Beilstein J. Org. Chem.2017,13, 1288–1302, doi:10.3762/bjoc.13.125
, medicine and engineering. Automation, robotics, artificial intelligence, and evolutionaryalgorithms are now converging to generate what might broadly be called in silico-based adaptive evolution of materials. These methods are being applied to organic chemistry to systematize reactions, create synthesis
methods and their potential impacts in chemistry, engineering, and medicine.
Keywords: automated chemical synthesis; deep learning; evolutionaryalgorithms; in silico evolution; machine learning; materials design and development; neural networks; Introduction
There is still not a clear understanding of
of evolutionaryalgorithms to explore materials space more quickly and effectively than other methods. When coupled with learning algorithms, in silico evolutionary adaptation is possible, as we now describe.
Evolving materials for the future
The development and application of evolutionary methods
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Graphical Abstract
Figure 1:
Hypothesized evolution of ‘life’ and ‘intelligence’.