Machine learning offers new way of designing chiral…

Machine learning offers new way of designing chiral crystals

Engineers and chemists at Hiroshima University successfully used the technology underlying facial recognition to design chiral crystals. This is the first study reporting the use of this technology, called logistic regression analysis, to predict which chemical groups are best for making chiral molecules. Results were published in Chemistry Letters.

Chirality describes the quality of possessing a mirror image to something else, but without the ability to superimpose it. Your left foot, for example, is a mirror of your right. They look similar, but they are not the same. This is why you cannot wear a left shoe on your right foot.

The idea is similar in chemistry. Two molecules can have the same makeup of elements, but their geometry can differ. A left-handed chiral helix can have a corresponding right-handed helix.

However, making a mirror image of a chiral molecule is more complicated than just rearranging some bonds. An extra layer of complexity arises when making a crystal, a highly ordered series of atoms or molecules that can extend in three dimensions.

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