At various points along the path toward productive nanosystems
for molecular manufacturing it would be useful to be able to
calculate the properties and reactions of assemblies of atoms of
various sizes. Within the domain of non-relativistic quantum
mechanics, such information is supplied by the Schrödinger
equation, but this can only be solved analytically for the
hydrogen atom and ions with only one electron. For larger atoms
and molecules, numerical solutions require compromises between
computational feasibility and accuracy. Recent work from
researchers at Argonne National Laboratory suggests that machine
learning can be an efficient alternative to numerical
computations. A hat tip to KurzweilAI.net for pointing to this
New Scientist article by Lisa Grossman “Molecules from scratch
without the fiendish physics“: A SUITE of artificial
intelligence algorithms may become the ultimate chemistry set.
Software can now quickly predict a property of molecules from
their theoretical structure. Similar advances sho