4.6 Review

Algorithms for the self-optimisation of chemical reactions

期刊

REACTION CHEMISTRY & ENGINEERING
卷 4, 期 9, 页码 1545-1554

出版社

ROYAL SOC CHEMISTRY
DOI: 10.1039/c9re00209j

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资金

  1. EPSRC
  2. University of Leeds
  3. AstraZeneca
  4. EPSRC project Cognitive Chemical Manufacturing [EP/R032807/1]
  5. EPSRC [EP/R032807/1, 1803783] Funding Source: UKRI

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Self-optimising chemical systems have experienced a growing momentum in recent years, with the evolution of self-optimising platforms leading to their application for reaction screening and chemical synthesis. With the desire for improved process sustainability, self-optimisation provides a cheaper, faster and greener approach to the chemical development process. The use of such platforms aims to enhance the capabilities of the researcher by removing the need for labor-intensive experimentation, allowing them to focus on more challenging tasks. The establishment of these systems have enabled opportunities for self-optimising platforms to become a key element of a laboratory's repertoire. To enable the wider adoption of self-optimising chemical platforms, this review summarises the history of algorithmic usage in chemical reaction self-optimisation, detailing the functionality of the algorithms and their applications in a way that is accessible for chemists and highlights opportunities for the further exploitation of algorithms in chemical synthesis moving forward.

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