Autochemistry: A Research Paradigm Based on Artificial Intelligence and Big Data

26 February 2019, Version 3
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

Artificial Intelligence technologies affect every domain and process in industry. Many solutions with different maturity levels have been created or are in development. With this paper we collect initiatives in the domain of chemical science and bring these resources together into a common process model.
We define ten building blocks, analyse their role in the architecture and evaluate their impact to the current system. Finally we discuss the changes and the transition that occurs to the lab worker and the chemist.
This paper introduces Autochemistry as a meme and for further development and discussion. We just can provide a first sketch to this exciting new area of scientific principles changing the anthropocentric fundament of chemistry research to a technocentric one.

Keywords

Autochemistry
Artificial intelligence technology
publishing standards
research capabilities
Theoretical Study
Neural Networks Understanding
Communication Efficiency
chemometric techniques

Comments

Comments are not moderated before they are posted, but they can be removed by the site moderators if they are found to be in contravention of our Commenting Policy [opens in a new tab] - please read this policy before you post. Comments should be used for scholarly discussion of the content in question. You can find more information about how to use the commenting feature here [opens in a new tab] .
This site is protected by reCAPTCHA and the Google Privacy Policy [opens in a new tab] and Terms of Service [opens in a new tab] apply.