Management and Engineering, Nanjing University, Nanjing 210093, China.
Jing MaKey Laboratory of Mesoscopic Chemistry of MOE, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, China.

Funding

National Key Research and Development Program of China 2019YFC0408303National Natural Science Foundation of China 62073160, 22033004, 2273035
6 · The paper itself

Abstract

Chemical synthesis is state-of-the-art, and, therefore, it is generally based on chemical intuition or experience of researchers. The upgraded paradigm that incorporates automation technology and machine learning (ML) algorithms has recently been merged into almost every subdiscipline of chemical science, from material discovery to catalyst/reaction design to synthetic route planning, which often takes the form of unmanned systems. The ML algorithms and their application scenarios in unmanned systems for chemical synthesis were presented. The prospects for strengthening the connection between reaction pathway exploration and the existing automatic reaction platform and solutions for improving autonomation through information extraction, robots, computer vision, and intelligent scheduling were proposed.

Indexed as

automatic chemical systemscoordinated multi-robot systemsmachine learningvirtual screening

Identifiers

PMID36903478
PMCPMC10004533

What OpenQuestion holds

Textfull text, public
LicenceCC BY
measurements read14
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.